[ { "key": "8579496fc9a93fcc121b47dfd03cd9a3", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 2, 2060 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were born before the year 2060?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2060\"", "question_refine_tok": [ "how", "many", "patients", "were", "born", "before", "the", "year", "2060", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2060\"" ], "answer": [ "10386" ] }, { "key": "8ef884f5ab354b39fa29558e7dbe5606", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "53190" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had the diagnosis icd9 code 53190?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"53190\"", "question_refine_tok": [ "how", "many", "patients", "had", "the", "diagnosis", "icd9", "code", "53190", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"53190\"" ], "answer": [ "153" ] }, { "key": "a5fd6085c174de907250cf4840601a22", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "9951" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "let me know the number of patients who have diagnosis icd9 code 9951.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"9951\"", "question_refine_tok": [ "let", "me", "know", "the", "number", "of", "patients", "who", "have", "diagnosis", "icd9", "code", "9951", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"9951\"" ], "answer": [ "127" ] }, { "key": "a030ada88d94f5f9ef48362a97aa413d", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Crnry athrscl natve vssl" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the total number of patiemts who had crnry athrscl natve vssl?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Crnry athrscl natve vssl\"", "question_refine_tok": [ "what", "is", "the", "total", "number", "of", "patiemts", "who", "had", "crnry", "athrscl", "natve", "vssl", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Crnry", "athrscl", "natve", "vssl\"" ], "answer": [ "10775" ] }, { "key": "a56ed1d77f9cf8150b6a9151dabac4bf", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Tobacco use disorder" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients who have been diagnosed with tobacco use disorder.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Tobacco use disorder\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "who", "have", "been", "diagnosed", "with", "tobacco", "use", "disorder", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Tobacco", "use", "disorder\"" ], "answer": [ "3001" ] }, { "key": "80d30178f68e2492cc13d95f53b2ffaa", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Retain plastic fragments" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose diagnosis short title is retain plastic fragments.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Retain plastic fragments\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "diagnosis", "short", "title", "is", "retain", "plastic", "fragments", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Retain", "plastic", "fragments\"" ], "answer": [ "1" ] }, { "key": "80493e9bb6cabefb1d4a01cb9851ea70", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Chordae tendinae rupture" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me the number of patients who have been diagnosed with chordae tendinae rupture.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Chordae tendinae rupture\"", "question_refine_tok": [ "provide", "me", "the", "number", "of", "patients", "who", "have", "been", "diagnosed", "with", "chordae", "tendinae", "rupture", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Chordae", "tendinae", "rupture\"" ], "answer": [ "87" ] }, { "key": "0b323ac6dda39e3588c51d5acb16b4fc", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 4, 0, "Hemorrhage complicating a procedure" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients had hemorrhage complicating a procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Hemorrhage complicating a procedure\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "had", "hemorrhage", "complicating", "a", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Hemorrhage", "complicating", "a", "procedure\"" ], "answer": [ "1498" ] }, { "key": "bb1f244e6a3ef486f168b21b2c86e93d", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 4, 0, "Mitral valve disorders" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients diagnosed with mitral valve disorders.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Mitral valve disorders\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "diagnosed", "with", "mitral", "valve", "disorders", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Mitral", "valve", "disorders\"" ], "answer": [ "2651" ] }, { "key": "ac68bab7e7f4cd79ac543b18d76d24d3", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 5771 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calulate the total number of patients who had icd9 code 5771", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"5771\"", "question_refine_tok": [ "Calulate", "the", "total", "number", "of", "patients", "who", "had", "icd9", "code", "5771" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5771\"" ], "answer": [ "55" ] }, { "key": "0356aee9e4219b42d469d4adb3bf0729", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 8848 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose procedure icd9 code is 8848.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"8848\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "procedure", "icd9", "code", "is", "8848", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8848\"" ], "answer": [ "546" ] }, { "key": "0a61c544738a373b8324d8335031a7c6", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "Radiotherapeut proc NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the total number of patients who had radiotherapeut proc nec", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"Radiotherapeut proc NEC\"", "question_refine_tok": [ "calculate", "the", "total", "number", "of", "patients", "who", "had", "radiotherapeut", "proc", "nec" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Radiotherapeut", "proc", "NEC\"" ], "answer": [ "252" ] }, { "key": "adce510d770aef3a1b9e9014e766798c", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "1 int mam-cor art bypass" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients who had single internal mammary-coronary artery bypass.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"1 int mam-cor art bypass\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "who", "had", "single", "internal", "mammary", "-", "coronary", "artery", "bypass", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"1", "int", "mam-cor", "art", "bypass\"" ], "answer": [ "4397" ] }, { "key": "bb120bab7f84d17e1af739be0525fd30", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Zyrtec" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients use the drug zyrtec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Zyrtec\"", "question_refine_tok": [ "how", "many", "patients", "use", "the", "drug", "zyrtec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Zyrtec\"" ], "answer": [ "18" ] }, { "key": "9599d62908a1ba42d4b04b1abcdbe094", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "DiphenhydrAMINE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients have a diphenhydramine prescription?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"DiphenhydrAMINE\"", "question_refine_tok": [ "How", "many", "patients", "have", "a", "diphenhydramine", "prescription", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"DiphenhydrAMINE\"" ], "answer": [ "3275" ] }, { "key": "a923f3ce780d550018dd0df1f1e55570", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Oxycodone SR (OxyconTIN)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients were given the drug oxycodone sr (oxycontin)?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Oxycodone SR (OxyconTIN)\"", "question_refine_tok": [ "what", "number", "of", "patients", "were", "given", "the", "drug", "oxycodone", "sr", "(", "oxycontin", ")", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Oxycodone", "SR", "(OxyconTIN)\"" ], "answer": [ "801" ] }, { "key": "ba1d361e366b1ec723817cb2a1011859", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Syringe (Neonatal)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients use the neonatal syringe?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Syringe (Neonatal)\"", "question_refine_tok": [ "how", "many", "patients", "use", "the", "neonatal", "syringe", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Syringe", "(Neonatal)\"" ], "answer": [ "1044" ] }, { "key": "9057aad89e8f66541aadbb45ad8f4747", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Bethanechol" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients are on bethanechol prescription?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Bethanechol\"", "question_refine_tok": [ "which", "patients", "are", "on", "bethanechol", "prescription", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Bethanechol\"" ], "answer": [ "34" ] }, { "key": "04e471a143d212d6e201d787eea68d7d", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Caspofungin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients used the drug name capso fungin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Caspofungin\"", "question_refine_tok": [ "how", "many", "patients", "used", "the", "drug", "name", "capso", "fungin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Caspofungin\"" ], "answer": [ "376" ] }, { "key": "08e84aa74e5e3adb7969241939f3af64", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "ERGO400T" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients used the drug code ergo400t?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"ERGO400T\"", "question_refine_tok": [ "How", "many", "patients", "used", "the", "drug", "code", "ergo400t", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"ERGO400T\"" ], "answer": [ "2783" ] }, { "key": "8c6bcade1f9fdf7786a7a64151da5b73", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "HEPA10SYR" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients uses the drug code hepa10syr?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"HEPA10SYR\"", "question_refine_tok": [ "how", "many", "patients", "uses", "the", "drug", "code", "hepa10syr", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"HEPA10SYR\"" ], "answer": [ "5885" ] }, { "key": "0eae72d2c42207e67c86012d0be36650", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 50817 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have lab test item id 50817?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"50817\"", "question_refine_tok": [ "how", "many", "patients", "have", "lab", "test", "item", "i", "d", "50817", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"50817\"" ], "answer": [ "17083" ] }, { "key": "93afecdf36b6ce7b81f6d82625a068fb", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 50953 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have lab test item id 50953?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"50953\"", "question_refine_tok": [ "which", "patients", "have", "lab", "test", "item", "i", "d", "50953", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"50953\"" ], "answer": [ "7902" ] }, { "key": "0bc7d1325aa939738ec24177f53a0fd4", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 18, 2, 2064 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the married patients were born before 2064", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2064\"", "question_refine_tok": [ "How", "many", "of", "the", "married", "patients", "were", "born", "before", "2064" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2064\"" ], "answer": [ "5595" ] }, { "key": "103c53116811183189bbac6240b1c38e", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 19, 4, 2165.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many married patients died in or before 2165?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2165.0\"", "question_refine_tok": [ "How", "many", "married", "patients", "died", "in", "or", "before", "2165", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2165.0\"" ], "answer": [ "4532" ] }, { "key": "87f0df33656ad30a1df51ab8f9d3d7b4", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 1, 4, 0, "Other convulsions" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of married patients suffered from other convulsions?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DIAGNOSES.\"LONG_TITLE\" = \"Other convulsions\"", "question_refine_tok": [ "what", "number", "of", "married", "patients", "suffered", "from", "other", "convulsions", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Other", "convulsions\"" ], "answer": [ "706" ] }, { "key": "0149a04bfc4bbf58198b7cc5bd248ad1", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 1, 4, 0, "Portal hypertension" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many single patients had a diagnosis long title protal hypertension?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DIAGNOSES.\"LONG_TITLE\" = \"Portal hypertension\"", "question_refine_tok": [ "How", "many", "single", "patients", "had", "a", "diagnosis", "long", "title", "protal", "hypertension", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Portal", "hypertension\"" ], "answer": [ "283" ] }, { "key": "acc18041b791fa3f2145584de2f52fa2", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 2, 3, 0, "Radiotherapeut proc NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of married patients underwent the procedure titled radiotherapeut proc nec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND PROCEDURES.\"SHORT_TITLE\" = \"Radiotherapeut proc NEC\"", "question_refine_tok": [ "what", "number", "of", "married", "patients", "underwent", "the", "procedure", "titled", "radiotherapeut", "proc", "nec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Radiotherapeut", "proc", "NEC\"" ], "answer": [ "144" ] }, { "key": "0ba1f09761ef0b9798676d7a93899e8b", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 2, 3, 0, "Ins drug-elut coronry st" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get the number of married patients who had insertion of drug-eluting coronary artery stent(s).", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND PROCEDURES.\"SHORT_TITLE\" = \"Ins drug-elut coronry st\"", "question_refine_tok": [ "get", "the", "number", "of", "married", "patients", "who", "had", "insertion", "of", "drug", "-", "eluting", "coronary", "artery", "stent(s", ")", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Ins", "drug-elut", "coronry", "st\"" ], "answer": [ "658" ] }, { "key": "079fc93fe997ed5c22fbe560d68ebb31", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 18, 2, 2197 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of female patients whose year of birth is before 2197.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2197\"", "question_refine_tok": [ "find", "the", "number", "of", "female", "patients", "whose", "year", "of", "birth", "is", "before", "2197", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2197\"" ], "answer": [ "20252" ] }, { "key": "09bcb63460706eb5e0799aa702c1c7e3", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "M" ], [ 1, 2, 0, "25002" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me with the number of male patients who had diagnosis icd9 code 25002.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DIAGNOSES.\"ICD9_CODE\" = \"25002\"", "question_refine_tok": [ "provide", "me", "with", "the", "number", "of", "male", "patients", "who", "had", "diagnosis", "icd9", "code", "25002", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"25002\"" ], "answer": [ "242" ] }, { "key": "107ad04abc71c4c4fe456c0df5415253", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 3, 0, "Bacteremia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients had the diagnosis short title bacteremia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Bacteremia\"", "question_refine_tok": [ "how", "many", "female", "patients", "had", "the", "diagnosis", "short", "title", "bacteremia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Bacteremia\"" ], "answer": [ "564" ] }, { "key": "a5cc6a0d4db1e239abdee050cabc3798", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 3, 0, "Lap surg convert to open" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of female patients whose diagnoses is titled lap surg convert to open.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Lap surg convert to open\"", "question_refine_tok": [ "find", "the", "number", "of", "female", "patients", "whose", "diagnoses", "is", "titled", "lap", "surg", "convert", "to", "open", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Lap", "surg", "convert", "to", "open\"" ], "answer": [ "70" ] }, { "key": "83ec356d7434ad2b1a3ff520127d3ce8", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 4, 0, "Constipation, unspecified" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients are diagnosed with unspecified constipation?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"LONG_TITLE\" = \"Constipation, unspecified\"", "question_refine_tok": [ "how", "many", "female", "patients", "are", "diagnosed", "with", "unspecified", "constipation", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Constipation,", "unspecified\"" ], "answer": [ "426" ] }, { "key": "a95ae3ec84a4478fe2ba16078b12904a", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "F" ], [ 2, 2, 0, 3727 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the female patients who have procedure icd9 code 3727.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PROCEDURES.\"ICD9_CODE\" = \"3727\"", "question_refine_tok": [ "find", "the", "female", "patients", "who", "have", "procedure", "icd9", "code", "3727", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"3727\"" ], "answer": [ "81" ] }, { "key": "a81dae5ff42498734e857c5b7dc46deb", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "F" ], [ 2, 3, 0, "Abdomen artery incision" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients underwent the procedure of abdomen artery incision?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PROCEDURES.\"SHORT_TITLE\" = \"Abdomen artery incision\"", "question_refine_tok": [ "how", "many", "female", "patients", "underwent", "the", "procedure", "of", "abdomen", "artery", "incision", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Abdomen", "artery", "incision\"" ], "answer": [ "22" ] }, { "key": "a73aa7de83493b191fbc445d5a71523b", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 6, 0, "M" ], [ 3, 5, 0, "MEPE50I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had the drug code mepe50i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"MEPE50I\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "the", "drug", "code", "mepe50i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"MEPE50I\"" ], "answer": [ "3647" ] }, { "key": "85458bc20e32da11c87969332a42276f", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 6, 0, "M" ], [ 3, 5, 0, "LIPID250I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had the drug code lipid250i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"LIPID250I\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "the", "drug", "code", "lipid250i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"LIPID250I\"" ], "answer": [ "20" ] }, { "key": "0cc42c38501862128c59ef2444eaea0e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 6, 0, "Ferritin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients have undergone the lab test for ferritin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"LABEL\" = \"Ferritin\"", "question_refine_tok": [ "how", "many", "male", "patients", "have", "undergone", "the", "lab", "test", "for", "ferritin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"LABEL\"", "=", "\"Ferritin\"" ], "answer": [ "4084" ] }, { "key": "a819a3814f2f34b5124ec8353cbf07f0", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "PORT" ], [ 0, 4, 2, 45 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged less than 45 years speak the language port?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"PORT\" AND DEMOGRAPHIC.\"AGE\" < \"45\"", "question_refine_tok": [ "how", "many", "patients", "aged", "less", "than", "45", "years", "speak", "the", "language", "port", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"PORT\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"45\"" ], "answer": [ "101" ] }, { "key": "9391ab36c2bddfe0cf474a3d26392232", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 7, 0, "RUSS" ], [ 1, 3, 0, "Proteus infection NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of russian speaking patients who are diagnosed with proteus infection nos.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"RUSS\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Proteus infection NOS\"", "question_refine_tok": [ "find", "the", "number", "of", "russian", "speaking", "patients", "who", "are", "diagnosed", "with", "proteus", "infection", "nos", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"RUSS\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Proteus", "infection", "NOS\"" ], "answer": [ "8" ] }, { "key": "0db846be36da67fce1f489804cad086f", "format": { "table": [ 0 ], "cond": [ [ 0, 8, 0, "JEHOVAH'S WITNESS" ], [ 0, 4, 2, 71 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get the number of jehovah's witness religious background patients who are less than 71 years of age.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"RELIGION\" = \"JEHOVAH'S WITNESS\" AND DEMOGRAPHIC.\"AGE\" < \"71\"", "question_refine_tok": [ "get", "the", "number", "of", "jehovah", "'s", "witness", "religious", "background", "patients", "who", "are", "less", "than", "71", "years", "of", "age", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"JEHOVAH'S", "WITNESS\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"71\"" ], "answer": [ "79" ] }, { "key": "ae1e928c2c207060f138688ce4abb351", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 8, 0, "PROTESTANT QUAKER" ], [ 1, 3, 0, "Pressure ulcer, stage I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients follow the protestant quaker religion and were diagnosed with pressure ulcer, stage i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"RELIGION\" = \"PROTESTANT QUAKER\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Pressure ulcer, stage I\"", "question_refine_tok": [ "how", "many", "patients", "follow", "the", "protestant", "quaker", "religion", "and", "were", "diagnosed", "with", "pressure", "ulcer", ",", "stage", "i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"PROTESTANT", "QUAKER\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Pressure", "ulcer,", "stage", "I\"" ], "answer": [ "16" ] }, { "key": "035d34423915656ea2221529022d86c5", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 22, 2, 2135 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients admitted before the year 2135 who had elective admission.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2135\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "admitted", "before", "the", "year", "2135", "who", "had", "elective", "admission", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2135\"" ], "answer": [ "2481" ] }, { "key": "80cf621c35042d6d096cdaeab1b5b902", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "NEWBORN" ], [ 0, 22, 2, 2177 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "show the number of admissions before the year 2177 whose admission type is newborn.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"NEWBORN\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2177\"", "question_refine_tok": [ "show", "the", "number", "of", "admissions", "before", "the", "year", "2177", "whose", "admission", "type", "is", "newborn", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2177\"" ], "answer": [ "5992" ] }, { "key": "8301ca160becb385bbe5a62015fc5921", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 1, 2, 0, "40391" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose admission type is emergency and diagnosis icd9 code is 40391.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DIAGNOSES.\"ICD9_CODE\" = \"40391\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "whose", "admission", "type", "is", "emergency", "and", "diagnosis", "icd9", "code", "is", "40391", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"40391\"" ], "answer": [ "1602" ] }, { "key": "05ba071627d319e108fbf4c830334200", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 1, 2, 0, "2763" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with an emergency admission type had the diagnosis icd9 code 2763?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DIAGNOSES.\"ICD9_CODE\" = \"2763\"", "question_refine_tok": [ "how", "many", "patients", "with", "an", "emergency", "admission", "type", "had", "the", "diagnosis", "icd9", "code", "2763", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2763\"" ], "answer": [ "871" ] }, { "key": "86de234b4ea86613c4fd4865e6be4b05", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 1, 2, 0, "56210" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with an emergency admission type had the diagnosis icd9 code 56210?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DIAGNOSES.\"ICD9_CODE\" = \"56210\"", "question_refine_tok": [ "how", "many", "patients", "with", "an", "emergency", "admission", "type", "had", "the", "diagnosis", "icd9", "code", "56210", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"56210\"" ], "answer": [ "690" ] }, { "key": "01a951685204b898d99630d8b079ffd9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 1, 4, 0, "Drug induced neutropenia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with admission type elective and diagnosed with drug induced neutropenia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DIAGNOSES.\"LONG_TITLE\" = \"Drug induced neutropenia\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "admission", "type", "elective", "and", "diagnosed", "with", "drug", "induced", "neutropenia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Drug", "induced", "neutropenia\"" ], "answer": [ "5" ] }, { "key": "a6b131aab0d840f347b9ad994e7744db", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 2, 2, 0, 252 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with elective admission type and with procedure icd9 code 252?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND PROCEDURES.\"ICD9_CODE\" = \"252\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "elective", "admission", "type", "and", "with", "procedure", "icd9", "code", "252", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"252\"" ], "answer": [ "6" ] }, { "key": "04b3c1d2e1694aabd62095b2d46a67f5", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 2, 3, 0, "Unilat rad neck dissect" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Look for the number of elective hospital admission patients who had a unilateral radical neck dissection procedure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND PROCEDURES.\"SHORT_TITLE\" = \"Unilat rad neck dissect\"", "question_refine_tok": [ "Look", "for", "the", "number", "of", "elective", "hospital", "admission", "patients", "who", "had", "a", "unilateral", "radical", "neck", "dissection", "procedure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Unilat", "rad", "neck", "dissect\"" ], "answer": [ "31" ] }, { "key": "89878ec7ea816d9b35addf46468da048", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 2, 3, 0, "Cont inv mec ven 96+ hrs" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "look for the number of emergency hospital admitted patients who had cont inv mec ven 96+ hrs as short title of procedure .", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PROCEDURES.\"SHORT_TITLE\" = \"Cont inv mec ven 96+ hrs\"", "question_refine_tok": [ "look", "for", "the", "number", "of", "emergency", "hospital", "admitted", "patients", "who", "had", "cont", "inv", "mec", "ven", "96", "+", "hrs", "as", "short", "title", "of", "procedure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Cont", "inv", "mec", "ven", "96+", "hrs\"" ], "answer": [ "4669" ] }, { "key": "844c051a7fc31f50e5125392d2710bb8", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 3, 4, 0, "Timolol Maleate 0.5%" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients admitted on an emergency basis who had prescription for timolol maleate 0.5%.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PRESCRIPTIONS.\"DRUG\" = \"Timolol Maleate 0.5%\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "admitted", "on", "an", "emergency", "basis", "who", "had", "prescription", "for", "timolol", "maleate", "0.5", "%", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Timolol", "Maleate", "0.5%\"" ], "answer": [ "298" ] }, { "key": "9193bc2c5d90be4e199fc6a421133f88", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 4, 6, 0, "LD, Body Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the number of patients admitted to emergency who had an ld body fluid test by lab", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND LAB.\"LABEL\" = \"LD, Body Fluid\"", "question_refine_tok": [ "Calculate", "the", "number", "of", "patients", "admitted", "to", "emergency", "who", "had", "an", "ld", "body", "fluid", "test", "by", "lab" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "LAB.\"LABEL\"", "=", "\"LD,", "Body", "Fluid\"" ], "answer": [ "341" ] }, { "key": "9e2bb2a0d86e0e587fb393ad10311fbd", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 4, 6, 0, "Reticulocyte Count, Manual" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of emergency hospital admission patients who had manual reticulocyte count lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND LAB.\"LABEL\" = \"Reticulocyte Count, Manual\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "had", "manual", "reticulocyte", "count", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "LAB.\"LABEL\"", "=", "\"Reticulocyte", "Count,", "Manual\"" ], "answer": [ "618" ] }, { "key": "0bd77a0aa119fff1491ad47e43c104cb", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 0, 4, 2, 74 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients under the age of 74 whose insurance is self pay.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DEMOGRAPHIC.\"AGE\" < \"74\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "under", "the", "age", "of", "74", "whose", "insurance", "is", "self", "pay", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"74\"" ], "answer": [ "582" ] }, { "key": "025ce5d0a492bc418ed5e2d467822479", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 0, 18, 2, 2104 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who were born before 2104 and have medicare insurance .", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2104\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "were", "born", "before", "2104", "and", "have", "medicare", "insurance", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2104\"" ], "answer": [ "16311" ] }, { "key": "8745cad27000303a093d0dd8dafeeb7b", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 0, 22, 2, 2187 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with medicare insurance and admitted before 2187?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2187\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "medicare", "insurance", "and", "admitted", "before", "2187", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2187\"" ], "answer": [ "17927" ] }, { "key": "0e41987fae64a3292dbb83fe18b6d6eb", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 0, 22, 2, 2154 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients admitted before the year 2154 who had medicare insurance.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2154\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "admitted", "before", "the", "year", "2154", "who", "had", "medicare", "insurance", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2154\"" ], "answer": [ "11099" ] }, { "key": "936aa04d2d6d3b1065c9100730171751", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 0, 16, 0, "BRADYCARDIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many white patients had the primary disease bradycardia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRADYCARDIA\"", "question_refine_tok": [ "how", "many", "white", "patients", "had", "the", "primary", "disease", "bradycardia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRADYCARDIA\"" ], "answer": [ "80" ] }, { "key": "01443480ca76e4369b245ea13b9f1df1", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "AMERICAN INDIAN/ALASKA NATIVE" ], [ 0, 4, 2, 67 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients of american indian/alaska native ethnicity are younger than 67 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"AMERICAN INDIAN/ALASKA NATIVE\" AND DEMOGRAPHIC.\"AGE\" < \"67\"", "question_refine_tok": [ "how", "many", "patients", "of", "american", "indian/alaska", "native", "ethnicity", "are", "younger", "than", "67", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"AMERICAN", "INDIAN/ALASKA", "NATIVE\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"67\"" ], "answer": [ "38" ] }, { "key": "04f28582e0964c9954df581b93f8ecc7", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 0, 4, 2, 68 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the patients from a black/haitian ethnic origin were aged below 68? ", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND DEMOGRAPHIC.\"AGE\" < \"68\"", "question_refine_tok": [ "How", "many", "of", "the", "patients", "from", "a", "black/haitian", "ethnic", "origin", "were", "aged", "below", "68", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"68\"" ], "answer": [ "52" ] }, { "key": "03003e36361d3201de108c4f119f7e70", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 4, 2, 67 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many asian patients are less than 67 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"AGE\" < \"67\"", "question_refine_tok": [ "how", "many", "asian", "patients", "are", "less", "than", "67", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"67\"" ], "answer": [ "1035" ] }, { "key": "090932307c30b9e5035ed9b8e269495a", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 4, 2, 80 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients less than 80 years of age who have asian ethnic background.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"AGE\" < \"80\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "less", "than", "80", "years", "of", "age", "who", "have", "asian", "ethnic", "background", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"80\"" ], "answer": [ "1178" ] }, { "key": "0a93280ed4a8b3eeff94a94266661162", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 0, 18, 2, 2052 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were there whose ethnicity is white and born before the year 2052?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2052\"", "question_refine_tok": [ "how", "many", "patients", "were", "there", "whose", "ethnicity", "is", "white", "and", "born", "before", "the", "year", "2052", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2052\"" ], "answer": [ "5935" ] }, { "key": "a6b46b322c8929ee2ac3a05ac85f943c", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "HISPANIC/LATINO - PUERTO RICAN" ], [ 0, 18, 2, 2107 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the total number of patients from hispanic/latino - puertorican ethnic origin who were born before 2107.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"HISPANIC/LATINO - PUERTO RICAN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2107\"", "question_refine_tok": [ "What", "is", "the", "total", "number", "of", "patients", "from", "hispanic/latino", "-", "puertorican", "ethnic", "origin", "who", "were", "born", "before", "2107", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"HISPANIC/LATINO", "-", "PUERTO", "RICAN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2107\"" ], "answer": [ "84" ] }, { "key": "0565e307a3edfe84e93e464b872149ad", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 1, 3, 0, "Hx of GI malignancy NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with white ethnicity and diagnosed for hx of gi malignancy nec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Hx of GI malignancy NEC\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "white", "ethnicity", "and", "diagnosed", "for", "hx", "of", "gi", "malignancy", "nec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Hx", "of", "GI", "malignancy", "NEC\"" ], "answer": [ "63" ] }, { "key": "02f5addb91754a1b056140844e000bd5", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 0 ], [ 0, 16, 0, "AORTIC INSUFFICIENCY\\RE-DO STERNOTOMY; AORTIC VALVE REPLACEMENT " ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose death status is 0 and primary disease is aortic insufficiency/re-do sternotomy; aortic valve replacement.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"AORTIC INSUFFICIENCY\\RE-DO STERNOTOMY; AORTIC VALVE REPLACEMENT \"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "death", "status", "is", "0", "and", "primary", "disease", "is", "aortic", "insufficiency", "/", "re", "-", "do", "sternotomy", ";", "aortic", "valve", "replacement", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"AORTIC", "INSUFFICIENCY\\RE-DO", "STERNOTOMY;", "AORTIC", "VALVE", "REPLACEMENT", "", "", "\"" ], "answer": [ "1" ] }, { "key": "048d0ff6b504840d3588dc9a9c25604c", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 4, 2, 43 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of dead patients who were less than 43 years of age.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"AGE\" < \"43\"", "question_refine_tok": [ "provide", "the", "number", "of", "dead", "patients", "who", "were", "less", "than", "43", "years", "of", "age", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"" ], "answer": [ "780" ] }, { "key": "90d554b6e10b435fb43351c3105183f3", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 22, 2, 2123 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of dead patients who were admitted to hospital before 2123.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2123\"", "question_refine_tok": [ "calculate", "the", "number", "of", "dead", "patients", "who", "were", "admitted", "to", "hospital", "before", "2123", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2123\"" ], "answer": [ "3492" ] }, { "key": "abaad794f2c8a34d9d287b6128688cc8", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 3, 0, "Ac diastolic hrt failure" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose death status is 0 and diagnosis short title is ac diastolic heart failure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Ac diastolic hrt failure\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "whose", "death", "status", "is", "0", "and", "diagnosis", "short", "title", "is", "ac", "diastolic", "heart", "failure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Ac", "diastolic", "hrt", "failure\"" ], "answer": [ "207" ] }, { "key": "a0096afa6e0df0f8dee83cc6ad39b510", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 3, 0, "Epistaxis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with epistaxis have unspecified death status?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Epistaxis\"", "question_refine_tok": [ "how", "many", "patients", "with", "epistaxis", "have", "unspecified", "death", "status", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Epistaxis\"" ], "answer": [ "134" ] }, { "key": "93093c6a157686346ac1a429056360d6", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 3, 0, "Hx-rectal & anal malign" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients with a diagnoses of personal history of other malignant neoplasm of rectum, rectosigmoid junction and anus and are still alive.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Hx-rectal & anal malign\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "with", "a", "diagnoses", "of", "personal", "history", "of", "other", "malignant", "neoplasm", "of", "rectum", ",", "rectosigmoid", "junction", "and", "anus", "and", "are", "still", "alive", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Hx-rectal", "&", "anal", "malign\"" ], "answer": [ "44" ] }, { "key": "099eef47c1de13d69881354a8d6bcf98", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 3, 0, "BPH w/o urinary obs/LUTS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients whose death status is 0 and diagnoses title is bph w/o urinaryobs/luts.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"SHORT_TITLE\" = \"BPH w/o urinary obs/LUTS\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "whose", "death", "status", "is", "0", "and", "diagnoses", "title", "is", "bph", "w/o", "urinaryobs", "/", "luts", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"BPH", "w/o", "urinary", "obs/LUTS\"" ], "answer": [ "766" ] }, { "key": "03ea6a2d85bb58573fed1557472bfa36", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 3, 0, "Metabolic encephalopathy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with metabolic encephalopathy diagnoses are still alive?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Metabolic encephalopathy\"", "question_refine_tok": [ "how", "many", "patients", "with", "metabolic", "encephalopathy", "diagnoses", "are", "still", "alive", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Metabolic", "encephalopathy\"" ], "answer": [ "149" ] }, { "key": "8277ad242f4a67242afb6df8fa62a4b1", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 0, 15, 0, "DISCH-TRAN TO PSYCH HOSP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients were admitted through the emergency department and were discharged to discharge-transitioning to psychiatric hospital?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISCH-TRAN TO PSYCH HOSP\"", "question_refine_tok": [ "How", "many", "patients", "were", "admitted", "through", "the", "emergency", "department", "and", "were", "discharged", "to", "discharge-transitioning", "to", "psychiatric", "hospital", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISCH-TRAN", "TO", "PSYCH", "HOSP\"" ], "answer": [ "263" ] }, { "key": "0a1cd1f71bf51049de78aa0501e9fa78", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRANSFER FROM HOSP/EXTRAM" ], [ 0, 4, 2, 59 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of inpatient hospital admission patients who are less than 59 years old?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRANSFER FROM HOSP/EXTRAM\" AND DEMOGRAPHIC.\"AGE\" < \"59\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "inpatient", "hospital", "admission", "patients", "who", "are", "less", "than", "59", "years", "old", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRANSFER", "FROM", "HOSP/EXTRAM\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"59\"" ], "answer": [ "2481" ] }, { "key": "927bcc5acfc5a7c2f5b2ebf99de1cd47", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRSF WITHIN THIS FACILITY" ], [ 0, 4, 2, 59 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me with the number of patients less than 59 years who were transferred within the facility.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRSF WITHIN THIS FACILITY\" AND DEMOGRAPHIC.\"AGE\" < \"59\"", "question_refine_tok": [ "provide", "me", "with", "the", "number", "of", "patients", "less", "than", "59", "years", "who", "were", "transferred", "within", "the", "facility", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRSF", "WITHIN", "THIS", "FACILITY\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"59\"" ], "answer": [ "3" ] }, { "key": "a85f7ee77ab7acd707cc19c80b4acf63", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 0, 18, 2, 2071 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Count the number of patients born before 2071 who had an emergency room hospital admission.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2071\"", "question_refine_tok": [ "Count", "the", "number", "of", "patients", "born", "before", "2071", "who", "had", "an", "emergency", "room", "hospital", "admission", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2071\"" ], "answer": [ "6614" ] }, { "key": "ba3064e8b2f13a2448df23529f31de36", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRANSFER FROM HOSP/EXTRAM" ], [ 0, 22, 2, 2131 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with admission location as transfer from hosp/extram and were admitted before the year 2131?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRANSFER FROM HOSP/EXTRAM\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2131\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "admission", "location", "as", "transfer", "from", "hosp", "/", "extram", "and", "were", "admitted", "before", "the", "year", "2131", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRANSFER", "FROM", "HOSP/EXTRAM\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2131\"" ], "answer": [ "2378" ] }, { "key": "04221395dc9c6a9e5c880d1dc78a5031", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "DISCH-TRAN TO PSYCH HOSP" ], [ 0, 4, 2, 77 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are discharged from disch tran to psych hosp that are under age 77?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISCH-TRAN TO PSYCH HOSP\" AND DEMOGRAPHIC.\"AGE\" < \"77\"", "question_refine_tok": [ "how", "many", "patients", "are", "discharged", "from", "disch", "tran", "to", "psych", "hosp", "that", "are", "under", "age", "77", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISCH-TRAN", "TO", "PSYCH", "HOSP\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"77\"" ], "answer": [ "413" ] }, { "key": "bba6972bfb39756cdb923e4518ec3895", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SHORT TERM HOSPITAL" ], [ 0, 22, 2, 2182 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose discharge location is short term hospital and who were admitted to the hospital before year 2182.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SHORT TERM HOSPITAL\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2182\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "discharge", "location", "is", "short", "term", "hospital", "and", "who", "were", "admitted", "to", "the", "hospital", "before", "year", "2182", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SHORT", "TERM", "HOSPITAL\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2182\"" ], "answer": [ "1189" ] }, { "key": "0d2d4b9ce812c7d9805538e58b0de30e", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "ABDOMINAL PAIN" ], [ 0, 4, 2, 68 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with primary disease abdominal pain who were aged less than 68 years?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"ABDOMINAL PAIN\" AND DEMOGRAPHIC.\"AGE\" < \"68\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "primary", "disease", "abdominal", "pain", "who", "were", "aged", "less", "than", "68", "years", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ABDOMINAL", "PAIN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"68\"" ], "answer": [ "290" ] }, { "key": "074e5b4530d549289801849ce3cdde02", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "ABDOMINAL ABSCESS" ], [ 0, 4, 2, 68 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the total number of patients aged below 68 who had abdominal abscess as primary disease ", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"ABDOMINAL ABSCESS\" AND DEMOGRAPHIC.\"AGE\" < \"68\"", "question_refine_tok": [ "what", "is", "the", "total", "number", "of", "patients", "aged", "below", "68", "who", "had", "abdominal", "abscess", "as", "primary", "disease" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ABDOMINAL", "ABSCESS\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"68\"" ], "answer": [ "8" ] }, { "key": "8757aa09f5f4b407395c6608aecb69e0", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "BOWEL OBSTRUCTION" ], [ 0, 10, 1, 10 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients with bowel obstruction primary disease who have been admitted to hospital for more than 10 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BOWEL OBSTRUCTION\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"10\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "with", "bowel", "obstruction", "primary", "disease", "who", "have", "been", "admitted", "to", "hospital", "for", "more", "than", "10", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BOWEL", "OBSTRUCTION\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"10\"" ], "answer": [ "51" ] }, { "key": "9ff64e587978e15c158f7b6b80563161", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "UPPER GI BLEED" ], [ 0, 18, 2, 2112 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with primary disease upper gi bleed and are born before 2112?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"UPPER GI BLEED\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2112\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "primary", "disease", "upper", "gi", "bleed", "and", "are", "born", "before", "2112", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"UPPER", "GI", "BLEED\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2112\"" ], "answer": [ "397" ] }, { "key": "bb83ddfb2b58462bada823ae66a5bd95", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "GUILLAIN BARRE SYNDROME" ], [ 0, 18, 2, 2109 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients born before the year 2109 were primarily diagnosed for guillain barre syndrome?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GUILLAIN BARRE SYNDROME\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2109\"", "question_refine_tok": [ "How", "many", "patients", "born", "before", "the", "year", "2109", "were", "primarily", "diagnosed", "for", "guillain", "barre", "syndrome", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GUILLAIN", "BARRE", "SYNDROME\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2109\"" ], "answer": [ "2" ] }, { "key": "9fa63394a37b2f80110759367790716a", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SEPSIS" ], [ 0, 22, 2, 2203 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were admitted to the hospital before year 2203 with sepsis as the primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SEPSIS\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2203\"", "question_refine_tok": [ "how", "many", "patients", "were", "admitted", "to", "the", "hospital", "before", "year", "2203", "with", "sepsis", "as", "the", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SEPSIS\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2203\"" ], "answer": [ "1090" ] }, { "key": "a5b6345934da2a50fd6dd880ba5fb59a", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 16, 0, "GASTROINTESTINAL BLEED" ], [ 3, 6, 0, "TP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients have gastrointestinal bleed and tp drug route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GASTROINTESTINAL BLEED\" AND PRESCRIPTIONS.\"ROUTE\" = \"TP\"", "question_refine_tok": [ "How", "many", "patients", "have", "gastrointestinal", "bleed", "and", "tp", "drug", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GASTROINTESTINAL", "BLEED\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"TP\"" ], "answer": [ "164" ] }, { "key": "0047b985a745f591fd904a526f46c5ec", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 83 ], [ 0, 10, 1, 6 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "let me know the number of patients less than 83 years who stayed in hospital for more than 6 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"83\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"6\"", "question_refine_tok": [ "let", "me", "know", "the", "number", "of", "patients", "less", "than", "83", "years", "who", "stayed", "in", "hospital", "for", "more", "than", "6", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"83\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"6\"" ], "answer": [ "19859" ] }, { "key": "0efb1f3ea07563c82ed22210954a7e05", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 72 ], [ 0, 19, 4, 2132.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get the number of patients who died in or before 2132 and were less than 72 years of age.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"72\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2132.0\"", "question_refine_tok": [ "Get", "the", "number", "of", "patients", "who", "died", "in", "or", "before", "2132", "and", "were", "less", "than", "72", "years", "of", "age", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"72\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2132.0\"" ], "answer": [ "2143" ] }, { "key": "aa3651ed4202392f2f09a7769737f61b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 83 ], [ 1, 3, 0, "Pneumococcal pneumonia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients less than 83 years of age who were diagnosed with pneumococcal pneumonia.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"83\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Pneumococcal pneumonia\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "less", "than", "83", "years", "of", "age", "who", "were", "diagnosed", "with", "pneumococcal", "pneumonia", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"83\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Pneumococcal", "pneumonia\"" ], "answer": [ "170" ] }, { "key": "0039685df6e3097e7f1e2742a86d106a", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 51 ], [ 1, 3, 0, "Preterm NEC 2500+g" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients below 51 years of age are diagnosed with preterm nec 2500+g?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"51\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Preterm NEC 2500+g\"", "question_refine_tok": [ "how", "many", "patients", "below", "51", "years", "of", "age", "are", "diagnosed", "with", "preterm", "nec", "2500", "+", "g", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"51\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Preterm", "NEC", "2500+g\"" ], "answer": [ "742" ] }, { "key": "0640f668a6444cfc4761651f76cfad7b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 81 ], [ 1, 4, 0, "Unspecified septicemia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients diagnosed with unspecified septicemia aged less than 81 years.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"81\" AND DIAGNOSES.\"LONG_TITLE\" = \"Unspecified septicemia\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "diagnosed", "with", "unspecified", "septicemia", "aged", "less", "than", "81", "years", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"81\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Unspecified", "septicemia\"" ], "answer": [ "2517" ] }, { "key": "0ebff2e801d7f07f735ed115ff6846e8", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 44 ], [ 2, 3, 0, "Oth uni salpingo-oophor" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are below 44 years of age and followed the procedure uni salpingo-oophor?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"44\" AND PROCEDURES.\"SHORT_TITLE\" = \"Oth uni salpingo-oophor\"", "question_refine_tok": [ "how", "many", "patients", "are", "below", "44", "years", "of", "age", "and", "followed", "the", "procedure", "uni", "salpingo", "-", "oophor", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"44\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Oth", "uni", "salpingo-oophor\"" ], "answer": [ "9" ] }, { "key": "870bc97deb5038b9b33dc9a92d1b7a84", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 30 ], [ 4, 4, 0, "abnormal" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients younger than 30 years who had abnormal lab test status.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"30\" AND LAB.\"FLAG\" = \"abnormal\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "younger", "than", "30", "years", "who", "had", "abnormal", "lab", "test", "status", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"30\"", "AND", "LAB.\"FLAG\"", "=", "\"abnormal\"" ], "answer": [ "9309" ] }, { "key": "8182d5043bd51f337b846751434757f1", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 41 ], [ 4, 4, 0, "delta" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients less than 41 years who have delta abnormal lab test status.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"41\" AND LAB.\"FLAG\" = \"delta\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "less", "than", "41", "years", "who", "have", "delta", "abnormal", "lab", "test", "status", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"41\"", "AND", "LAB.\"FLAG\"", "=", "\"delta\"" ], "answer": [ "2862" ] }, { "key": "aa0feba409fddd516dabb88f3e4e1131", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 85 ], [ 4, 6, 0, "Heparin, LMW" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients under the age of 85 had lab test named heparin,imw?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"85\" AND LAB.\"LABEL\" = \"Heparin, LMW\"", "question_refine_tok": [ "what", "number", "of", "patients", "under", "the", "age", "of", "85", "had", "lab", "test", "named", "heparin", ",", "imw", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"85\"", "AND", "LAB.\"LABEL\"", "=", "\"Heparin,", "LMW\"" ], "answer": [ "229" ] }, { "key": "9b6dfdf4c90e8cacd7a41b3d04f7e83e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 56 ], [ 4, 6, 0, "Sodium, Whole Blood" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among patients aged below 56, how many of them had a lab test for sodium, whole blood?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"56\" AND LAB.\"LABEL\" = \"Sodium, Whole Blood\"", "question_refine_tok": [ "among", "patients", "aged", "below", "56", ",", "how", "many", "of", "them", "had", "a", "lab", "test", "for", "sodium", ",", "whole", "blood", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"56\"", "AND", "LAB.\"LABEL\"", "=", "\"Sodium,", "Whole", "Blood\"" ], "answer": [ "6291" ] }, { "key": "0332dda726da118eaa7ca1bd76d407df", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 7 ], [ 1, 3, 0, "Single lb in-hosp w cs" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose hospital stay is above 7 days and diagnosed with single ib in-hosp w cs?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"7\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Single lb in-hosp w cs\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "hospital", "stay", "is", "above", "7", "days", "and", "diagnosed", "with", "single", "ib", "in", "-", "hosp", "w", "cs", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"7\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Single", "lb", "in-hosp", "w", "cs\"" ], "answer": [ "809" ] }, { "key": "08fc7705c2b867f49f66d8f30eeba98e", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 26 ], [ 1, 3, 0, "Joint replaced knee" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients with knee joint replacement diagnoses who were hospitalized for more than 26 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"26\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Joint replaced knee\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "with", "knee", "joint", "replacement", "diagnoses", "who", "were", "hospitalized", "for", "more", "than", "26", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"26\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Joint", "replaced", "knee\"" ], "answer": [ "27" ] }, { "key": "0c72214ea0e062654437473e15068aa3", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 7 ], [ 1, 3, 0, "Acidosis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients diagnosed for acidosis stayed in the hospital for more than 7 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"7\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Acidosis\"", "question_refine_tok": [ "what", "number", "of", "patients", "diagnosed", "for", "acidosis", "stayed", "in", "the", "hospital", "for", "more", "than", "7", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"7\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Acidosis\"" ], "answer": [ "2113" ] }, { "key": "9199807b13cd1e04881141d5212e9079", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 7 ], [ 1, 3, 0, "Alzheimer's disease" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients diagnosed with alzheimer's disease who were admitted for more than 7 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"7\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Alzheimer's disease\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "diagnosed", "with", "alzheimer", "'s", "disease", "who", "were", "admitted", "for", "more", "than", "7", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"7\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Alzheimer's", "disease\"" ], "answer": [ "206" ] }, { "key": "9414e815191f08f8729bdad33e6d48be", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 26 ], [ 3, 4, 0, "Lorazepam" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Look for the number of patients on a lorazepam prescription who stayed in hospital for more than 26 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"26\" AND PRESCRIPTIONS.\"DRUG\" = \"Lorazepam\"", "question_refine_tok": [ "Look", "for", "the", "number", "of", "patients", "on", "a", "lorazepam", "prescription", "who", "stayed", "in", "hospital", "for", "more", "than", "26", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"26\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Lorazepam\"" ], "answer": [ "1843" ] }, { "key": "87cb983ef7e62ae3398a8fd6ef8c6b16", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 16 ], [ 3, 4, 0, "SW" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose hospital stay is above 16 days and with drug sw?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"16\" AND PRESCRIPTIONS.\"DRUG\" = \"SW\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "hospital", "stay", "is", "above", "16", "days", "and", "with", "drug", "sw", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"16\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"SW\"" ], "answer": [ "4561" ] }, { "key": "8e7a52d33c8a0a9838c49596461d2ca3", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 8 ], [ 3, 4, 0, "Acetylcysteine 20%" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "From the total number of patients treated with acetylcysteine 20%, calculate the number of those who had a hospital stay of more than 8 days", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"8\" AND PRESCRIPTIONS.\"DRUG\" = \"Acetylcysteine 20%\"", "question_refine_tok": [ "From", "the", "total", "number", "of", "patients", "treated", "with", "acetylcysteine", "20", "%", ",", "calculate", "the", "number", "of", "those", "who", "had", "a", "hospital", "stay", "of", "more", "than", "8", "days" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"8\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Acetylcysteine", "20%\"" ], "answer": [ "2632" ] }, { "key": "9192083f15618c3944fab5819282ce1f", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2148 ], [ 1, 3, 0, "Obesity NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients admitted before 2148 who are diagnosed with unspecified obesity.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2148\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Obesity NOS\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "admitted", "before", "2148", "who", "are", "diagnosed", "with", "unspecified", "obesity", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2148\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Obesity", "NOS\"" ], "answer": [ "657" ] }, { "key": "05c34fdbc7ab6c2cd547aa61e361051c", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2175 ], [ 1, 3, 0, "Long-term use steroids" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of total number of patients admitted before 2157, how many of them had long-term use of steroids?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2175\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Long-term use steroids\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "admitted", "before", "2157", ",", "how", "many", "of", "them", "had", "long-term", "use", "of", "steroids", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2175\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Long-term", "use", "steroids\"" ], "answer": [ "550" ] }, { "key": "8c88f561e27ab905c51f995f000f9920", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2187 ], [ 1, 3, 0, "Other lung disease NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted before 2187 are diagnosed with other lung disease nec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2187\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Other lung disease NEC\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "before", "2187", "are", "diagnosed", "with", "other", "lung", "disease", "nec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2187\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Other", "lung", "disease", "NEC\"" ], "answer": [ "544" ] }, { "key": "80d0e73a185289625d60921e65b0f2d8", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2172 ], [ 1, 4, 0, "Contact dermatitis and other eczema, unspecified cause" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Among the patients admitted before the year 2172, how many had contact dermatitis and other eczema with an unspecified cause?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2172\" AND DIAGNOSES.\"LONG_TITLE\" = \"Contact dermatitis and other eczema, unspecified cause\"", "question_refine_tok": [ "Among", "the", "patients", "admitted", "before", "the", "year", "2172", ",", "how", "many", "had", "contact", "dermatitis", "and", "other", "eczema", "with", "an", "unspecified", "cause", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2172\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Contact", "dermatitis", "and", "other", "eczema,", "unspecified", "cause\"" ], "answer": [ "101" ] }, { "key": "9fcbd4ae3ba6806cdd14afc747ca9ca3", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2179 ], [ 1, 4, 0, "Pressure ulcer, stage II" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted before 2179 and diagnosed with pressure ulcer, stage ii?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2179\" AND DIAGNOSES.\"LONG_TITLE\" = \"Pressure ulcer, stage II\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "before", "2179", "and", "diagnosed", "with", "pressure", "ulcer", ",", "stage", "ii", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2179\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Pressure", "ulcer,", "stage", "II\"" ], "answer": [ "303" ] }, { "key": "a653e009b44f6b042361642164f758e9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2174 ], [ 1, 4, 0, "Sepsis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Look for the patients admitted before 2174 that were diagnosed with sepsis.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2174\" AND DIAGNOSES.\"LONG_TITLE\" = \"Sepsis\"", "question_refine_tok": [ "Look", "for", "the", "patients", "admitted", "before", "2174", "that", "were", "diagnosed", "with", "sepsis", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2174\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Sepsis\"" ], "answer": [ "853" ] }, { "key": "0eb32f428a68a982f36ee3562f936b6e", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2155 ], [ 2, 3, 0, "Dx ultrasound-heart" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the total number of patients admitted before the year 2155 who had dx ultrasound-heart?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2155\" AND PROCEDURES.\"SHORT_TITLE\" = \"Dx ultrasound-heart\"", "question_refine_tok": [ "What", "is", "the", "total", "number", "of", "patients", "admitted", "before", "the", "year", "2155", "who", "had", "dx", "ultrasound-heart", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2155\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Dx", "ultrasound-heart\"" ], "answer": [ "1716" ] }, { "key": "a77d67ccd0a105807ef5c3fb6cb2c019", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2146 ], [ 2, 3, 0, "Cardiopulm resuscita NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Provide the number of patients who were admitted before the year 2146 and had procedure short title as cardiopulm resuscita nos.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2146\" AND PROCEDURES.\"SHORT_TITLE\" = \"Cardiopulm resuscita NOS\"", "question_refine_tok": [ "Provide", "the", "number", "of", "patients", "who", "were", "admitted", "before", "the", "year", "2146", "and", "had", "procedure", "short", "title", "as", "cardiopulm", "resuscita", "nos", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2146\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Cardiopulm", "resuscita", "NOS\"" ], "answer": [ "286" ] }, { "key": "a8e264d96300a69aa8dea07d6d507559", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2150 ], [ 2, 4, 0, "Hemodialysis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of total number of patients admitted before the year 2150, how many of them had hemodialysis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2150\" AND PROCEDURES.\"LONG_TITLE\" = \"Hemodialysis\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "admitted", "before", "the", "year", "2150", ",", "how", "many", "of", "them", "had", "hemodialysis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2150\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Hemodialysis\"" ], "answer": [ "1025" ] }, { "key": "9fbf9e43a2cf665e8cf12a1fddb6f556", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2187 ], [ 2, 4, 0, "(Aorto)coronary bypass of one coronary artery" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "specify the number of patients who were admitted in the year less that 2187 and had (aorto)coronary bypass of one coronary artery", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2187\" AND PROCEDURES.\"LONG_TITLE\" = \"(Aorto)coronary bypass of one coronary artery\"", "question_refine_tok": [ "specify", "the", "number", "of", "patients", "who", "were", "admitted", "in", "the", "year", "less", "that", "2187", "and", "had", " ", "(", "aorto)coronary", "bypass", "of", "one", "coronary", "artery" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2187\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"(Aorto)coronary", "bypass", "of", "one", "coronary", "artery\"" ], "answer": [ "808" ] }, { "key": "025c24d1e68c126598c7046e63752ab8", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2162 ], [ 2, 4, 0, "Percutaneous [endoscopic] gastrojejunostomy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of total number of patients admitted before the year 2162, how many had percutaneous (endoscopic) gastrojejunostomy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2162\" AND PROCEDURES.\"LONG_TITLE\" = \"Percutaneous [endoscopic] gastrojejunostomy\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "admitted", "before", "the", "year", "2162", ",", "how", "many", "had", "percutaneous", "(", "endoscopic", ")", "gastrojejunostomy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2162\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Percutaneous", "[endoscopic]", "gastrojejunostomy\"" ], "answer": [ "95" ] }, { "key": "aa7c9f0f083c93b10c5c1410673a02c2", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 22, 2, 2174 ], [ 3, 4, 0, "Cefpodoxime Proxetil" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients who were admitted before the year 2174 and given the drug cefpodoxime proxetil.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2174\" AND PRESCRIPTIONS.\"DRUG\" = \"Cefpodoxime Proxetil\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "who", "were", "admitted", "before", "the", "year", "2174", "and", "given", "the", "drug", "cefpodoxime", "proxetil", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2174\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Cefpodoxime", "Proxetil\"" ], "answer": [ "326" ] }, { "key": "aac4912698c7b291c95cb3f2419634a6", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Atriovent block complete" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose diagnosis short title is atriovent block complete and drug type is base.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Atriovent block complete\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "diagnosis", "short", "title", "is", "atriovent", "block", "complete", "and", "drug", "type", "is", "base", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Atriovent", "block", "complete\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "464" ] }, { "key": "0c29bb8002f39c1b47df9dd0077c7ef2", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Physical restrain status" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with physical restrain status were treated with base drug?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Physical restrain status\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "how", "many", "patients", "with", "physical", "restrain", "status", "were", "treated", "with", "base", "drug", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Physical", "restrain", "status\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "224" ] }, { "key": "968b80474dc7adef444d9996b1f46a94", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Bleed esoph var oth dis" ], [ 3, 3, 0, "MAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients with bleed esoph var other disease who were treated with main drug ", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Bleed esoph var oth dis\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"MAIN\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "with", "bleed", "esoph", "var", "other", "disease", "who", "were", "treated", "with", "main", "drug" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Bleed", "esoph", "var", "oth", "dis\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"MAIN\"" ], "answer": [ "285" ] }, { "key": "a9d92fdd4552de6119472381096c41d5", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Diaphragmatic hernia" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with drug type base were diagnosed with diaphragmatic hernia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Diaphragmatic hernia\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "how", "many", "patients", "with", "drug", "type", "base", "were", "diagnosed", "with", "diaphragmatic", "hernia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Diaphragmatic", "hernia\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "578" ] }, { "key": "b9e81a7036c0f844cb0892ae06fa0c72", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Rec depr psych-psychotic" ], [ 3, 6, 0, "PO/NG" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients have diagnosis short title as rec depr psych-psychotic and drug route as po/ng?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Rec depr psych-psychotic\" AND PRESCRIPTIONS.\"ROUTE\" = \"PO/NG\"", "question_refine_tok": [ "what", "number", "of", "patients", "have", "diagnosis", "short", "title", "as", "rec", "depr", "psych", "-", "psychotic", "and", "drug", "route", "as", "po", "/", "ng", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Rec", "depr", "psych-psychotic\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"PO/NG\"" ], "answer": [ "4" ] }, { "key": "a71d8a20f3c1c0d0fc6a9372df547def", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 3, 0, "Dysphagia NOS" ], [ 4, 6, 0, "Ketone" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the patients who have to be tested for ketones with diagnosis of dysphagia nos.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Dysphagia NOS\" AND LAB.\"LABEL\" = \"Ketone\"", "question_refine_tok": [ "find", "the", "patients", "who", "have", "to", "be", "tested", "for", "ketones", "with", "diagnosis", "of", "dysphagia", "nos", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Dysphagia", "NOS\"", "AND", "LAB.\"LABEL\"", "=", "\"Ketone\"" ], "answer": [ "311" ] }, { "key": "0d8e3bc0c9b32c93056a71cbc2e7882e", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 4, 0, "Personal history of colonic polyps" ], [ 4, 4, 0, "abnormal" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients who were diagnosed with personal history of colonic polyps and lab test result is abnormal.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Personal history of colonic polyps\" AND LAB.\"FLAG\" = \"abnormal\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "who", "were", "diagnosed", "with", "personal", "history", "of", "colonic", "polyps", "and", "lab", "test", "result", "is", "abnormal", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Personal", "history", "of", "colonic", "polyps\"", "AND", "LAB.\"FLAG\"", "=", "\"abnormal\"" ], "answer": [ "274" ] }, { "key": "979b37be2f3e1e3afc9d8298e975b5a1", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 4, 0, "Seroma complicating a procedure" ], [ 4, 8, 0, "Hematology" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients categorized under hematology lab test who have been diagnosed with seroma complicating a procedure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Seroma complicating a procedure\" AND LAB.\"CATEGORY\" = \"Hematology\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "categorized", "under", "hematology", "lab", "test", "who", "have", "been", "diagnosed", "with", "seroma", "complicating", "a", "procedure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Seroma", "complicating", "a", "procedure\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Hematology\"" ], "answer": [ "79" ] }, { "key": "9ce3e6d4028ec80eb96214edc77b6496", "format": { "table": [ 0, 3, 4 ], "cond": [ [ 3, 3, 0, "MAIN" ], [ 4, 6, 0, "Sodium, Urine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients had a lab test for sodium urine and were treated with a base drug?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE PRESCRIPTIONS.\"DRUG_TYPE\" = \"MAIN\" AND LAB.\"LABEL\" = \"Sodium, Urine\"", "question_refine_tok": [ "How", "many", "patients", "had", "a", "lab", "test", "for", "sodium", "urine", "and", "were", "treated", "with", "a", "base", "drug", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"MAIN\"", "AND", "LAB.\"LABEL\"", "=", "\"Sodium,", "Urine\"" ], "answer": [ "10318" ] }, { "key": "0f8c99adf2a5dc590120e3fc5f613dbc", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 11 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "what is the insurance and primary disease of the patient id 2560?", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "insurance", "and", "primary", "disease", "of", "the", "patient", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "Private" ] }, { "key": "0baa58e5517b4fcb7f72da30a3aac78f", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 3 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "provide the admission time and marital status of subject id 6983.", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "provide", "the", "admission", "time", "and", "marital", "status", "of", "subject", "i", "d", "6983", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "MARRIED", "MARRIED" ] }, { "key": "a67c695125c7528403160bb8cda092c5", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 81923 ] ], "agg_col": [ [ 0, 11 ] ], "sel": 0 }, "question_refine": "find the insurance of subject id 81923.", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"81923\"", "question_refine_tok": [ "find", "the", "insurance", "of", "subject", " ", "i", "d", "81923", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"81923\"" ], "answer": [ "Medicaid" ] }, { "key": "9bfdaf5eab2c02d8ca8b4d3868f647de", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 81923 ] ], "agg_col": [ [ 0, 5 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "Let me know the birth date and long title of procedure for patient with patient id 81923.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",PROCEDURES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"81923\"", "question_refine_tok": [ "Let", "me", "know", "the", "birth", "date", "and", "long", "title", "of", "procedure", "for", "patient", "with", "patient", "id", "81923", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",PROCEDURES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"81923\"" ], "answer": [ "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00", "2121-03-31 00:00:00" ] }, { "key": "0de72540235585ad871c25fec25eb251", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 29961 ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "mention the admission type of patient with patinet id 29961?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"29961\"", "question_refine_tok": [ "mention", "the", "admission", "type", "of", "patient", "with", "patinet", "i", "d", "29961", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"29961\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "9dd44561bfa5bd9f73dfe4899716bc2f", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 62296 ] ], "agg_col": [ [ 0, 9 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "for patient id 62296, specify the type of admission and icd9 code", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"62296\"", "question_refine_tok": [ "for", "patient", "i", "d", "62296", ",", "specify", "the", "type", "of", "admission", "and", "icd9", "code" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"62296\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "a56ec4b79f7a126662d66143bb58778c", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 62296 ] ], "agg_col": [ [ 0, 11 ], [ 0, 17 ] ], "sel": 0 }, "question_refine": "when did patient id 62296 die? specify date of death and insurance", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DOD\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"62296\"", "question_refine_tok": [ "when", "did", "patient", "i", "d", "62296", "die", "?", "specify", "date", "of", "death", "and", "insurance" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DOD\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"62296\"" ], "answer": [ "Medicare" ] }, { "key": "9dd26663715f8b95ce884e287fa2cf46", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15898 ] ], "agg_col": [ [ 0, 3 ], [ 0, 14 ] ], "sel": 0 }, "question_refine": "provide me the marital status and location of admission for patient with patient id 15898.", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15898\"", "question_refine_tok": [ "provide", "me", "the", "marital", "status", "and", "location", "of", "admission", "for", "patient", "with", "patient", "i", "d", "15898", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15898\"" ], "answer": [ "MARRIED" ] }, { "key": "a54ae2601c44ed2b62c5ebb49a3e2bc1", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15898 ] ], "agg_col": [ [ 0, 6 ], [ 0, 11 ] ], "sel": 0 }, "question_refine": "what is the gender and insurance of patient id 15898?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15898\"", "question_refine_tok": [ "what", "is", "the", "gender", "and", "insurance", "of", "patient", "i", "d", "15898", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15898\"" ], "answer": [ "M" ] }, { "key": "9443e783a3381f9fb38fb35508104e41", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15898 ] ], "agg_col": [ [ 0, 9 ], [ 0, 21 ] ], "sel": 0 }, "question_refine": "for patient id 15898, specify the type of admission along-with discharge time.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DISCHTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15898\"", "question_refine_tok": [ "for", "patient", "i", "d", "15898", ",", "specify", "the", "type", "of", "admission", "along", "-", "with", "discharge", "time", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DISCHTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15898\"" ], "answer": [ "EMERGENCY" ] }, { "key": "a694708e8c8e1e881b4f7f3ba9eb3515", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15898 ] ], "agg_col": [ [ 0, 11 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "specify the discharge location and insurance details of patients id 15898", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15898\"", "question_refine_tok": [ "specify", "the", "discharge", "location", "and", "insurance", "details", "of", "patients", "i", "d", "15898" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15898\"" ], "answer": [ "Private" ] }, { "key": "bb0ca9729b899a9e0d95157686fd1e6d", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 7273 ] ], "agg_col": [ [ 0, 9 ], [ 4, 4 ] ], "sel": 0 }, "question_refine": "provide me the type of admission and abnormal lab test status for the patient with patient id 7273.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"FLAG\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"7273\"", "question_refine_tok": [ "provide", "me", "the", "type", "of", "admission", "and", "abnormal", "lab", "test", "status", "for", "the", "patient", "with", "patient", "i", "d", "7273", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"FLAG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"7273\"" ], "answer": [ "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN" ] }, { "key": "0a1214e9a3a0b594551a1bfd09e5ab34", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 8990 ] ], "agg_col": [ [ 0, 11 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "tell me the primary disease and health insurance of patient with patient id 8990.", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"8990\"", "question_refine_tok": [ "tell", "me", "the", "primary", "disease", "and", "health", "insurance", "of", "patient", "with", "patient", "i", "d", "8990", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"8990\"" ], "answer": [ "Medicare", "Medicare", "Medicare" ] }, { "key": "83e3314b9aa82aaf732ff1c45a51d195", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 74032 ] ], "agg_col": [ [ 0, 3 ], [ 0, 8 ] ], "sel": 0 }, "question_refine": "Is the subject id 74032 married, find his religion ?", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"RELIGION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"74032\"", "question_refine_tok": [ "Is", "the", "subject", "id", "74032", "married", ",", "find", "his", "religion", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"RELIGION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"74032\"" ], "answer": [ "MARRIED", "MARRIED" ] }, { "key": "0ffc8a41b8b94e7bc01da17aac9180bf", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 74032 ] ], "agg_col": [ [ 0, 8 ], [ 0, 17 ] ], "sel": 0 }, "question_refine": "for patient id 74032, specify the religion and date of death", "sql": "SELECT DEMOGRAPHIC.\"RELIGION\",DEMOGRAPHIC.\"DOD\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"74032\"", "question_refine_tok": [ "for", "patient", "i", "d", "74032", ",", "specify", "the", "religion", "and", "date", "of", "death" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"RELIGION\",DEMOGRAPHIC.\"DOD\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"74032\"" ], "answer": [ "CATHOLIC", "CATHOLIC" ] }, { "key": "96eb14b8712f7434b707c60b571e1fab", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 74032 ] ], "agg_col": [ [ 0, 9 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "Report to me the type of admission and long title of diagnoses for patient with patient id 74032.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"74032\"", "question_refine_tok": [ "Report", "to", "me", "the", "type", "of", "admission", "and", "long", "title", "of", "diagnoses", "for", "patient", "with", "patient", "id", "74032", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"74032\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "ELECTIVE", "ELECTIVE", "ELECTIVE" ] }, { "key": "8a5fa1893e263b7824be6154da85bc46", "format": { "table": [ 1, 3 ], "cond": [ [ 1, 0, 0, 74032 ] ], "agg_col": [ [ 1, 3 ], [ 3, 3 ] ], "sel": 0 }, "question_refine": "for patient id 74032, specify the icd9 code and type of drug he was treated with.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",PRESCRIPTIONS.\"DRUG_TYPE\" FROM DIAGNOSES INNER JOIN PRESCRIPTIONS on DIAGNOSES.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SUBJECT_ID\" = \"74032\"", "question_refine_tok": [ "for", "patient", "i", "d", "74032", ",", "specify", "the", "icd9", "code", "and", "type", "of", "drug", "he", "was", "treated", "with", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",PRESCRIPTIONS.\"DRUG_TYPE\"", "FROM", "DIAGNOSES", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DIAGNOSES.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"74032\"" ], "answer": [ "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hypothyroidism NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Subarachnoid hemorrhage", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Postprocedural fever", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Oral soft tissue dis NEC", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral hemorrhage", "Intracerebral 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"Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Obstructiv hydrocephalus", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Protein-cal malnutr NOS", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush", "Thrush" ] }, { "key": "8afc8483734580cedaa6752df314019b", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 21796 ] ], "agg_col": [ [ 0, 9 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "give the admission type and procedure icd9 code of subject id 21796.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"21796\"", "question_refine_tok": [ "give", "the", "admission", "type", "and", "procedure", "icd9", "code", "of", "subject", "i", "d", "21796", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"21796\"" ], "answer": [ "NEWBORN" ] }, { "key": "a6a732ecc77a93f6fac9453d69cce42b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 21796 ] ], "agg_col": [ [ 0, 11 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "what is the insurance and diagnosis icd9 code of subject id 21796?", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"21796\"", "question_refine_tok": [ "what", "is", "the", "insurance", "and", "diagnosis", "icd9", "code", "of", "subject", "i", "d", "21796", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"21796\"" ], "answer": [ "Medicaid", "Medicaid", "Medicaid" ] }, { "key": "83d32631dfda27dba407f6d734b73fa0", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 3623 ] ], "agg_col": [ [ 0, 12 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "Specify the ethnic origin of patient id 3623 along with the primary disease", "sql": "SELECT DEMOGRAPHIC.\"ETHNICITY\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"3623\"", "question_refine_tok": [ "Specify", "the", "ethnic", "origin", "of", "patient", "id", "3623", "along", "with", "the", "primary", "disease" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ETHNICITY\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"3623\"" ], "answer": [ "WHITE", "WHITE" ] }, { "key": "0d961118addaebaa19d6836fa18f8533", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 3623 ] ], "agg_col": [ [ 0, 13 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "what is the death status and procedure for the patient id 3623?", "sql": "SELECT DEMOGRAPHIC.\"EXPIRE_FLAG\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"3623\"", "question_refine_tok": [ "what", "is", "the", "death", "status", "and", "procedure", "for", "the", "patient", "i", "d", "3623", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"EXPIRE_FLAG\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"3623\"" ], "answer": [ "1", "1", "1", "1", "1", "1", "1" ] }, { "key": "0937cf4727c2462f5e8abdd61cd9d4ae", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 94762 ] ], "agg_col": [ [ 0, 17 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "Find the time of admission and date of death for the patient with patient id 94762.", "sql": "SELECT DEMOGRAPHIC.\"DOD\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"94762\"", "question_refine_tok": [ "Find", "the", "time", "of", "admission", "and", "date", "of", "death", "for", "the", "patient", "with", "patient", "id", "94762", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOD\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"94762\"" ], "answer": [ "2165-06-24 00:00:00", "2165-06-24 00:00:00" ] }, { "key": "b9aa179b2e1b13244a6c6d611d1c568b", "format": { "table": [ 2, 3 ], "cond": [ [ 2, 0, 0, 52012 ] ], "agg_col": [ [ 2, 2 ], [ 3, 3 ] ], "sel": 0 }, "question_refine": "for patient id 52012, specify icd9 code and drug type he was treated with. ", "sql": "SELECT PROCEDURES.\"ICD9_CODE\",PRESCRIPTIONS.\"DRUG_TYPE\" FROM PROCEDURES INNER JOIN PRESCRIPTIONS on PROCEDURES.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PROCEDURES.\"SUBJECT_ID\" = \"52012\"", "question_refine_tok": [ "for", "patient", "i", "d", "52012", ",", "specify", "icd9", "code", "and", "drug", "type", "he", "was", "treated", "with", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\",PRESCRIPTIONS.\"DRUG_TYPE\"", "FROM", "PROCEDURES", "INNER", "JOIN", "PRESCRIPTIONS", "on", "PROCEDURES.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"52012\"" ], "answer": [ "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611", "8611" ] }, { "key": "02c34ef8864566dbd0a9c9ad006c1b21", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 813 ] ], "agg_col": [ [ 0, 16 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find the primary disease and admission time of subject id 813.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"813\"", "question_refine_tok": [ "find", "the", "primary", "disease", "and", "admission", "time", "of", "subject", "i", "d", "813", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"813\"" ], "answer": [ "GASTROINTESTINAL BLEED" ] }, { "key": "9caa2cf0a890f946d83543002a038823", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 18480 ] ], "agg_col": [ [ 0, 3 ] ], "sel": 0 }, "question_refine": "specify the marital status of patient id 18480", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18480\"", "question_refine_tok": [ "specify", "the", "marital", "status", "of", "patient", "i", "d", "18480" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18480\"" ], "answer": [ "MARRIED" ] }, { "key": "8df86af35155206db971854cf41e6139", "format": { "table": [ 2 ], "cond": [ [ 2, 0, 0, 18480 ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "specify the icd9 code for patient id 18480", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"SUBJECT_ID\" = \"18480\"", "question_refine_tok": [ "specify", "the", "icd9", "code", "for", "patient", "i", "d", "18480" ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"18480\"" ], "answer": [ "AICD check" ] }, { "key": "96c7391dfa5656e7563b51eacaee15a7", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 18480 ] ], "agg_col": [ [ 0, 9 ], [ 4, 6 ] ], "sel": 0 }, "question_refine": "find out the type of admission and lab test ordered for patient with patient id 18480.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"LABEL\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18480\"", "question_refine_tok": [ "find", "out", "the", "type", "of", "admission", "and", "lab", "test", "ordered", "for", "patient", "with", "patient", "i", "d", "18480", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"LABEL\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18480\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "0d831e485ec42f39a9ea116cfdbc75d8", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 18480 ] ], "agg_col": [ [ 0, 16 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "specify primary disease and icd9 code of patient id 18480", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18480\"", "question_refine_tok": [ "specify", "primary", "disease", "and", "icd9", "code", "of", "patient", "i", "d", "18480" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18480\"" ], "answer": [ "VENTRICULAR TACHYCARDIA" ] }, { "key": "9eb795c180ef3542b20bf25bf1068a44", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 23602 ] ], "agg_col": [ [ 0, 4 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "specify the age of patient id 23602 along-with duration of hospital stay", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"23602\"", "question_refine_tok": [ "specify", "the", "age", "of", "patient", "i", "d", "23602", "along", "-", "with", "duration", "of", "hospital", "stay" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"23602\"" ], "answer": [ "77" ] }, { "key": "8238d13af1c7221b7d779d9fef77afac", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 990 ] ], "agg_col": [ [ 0, 6 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "What is the gender and number of days of hospital stay of subject id 990?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"990\"", "question_refine_tok": [ "What", "is", "the", "gender", "and", "number", "of", "days", "of", "hospital", "stay", "of", "subject", "id", "990", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"990\"" ], "answer": [ "F" ] }, { "key": "85e956546e153bf735b2920719b34d1a", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 16438 ] ], "agg_col": [ [ 0, 12 ] ], "sel": 0 }, "question_refine": "which ethnic background does the patient with patient id 16438 belong to?", "sql": "SELECT DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"16438\"", "question_refine_tok": [ "which", "ethnic", "background", "does", "the", "patient", "with", "patient", "i", "d", "16438", "belong", "to", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"16438\"" ], "answer": [ "OTHER" ] }, { "key": "8b62448995e510e40daf7f3d776d9ce3", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 16438 ] ], "agg_col": [ [ 0, 5 ], [ 0, 9 ] ], "sel": 0 }, "question_refine": "specify the birthdate and admission type of patient id 16438", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"16438\"", "question_refine_tok": [ "specify", "the", "birthdate", "and", "admission", "type", "of", "patient", "i", "d", "16438" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"16438\"" ], "answer": [ "2049-06-06 00:00:00" ] }, { "key": "9261992dc4b198991f00da4ec688e081", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 9271 ] ], "agg_col": [ [ 0, 11 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "find out the short title of diagnoses and health insurance by which patient with patient id 9271 is covered.", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"9271\"", "question_refine_tok": [ "find", "out", "the", "short", "title", "of", "diagnoses", "and", "health", "insurance", "by", "which", "patient", "with", "patient", "i", "d", "9271", "is", "covered", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"9271\"" ], "answer": [ "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare" ] }, { "key": "8298e685eb1bddee9cd3852aeeac2591", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2110 ] ], "agg_col": [ [ 0, 2 ] ], "sel": 0 }, "question_refine": "tell me the name of patient with patient id 2110.", "sql": "SELECT DEMOGRAPHIC.\"NAME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2110\"", "question_refine_tok": [ "tell", "me", "the", "name", "of", "patient", "with", "patient", "i", "d", "2110", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2110\"" ], "answer": [ "Chandra Schulman" ] }, { "key": "ae0a0d761414ab17b03de7bb99fefdf0", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 2110 ] ], "agg_col": [ [ 0, 2 ], [ 4, 8 ] ], "sel": 0 }, "question_refine": "For patient id 2110, specify name and lab test category", "sql": "SELECT DEMOGRAPHIC.\"NAME\",LAB.\"CATEGORY\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2110\"", "question_refine_tok": [ "For", "patient", "id", "2110", ",", "specify", "name", "and", "lab", "test", "category" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\",LAB.\"CATEGORY\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2110\"" ], "answer": [ "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman", "Chandra Schulman" ] }, { "key": "911a7e18c4158df6d085cde9accd23fa", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2110 ] ], "agg_col": [ [ 0, 6 ], [ 0, 11 ] ], "sel": 0 }, "question_refine": "find the gender of subject id 2110 and what type of insurance he has?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2110\"", "question_refine_tok": [ "find", "the", "gender", "of", "subject", "i", "d", "2110", "and", "what", "type", "of", "insurance", "he", "has", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2110\"" ], "answer": [ "F" ] }, { "key": "870d86f73c268c7bc4250688a84e6019", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 2110 ] ], "agg_col": [ [ 0, 16 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "let me know the diagnoses icd9 code and primary disease of patient with patient id 2110.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2110\"", "question_refine_tok": [ "let", "me", "know", "the", "diagnoses", "icd9", "code", "and", "primary", "disease", "of", "patient", "with", "patient", "i", "d", "2110", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2110\"" ], "answer": [ "NEWBORN", "NEWBORN", "NEWBORN" ] }, { "key": "858020d1729895a7067c676d9f0fb0cd", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 42820 ] ], "agg_col": [ [ 0, 6 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "specify gender and death status of patient id 42820", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"42820\"", "question_refine_tok": [ "specify", "gender", "and", "death", "status", "of", "patient", "i", "d", "42820" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"42820\"" ], "answer": [ "F", "F", "F", "F", "F", "F", "F" ] }, { "key": "94b7c34d08a1a683e0a44fc75d03d1ed", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 0, 0, 42820 ] ], "agg_col": [ [ 0, 15 ], [ 3, 2 ] ], "sel": 0 }, "question_refine": "what is the discharge location and icu stay id of subject id 42820?", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\",PRESCRIPTIONS.\"ICUSTAY_ID\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"42820\"", "question_refine_tok": [ "what", "is", "the", "discharge", "location", "and", "icu", "stay", "i", "d", "of", "subject", "i", "d", "42820", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\",PRESCRIPTIONS.\"ICUSTAY_ID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"42820\"" ], "answer": [ "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF", "SNF" ] }, { "key": "960022d3a73ef1ab54324b4e160c949f", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 55094 ] ], "agg_col": [ [ 0, 6 ], [ 0, 21 ] ], "sel": 0 }, "question_refine": "let me know the gender and time of discharge for patient with patient id 55094.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DISCHTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"55094\"", "question_refine_tok": [ "let", "me", "know", "the", "gender", "and", "time", "of", "discharge", "for", "patient", "with", "patient", "i", "d", "55094", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DISCHTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"55094\"" ], "answer": [ "M", "M", "M", "M" ] }, { "key": "1065d3da85adb5db505b96073e508383", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 55094 ] ], "agg_col": [ [ 0, 7 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "what is the language and admission time of patient id 55094?", "sql": "SELECT DEMOGRAPHIC.\"LANGUAGE\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"55094\"", "question_refine_tok": [ "what", "is", "the", "language", "and", "admission", "time", "of", "patient", "i", "d", "55094", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"LANGUAGE\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"55094\"" ], "answer": [ "ENGL", "ENGL", "ENGL", "ENGL" ] }, { "key": "970e9b038620185bfb8a00422ddfefa7", "format": { "table": [ 1 ], "cond": [ [ 1, 0, 0, 55094 ] ], "agg_col": [ [ 1, 2 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "get the short title as well as the icd9 code of diagnoses for patient with patient id 55094.", "sql": "SELECT DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"SHORT_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"SUBJECT_ID\" = \"55094\"", "question_refine_tok": [ "get", "the", "short", "title", "as", "well", "as", "the", "icd9", "code", "of", "diagnoses", "for", "patient", "with", "patient", "i", "d", "55094", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"55094\"" ], "answer": [ "4019", "5771", "30401", "2910", "30391", "5770", "45382", "51881", "V1241", "45621", "51881", "5722", "5789", "5793", "2851", "5723", "53019", "30401", "56731", "V1241", "99591", "56981", "30503", "79029", "4019", "42789", "2762", "5680", "78720", "5601", "E9300", "5070", "56881", "0389", "99662", "4019", "30390", "5770", "30401", "99592", "56981", "2639", "5849", "5569", "2763", "6930", "34839", "56722", "42732", "51881", "2859", "2639", "30390", "4019", "30400", "57451", "5768", "3051", "5772", "591", "56731", "0417", "5770", "5771" ] }, { "key": "84036ecc9eb02b475645146cd8e64bca", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 29767 ] ], "agg_col": [ [ 0, 3 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "for patient id 29767, specify the time of admission and marital status. ", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"29767\"", "question_refine_tok": [ "for", "patient", "i", "d", "29767", ",", "specify", "the", "time", "of", "admission", "and", "marital", "status", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"29767\"" ], "answer": [ "SINGLE", "SINGLE", "SINGLE", "SINGLE" ] }, { "key": "0ec6a8fdb77b6d9be68aa50953e66199", "format": { "table": [ 3 ], "cond": [ [ 3, 0, 0, 74345 ] ], "agg_col": [ [ 3, 4 ] ], "sel": 0 }, "question_refine": "which medication is prescribed to patient with patient id 74345?", "sql": "SELECT PRESCRIPTIONS.\"DRUG\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"SUBJECT_ID\" = \"74345\"", "question_refine_tok": [ "which", "medication", "is", "prescribed", "to", "patient", "with", "patient", "i", "d", "74345", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"DRUG\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"SUBJECT_ID\"", "=", "\"74345\"" ], "answer": [ "Topiramate (Topamax)", "Topiramate (Topamax)", "Metoprolol Succinate XL", "Acetaminophen", "Citalopram Hydrobromide", "Hydrochlorothiazide", "Sodium Chloride 0.9% Flush", "Lorazepam", "Aspirin", "Heparin", "Lorazepam", "Lorazepam" ] }, { "key": "049e61dadb202251580c94f778bee0d5", "format": { "table": [ 2 ], "cond": [ [ 2, 0, 0, 10317 ] ], "agg_col": [ [ 2, 2 ] ], "sel": 0 }, "question_refine": "find the procedure icd9 code for patient with patient id 10317.", "sql": "SELECT PROCEDURES.\"ICD9_CODE\" FROM PROCEDURES WHERE PROCEDURES.\"SUBJECT_ID\" = \"10317\"", "question_refine_tok": [ "find", "the", "procedure", "icd9", "code", "for", "patient", "with", "patient", "i", "d", "10317", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"10317\"" ], "answer": [ "4233" ] }, { "key": "acc06fbcc04ac4f4e727cebaf4062a9f", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 10317 ] ], "agg_col": [ [ 0, 9 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "Tell me the type of admission and status of death of the patient with patient id 10317.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"10317\"", "question_refine_tok": [ "Tell", "me", "the", "type", "of", "admission", "and", "status", "of", "death", "of", "the", "patient", "with", "patient", "id", "10317", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"10317\"" ], "answer": [ "EMERGENCY" ] }, { "key": "9c68aaf881646e162da53a41904bb65c", "format": { "table": [ 1, 2 ], "cond": [ [ 1, 0, 0, 25167 ] ], "agg_col": [ [ 1, 3 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "tell me short title of both diagnoses and procedure for patient with patient id 25167.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",PROCEDURES.\"SHORT_TITLE\" FROM DIAGNOSES INNER JOIN PROCEDURES on DIAGNOSES.HADM_ID = PROCEDURES.HADM_ID WHERE DIAGNOSES.\"SUBJECT_ID\" = \"25167\"", "question_refine_tok": [ "tell", "me", "short", "title", "of", "both", "diagnoses", "and", "procedure", "for", "patient", "with", "patient", "i", "d", "25167", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DIAGNOSES", "INNER", "JOIN", "PROCEDURES", "on", "DIAGNOSES.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"25167\"" ], "answer": [ "Pleural effusion NOS", "Pleural effusion NOS", "Pleural effusion NOS", "Pleural effusion NOS", "Depressive disorder NEC", "Depressive disorder NEC", "Depressive disorder NEC", "Depressive disorder NEC", "CHF NOS", "CHF NOS", "CHF NOS", "CHF NOS", "Atrial fibrillation", "Atrial fibrillation", "Atrial fibrillation", "Atrial fibrillation", "Int inf clstrdium dfcile", "Int inf clstrdium dfcile", "Int inf clstrdium dfcile", "Int inf clstrdium dfcile", "Esophageal reflux", "Esophageal reflux", "Esophageal reflux", "Esophageal reflux", "Pneumonia, organism NOS", "Pneumonia, organism NOS", "Hypertension NOS", "Hypertension NOS", "Surg compl-heart", "Surg compl-heart", "Depressive disorder NEC", "Depressive disorder NEC", "Urin tract infection NOS", "Urin tract infection NOS", "Anemia NOS", "Anemia NOS", "Subtrochanteric fx-close", "Subtrochanteric fx-close" ] }, { "key": "0ad552d2835d64ccd539c3214e2b6d7a", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 42067 ] ], "agg_col": [ [ 0, 3 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "specify the icd9 code and marital status of patient id 42067", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"42067\"", "question_refine_tok": [ "specify", "the", "icd9", "code", "and", "marital", "status", "of", "patient", "i", "d", "42067" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"42067\"" ], "answer": [ "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE" ] }, { "key": "86e4d08413e5636824dff09159204fb6", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 42067 ] ], "agg_col": [ [ 0, 9 ], [ 0, 14 ] ], "sel": 0 }, "question_refine": "get me the type and location of admission for patient with patient id 42067.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"42067\"", "question_refine_tok": [ "get", "me", "the", "type", "and", "location", "of", "admission", "for", "patient", "with", "patient", "i", "d", "42067", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"42067\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "0973408eb98d40424801e271ad64b414", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 31066 ] ], "agg_col": [ [ 0, 4 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "tell me the age and gender of patient with patient id 31066.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"31066\"", "question_refine_tok": [ "tell", "me", "the", "age", "and", "gender", "of", "patient", "with", "patient", "i", "d", "31066", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"31066\"" ], "answer": [ "63" ] }, { "key": "852b7afdced4dc86dc87fd466e175e75", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 31066 ] ], "agg_col": [ [ 0, 14 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "For patient id 31066, specify the time and location of admission", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"31066\"", "question_refine_tok": [ "For", "patient", "id", "31066", ",", "specify", "the", "time", "and", "location", "of", "admission" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"31066\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "9541bf65cdb398401106f5777b89c091", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 99936 ] ], "agg_col": [ [ 0, 10 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find out the admission time and days for which patient with patient id 99936 stayed in hospital.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"99936\"", "question_refine_tok": [ "find", "out", "the", "admission", "time", "and", "days", "for", "which", "patient", "with", "patient", "i", "d", "99936", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"99936\"" ], "answer": [ "7" ] }, { "key": "8356929e7065d7dfd4d5e6dace1ea0ea", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 1121 ] ], "agg_col": [ [ 0, 9 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "what is the admission type and death status of patient id 1121?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"1121\"", "question_refine_tok": [ "what", "is", "the", "admission", "type", "and", "death", "status", "of", "patient", "i", "d", "1121", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"1121\"" ], "answer": [ "URGENT", "ELECTIVE" ] }, { "key": "95f8a3f0cc5f6486ee39cf3575176b39", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 30011 ] ], "agg_col": [ [ 0, 3 ], [ 0, 12 ] ], "sel": 0 }, "question_refine": "what is the marital status and the ethnic group of subject id 30011?", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"30011\"", "question_refine_tok": [ "what", "is", "the", "marital", "status", "and", "the", "ethnic", "group", "of", "subject", "i", "d", "30011", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"30011\"" ], "answer": [ "SINGLE", "SINGLE", "SINGLE", "SINGLE", "SINGLE" ] }, { "key": "8e3b5d9cb36613efab2204fe93749087", "format": { "table": [ 1, 2 ], "cond": [ [ 1, 0, 0, 30011 ] ], "agg_col": [ [ 1, 4 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "for patient id 30011, specify the icd9 code and procedural long title.", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\",PROCEDURES.\"LONG_TITLE\" FROM DIAGNOSES INNER JOIN PROCEDURES on DIAGNOSES.HADM_ID = PROCEDURES.HADM_ID WHERE DIAGNOSES.\"SUBJECT_ID\" = \"30011\"", "question_refine_tok": [ "for", "patient", "i", "d", "30011", ",", "specify", "the", "icd9", "code", "and", "procedural", "long", "title", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\",PROCEDURES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "INNER", "JOIN", "PROCEDURES", "on", "DIAGNOSES.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"30011\"" ], "answer": [ "Cerebral aneurysm, nonruptured", "Cerebral aneurysm, nonruptured", "Other and unspecified hyperlipidemia", "Other and unspecified hyperlipidemia", "Osteoporosis, unspecified", "Osteoporosis, unspecified", "Urinary tract infection, site not specified", "Urinary tract infection, site not specified", "Unspecified essential hypertension", "Unspecified essential hypertension", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Pure hypercholesterolemia", "Pure hypercholesterolemia", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Unspecified essential hypertension", "Unspecified essential hypertension", "Cerebral aneurysm, nonruptured", "Cerebral aneurysm, nonruptured", "Osteoporosis, unspecified", "Osteoporosis, unspecified", "Pure hypercholesterolemia", "Pure hypercholesterolemia", "Depressive disorder, not elsewhere classified", "Depressive disorder, not elsewhere classified", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Unspecified gastritis and gastroduodenitis, without mention of hemorrhage", "Cerebral aneurysm, nonruptured", "Cerebral aneurysm, nonruptured", "Pure hypercholesterolemia", "Pure hypercholesterolemia", "Arthropathy, unspecified, site unspecified", "Arthropathy, unspecified, site unspecified", "Other postprocedural status", "Other postprocedural status", "Osteoporosis, unspecified", "Osteoporosis, unspecified", "Other and unspecified hyperlipidemia", "Cerebral aneurysm, nonruptured", "Headache", "Acute posthemorrhagic anemia", "Abnormality of gait", "Osteoporosis, unspecified", "Unspecified essential hypertension", "Headache", "Pure hypercholesterolemia", "Postprocedural fever", "Cerebral aneurysm, nonruptured", "Nausea with vomiting", "Unspecified essential hypertension", "Osteoporosis, unspecified" ] }, { "key": "8921336d23bf3a3ede96a68bc5d3734d", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 29541 ] ], "agg_col": [ [ 0, 15 ] ], "sel": 0 }, "question_refine": "find the location of discharge for patient with patient id 29541.", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"29541\"", "question_refine_tok": [ "find", "the", "location", "of", "discharge", "for", "patient", "with", "patient", "i", "d", "29541", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"29541\"" ], "answer": [ "HOME", "HOME HEALTH CARE" ] }, { "key": "a87a6ac4913e7104cfdc88d987607f7a", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 0, 0, 81254 ] ], "agg_col": [ [ 0, 10 ], [ 3, 2 ] ], "sel": 0 }, "question_refine": "what is the days of hospital stay and icu stay id of the patient id 81254?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",PRESCRIPTIONS.\"ICUSTAY_ID\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"81254\"", "question_refine_tok": [ "what", "is", "the", "days", "of", "hospital", "stay", "and", "icu", "stay", "i", "d", "of", "the", "patient", "i", "d", "81254", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",PRESCRIPTIONS.\"ICUSTAY_ID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"81254\"" ], "answer": [ "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2" ] }, { "key": "86e3e3a08a930e116dd8720746f1458a", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 9575 ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "provide me the primary disease and diagnosis short title of the patient with patient id 9575.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"9575\"", "question_refine_tok": [ "provide", "me", "the", "primary", "disease", "and", "diagnosis", "short", "title", "of", "the", "patient", "with", "patient", "i", "d", "9575", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"9575\"" ], "answer": [ "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "LEFT ACETABULAR FRACTURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE" ] }, { "key": "9c56b4c2897b0d7575a947df9de27348", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 93033 ] ], "agg_col": [ [ 0, 4 ], [ 0, 9 ] ], "sel": 0 }, "question_refine": "find out the age and admission type for patient with patient id 93033.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"93033\"", "question_refine_tok": [ "find", "out", "the", "age", "and", "admission", "type", "for", "patient", "with", "patient", "i", "d", "93033", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"93033\"" ], "answer": [ "49" ] }, { "key": "9aa3166df35ac8dd6c2128b208797557", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 17519 ] ], "agg_col": [ [ 0, 14 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "When was patient id 17519 admitted? Specify the time and location.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"17519\"", "question_refine_tok": [ "When", "was", "patient", "id", "17519", "admitted", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"17519\"" ], "answer": [ "EMERGENCY ROOM ADMIT" ] }, { "key": "059ccad9787c25c4d0b649ce90a7089a", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 65652 ] ], "agg_col": [ [ 0, 4 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "tell me the age and primary disease of patient with patient id 65652.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"65652\"", "question_refine_tok": [ "tell", "me", "the", "age", "and", "primary", "disease", "of", "patient", "with", "patient", "i", "d", "65652", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"65652\"" ], "answer": [ "20" ] }, { "key": "8318a358e23fc3e43d9c6c3cb70e75af", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 71798 ] ], "agg_col": [ [ 0, 10 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "provide the duration of hospital stay and procedure title for subject id 71798.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",PROCEDURES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"71798\"", "question_refine_tok": [ "provide", "the", "duration", "of", "hospital", "stay", "and", "procedure", "title", "for", "subject", "i", "d", "71798", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",PROCEDURES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"71798\"" ], "answer": [ "2" ] }, { "key": "920c86ed33b3bf35707a12f566236c34", "format": { "table": [ 2, 3 ], "cond": [ [ 2, 0, 0, 24425 ] ], "agg_col": [ [ 2, 3 ], [ 3, 5 ] ], "sel": 0 }, "question_refine": "provide the procedure short title and drug code of subject id 24425.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\",PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" FROM PROCEDURES INNER JOIN PRESCRIPTIONS on PROCEDURES.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PROCEDURES.\"SUBJECT_ID\" = \"24425\"", "question_refine_tok": [ "provide", "the", "procedure", "short", "title", "and", "drug", "code", "of", "subject", "i", "d", "24425", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\",PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "FROM", "PROCEDURES", "INNER", "JOIN", "PRESCRIPTIONS", "on", "PROCEDURES.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"24425\"" ], "answer": [ "Vaccination NEC", "Vaccination NEC", "Vaccination NEC", "Vaccination NEC" ] }, { "key": "8f5493ee584c51f03ef9579a071809eb", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 17787 ] ], "agg_col": [ [ 4, 6 ], [ 4, 8 ] ], "sel": 0 }, "question_refine": "provide the lab test name and lab test category for subject id 17787?", "sql": "SELECT LAB.\"LABEL\",LAB.\"CATEGORY\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"17787\"", "question_refine_tok": [ "provide", "the", "lab", "test", "name", "and", "lab", "test", "category", "for", "subject", "i", "d", "17787", "?" ], "sql_tok": [ "SELECT", "LAB.\"LABEL\",LAB.\"CATEGORY\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"17787\"" ], "answer": [ "Bilirubin, Total", "Basophils", "Eosinophils", "Hematocrit", "Hemoglobin", "Lymphocytes", "MCH", "MCHC", "MCV", "Monocytes", "Neutrophils", "Platelet Count", "RDW", "Red Blood Cells", "White Blood Cells", "Atypical Lymphocytes", "Bands", "Metamyelocytes", "Myelocytes", "Nucleated Red Cells", "Bilirubin, Direct", "Bilirubin, Indirect" ] }, { "key": "0c07221b2c2484620093c9a79cee3a13", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 3 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "Tell me the marital status and primary disease of the patient with patient id 4589.", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "Tell", "me", "the", "marital", "status", "and", "primary", "disease", "of", "the", "patient", "with", "patient", "id", "4589", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "MARRIED" ] }, { "key": "07f0e3c655d09ea2d3886a5d981798d9", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 4 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "give me the age and death status of subject id 4589.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "give", "me", "the", "age", "and", "death", "status", "of", "subject", "i", "d", "4589", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "59" ] }, { "key": "0d9c835c74f82a7ac15ff2fd3e62ff33", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 8 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "give the religion and death status of subject id 4589.", "sql": "SELECT DEMOGRAPHIC.\"RELIGION\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "give", "the", "religion", "and", "death", "status", "of", "subject", "i", "d", "4589", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"RELIGION\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "CATHOLIC" ] }, { "key": "0efacb3835583867e1d4ae5ef2e93a42", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 10 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "Get me the diagnoses icd9 code and number of days for which the patient with patient id 4589 stayed in hospital.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "Get", "me", "the", "diagnoses", "icd9", "code", "and", "number", "of", "days", "for", "which", "the", "patient", "with", "patient", "id", "4589", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34", "34" ] }, { "key": "005e995d08f73daf175a5dc01609b2c4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 16 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "what is the primary disease and procedure icd9 code of the patient id 4589?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "and", "procedure", "icd9", "code", "of", "the", "patient", "i", "d", "4589", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE" ] }, { "key": "92fb353d2314296f863997a8c3222e89", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 91588 ] ], "agg_col": [ [ 0, 9 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "specify the admission type and icd9 code of patient id 91588", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"91588\"", "question_refine_tok": [ "specify", "the", "admission", "type", "and", "icd9", "code", "of", "patient", "i", "d", "91588" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"91588\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "0d3ca391f292a21d141383a2c31b76eb", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 91588 ] ], "agg_col": [ [ 0, 21 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "Look for time of discharge and procedure icd9 code for the patient with patient id 91588.", "sql": "SELECT DEMOGRAPHIC.\"DISCHTIME\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"91588\"", "question_refine_tok": [ "Look", "for", "time", "of", "discharge", "and", "procedure", "icd9", "code", "for", "the", "patient", "with", "patient", "id", "91588", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHTIME\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"91588\"" ], "answer": [ "2165-10-24 12:15:00", "2165-10-24 12:15:00", "2165-10-24 12:15:00", "2165-10-24 12:15:00", "2165-10-24 12:15:00", "2165-10-24 12:15:00", "2165-11-13 13:40:00", "2165-11-13 13:40:00", "2165-11-13 13:40:00" ] }, { "key": "a8548cc3da3f7647e4b65fbcb65de4f3", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 7578 ] ], "agg_col": [ [ 0, 6 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "specify the gender and icd9 code for patient id 7578", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"7578\"", "question_refine_tok": [ "specify", "the", "gender", "and", "icd9", "code", "for", "patient", " ", "i", "d", "7578" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"7578\"" ], "answer": [ "F" ] }, { "key": "900f55c158193f37d975c8fdc34ff9ea", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 76446 ] ], "agg_col": [ [ 0, 3 ], [ 0, 12 ] ], "sel": 0 }, "question_refine": "get the marital status and ethnic background for the patient with patient id 76446.", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"76446\"", "question_refine_tok": [ "get", "the", "marital", "status", "and", "ethnic", "background", "for", "the", "patient", "with", "patient", "i", "d", "76446", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\",DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"76446\"" ], "answer": [ "WIDOWED", "WIDOWED" ] }, { "key": "9c874fe6e6c7f98ee202077204a7da76", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 84129 ] ], "agg_col": [ [ 0, 4 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "let me know the age and gender of patient with patient id 84129.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"84129\"", "question_refine_tok": [ "let", "me", "know", "the", "age", "and", "gender", "of", "patient", "with", "patient", "i", "d", "84129", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"84129\"" ], "answer": [ "64" ] }, { "key": "84b0290e9818cc962a5314dbfa000d95", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 84129 ] ], "agg_col": [ [ 0, 6 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "tell me the time of admission and gender of patient with patient id 84129.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"84129\"", "question_refine_tok": [ "tell", "me", "the", "time", "of", "admission", "and", "gender", "of", "patient", "with", "patient", "i", "d", "84129", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"84129\"" ], "answer": [ "M" ] }, { "key": "0acae8b8eed1e67cb616c7a2daa79ff9", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 17570 ] ], "agg_col": [ [ 0, 9 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "what is the admission type and discharge location of subject id 17570?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"17570\"", "question_refine_tok": [ "what", "is", "the", "admission", "type", "and", "discharge", "location", "of", "subject", "i", "d", "17570", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"17570\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "9bc647942515a09bbe2ff57ebcd61548", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 17570 ] ], "agg_col": [ [ 0, 13 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "what is the death status and admission time of the patient id 17570?", "sql": "SELECT DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"17570\"", "question_refine_tok": [ "what", "is", "the", "death", "status", "and", "admission", "time", "of", "the", "patient", "i", "d", "17570", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"17570\"" ], "answer": [ "1", "1", "1" ] }, { "key": "0c27eb4d99b5a50b55dcea73a2a9f54f", "format": { "table": [ 2 ], "cond": [ [ 2, 0, 0, 14755 ] ], "agg_col": [ [ 2, 4 ] ], "sel": 0 }, "question_refine": "specify icd9 code for patient id 14755", "sql": "SELECT PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"SUBJECT_ID\" = \"14755\"", "question_refine_tok": [ "specify", "icd9", "code", "for", "patient", "i", "d", "14755" ], "sql_tok": [ "SELECT", "PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"14755\"" ], "answer": [ "Excision of lesion or tissue of cerebral meninges", "Enteral infusion of concentrated nutritional substances", "Venous catheterization, not elsewhere classified", "Closed [endoscopic] biopsy of bronchus", "Spinal tap", "Spinal tap", "Arterial catheterization", "Continuous invasive mechanical ventilation for 96 consecutive hours or more" ] }, { "key": "b9ab5cd512dc4b1ef951bf1b2ae7c4b4", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 14755 ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "Tell me the short title of diagnoses and the primary disease the patient with patient id 14755 is suffering from.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"14755\"", "question_refine_tok": [ "Tell", "me", "the", "short", "title", "of", "diagnoses", "and", "the", "primary", "disease", "the", "patient", "with", "patient", "id", "14755", "is", "suffering", "from", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"14755\"" ], "answer": [ "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA", "BRAIN MENINGIOMA/SDA" ] }, { "key": "0db15c35e6c41cf480f6713995234237", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 85673 ] ], "agg_col": [ [ 0, 14 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "when was subject id 85673 admitted and what is his admission location?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"85673\"", "question_refine_tok": [ "when", "was", "subject", "i", "d", "85673", "admitted", "and", "what", "is", "his", "admission", "location", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"85673\"" ], "answer": [ "CLINIC REFERRAL/PREMATURE" ] }, { "key": "a57641d52d641c6d2ad66a4940f1907d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 85673 ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "give the primary disease and diagnosis of subject id 85673.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"85673\"", "question_refine_tok": [ "give", "the", "primary", "disease", "and", "diagnosis", "of", "subject", "i", "d", "85673", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"85673\"" ], "answer": [ "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS", "HEMOPYTSIS" ] }, { "key": "883cbf3acbf8e13c98474bd9646d166c", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 25543 ] ], "agg_col": [ [ 0, 9 ], [ 0, 14 ] ], "sel": 0 }, "question_refine": "find out the location and type of admission for patient with patient id 25543.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"25543\"", "question_refine_tok": [ "find", "out", "the", "location", "and", "type", "of", "admission", "for", "patient", "with", "patient", "i", "d", "25543", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"25543\"" ], "answer": [ "NEWBORN" ] }, { "key": "92413ed17c3ba949012342e10ea2d3eb", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 26285 ] ], "agg_col": [ [ 0, 11 ] ], "sel": 0 }, "question_refine": "specify the insurance type for patient id 26285", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"26285\"", "question_refine_tok": [ "specify", "the", "insurance", "type", "for", "patient", "i", "d", "26285" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"26285\"" ], "answer": [ "Medicare", "Medicare" ] }, { "key": "9fc8f707889402c55fd06f0f86b6dae0", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 26285 ] ], "agg_col": [ [ 0, 15 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "For patient id 26285, specify his or her primary disease and discharge location", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"26285\"", "question_refine_tok": [ "For", "patient", "id", "26285", ",", "specify", "his", "or", "her", "primary", "disease", "and", "discharge", "location" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"26285\"" ], "answer": [ "HOME", "DEAD/EXPIRED" ] }, { "key": "08dc87e4a9287db3def0945eeed8fee6", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 18351 ] ], "agg_col": [ [ 0, 10 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "let me know the discharge location and number of days for which patient with patient id 18351 was hospitalized.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18351\"", "question_refine_tok": [ "let", "me", "know", "the", "discharge", "location", "and", "number", "of", "days", "for", "which", "patient", "with", "patient", "i", "d", "18351", "was", "hospitalized", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18351\"" ], "answer": [ "6" ] }, { "key": "9fb423ffd840af9eb8e6369bfd236cbd", "format": { "table": [ 1 ], "cond": [ [ 1, 0, 0, 18351 ] ], "agg_col": [ [ 1, 2 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "what is the diagnosis icd9 code and diagnosis long title of subject id 18351?", "sql": "SELECT DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"SUBJECT_ID\" = \"18351\"", "question_refine_tok": [ "what", "is", "the", "diagnosis", "icd9", "code", "and", "diagnosis", "long", "title", "of", "subject", "i", "d", "18351", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"18351\"" ], "answer": [ "5680", "99591", "0389", "V6441", "6140", "6143", "6200" ] }, { "key": "84d8e114a207be5d52e10d970eb77b2d", "format": { "table": [ 1 ], "cond": [ [ 1, 0, 0, 18351 ] ], "agg_col": [ [ 1, 3 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "let me know both the short title and long title of diagnoses for the patient with patient id 18351.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"SUBJECT_ID\" = \"18351\"", "question_refine_tok": [ "let", "me", "know", "both", "the", "short", "title", "and", "long", "title", "of", "diagnoses", "for", "the", "patient", "with", "patient", "i", "d", "18351", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"18351\"" ], "answer": [ "Peritoneal adhesions", "Sepsis", "Septicemia NOS", "Lap surg convert to open", "Ac salpingo-oophoritis", "Acute parametritis", "Follicular cyst of ovary" ] }, { "key": "03eedd461511a1af0baa8f05815fca31", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 17595 ] ], "agg_col": [ [ 0, 9 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find out the type and time of admission for the patient with patient id 17595.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"17595\"", "question_refine_tok": [ "find", "out", "the", "type", "and", "time", "of", "admission", "for", "the", "patient", "with", "patient", "i", "d", "17595", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"17595\"" ], "answer": [ "ELECTIVE" ] }, { "key": "a488c5129d8241bbe3dd4224e84a6966", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 18372 ] ], "agg_col": [ [ 0, 11 ] ], "sel": 0 }, "question_refine": "what is the insurance of patient id 18372?", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18372\"", "question_refine_tok": [ "what", "is", "the", "insurance", "of", "patient", "i", "d", "18372", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18372\"" ], "answer": [ "Private" ] }, { "key": "02f8dd7774d30589e41d84979f58ce9e", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 18372 ] ], "agg_col": [ [ 0, 9 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "Let me know the short title for the procedure and type of admission for patient with patient id 18372.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18372\"", "question_refine_tok": [ "Let", "me", "know", "the", "short", "title", "for", "the", "procedure", "and", "type", "of", "admission", "for", "patient", "with", "patient", "id", "18372", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18372\"" ], "answer": [ "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN" ] }, { "key": "ac54a82fadd7f1ed60b5f097dcccc668", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 18372 ] ], "agg_col": [ [ 0, 10 ], [ 4, 8 ] ], "sel": 0 }, "question_refine": "Calculate the days of hospital stay and lab test category for patient with patient id 18372.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",LAB.\"CATEGORY\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18372\"", "question_refine_tok": [ "Calculate", "the", "days", "of", "hospital", "stay", "and", "lab", "test", "category", "for", "patient", "with", "patient", "id", "18372", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",LAB.\"CATEGORY\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18372\"" ], "answer": [ "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26", "26" ] }, { "key": "ac525e56df0431370a3602e15ee25b9b", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 43220 ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "which type of admission did the patient with patient id 43220 have?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"43220\"", "question_refine_tok": [ "which", "type", "of", "admission", "did", "the", "patient", "with", "patient", "i", "d", "43220", "have", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"43220\"" ], "answer": [ "EMERGENCY" ] }, { "key": "057a0a3ac122c6beeb2e96672cd199bb", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15061 ] ], "agg_col": [ [ 0, 6 ] ], "sel": 0 }, "question_refine": "what is the gender of the patient id 15061?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15061\"", "question_refine_tok": [ "what", "is", "the", "gender", "of", "the", "patient", "i", "d", "15061", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15061\"" ], "answer": [ "F", "F" ] }, { "key": "0544e73e214a56960c9f5b987528deae", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 74463 ] ], "agg_col": [ [ 0, 5 ] ], "sel": 0 }, "question_refine": "on which date was the patient with patient id 74463 born?", "sql": "SELECT DEMOGRAPHIC.\"DOB\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"74463\"", "question_refine_tok": [ "on", "which", "date", "was", "the", "patient", "with", "patient", "i", "d", "74463", "born", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"74463\"" ], "answer": [ "2024-07-13 00:00:00", "2024-07-13 00:00:00" ] }, { "key": "a54b66567c23a6ca8e774a4507f148c5", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 22377 ] ], "agg_col": [ [ 4, 2 ], [ 4, 4 ] ], "sel": 0 }, "question_refine": "give me the lab test item id and lab test abnormal status of patient with patient id 22377.", "sql": "SELECT LAB.\"ITEMID\",LAB.\"FLAG\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"22377\"", "question_refine_tok": [ "give", "me", "the", "lab", "test", "item", "i", "d", "and", "lab", "test", "abnormal", "status", "of", "patient", "with", "patient", "i", "d", "22377", "." ], "sql_tok": [ "SELECT", "LAB.\"ITEMID\",LAB.\"FLAG\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"22377\"" ], "answer": [ "50885", "50885", "50883", "50883", "50884", "50884" ] }, { "key": "05a7c3b6372bf41e57ed975badd14080", "format": { "table": [ 2 ], "cond": [ [ 2, 0, 0, 1875 ] ], "agg_col": [ [ 2, 2 ] ], "sel": 0 }, "question_refine": "provide me the procedure icd9 code of patient with patient id 1875.", "sql": "SELECT PROCEDURES.\"ICD9_CODE\" FROM PROCEDURES WHERE PROCEDURES.\"SUBJECT_ID\" = \"1875\"", "question_refine_tok": [ "provide", "me", "the", "procedure", "icd9", "code", "of", "patient", "with", "patient", "i", "d", "1875", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"1875\"" ], "answer": [ "5771", "403", "5651" ] }, { "key": "8a0ddd453e433d0189e15fe7e1259821", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 1875 ] ], "agg_col": [ [ 0, 20 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "Give me the time of admission and diagnoses icd9 code for the patient with patient id 1875.", "sql": "SELECT DEMOGRAPHIC.\"ADMITTIME\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"1875\"", "question_refine_tok": [ "Give", "me", "the", "time", "of", "admission", "and", "diagnoses", "icd9", "code", "for", "the", "patient", "with", "patient", "id", "1875", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMITTIME\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"1875\"" ], "answer": [ "2120-04-15 09:15:00", "2120-04-15 09:15:00", "2120-04-15 09:15:00", "2120-04-15 09:15:00", "2120-04-15 09:15:00", "2120-04-15 09:15:00" ] }, { "key": "0b8b878c3c9bf9cfc59e3c2528341dfa", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 1875 ] ], "agg_col": [ [ 0, 21 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "for patient id 1875, specify the icd9 code and discharge time", "sql": "SELECT DEMOGRAPHIC.\"DISCHTIME\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"1875\"", "question_refine_tok": [ "for", "patient", "i", "d", "1875", ",", "specify", "the", "icd9", "code", "and", "discharge", "time" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHTIME\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"1875\"" ], "answer": [ "2120-04-22 12:27:00", "2120-04-22 12:27:00", "2120-04-22 12:27:00", "2120-04-22 12:27:00", "2120-04-22 12:27:00", "2120-04-22 12:27:00" ] }, { "key": "07f753a76f9e4833bde8ba792b3b14c9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 8440 ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "what is the primary disease and diagnosis of the patient id 8440?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"8440\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "and", "diagnosis", "of", "the", "patient", "i", "d", "8440", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"8440\"" ], "answer": [ "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED", "GASTROINTESTINAL BLEED" ] }, { "key": "8e805d4d6cc73e525091b4a6fab529c6", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 11221 ] ], "agg_col": [ [ 0, 10 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "tell me the discharge location and the number of days for which patient with patient id 11221 stayed in hospital.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"11221\"", "question_refine_tok": [ "tell", "me", "the", "discharge", "location", "and", "the", "number", "of", "days", "for", "which", "patient", "with", "patient", "i", "d", "11221", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"11221\"" ], "answer": [ "43" ] }, { "key": "097b18ee7c4e8dd38cc66dd22ba9274a", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 0, 5 ] ], "sel": 0 }, "question_refine": "give me the birth date of patient stephanie suchan ?", "sql": "SELECT DEMOGRAPHIC.\"DOB\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "give", "me", "the", "birth", "date", "of", "patient", "stephanie", "suchan", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "2089-03-29 00:00:00" ] }, { "key": "0f58d7c3462afbaf1092a9aaca163031", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Edward Castillo" ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "specify type of admission of patient edward castillo", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Edward Castillo\"", "question_refine_tok": [ "specify", "type", "of", "admission", "of", "patient", "edward", "castillo" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Edward", "Castillo\"" ], "answer": [ "EMERGENCY", "EMERGENCY" ] }, { "key": "0709ceb7a5a37d731d4c3fb50129fc8b", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Bessie Giordano" ] ], "agg_col": [ [ 0, 16 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "tell me the time of admission and primary disease of patient bessie giordano.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Bessie Giordano\"", "question_refine_tok": [ "tell", "me", "the", "time", "of", "admission", "and", "primary", "disease", "of", "patient", "bessie", "giordano", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Bessie", "Giordano\"" ], "answer": [ "NEWBORN" ] }, { "key": "0b3cc42f4f1d52225bcdb7f071c2b474", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Chandra Schulman" ] ], "agg_col": [ [ 4, 2 ], [ 4, 6 ] ], "sel": 0 }, "question_refine": "let me know the name of lab test and lab test item id for patient chandra schulman.", "sql": "SELECT LAB.\"ITEMID\",LAB.\"LABEL\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Chandra Schulman\"", "question_refine_tok": [ "let", "me", "know", "the", "name", "of", "lab", "test", "and", "lab", "test", "item", "i", "d", "for", "patient", "chandra", "schulman", "." ], "sql_tok": [ "SELECT", "LAB.\"ITEMID\",LAB.\"LABEL\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Chandra", "Schulman\"" ], "answer": [ "50883", "50884", "50885", "51143", "51144", "51146", "51200", "51221", "51222", "51244", "51248", "51249", "51250", "51251", "51254", "51255", "51256", "51265", "51277", "51279", "51301" ] }, { "key": "9b4df08cff80e56aef9dc4d37513e33e", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jonathan Wiggins" ] ], "agg_col": [ [ 0, 9 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "get me the type of admission and primary disease for which jonathan wiggins was admitted.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jonathan Wiggins\"", "question_refine_tok": [ "get", "me", "the", "type", "of", "admission", "and", "primary", "disease", "for", "which", "jonathan", "wiggins", "was", "admitted", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jonathan", "Wiggins\"" ], "answer": [ "EMERGENCY" ] }, { "key": "08dbe3cffc1c334b730854b6454b0bb9", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Elizabeth Bateman" ] ], "agg_col": [ [ 0, 14 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "Provide the admission location as well as discharge location of Elizabeth Bateman.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Elizabeth Bateman\"", "question_refine_tok": [ "Provide", "the", "admission", "location", "as", "well", "as", "discharge", "location", "of", "Elizabeth", "Bateman", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Elizabeth", "Bateman\"" ], "answer": [ "CLINIC REFERRAL/PREMATURE", "EMERGENCY ROOM ADMIT" ] }, { "key": "0d8668ce9bb2d5b309822a5b89240277", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "John Gartman" ] ], "agg_col": [ [ 0, 5 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find out the birth date and time of admission for patient john gartman.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"John Gartman\"", "question_refine_tok": [ "find", "out", "the", "birth", "date", "and", "time", "of", "admission", "for", "patient", "john", "gartman", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"John", "Gartman\"" ], "answer": [ "2083-08-25 00:00:00" ] }, { "key": "918aed487b54ba746f5dca74673a1e95", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Lue White" ] ], "agg_col": [ [ 0, 5 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "What is the date of birth and gender of Lue White?", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Lue White\"", "question_refine_tok": [ "What", "is", "the", "date", "of", "birth", "and", "gender", "of", "Lue", "White", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Lue", "White\"" ], "answer": [ "2078-01-19 00:00:00", "2078-01-19 00:00:00" ] }, { "key": "8b107fae68ba2796d3985f4bf3a26324", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Alice Nixon" ] ], "agg_col": [ [ 0, 14 ] ], "sel": 0 }, "question_refine": "Find the admission location for Alice Nixon.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Alice Nixon\"", "question_refine_tok": [ "Find", "the", "admission", "location", "for", "Alice", "Nixon", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Alice", "Nixon\"" ], "answer": [ "CLINIC REFERRAL/PREMATURE" ] }, { "key": "0cdaeea27c2f1e7de2ef4c3f9622d5cb", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Ida Cook" ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "let me know the type of admission patient ida cook had.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Ida Cook\"", "question_refine_tok": [ "let", "me", "know", "the", "type", "of", "admission", "patient", "ida", "cook", "had", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Ida", "Cook\"" ], "answer": [ "EMERGENCY" ] }, { "key": "a630f58e3b1231385d4ebbb1edbb136d", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Troy Friedman" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "patient troy friedman was hospitalized for how many days?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Troy Friedman\"", "question_refine_tok": [ "patient", "troy", "friedman", "was", "hospitalized", "for", "how", "many", "days", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Troy", "Friedman\"" ], "answer": [ "1" ] }, { "key": "871b48c28ceee54f43ba16f2a5d5dd15", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Troy Friedman" ] ], "agg_col": [ [ 0, 10 ], [ 0, 14 ] ], "sel": 0 }, "question_refine": "specify the duration of hospital stay and admission location of patient troy friedman", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Troy Friedman\"", "question_refine_tok": [ "specify", "the", "duration", "of", "hospital", "stay", "and", "admission", "location", "of", "patient", "troy", "friedman" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Troy", "Friedman\"" ], "answer": [ "1" ] }, { "key": "9e02c9f4d586d088bda7a218471308b9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Bruce Harris" ] ], "agg_col": [ [ 0, 16 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "Specify primary disease of patient Bruce Harris along with the icd9 code.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Bruce Harris\"", "question_refine_tok": [ "Specify", "primary", "disease", "of", "patient", "Bruce", "Harris", "along", "with", "the", "icd9", "code", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Bruce", "Harris\"" ], "answer": [ "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "AMPULLARY MASS/SDA", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "FTT", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "COLANGITIS", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "ANEMIA", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS", "SEPSIS" ] }, { "key": "01274bda0990333efe5fa68ca23a1718", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Thomas Jeanbaptiste" ] ], "agg_col": [ [ 0, 14 ], [ 0, 15 ] ], "sel": 0 }, "question_refine": "What is the admission location and discharge location of Thomas Jeanbaptiste?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Thomas Jeanbaptiste\"", "question_refine_tok": [ "What", "is", "the", "admission", "location", "and", "discharge", "location", "of", "Thomas", "Jeanbaptiste", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Thomas", "Jeanbaptiste\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "bb3c00803833e41059a3bff677c51b73", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Lawrence Wibbens" ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title of procedure for patient lawrence wibbens.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Lawrence Wibbens\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "of", "procedure", "for", "patient", "lawrence", "wibbens", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Lawrence", "Wibbens\"" ], "answer": [ "Bronchoscopy thru stoma", "Close sm bowel fist NEC", "Closed bronchial biopsy", "Cont inv mec ven 96+ hrs", "Enterostomy NEC", "Entral infus nutrit sub", "Laparoscopy", "Oth periton adhesiolysis", "Other destru pancrea les", "Other gastrostomy", "Parent infus nutrit sub", "Part sm bowel resect NEC", "Percu abdominal drainage", "Percu abdominal drainage", "Percu abdominal drainage", "Percu abdominal drainage", "Percu abdominal drainage", "Percu abdominal drainage", "Percu abdominal drainage", "Temporary tracheostomy", "Venous cath NEC", "Venous cath NEC", "Venous cath NEC", "Alcohol detoxification", "Cont inv mec ven <96 hrs", "Insert endotracheal tube", "Parent infus nutrit sub", "Venous cath NEC", "Abdominal wall incision", "Endosc inser stent bile", "Endosc retro cholangiopa", "Endosc retro cholangiopa", "Oth perc proc bil trct", "Oth perc proc bil trct", "Parent infus nutrit sub", "Percu abdominal drainage", "Percu abdominal drainage", "Venous cath NEC", "Arterial catheterization", "Cont inv mec ven <96 hrs", "Insert endotracheal tube", "Parent infus nutrit sub", "Retroperiton fistulogram", "Sm bowel endoscopy NEC", "Sm bowel endoscopy NEC", "Sm bowel endoscopy NEC", "Venous cath NEC" ] }, { "key": "977ecca508723a7bb321e261d6c47f72", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Tracy Farmer" ] ], "agg_col": [ [ 1, 3 ] ], "sel": 0 }, "question_refine": "what is the diagnosis of Tracy Farmer?", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Tracy Farmer\"", "question_refine_tok": [ "what", "is", "the", "diagnosis", "of", "Tracy", "Farmer", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Tracy", "Farmer\"" ], "answer": [ "Infant diabet mother syn", "Need prphyl vc vrl hepat", "Single lb in-hosp w cs", "Ventricular sept defect" ] }, { "key": "8523810ad3d2b35ea44fef5080962db1", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jane Dillard" ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "which type of admission did patient jane dillard have?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jane Dillard\"", "question_refine_tok": [ "which", "type", "of", "admission", "did", "patient", "jane", "dillard", "have", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jane", "Dillard\"" ], "answer": [ "EMERGENCY" ] }, { "key": "8c1239d9e940eb0ebcff0e32c2c18d7b", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Walter Locher" ] ], "agg_col": [ [ 0, 13 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "Tell me which primary disease the patient Walter Locher is suffering from and whether he is still alive or not.", "sql": "SELECT DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Walter Locher\"", "question_refine_tok": [ "Tell", "me", "which", "primary", "disease", "the", "patient", "Walter", "Locher", "is", "suffering", "from", "and", "whether", "he", "is", "still", "alive", "or", "not", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Walter", "Locher\"" ], "answer": [ "1", "1" ] }, { "key": "0521be1733cdf14bfb3164d5bc911bbf", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Hector Blair" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "give the primary disease of hector blair.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Hector Blair\"", "question_refine_tok": [ "give", "the", "primary", "disease", "of", "hector", "blair", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Hector", "Blair\"" ], "answer": [ "ST ELEVATED MYOCARDIAL INFARCTION\\CARDIAC CATH" ] }, { "key": "8434959e3330dc710ffe491da1f8652a", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Joseph Dillman" ] ], "agg_col": [ [ 0, 13 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "familiarize me with the death status and primary disease of the patient joseph dillman.", "sql": "SELECT DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Joseph Dillman\"", "question_refine_tok": [ "familiarize", "me", "with", "the", "death", "status", "and", "primary", "disease", "of", "the", "patient", "joseph", "dillman", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"EXPIRE_FLAG\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Joseph", "Dillman\"" ], "answer": [ "1", "1" ] }, { "key": "854f86a9a79899086eb022b3f0a6fb37", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Brian Brock" ] ], "agg_col": [ [ 0, 3 ] ], "sel": 0 }, "question_refine": "let me know if patient brian brock is married or unmarried.", "sql": "SELECT DEMOGRAPHIC.\"MARITAL_STATUS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Brian Brock\"", "question_refine_tok": [ "let", "me", "know", "if", "patient", "brian", "brock", "is", "married", "or", "unmarried", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Brian", "Brock\"" ], "answer": [ "MARRIED" ] }, { "key": "0be089824bb2caf402523cf69d0356a8", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Brian Brock" ] ], "agg_col": [ [ 0, 16 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "Tell me the procedure icd9 code and the primary disease for the patient Brian Brock.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Brian Brock\"", "question_refine_tok": [ "Tell", "me", "the", "procedure", "icd9", "code", "and", "the", "primary", "disease", "for", "the", "patient", "Brian", "Brock", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Brian", "Brock\"" ], "answer": [ "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA" ] }, { "key": "a41111f8a4127aa5b8e8d59c2162e99d", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Dawn Cooper" ] ], "agg_col": [ [ 0, 21 ] ], "sel": 0 }, "question_refine": "find out the time at which patient dawn cooper was discharged.", "sql": "SELECT DEMOGRAPHIC.\"DISCHTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Dawn Cooper\"", "question_refine_tok": [ "find", "out", "the", "time", "at", "which", "patient", "dawn", "cooper", "was", "discharged", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Dawn", "Cooper\"" ], "answer": [ "2163-01-17 23:59:00", "2163-03-08 15:51:00", "2163-03-22 16:51:00", "2163-04-11 19:56:00", "2163-05-21 16:39:00", "2164-02-16 16:00:00", "2164-04-03 18:00:00", "2164-05-29 16:15:00", "2164-08-29 16:45:00", "2164-10-01 16:59:00", "2165-02-04 18:30:00", "2165-03-29 21:00:00", "2167-10-02 14:39:00", "2168-05-19 08:00:00" ] }, { "key": "826d5098068860a440ae7a843a7e90df", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Jeff Jarvis" ] ], "agg_col": [ [ 0, 10 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "let me know the procedure icd9 code and days for which patient jeff jarvis was hospitalized.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jeff Jarvis\"", "question_refine_tok": [ "let", "me", "know", "the", "procedure", "icd9", "code", "and", "days", "for", "which", "patient", "jeff", "jarvis", "was", "hospitalized", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jeff", "Jarvis\"" ], "answer": [ "6", "6", "6", "6", "6", "6", "6", "6", "6" ] }, { "key": "930137d96be60c455240dc71e1aff79b", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Michael Witt" ] ], "agg_col": [ [ 0, 14 ] ], "sel": 0 }, "question_refine": "what is the admission location of the patient michael witt?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Michael Witt\"", "question_refine_tok": [ "what", "is", "the", "admission", "location", "of", "the", "patient", "michael", "witt", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Michael", "Witt\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "9e90f00cc0c6d266800eea37d3d08242", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Michael Witt" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "specify the primary disease of patient michael witt", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Michael Witt\"", "question_refine_tok": [ "specify", "the", "primary", "disease", "of", "patient", "michael", "witt" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Michael", "Witt\"" ], "answer": [ "NEWBORN" ] }, { "key": "ae3c7627e3ba7750105510476460e8e4", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Steven Sepulveda" ] ], "agg_col": [ [ 0, 4 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "What is the age and primary disease of Steven Sepulveda?", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Steven Sepulveda\"", "question_refine_tok": [ "What", "is", "the", "age", "and", "primary", "disease", "of", "Steven", "Sepulveda", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Steven", "Sepulveda\"" ], "answer": [ "64", "64" ] }, { "key": "8992cac76fa0ec727f4a010671a5ce78", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Steven Sepulveda" ] ], "agg_col": [ [ 0, 16 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title of procedure and primary disease of patient steven sepulveda.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Steven Sepulveda\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "of", "procedure", "and", "primary", "disease", "of", "patient", "steven", "sepulveda", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Steven", "Sepulveda\"" ], "answer": [ "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT; MYOMECTOMY/SDA", "SEVERE HYPERTROPHIC CARDIOMYOPATHY\\SEPTAL ETHANOL ABLATION", "SEVERE HYPERTROPHIC CARDIOMYOPATHY\\SEPTAL ETHANOL ABLATION", "SEVERE HYPERTROPHIC CARDIOMYOPATHY\\SEPTAL ETHANOL ABLATION", "SEVERE HYPERTROPHIC CARDIOMYOPATHY\\SEPTAL ETHANOL ABLATION" ] }, { "key": "87f5b4b9f0dde37c48f8c9c18eeff623", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "James Sloan" ] ], "agg_col": [ [ 0, 15 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "provide me with the long title of diagnoses and location of discharge for patient james sloan.", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\",DIAGNOSES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"James Sloan\"", "question_refine_tok": [ "provide", "me", "with", "the", "long", "title", "of", "diagnoses", "and", "location", "of", "discharge", "for", "patient", "james", "sloan", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"James", "Sloan\"" ], "answer": [ "HOME", "HOME", "HOME", "HOME", "HOME", "HOME" ] }, { "key": "9b805afb13a94b6007d685fa0474e38f", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "55221" ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "what is the diagnosis of the diagnosis icd9 code 55221?", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"55221\"", "question_refine_tok": [ "what", "is", "the", "diagnosis", "of", "the", "diagnosis", "icd9", "code", "55221", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"55221\"" ], "answer": [ "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction", "Incisional ventral hernia with obstruction" ] }, { "key": "9f47c8570c1f03b0c2ced60a72ab7677", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "V202" ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "find the diagnostic decription of diagnoses icd9 code v202.", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"V202\"", "question_refine_tok": [ "find", "the", "diagnostic", "decription", "of", "diagnoses", "icd9", "code", "v202", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"V202\"" ], "answer": [ "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check", "Routine infant or child health check" ] }, { "key": "a94595edf4ac21c5e9a133c27d329a9c", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 540 ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "mention the procedure short title for procedure icd9 code 540.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"540\"", "question_refine_tok": [ "mention", "the", "procedure", "short", "title", "for", "procedure", "icd9", "code", "540", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"540\"" ], "answer": [ "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision", "Abdominal wall incision" ] }, { "key": "8a69b24d8c7e69c40ff4414c274c3334", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 9955 ] ], "agg_col": [ [ 2, 4 ] ], "sel": 0 }, "question_refine": "mention the long title of the procedure of procedure icd9 code 9955.", "sql": "SELECT PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"9955\"", "question_refine_tok": [ "mention", "the", "long", "title", "of", "the", "procedure", "of", "procedure", "icd9", "code", "9955", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9955\"" ], "answer": [ "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration of vaccine against other diseases", "Prophylactic administration 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"Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", 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"Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct", "Endoscopic insertion of stent (tube) into bile duct" ] }, { "key": "9d22d5180be72d9ae37019d4cc5355aa", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 331 ] ], "agg_col": [ [ 2, 4 ] ], "sel": 0 }, "question_refine": "tell me the long title of procedure for procedure icd9 code 331.", "sql": "SELECT PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"331\"", "question_refine_tok": [ "tell", "me", "the", "long", "title", "of", "procedure", "for", "procedure", "icd9", "code", "331", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"331\"" ], "answer": [ "Incision of lung", "Incision of lung", "Incision of lung" ] }, { "key": "a41467630e807935e79cb022a27386f1", "format": { "table": [ 3 ], "cond": [ [ 3, 4, 0, "Nitroglycerin SL" ] ], "agg_col": [ [ 3, 6 ] ], "sel": 0 }, "question_refine": "How is Nitroglycerin SL administered?", "sql": "SELECT PRESCRIPTIONS.\"ROUTE\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"DRUG\" = \"Nitroglycerin SL\"", "question_refine_tok": [ "How", "is", "Nitroglycerin", "SL", "administered", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"ROUTE\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Nitroglycerin", "SL\"" ], "answer": [ "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", "SL", 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"BASE", "BASE", "BASE" ] }, { "key": "0a0f24160b5c1caf4686cf54d67538fe", "format": { "table": [ 3 ], "cond": [ [ 3, 5, 0, "NYST500T" ] ], "agg_col": [ [ 3, 4 ], [ 3, 6 ] ], "sel": 0 }, "question_refine": "what is the drug name and drug route of drug code nyst500t?", "sql": "SELECT PRESCRIPTIONS.\"DRUG\",PRESCRIPTIONS.\"ROUTE\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"NYST500T\"", "question_refine_tok": [ "what", "is", "the", "drug", "name", "and", "drug", "route", "of", "drug", "code", "nyst500", "t", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"DRUG\",PRESCRIPTIONS.\"ROUTE\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"NYST500T\"" ], "answer": [ "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", "Nystatin", 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"FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"" ], "answer": [ "1309" ] }, { "key": "0184df207ef06907df1fb65797ab9b69", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 2, 2146 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients who were born before 2146.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2146\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "who", "were", "born", "before", "2146", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2146\"" ], "answer": [ "40697" ] }, { "key": "9e2e39278d691cbd1bca1da3cfca362f", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "42842" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients with diagnoses icd9 code 42842.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"42842\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "with", "diagnoses", "icd9", "code", "42842", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"42842\"" ], "answer": [ "151" ] }, { "key": "97d303ec02cd44af836860b5bbec1d68", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "2920" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have diagnoses icd9 code 2920?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"2920\"", "question_refine_tok": [ "which", "patients", "have", "diagnoses", "icd9", "code", "2920", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2920\"" ], "answer": [ "167" ] }, { "key": "04531e28c38575a4a2bdca04faa8c77b", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Hx traumatic fracture" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with hx traumatic fracture?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Hx traumatic fracture\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "hx", "traumatic", "fracture", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Hx", "traumatic", "fracture\"" ], "answer": [ "85" ] }, { "key": "aaaa09cf4ad17119ae748e7b44f1d7c6", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 41 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had the procedure under icd9 code 41?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"41\"", "question_refine_tok": [ "how", "many", "patients", "had", "the", "procedure", "under", "icd9", "code", "41", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"41\"" ], "answer": [ "0" ] }, { "key": "88f2ae995e293195ccf9d017638d422c", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 4, 0, "Arthrocentesis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the total number of patients who had arthrocentesis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"LONG_TITLE\" = \"Arthrocentesis\"", "question_refine_tok": [ "what", "is", "the", "total", "number", "of", "patients", "who", "had", "arthrocentesis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Arthrocentesis\"" ], "answer": [ "308" ] }, { "key": "87d3070d03de888cbc5b8b08d0b7a471", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Potassium Chloride (Powder)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients who have been prescribed potassium chloride (powder) drug.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Potassium Chloride (Powder)\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "who", "have", "been", "prescribed", "potassium", "chloride", "(", "powder", ")", "drug", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Potassium", "Chloride", "(Powder)\"" ], "answer": [ "1950" ] }, { "key": "9aaae00ca767b3d793f63b3cf50e3542", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "RIS1L" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with drug code ris1l?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"RIS1L\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "drug", "code", "ris1l", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"RIS1L\"" ], "answer": [ "37" ] }, { "key": "9e44eba73424833811971163b94d92f3", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "ZOSY4FPB" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had zosy4fpb as their drug code?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"ZOSY4FPB\"", "question_refine_tok": [ "how", "many", "patients", "had", "zosy4fpb", "as", "their", "drug", "code", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"ZOSY4FPB\"" ], "answer": [ "4357" ] }, { "key": "8ed7381131391075a911f31c05c9e3ed", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "OXYM15" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have drug code oxym15?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"OXYM15\"", "question_refine_tok": [ "how", "many", "patients", "have", "drug", "code", "oxym15", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"OXYM15\"" ], "answer": [ "718" ] }, { "key": "8ee267d3ebb2638adb49055bf5643383", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "VORI200" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who have drug code vori200?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"VORI200\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "have", "drug", "code", "vori200", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"VORI200\"" ], "answer": [ "219" ] }, { "key": "aa660f69986b6a3c7a9f71b58ef849d6", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 50802 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have lab test item id 50802?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"50802\"", "question_refine_tok": [ "which", "patients", "have", "lab", "test", "item", "i", "d", "50802", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"50802\"" ], "answer": [ "31056" ] }, { "key": "008452ec0d8e3074023da5b599850454", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 50922 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are tested with lab item id 50922?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"50922\"", "question_refine_tok": [ "how", "many", "patients", "are", "tested", "with", "lab", "item", "i", "d", "50922", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"50922\"" ], "answer": [ "5910" ] }, { "key": "0a1dcb8cb5d013e3feb7229a7b8ac869", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "Magnesium, Urine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get me the number of patients who had a urine magnesium lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"Magnesium, Urine\"", "question_refine_tok": [ "Get", "me", "the", "number", "of", "patients", "who", "had", "a", "urine", "magnesium", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"Magnesium,", "Urine\"" ], "answer": [ "356" ] }, { "key": "a848894f5b91889403e955cc65b906b8", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "Glucose, CSF" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Which patients had a csf glucose lab test done?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"Glucose, CSF\"", "question_refine_tok": [ "Which", "patients", "had", "a", "csf", "glucose", "lab", "test", "done", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"Glucose,", "CSF\"" ], "answer": [ "2375" ] }, { "key": "9fd1f00aa01bc66079062d70eff0e854", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 16, 0, "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT WITH MVR; ? MAZE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are married and diagnosed with primary disease coronary artery disease or coronary artery bypass graft with mvr maze?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT WITH MVR; ? MAZE\"", "question_refine_tok": [ "how", "many", "patients", "are", "married", "and", "diagnosed", "with", "primary", "disease", "coronary", "artery", "disease", "or", "coronary", "artery", "bypass", "graft", "with", "mvr", "maze", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CORONARY", "ARTERY", "DISEASE\\CORONARY", "ARTERY", "BYPASS", "GRAFT", "WITH", "MVR;", "?", "MAZE\"" ], "answer": [ "1" ] }, { "key": "0feb6c94275dae4ee5dc08799c8e771b", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 16, 0, "GUILLAIN BARRE SYNDROME" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had guillain barre syndrome as their primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"GUILLAIN BARRE SYNDROME\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "guillain", "barre", "syndrome", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GUILLAIN", "BARRE", "SYNDROME\"" ], "answer": [ "2" ] }, { "key": "9784119760b70ee84b43a5775f019e0c", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 4, 2, 89 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of female patients under the age of 89.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"AGE\" < \"89\"", "question_refine_tok": [ "count", "the", "number", "of", "female", "patients", "under", "the", "age", "of", "89", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"89\"" ], "answer": [ "18971" ] }, { "key": "8c655677cdaca2684d688418d197aed1", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "M" ], [ 1, 2, 0, "5119" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the male patients who have diagnoses icd9 code 5119.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DIAGNOSES.\"ICD9_CODE\" = \"5119\"", "question_refine_tok": [ "find", "the", "male", "patients", "who", "have", "diagnoses", "icd9", "code", "5119", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"5119\"" ], "answer": [ "1342" ] }, { "key": "8206c4526c7bf28ff92cc711d5e4eb9e", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 3, 0, "Constipation NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients have been diagnosed with unspecified constipation?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Constipation NOS\"", "question_refine_tok": [ "how", "many", "female", "patients", "have", "been", "diagnosed", "with", "unspecified", "constipation", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Constipation", "NOS\"" ], "answer": [ "426" ] }, { "key": "ac6c964a4c0b2e2ccf71af7ff7e02fac", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "NEWBORN" ], [ 0, 18, 2, 2168 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of newborns who were born before the year 2168.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"NEWBORN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2168\"", "question_refine_tok": [ "give", "the", "number", "of", "newborns", "who", "were", "born", "before", "the", "year", "2168", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2168\"" ], "answer": [ "5340" ] }, { "key": "808ab7ccfd71b1f2114350a202cbae90", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 4, 6, 0, "Lactate" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients on elective admission who had a lab test for lactate", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND LAB.\"LABEL\" = \"Lactate\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "on", "elective", "admission", "who", "had", "a", "lab", "test", "for", "lactate" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "LAB.\"LABEL\"", "=", "\"Lactate\"" ], "answer": [ "5048" ] }, { "key": "96c68e89c04906418748aa32f756ecae", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 4, 6, 0, "Ferritin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted in emergency were tested for ferritin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND LAB.\"LABEL\" = \"Ferritin\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "in", "emergency", "were", "tested", "for", "ferritin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "LAB.\"LABEL\"", "=", "\"Ferritin\"" ], "answer": [ "7349" ] }, { "key": "9dc64d2612463b12a1c7a0fff2cb8a79", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 1, 3, 0, "Portal hypertension" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "show me the number of white ethnic background patients who have the diagnoses of portal hypertension.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Portal hypertension\"", "question_refine_tok": [ "show", "me", "the", "number", "of", "white", "ethnic", "background", "patients", "who", "have", "the", "diagnoses", "of", "portal", "hypertension", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Portal", "hypertension\"" ], "answer": [ "590" ] }, { "key": "07495e00ef62b05d9783f9928d656d1f", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 1, 3, 0, "Pleural effusion NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with white ethnic background are diagnosed with unspecified pleural effusion?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Pleural effusion NOS\"", "question_refine_tok": [ "how", "many", "patients", "with", "white", "ethnic", "background", "are", "diagnosed", "with", "unspecified", "pleural", "effusion", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Pleural", "effusion", "NOS\"" ], "answer": [ "1959" ] }, { "key": "0e8272658be25dcd6baac667cfc23de8", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SIGMOID DIVERTICULITIS, COLOVESTICAL FISTULA/SDA" ], [ 0, 10, 1, 26 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the patients with sigmoid diverticulitis colovestical fistula/SDA as their primary disease had a hospital stay for more than 26 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SIGMOID DIVERTICULITIS, COLOVESTICAL FISTULA/SDA\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"26\"", "question_refine_tok": [ "How", "many", "of", "the", "patients", "with", "sigmoid", "diverticulitis", "colovestical", "fistula/SDA", "as", "their", "primary", "disease", "had", "a", "hospital", "stay", "for", "more", "than", "26", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SIGMOID", "DIVERTICULITIS,", "COLOVESTICAL", "FISTULA/SDA\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"26\"" ], "answer": [ "1" ] }, { "key": "ba4ce0085b3d0896060058362147c7a4", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "GUILLAIN BARRE SYNDROME" ], [ 0, 10, 1, 10 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the total number of patients with guillain barre syndrome as their primary disease who stayed at the hospital for more than 10 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GUILLAIN BARRE SYNDROME\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"10\"", "question_refine_tok": [ "Calculate", "the", "total", "number", "of", "patients", "with", "guillain", "barre", "syndrome", "as", "their", "primary", "disease", "who", "stayed", "at", "the", "hospital", "for", "more", "than", "10", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GUILLAIN", "BARRE", "SYNDROME\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"10\"" ], "answer": [ "2" ] }, { "key": "89a0044a0f95cc0d7cc6757f5a6c4d6f", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 16, 0, "VENTRICULAR TACHYCARDIA" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among patients treated with base drug, how many of them had ventricular tachycardia as primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"VENTRICULAR TACHYCARDIA\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "among", "patients", "treated", "with", "base", "drug", ",", "how", "many", "of", "them", "had", "ventricular", "tachycardia", "as", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"VENTRICULAR", "TACHYCARDIA\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "46" ] }, { "key": "034ba91dc253e7717c3102b2a97d2f49", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 16, 0, "ABDOMINAL ABSCESS" ], [ 3, 3, 0, "MAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients with abdominal abscess had drug type as main?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"ABDOMINAL ABSCESS\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"MAIN\"", "question_refine_tok": [ "what", "number", "of", "patients", "with", "abdominal", "abscess", "had", "drug", "type", "as", "main", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ABDOMINAL", "ABSCESS\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"MAIN\"" ], "answer": [ "15" ] }, { "key": "979a734ab882143afcde05bf1b13cbd9", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 16, 0, "BRADYCARDIA" ], [ 4, 4, 0, "abnormal" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients with bradycardia had abnormal lab test results?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRADYCARDIA\" AND LAB.\"FLAG\" = \"abnormal\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "with", "bradycardia", "had", "abnormal", "lab", "test", "results", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRADYCARDIA\"", "AND", "LAB.\"FLAG\"", "=", "\"abnormal\"" ], "answer": [ "109" ] }, { "key": "84ba1a3f8200ea0590903ea10ecc011c", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 27 ], [ 0, 10, 1, 16 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients under the age of 27 stayed in the hospital for more than 16 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"27\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"16\"", "question_refine_tok": [ "how", "many", "patients", "under", "the", "age", "of", "27", "stayed", "in", "the", "hospital", "for", "more", "than", "16", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"27\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"16\"" ], "answer": [ "1551" ] }, { "key": "06013ea409dea85892342d222c94f3dd", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 81 ], [ 1, 2, 0, "28522" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 81 years had the diagnosis icd9 code 28522?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"81\" AND DIAGNOSES.\"ICD9_CODE\" = \"28522\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "81", "years", "had", "the", "diagnosis", "icd9", "code", "28522", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"81\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"28522\"" ], "answer": [ "286" ] }, { "key": "072bad6b44992233a722bf1135799e59", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 56 ], [ 3, 4, 0, "Insulin Human Regular" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients under the age of 56 whose drug name is insulin human regular.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"56\" AND PRESCRIPTIONS.\"DRUG\" = \"Insulin Human Regular\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "under", "the", "age", "of", "56", "whose", "drug", "name", "is", "insulin", "human", "regular", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"56\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Insulin", "Human", "Regular\"" ], "answer": [ "2018" ] }, { "key": "8e7cd8188de5a262b484f55dbfdfb16a", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 83 ], [ 3, 5, 0, "NTGBASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients of age less than 83 years had the drug ntgbase?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"83\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"NTGBASE\"", "question_refine_tok": [ "how", "many", "patients", "of", "age", "less", "than", "83", "years", "had", "the", "drug", "ntgbase", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"83\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"NTGBASE\"" ], "answer": [ "7170" ] }, { "key": "0765275a7a13477bb0464fab046ee5a0", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 6 ], [ 1, 2, 0, "60000" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "show me the number of patients hospitalized for more than 6 days who have diagnoses icd9 code 60000.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"6\" AND DIAGNOSES.\"ICD9_CODE\" = \"60000\"", "question_refine_tok": [ "show", "me", "the", "number", "of", "patients", "hospitalized", "for", "more", "than", "6", "days", "who", "have", "diagnoses", "icd9", "code", "60000", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"6\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"60000\"" ], "answer": [ "615" ] }, { "key": "089c48c2efaae378b3bf7ee0d9fa4894", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2200 ], [ 2, 4, 0, "Endoscopic removal of stone(s) from biliary tract" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients admitted before 2200 who had endoscopic removal of stone(s) from biliary tract.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2200\" AND PROCEDURES.\"LONG_TITLE\" = \"Endoscopic removal of stone(s) from biliary tract\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "admitted", "before", "2200", "who", "had", "endoscopic", "removal", "of", "stone(s", ")", "from", "biliary", "tract", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2200\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Endoscopic", "removal", "of", "stone(s)", "from", "biliary", "tract\"" ], "answer": [ "253" ] }, { "key": "8447e58e57394384f3f325e732cdd313", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Fx surg nck humerus-clos" ], [ 3, 6, 0, "IV" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of patients on iv route of drug administration who are diagnosed with closed fracture of surgical neck of humerus.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Fx surg nck humerus-clos\" AND PRESCRIPTIONS.\"ROUTE\" = \"IV\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "patients", "on", "iv", "route", "of", "drug", "administration", "who", "are", "diagnosed", "with", "closed", "fracture", "of", "surgical", "neck", "of", "humerus", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Fx", "surg", "nck", "humerus-clos\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"IV\"" ], "answer": [ "37" ] }, { "key": "93e86557c8c38990642ec50166303b6b", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Acute kidney failure NOS" ], [ 3, 6, 0, "TP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give me the list of patients who were diagnosed with acute kidney failure (unspecified) that were administered the drug via the tp route.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Acute kidney failure NOS\" AND PRESCRIPTIONS.\"ROUTE\" = \"TP\"", "question_refine_tok": [ "Give", "me", "the", "list", "of", "patients", "who", "were", "diagnosed", "with", "acute", "kidney", "failure", "(", "unspecified", ")", "that", "were", "administered", "the", "drug", "via", "the", "tp", "route", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Acute", "kidney", "failure", "NOS\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"TP\"" ], "answer": [ "3352" ] }, { "key": "06309c2f77f11d404ae955cf4e39d47b", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 3, 0, "DMI keto nt st uncntrld" ], [ 4, 8, 0, "Blood Gas" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose diagnosis short title is dmi keto nt st uncontrolled and lab test category is blood gas.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"DMI keto nt st uncntrld\" AND LAB.\"CATEGORY\" = \"Blood Gas\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "diagnosis", "short", "title", "is", "dmi", "keto", "nt", "st", "uncontrolled", "and", "lab", "test", "category", "is", "blood", "gas", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"DMI", "keto", "nt", "st", "uncntrld\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Blood", "Gas\"" ], "answer": [ "123" ] }, { "key": "870f5b622617243df5706ef4fa1a51da", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 4, 0, "Other Staphylococcus pneumonia" ], [ 4, 8, 0, "Blood Gas" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with staphylococcus pneumonia have blood gas lab test category?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Other Staphylococcus pneumonia\" AND LAB.\"CATEGORY\" = \"Blood Gas\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "staphylococcus", "pneumonia", "have", "blood", "gas", "lab", "test", "category", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Other", "Staphylococcus", "pneumonia\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Blood", "Gas\"" ], "answer": [ "19" ] }, { "key": "811e1ba5eb77fdade7bbd13a6f350757", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 3343 ] ], "agg_col": [ [ 4, 2 ], [ 4, 5 ] ], "sel": 0 }, "question_refine": "Specify the item id along with the lab test value for patient ID 3343", "sql": "SELECT LAB.\"ITEMID\",LAB.\"VALUE_UNIT\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"3343\"", "question_refine_tok": [ "Specify", "the", "item", "id", "along", "with", "the", "lab", "test", "value", "for", "patient", "ID", "3343" ], "sql_tok": [ "SELECT", "LAB.\"ITEMID\",LAB.\"VALUE_UNIT\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"3343\"" ], "answer": [ "50885", "50885", "51146", "51200", "51221", "51222", "51244", "51248", "51249", "51250", "51254", "51256", "51265", "51277", "51279", "51301", "51143", "51144", "51251", "51255", "51257", "50883", "50883", "50884", "50884" ] }, { "key": "0b265651dd99d7806feaa26008b010e8", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 4589 ] ], "agg_col": [ [ 0, 16 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find out the time of admission and primary disease of patient with patient id 4589.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"4589\"", "question_refine_tok": [ "find", "out", "the", "time", "of", "admission", "and", "primary", "disease", "of", "patient", "with", "patient", "i", "d", "4589", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"4589\"" ], "answer": [ "CONGESTIVE HEART FAILURE" ] }, { "key": "ad6a9c9720c5a63538b4bfe468e3cafa", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 18351 ] ], "agg_col": [ [ 0, 5 ] ], "sel": 0 }, "question_refine": "what is the date of birth of the patient id 18351?", "sql": "SELECT DEMOGRAPHIC.\"DOB\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"18351\"", "question_refine_tok": [ "what", "is", "the", "date", "of", "birth", "of", "the", "patient", "i", "d", "18351", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"18351\"" ], "answer": [ "2097-06-12 00:00:00" ] }, { "key": "807ed8b40c34e53869ce863c6ed2489a", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 19187 ] ], "agg_col": [ [ 4, 6 ] ], "sel": 0 }, "question_refine": "which lab test has been ordered for patient with patient id 19187?", "sql": "SELECT LAB.\"LABEL\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"19187\"", "question_refine_tok": [ "which", "lab", "test", "has", "been", "ordered", "for", "patient", "with", "patient", "i", "d", "19187", "?" ], "sql_tok": [ "SELECT", "LAB.\"LABEL\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"19187\"" ], "answer": [ "Bilirubin, Total", "Basophils", "Eosinophils", "Hematocrit", "Hemoglobin", "Lymphocytes", "MCH", "MCHC", "MCV", "Monocytes", "Neutrophils", "Platelet Count", "RDW", "Red Blood Cells", "White Blood Cells", "Base Excess", "Calculated Total CO2", "pCO2", "pH", "pO2", "Atypical Lymphocytes", "Bands", "Metamyelocytes", "Myelocytes", "Nucleated Red Cells", "Bilirubin, Direct", "Bilirubin, Indirect", "Alveolar-arterial Gradient", "Other Cells" ] }, { "key": "93b51307495b8a4c78161d7b0c6b6aaf", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 32418 ] ], "agg_col": [ [ 0, 6 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "what is the gender and death status of subject id 32418?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"32418\"", "question_refine_tok": [ "what", "is", "the", "gender", "and", "death", "status", "of", "subject", "i", "d", "32418", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"32418\"" ], "answer": [ "F" ] }, { "key": "90cfc504183abdca82e353ac2a4eca19", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 64208 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "for how many days did the subject id 64208 stay in the hospital?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"64208\"", "question_refine_tok": [ "for", "how", "many", "days", "did", "the", "subject", "i", "d", "64208", "stay", "in", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"64208\"" ], "answer": [ "4" ] }, { "key": "079611ace011a01f44e1b3128b020e0c", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 5027 ] ], "agg_col": [ [ 0, 6 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "find out the time of admission and gender of patient with patient id 5027.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"5027\"", "question_refine_tok": [ "find", "out", "the", "time", "of", "admission", "and", "gender", "of", "patient", "with", "patient", "i", "d", "5027", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"5027\"" ], "answer": [ "M" ] }, { "key": "06d97dfc2dbf8ef1b61c77f6450b09e2", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 15061 ] ], "agg_col": [ [ 0, 10 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "Find out the time of admission and number of days for which the patient with patient id 15061 stayed in the hospital.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"15061\"", "question_refine_tok": [ "Find", "out", "the", "time", "of", "admission", "and", "number", "of", "days", "for", "which", "the", "patient", "with", "patient", "id", "15061", "stayed", "in", "the", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"15061\"" ], "answer": [ "8", "6" ] }, { "key": "0b70acfbd0281aad4f480933ffe64361", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 74463 ] ], "agg_col": [ [ 0, 10 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title of diagnoses and days for which patient with patient id 74463 was hospitalized.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"74463\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "of", "diagnoses", "and", "days", "for", "which", "patient", "with", "patient", "i", "d", "74463", "was", "hospitalized", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"74463\"" ], "answer": [ "4", "4", "4", "4", "4", "4", "4", "4", "4", "14", "14", "14", "14", "14", "14", "14", "14", "14", "14", "14", "14", "14", "14" ] }, { "key": "8404915c4b01e35617f74cf4e165a482", "format": { "table": [ 1, 2 ], "cond": [ [ 1, 0, 0, 74463 ] ], "agg_col": [ [ 1, 3 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "Let me know the short title of diagnoses and procedures for the patient with patient id 74463.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",PROCEDURES.\"SHORT_TITLE\" FROM DIAGNOSES INNER JOIN PROCEDURES on DIAGNOSES.HADM_ID = PROCEDURES.HADM_ID WHERE DIAGNOSES.\"SUBJECT_ID\" = \"74463\"", "question_refine_tok": [ "Let", "me", "know", "the", "short", "title", "of", "diagnoses", "and", "procedures", "for", "the", "patient", "with", "patient", "id", "74463", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DIAGNOSES", "INNER", "JOIN", "PROCEDURES", "on", "DIAGNOSES.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"74463\"" ], "answer": [ "Hypoxemia", "Hypoxemia", "Hypoxemia", "DMII wo cmp nt st uncntr", "DMII wo cmp nt st uncntr", "DMII wo cmp nt st uncntr", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Old myocardial infarct", "Old myocardial infarct", "Old myocardial infarct", "Abn react-artif implant", "Abn react-artif implant", "Abn react-artif implant", "Seroma complicting proc", "Seroma complicting proc", "Seroma complicting proc", "Long-term use anticoagul", "Long-term use anticoagul", "Long-term use anticoagul", "Aortic valve disorder", "Aortic valve disorder", "Aortic valve disorder", "Crnry athrscl natve vssl", "Crnry athrscl natve vssl", "Crnry athrscl natve vssl", "Atrial fibrillation", "Atrial fibrillation", "Atrial fibrillation", "Aortocoronary bypass", "Aortocoronary bypass", "Aortocoronary bypass", "Secundum atrial sept def", "Secundum atrial sept def", "Secundum atrial sept def", "Hypertension NOS", "Hypertension NOS", "Hypertension NOS", "Status-post ptca", "Status-post ptca", "Status-post ptca", "Subendo infarct, initial", "Subendo infarct, initial", "Subendo infarct, initial", "DMII wo cmp nt st uncntr", "DMII wo cmp nt st uncntr", "DMII wo cmp nt st uncntr", "Atrial fibrillation", "Atrial fibrillation", "Atrial fibrillation", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Hyperlipidemia NEC/NOS", "Mitral insuf/aort stenos", "Mitral insuf/aort stenos", "Mitral insuf/aort stenos", "Crnry athrscl natve vssl", "Crnry athrscl natve vssl", "Crnry athrscl natve vssl", "Aortocoronary bypass", "Aortocoronary bypass", "Aortocoronary bypass", "Hypertension NOS", "Hypertension NOS", "Hypertension NOS", "Chr airway obstruct NEC", "Chr airway obstruct NEC", "Chr airway obstruct NEC" ] }, { "key": "0c634bd307fe322fe7635e7c501216fb", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 0, 0, 42963 ] ], "agg_col": [ [ 0, 20 ], [ 3, 4 ] ], "sel": 0 }, "question_refine": "specify the admission time of patient id 42963 and name of drug he was treated with", "sql": "SELECT DEMOGRAPHIC.\"ADMITTIME\",PRESCRIPTIONS.\"DRUG\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"42963\"", "question_refine_tok": [ "specify", "the", "admission", "time", "of", "patient", "i", "d", "42963", "and", "name", "of", "drug", "he", "was", "treated", "with" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMITTIME\",PRESCRIPTIONS.\"DRUG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"42963\"" ], "answer": [ "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00", "2177-01-19 20:52:00" ] }, { "key": "978abea4b2ca331bf1fe71cf4ef8e76b", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Michelle Medina" ] ], "agg_col": [ [ 0, 9 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "let me know the type of admission and primary disease of patient michelle medina.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Michelle Medina\"", "question_refine_tok": [ "let", "me", "know", "the", "type", "of", "admission", "and", "primary", "disease", "of", "patient", "michelle", "medina", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Michelle", "Medina\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "967b4b86e33d04af0fe19b4704bc0947", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Estrella Carroll" ] ], "agg_col": [ [ 0, 4 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "let me know the age and procedure icd9 code for estrella carroll.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Estrella Carroll\"", "question_refine_tok": [ "let", "me", "know", "the", "age", "and", "procedure", "icd9", "code", "for", "estrella", "carroll", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Estrella", "Carroll\"" ], "answer": [ "58", "58", "58", "61", "61", "61", "61", "61", "61", "61", "61", "61" ] }, { "key": "84b5072282573a272fdb50327c7708c2", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "John Gartman" ] ], "agg_col": [ [ 1, 2 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "let me know the short title and icd9 code of diagnoses for patient john gartman.", "sql": "SELECT DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"John Gartman\"", "question_refine_tok": [ "let", "me", "know", "the", "short", "title", "and", "icd9", "code", "of", "diagnoses", "for", "patient", "john", "gartman", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"John", "Gartman\"" ], "answer": [ "25050", "2724", "2859", "36201", "4019", "41401", "4142", "45829", "51889", "56210", "7885", "79439", "V1083", "V1272" ] }, { "key": "8950462c2c058b210b4f8bf9ebd7df52", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Erik Dickerson" ] ], "agg_col": [ [ 0, 6 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "tell me the time of admission and gender of patient erik dickerson.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Erik Dickerson\"", "question_refine_tok": [ "tell", "me", "the", "time", "of", "admission", "and", "gender", "of", "patient", "erik", "dickerson", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Erik", "Dickerson\"" ], "answer": [ "M" ] }, { "key": "88cafcb9bcbf8a5b2e3f0e23b9239292", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Lue White" ] ], "agg_col": [ [ 0, 4 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "let me know the age and status of death of patient lue white.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Lue White\"", "question_refine_tok": [ "let", "me", "know", "the", "age", "and", "status", "of", "death", "of", "patient", "lue", "white", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Lue", "White\"" ], "answer": [ "55", "55" ] }, { "key": "a91662962db8e07e736ab98af1360c0e", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Lue White" ] ], "agg_col": [ [ 0, 5 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "What is the date of birth and admission time of Lue White?", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Lue White\"", "question_refine_tok": [ "What", "is", "the", "date", "of", "birth", "and", "admission", "time", "of", "Lue", "White", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Lue", "White\"" ], "answer": [ "2078-01-19 00:00:00", "2078-01-19 00:00:00" ] }, { "key": "028b981e8d52156a2146d57c9afa795c", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "David Trammell" ] ], "agg_col": [ [ 0, 5 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "What is the date of birth and primary disease of David Trammell?", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"David Trammell\"", "question_refine_tok": [ "What", "is", "the", "date", "of", "birth", "and", "primary", "disease", "of", "David", "Trammell", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"David", "Trammell\"" ], "answer": [ "2170-10-04 00:00:00" ] }, { "key": "a06c700768efa107c977fbd8f2d95989", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Herlinda Thomson" ] ], "agg_col": [ [ 0, 20 ] ], "sel": 0 }, "question_refine": "for patient herlinda thomson, specify the time of admission", "sql": "SELECT DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Herlinda Thomson\"", "question_refine_tok": [ "for", "patient", "herlinda", "thomson", ",", "specify", "the", "time", "of", "admission" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Herlinda", "Thomson\"" ], "answer": [ "2156-07-21 20:46:00" ] }, { "key": "aa3c4803c0aca1c991037d46ab8891a2", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Sheila Riley" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "for patient sheila riley, specify the duration of hospital stay", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Sheila Riley\"", "question_refine_tok": [ "for", "patient", "sheila", "riley", ",", "specify", "the", "duration", "of", "hospital", "stay" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Sheila", "Riley\"" ], "answer": [ "7" ] }, { "key": "09e03098584e026254e4f3b57ab3f524", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Alice Nixon" ] ], "agg_col": [ [ 2, 2 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title and icd9 code of procedure for patient alice nixon.", "sql": "SELECT PROCEDURES.\"ICD9_CODE\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Alice Nixon\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "and", "icd9", "code", "of", "procedure", "for", "patient", "alice", "nixon", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Alice", "Nixon\"" ], "answer": [ "3893", "5101", "5185" ] }, { "key": "ab0da7d05a345b85c091b469d2dc2d98", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Dona Cole" ] ], "agg_col": [ [ 0, 15 ], [ 3, 2 ] ], "sel": 0 }, "question_refine": "Specify the discharge location of patient Dona Cole along with the ICU stay ID", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\",PRESCRIPTIONS.\"ICUSTAY_ID\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Dona Cole\"", "question_refine_tok": [ "Specify", "the", "discharge", "location", "of", "patient", "Dona", "Cole", "along", "with", "the", "ICU", "stay", "ID" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\",PRESCRIPTIONS.\"ICUSTAY_ID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Dona", "Cole\"" ], "answer": [ "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME", "HOME" ] }, { "key": "0709550ec8aeff15ee0fd6fe36ed4c0f", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Theresa Vedovelli" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "Theresa Vedovelli is primarily suffering from which disease?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Theresa Vedovelli\"", "question_refine_tok": [ "Theresa", "Vedovelli", "is", "primarily", "suffering", "from", "which", "disease", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Theresa", "Vedovelli\"" ], "answer": [ "COMPLETE HEART BLOCK" ] }, { "key": "85a026e0c7b74858f0f566d3bbf499e0", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Bruce Harris" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 0 }, "question_refine": "find the age of subject name bruce harris.", "sql": "SELECT DEMOGRAPHIC.\"AGE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Bruce Harris\"", "question_refine_tok": [ "find", "the", "age", "of", "subject", "name", "bruce", "harris", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Bruce", "Harris\"" ], "answer": [ "70", "70", "70", "70", "70" ] }, { "key": "0138ed4f1a039573afe3d860e12c2de9", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Bruce Harris" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "for how long the patient bruce harris remained admitted in hospital?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Bruce Harris\"", "question_refine_tok": [ "for", "how", "long", "the", "patient", "bruce", "harris", "remained", "admitted", "in", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Bruce", "Harris\"" ], "answer": [ "93", "12", "23", "17", "24" ] }, { "key": "90d3424a81b4bfd9018d96003eb18bd8", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Wilbur Braatz" ] ], "agg_col": [ [ 0, 16 ], [ 3, 4 ] ], "sel": 0 }, "question_refine": "what is the primary disease and drug name of Wilbur Braatz?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",PRESCRIPTIONS.\"DRUG\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Wilbur Braatz\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "and", "drug", "name", "of", "Wilbur", "Braatz", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",PRESCRIPTIONS.\"DRUG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Wilbur", "Braatz\"" ], "answer": [ "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN" ] }, { "key": "9aed3ef959f024e0ffaf5f92500bda5a", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Betty Campbell" ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "mention the primary disease and diagnosis short title of the subject name betty campbell.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Betty Campbell\"", "question_refine_tok": [ "mention", "the", "primary", "disease", "and", "diagnosis", "short", "title", "of", "the", "subject", "name", "betty", "campbell", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Betty", "Campbell\"" ], "answer": [ "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA", "ANGIOEDEMA" ] }, { "key": "90a66ad09f084e315532cba91f3c36e6", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Thomas Nazario" ] ], "agg_col": [ [ 0, 14 ] ], "sel": 0 }, "question_refine": "From which location was the patient Thomas Nazario admitted to the hospital?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Thomas Nazario\"", "question_refine_tok": [ "From", "which", "location", "was", "the", "patient", "Thomas", "Nazario", "admitted", "to", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Thomas", "Nazario\"" ], "answer": [ "EMERGENCY ROOM ADMIT", "TRANSFER FROM HOSP/EXTRAM" ] }, { "key": "0ef6faed83eede01bf4c9bb3f186fe66", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Thomas Nazario" ] ], "agg_col": [ [ 2, 2 ], [ 2, 3 ] ], "sel": 0 }, "question_refine": "let me know both the short title and icd9 code of procedure of patient thomas nazario.", "sql": "SELECT PROCEDURES.\"ICD9_CODE\",PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Thomas Nazario\"", "question_refine_tok": [ "let", "me", "know", "both", "the", "short", "title", "and", "icd9", "code", "of", "procedure", "of", "patient", "thomas", "nazario", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\",PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Thomas", "Nazario\"" ], "answer": [ "3606", "3723", "8856", "9920", "3512", "3532", "3611", "3615", "3723", "3761", "3931", "3961", "8856" ] }, { "key": "a41c0a71e44265cf13545eae050408e0", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "James Cepeda" ] ], "agg_col": [ [ 0, 14 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "specify the primary disease of james cepeda and where he was admitted", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"James Cepeda\"", "question_refine_tok": [ "specify", "the", "primary", "disease", "of", "james", "cepeda", "and", "where", "he", "was", "admitted" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"James", "Cepeda\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "a8b30455030b0d504a6f7baf7a42414b", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Anna Johnson" ] ], "agg_col": [ [ 3, 2 ], [ 3, 4 ] ], "sel": 0 }, "question_refine": "what is the icu stay id and drug name of the patient anna johnson?", "sql": "SELECT PRESCRIPTIONS.\"ICUSTAY_ID\",PRESCRIPTIONS.\"DRUG\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Anna Johnson\"", "question_refine_tok": [ "what", "is", "the", "icu", "stay", "i", "d", "and", "drug", "name", "of", "the", "patient", "anna", "johnson", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"ICUSTAY_ID\",PRESCRIPTIONS.\"DRUG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Anna", "Johnson\"" ], "answer": [ "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532", "227532" ] }, { "key": "037db39747b876ad48d9d833698b4487", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Anna Johnson" ] ], "agg_col": [ [ 3, 5 ], [ 3, 7 ] ], "sel": 0 }, "question_refine": "provide the drug code and drug dose for anna johnson.", "sql": "SELECT PRESCRIPTIONS.\"FORMULARY_DRUG_CD\",PRESCRIPTIONS.\"DRUG_DOSE\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Anna Johnson\"", "question_refine_tok": [ "provide", "the", "drug", "code", "and", "drug", "dose", "for", "anna", "johnson", "." ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\",PRESCRIPTIONS.\"DRUG_DOSE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Anna", "Johnson\"" ], "answer": [ "CAFCIT", "CAFCIT", "CAFFCIT60I", "CAFFCIT60I", "CAFFCIT60I", "CAFFCIT60I", "D10W250I", "D10W250I", "D10W250I", "D10W250I", "GENT10I", "KCL40I", "KCL40I", "NACL4I", "NACL4I", "NACL4I", "NACL4I", "NCLINDIV", "NEOFAT", "NEOFAT", "NEOFER", "NEOSYR", "NEOSYR", "NEOSYRD5W", "NEOSYRNS", "NEOSYRSL", "NEOSYRSL", "NEOSYRSL", "NEOSYRSL", "NEOSYRSW", "NEOVITE", "NTPN", "NTPN", "NVAN500I" ] }, { "key": "02f1240111fceb0677dbe6db60180e46", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Fernando Wontor" ] ], "agg_col": [ [ 0, 5 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "let me know the birth date and short title of diagnoses for patient fernando wontor.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Fernando Wontor\"", "question_refine_tok": [ "let", "me", "know", "the", "birth", "date", "and", "short", "title", "of", "diagnoses", "for", "patient", "fernando", "wontor", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Fernando", "Wontor\"" ], "answer": [ "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00", "2024-07-13 00:00:00" ] }, { "key": "05892334ccb408737d46670f428672c0", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Annette Harris" ] ], "agg_col": [ [ 0, 15 ] ], "sel": 0 }, "question_refine": "what is the discharge location for the patient annette haris?", "sql": "SELECT DEMOGRAPHIC.\"DISCHARGE_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Annette Harris\"", "question_refine_tok": [ "what", "is", "the", "discharge", "location", "for", "the", "patient", "annette", "haris", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Annette", "Harris\"" ], "answer": [ "HOME" ] }, { "key": "0a7ebbf361bf96cd1fcfb073368908b5", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Robert Clayton" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "find the primary disease of robert clayton.", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Robert Clayton\"", "question_refine_tok": [ "find", "the", "primary", "disease", "of", "robert", "clayton", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Robert", "Clayton\"" ], "answer": [ "ATRIAL FIBRILLATION\\THORACOSCOPIC MAZE PROCEDURE BILATERAL/SDA", "DUODENAL ULCER;S/P ERCP" ] }, { "key": "a8e521fe75222082e06f1a643ea9daca", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Kurt Buczek" ] ], "agg_col": [ [ 0, 10 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "what is the number of days of hospital stay and diagnosis for the patient named Kurt Buczek?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Kurt Buczek\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "days", "of", "hospital", "stay", "and", "diagnosis", "for", "the", "patient", "named", "Kurt", "Buczek", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kurt", "Buczek\"" ], "answer": [ "5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9" ] }, { "key": "95832f8e506136d97ce571b7c5bd4e10", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Francis Baseler" ] ], "agg_col": [ [ 1, 2 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "what is the diagnosis code and diagnosis long title for the patient francis baseler?", "sql": "SELECT DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Francis Baseler\"", "question_refine_tok": [ "what", "is", "the", "diagnosis", "code", "and", "diagnosis", "long", "title", "for", "the", "patient", "francis", "baseler", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"ICD9_CODE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Francis", "Baseler\"" ], "answer": [ "27651", "2920", "3004", "3009", "30401", "30789", "33819", "3384", "4019", "42682", "5771", "7850", "78703", "78906", "9961", "E8497", "E9530", "V1251", "V189", "V554", "V5869", "V5883", "2639", "2809", "2869", "29634", "30400", "33829", "34690", "56962", "5771", "E9530", "V489", "V6284" ] }, { "key": "1017466aa786d9466aa74af6bd0700ec", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Travis Hofman" ] ], "agg_col": [ [ 0, 9 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "provide me the admission type and primary disease of patient travis hofman.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Travis Hofman\"", "question_refine_tok": [ "provide", "me", "the", "admission", "type", "and", "primary", "disease", "of", "patient", "travis", "hofman", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Travis", "Hofman\"" ], "answer": [ "EMERGENCY" ] }, { "key": "0526387ed551a149d6f3ef5ed44debd7", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Glen Tanner" ] ], "agg_col": [ [ 0, 9 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "tell me the type of admission and number of days for which patient glen tanner stayed in hospital.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Glen Tanner\"", "question_refine_tok": [ "tell", "me", "the", "type", "of", "admission", "and", "number", "of", "days", "for", "which", "patient", "glen", "tanner", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Glen", "Tanner\"" ], "answer": [ "ELECTIVE", "ELECTIVE" ] }, { "key": "93392d4f42172fe72a713de4056a2022", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Michael Witt" ] ], "agg_col": [ [ 0, 10 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "tell me the time of admission and days for which patient michael witt was hospitalized.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Michael Witt\"", "question_refine_tok": [ "tell", "me", "the", "time", "of", "admission", "and", "days", "for", "which", "patient", "michael", "witt", "was", "hospitalized", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Michael", "Witt\"" ], "answer": [ "3" ] }, { "key": "a557a27486342d06e45decaab91aeed8", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Caren Obrien" ] ], "agg_col": [ [ 0, 5 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "tell me the birth date and primary disease of patient caren obrien.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Caren Obrien\"", "question_refine_tok": [ "tell", "me", "the", "birth", "date", "and", "primary", "disease", "of", "patient", "caren", "obrien", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Caren", "Obrien\"" ], "answer": [ "1882-10-10 00:00:00" ] }, { "key": "9cea5cf9416c2b932de255262ed701f1", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Caren Obrien" ] ], "agg_col": [ [ 0, 5 ], [ 0, 17 ] ], "sel": 0 }, "question_refine": "let me know the birth date and death date of patient caren obrien.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DOD\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Caren Obrien\"", "question_refine_tok": [ "let", "me", "know", "the", "birth", "date", "and", "death", "date", "of", "patient", "caren", "obrien", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DOD\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Caren", "Obrien\"" ], "answer": [ "1882-10-10 00:00:00" ] }, { "key": "0dfbdefe2efe9810a0ad327a0d448a71", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Steven Sepulveda" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "for how many days did steven sepulveda stay in the hospital.", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Steven Sepulveda\"", "question_refine_tok": [ "for", "how", "many", "days", "did", "steven", "sepulveda", "stay", "in", "the", "hospital", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Steven", "Sepulveda\"" ], "answer": [ "4", "2" ] }, { "key": "a86dc1e19d6244f13305f53792c665ce", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "James Sloan" ] ], "agg_col": [ [ 0, 5 ], [ 0, 9 ] ], "sel": 0 }, "question_refine": "what is the date of birth and admission type of James Sloan?", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"James Sloan\"", "question_refine_tok": [ "what", "is", "the", "date", "of", "birth", "and", "admission", "type", "of", "James", "Sloan", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"James", "Sloan\"" ], "answer": [ "2121-01-08 00:00:00" ] }, { "key": "8bec95e32428f06d6b8734cae16910d0", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "James Sloan" ] ], "agg_col": [ [ 0, 11 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "tell me the insurance and primary disease of james sloan.", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"James Sloan\"", "question_refine_tok": [ "tell", "me", "the", "insurance", "and", "primary", "disease", "of", "james", "sloan", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"James", "Sloan\"" ], "answer": [ "Private" ] }, { "key": "0463b36bc02d774cc36b466eb3d32c4d", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Charley Pescatore" ] ], "agg_col": [ [ 0, 9 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "For patient Charley Pescatore, specify the admission type and duration of stay in the hospital", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Charley Pescatore\"", "question_refine_tok": [ "For", "patient", "Charley", "Pescatore", ",", "specify", "the", "admission", "type", "and", "duration", "of", "stay", "in", "the", "hospital" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Charley", "Pescatore\"" ], "answer": [ "NEWBORN" ] }, { "key": "9b6bb1dbb4f307b37a8895086eafcd38", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Dominga Garvin" ] ], "agg_col": [ [ 2, 4 ] ], "sel": 0 }, "question_refine": "give the procedure description of dominga garvin.", "sql": "SELECT PROCEDURES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Dominga Garvin\"", "question_refine_tok": [ "give", "the", "procedure", "description", "of", "dominga", "garvin", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Dominga", "Garvin\"" ], "answer": [ "Arteriography of cerebral arteries", "Enteral infusion of concentrated nutritional substances" ] }, { "key": "81e9f164c2850387ea449c4ba9ca050c", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Miguel Hodges" ] ], "agg_col": [ [ 0, 16 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "what is the primary disease and diagnosis for the patient name miguel hodges?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Miguel Hodges\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "and", "diagnosis", "for", "the", "patient", "name", "miguel", "hodges", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Miguel", "Hodges\"" ], "answer": [ "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE", "OVERDOSE" ] }, { "key": "a52b3652548d36c5e3f3bafc284608e4", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "78630" ] ], "agg_col": [ [ 1, 3 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "give the title and description of diagnoses icd9 code 78630.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"78630\"", "question_refine_tok": [ "give", "the", "title", "and", "description", "of", "diagnoses", "icd9", "code", "78630", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"78630\"" ], "answer": [ "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS", "Hemoptysis NOS" ] }, { "key": "8e472c2e5d903307b93d43dc9467159e", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "E8786" ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "what is the diagnosis long title of diagnosis icd9 code e8786?", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"E8786\"", "question_refine_tok": [ "what", "is", "the", "diagnosis", "long", "title", "of", "diagnosis", "icd9", "code", "e8786", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"E8786\"" ], "answer": [ "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of 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other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation", "Removal of other organ (partial) (total) causing abnormal patient reaction, or later complication, without mention of misadventure at time of operation" ] }, { "key": "aa19597bca0018f872dd2eeb8774d993", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "42823" ] ], "agg_col": [ [ 1, 3 ], [ 1, 4 ] ], "sel": 0 }, "question_refine": "Look for the diagnoses short title and long title of icd9 code 42823.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"42823\"", "question_refine_tok": [ "Look", "for", "the", "diagnoses", "short", "title", "and", "long", "title", "of", "icd9", "code", "42823", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\",DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"42823\"" ], "answer": [ "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on 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chr syst hrt fail", "Ac on chr syst hrt fail", "Ac on chr syst hrt fail" ] }, { "key": "977bc9261b04291c69b98ea4056c1554", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "42833" ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "provide me the long title of diagnoses for diagnoses icd9 code 42833.", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"42833\"", "question_refine_tok": [ "provide", "me", "the", "long", "title", "of", "diagnoses", "for", "diagnoses", "icd9", "code", "42833", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"42833\"" ], "answer": [ "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", 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diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure", "Acute on chronic diastolic heart failure" ] }, { "key": "bb111642a21315b380f245d80996b88a", "format": { "table": [ 1 ], "cond": [ [ 1, 2, 0, "7756" ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "what is the long title of diagnosis of icd9 code 7756?", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"ICD9_CODE\" = \"7756\"", "question_refine_tok": [ "what", "is", "the", "long", "title", "of", "diagnosis", "of", "icd9", "code", "7756", "?" ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"7756\"" ], "answer": [ "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia", "Neonatal hypoglycemia" ] }, { "key": "8f3d8dae93b4add45472e2ef34e06826", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 9744 ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title of procedure for procedure icd9 code 9744.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"9744\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "of", "procedure", "for", "procedure", "icd9", "code", "9744", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9744\"" ], "answer": [ "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys", "Nonop remov hrt asst sys" ] }, { "key": "019e78abb55f24f850aee87e473bc363", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 3726 ] ], "agg_col": [ [ 2, 4 ] ], "sel": 0 }, "question_refine": "what is the procedure long title of procedure icd9 code 3726?", "sql": "SELECT PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"3726\"", "question_refine_tok": [ "what", "is", "the", "procedure", "long", "title", "of", "procedure", "icd9", "code", "3726", "?" ], "sql_tok": [ "SELECT", "PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"3726\"" ], "answer": [ "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing", "Catheter based invasive electrophysiologic testing" ] }, { "key": "a5b799b623ab816af8a3d7263bd882cb", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 5361 ] ], "agg_col": [ [ 2, 3 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "get me the long title and short title of procedure for procedure icd9 code 5361.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\",PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"5361\"", "question_refine_tok": [ "get", "me", "the", "long", "title", "and", "short", "title", "of", "procedure", "for", "procedure", "icd9", "code", "5361", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\",PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5361\"" ], "answer": [ "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC", "Open incis hern-grft NEC" ] }, { "key": "895ca1f9dc05114c51436d4c28f1dbaa", "format": { "table": [ 2 ], "cond": [ [ 2, 2, 0, 4591 ] ], "agg_col": [ [ 2, 3 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "specify complete details of icd9 code 4591", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\",PROCEDURES.\"LONG_TITLE\" FROM PROCEDURES WHERE PROCEDURES.\"ICD9_CODE\" = \"4591\"", "question_refine_tok": [ "specify", "complete", "details", "of", "icd9", "code", "4591" ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\",PROCEDURES.\"LONG_TITLE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4591\"" ], "answer": [ "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom", "Sm-to-sm bowel anastom" ] }, { "key": "ba004a3e4242e9bae1c49388678321ec", "format": { "table": [ 3 ], "cond": [ [ 3, 4, 0, "Nitroglycerin SL" ] ], "agg_col": [ [ 3, 5 ] ], "sel": 0 }, "question_refine": "provide me the drug code for nitroglycerin sl.", "sql": "SELECT PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"DRUG\" = \"Nitroglycerin SL\"", "question_refine_tok": [ "provide", "me", "the", "drug", "code", "for", "nitroglycerin", "sl", "." ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Nitroglycerin", "SL\"" ], "answer": [ "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG3SL", "NTG4SL", "NTG4SL", "NTG4SL", "NTG3SL", "NTG3SL", 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"question_refine": "let me know the drug code and route of administration of lidocaine jelly 2% (urojet).", "sql": "SELECT PRESCRIPTIONS.\"FORMULARY_DRUG_CD\",PRESCRIPTIONS.\"ROUTE\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"DRUG\" = \"Lidocaine Jelly 2% (Urojet)\"", "question_refine_tok": [ "let", "me", "know", "the", "drug", "code", "and", "route", "of", "administration", "of", "lidocaine", "jelly", "2", "%", "(", "urojet", ")", "." ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\",PRESCRIPTIONS.\"ROUTE\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Lidocaine", "Jelly", "2%", "(Urojet)\"" ], "answer": [ "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", "LID2J", 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"MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN" ] }, { "key": "87728d8251e916027eaacb64dac36ccb", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of male patients.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\"", "question_refine_tok": [ "calculate", "the", "number", "of", "male", "patients", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"" ], "answer": [ "26121" ] }, { "key": "024563b12e10d2bfbba3b9049fdb34cd", "format": { "table": [ 0 ], "cond": [ [ 0, 8, 0, "GREEK ORTHODOX" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients belong to greek orthodox religion?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"RELIGION\" = \"GREEK ORTHODOX\"", "question_refine_tok": [ "how", "many", "patients", "belong", "to", "greek", "orthodox", "religion", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"GREEK", "ORTHODOX\"" ], "answer": [ "326" ] }, { "key": "054cab8f7975c46d400a46a17beb5a13", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients had emergency hospital admission?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\"", "question_refine_tok": [ "which", "patients", "had", "emergency", "hospital", "admission", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"" ], "answer": [ "32610" ] }, { "key": "8383881fa94d0f2f2f6fb0926ad61d32", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Private" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with private insurance?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "private", "insurance", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"" ], "answer": [ "19663" ] }, { "key": "a93baacae2d538d21878b556201cec87", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/CAPE VERDEAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the total number of patients have a black/cape verdean ethnic origin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/CAPE VERDEAN\"", "question_refine_tok": [ "How", "many", "of", "the", "total", "number", "of", "patients", "have", "a", "black/cape", "verdean", "ethnic", "origin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/CAPE", "VERDEAN\"" ], "answer": [ "167" ] }, { "key": "03ed80dd509832cdb2d2e7d7fd0e39f1", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the total number of asian patients. ", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\"", "question_refine_tok": [ "calculate", "the", "total", "number", "of", "asian", "patients", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"" ], "answer": [ "1306" ] }, { "key": "06e0f15a5f27b3648bf3f5ebf230eb3d", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who are still alive?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "are", "still", "alive", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"" ], "answer": [ "30761" ] }, { "key": "9c3b0945adc7bb0056a72123f8627678", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "CLINIC REFERRAL/PREMATURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were admitted on clinic referral/premature?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"CLINIC REFERRAL/PREMATURE\"", "question_refine_tok": [ "how", "many", "patients", "were", "admitted", "on", "clinic", "referral", "/", "premature", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"CLINIC", "REFERRAL/PREMATURE\"" ], "answer": [ "10554" ] }, { "key": "00904139a2ed10eebae557a135321017", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRSF WITHIN THIS FACILITY" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were transferred within this facilty?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRSF WITHIN THIS FACILITY\"", "question_refine_tok": [ "how", "many", "patients", "were", "transferred", "within", "this", "facilty", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRSF", "WITHIN", "THIS", "FACILITY\"" ], "answer": [ "5" ] }, { "key": "02df0bf53f302df39ca66c8e45f609c3", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "HOME" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who were discharged at home.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "were", "discharged", "at", "home", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"" ], "answer": [ "17019" ] }, { "key": "825152ca77b3c046ea92f81d47a817eb", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "DEAD/EXPIRED" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose discharge location is dead/expired.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DEAD/EXPIRED\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "discharge", "location", "is", "dead", "/", "expired", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DEAD/EXPIRED\"" ], "answer": [ "5813" ] }, { "key": "9c0511b4b79fb45a8f646934b25ee1f1", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "LEFT AGAINST MEDICAL ADVI" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who left the hospital against medical advice.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"LEFT AGAINST MEDICAL ADVI\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "left", "the", "hospital", "against", "medical", "advice", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"LEFT", "AGAINST", "MEDICAL", "ADVI\"" ], "answer": [ "305" ] }, { "key": "04e257060d814171a01a4a75a258d385", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "T5 FRACTURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are primarily suffering from t5 fracture?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"T5 FRACTURE\"", "question_refine_tok": [ "how", "many", "patients", "are", "primarily", "suffering", "from", "t5", "fracture", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"T5", "FRACTURE\"" ], "answer": [ "1" ] }, { "key": "0de053e6336b792bbab0dbed98a160b9", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "RUQ PAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients suffering from right upper quadrant pain primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"RUQ PAIN\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "suffering", "from", "right", "upper", "quadrant", "pain", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"RUQ", "PAIN\"" ], "answer": [ "3" ] }, { "key": "8e5b3b23c0faa725dddd16452c1d83cd", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "NEWBORN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find out the number of patients with a newborn primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"NEWBORN\"", "question_refine_tok": [ "Find", "out", "the", "number", "of", "patients", "with", "a", "newborn", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"NEWBORN\"" ], "answer": [ "7821" ] }, { "key": "9ead4702111aae4baa6cdeb38d1d16c9", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "PNEUMONIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients are suffering from pneumonia primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"PNEUMONIA\"", "question_refine_tok": [ "which", "patients", "are", "suffering", "from", "pneumonia", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PNEUMONIA\"" ], "answer": [ "1419" ] }, { "key": "03ad1ed58197cc476c639d7af7c662a3", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "TRANSIENT ISCHEMIC ATTACK" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the total number of patients who had transient ischemic attack as their primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"TRANSIENT ISCHEMIC ATTACK\"", "question_refine_tok": [ "Calculate", "the", "total", "number", "of", "patients", "who", "had", "transient", "ischemic", "attack", "as", "their", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"TRANSIENT", "ISCHEMIC", "ATTACK\"" ], "answer": [ "18" ] }, { "key": "94e979800c12fea24b8722c512dd7405", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "BLADDER CANCER/SDA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with primary disease bladder cancer/sda?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BLADDER CANCER/SDA\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "primary", "disease", "bladder", "cancer", "/", "sda", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BLADDER", "CANCER/SDA\"" ], "answer": [ "22" ] }, { "key": "9af2ac2fa84ad307ea5249d5fb48b41b", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "BOWEL OBSTRUCTION" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients who are diagnosed with bowel obstruction.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BOWEL OBSTRUCTION\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "who", "are", "diagnosed", "with", "bowel", "obstruction", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BOWEL", "OBSTRUCTION\"" ], "answer": [ "98" ] }, { "key": "84f60321f795ad3a40988a8e42b9ff0c", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "GANGRENE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with primary disease gangrene?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GANGRENE\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "primary", "disease", "gangrene", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GANGRENE\"" ], "answer": [ "12" ] }, { "key": "004cf3d0d60da7389659caadbfb4a825", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "PITUITARY BLEED" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had pituitary bleed?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"PITUITARY BLEED\"", "question_refine_tok": [ "how", "many", "patients", "had", "pituitary", "bleed", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PITUITARY", "BLEED\"" ], "answer": [ "1" ] }, { "key": "9268ab37a2d7fdb001795bef1e30dbe2", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CORONARY ARTERY DISEASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients with coronary artery primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CORONARY ARTERY DISEASE\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "with", "coronary", "artery", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CORONARY", "ARTERY", "DISEASE\"" ], "answer": [ "839" ] }, { "key": "0cb83c2bc10e573ed3e25a658d8318e4", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "HYPERGLYCEMIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients have been diagnosed with hyperglycemia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPERGLYCEMIA\"", "question_refine_tok": [ "what", "number", "of", "patients", "have", "been", "diagnosed", "with", "hyperglycemia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPERGLYCEMIA\"" ], "answer": [ "59" ] }, { "key": "971fc7bf3f897252845c4ebd01de0302", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 64 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are below 64 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"64\"", "question_refine_tok": [ "how", "many", "patients", "are", "below", "64", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"64\"" ], "answer": [ "25586" ] }, { "key": "82de3dcebd85dfb2141910f538b7fe07", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 27 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tally the number of patients under the age of 27.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"27\"", "question_refine_tok": [ "tally", "the", "number", "of", "patients", "under", "the", "age", "of", "27", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"27\"" ], "answer": [ "9392" ] }, { "key": "0ebb2c6d344b9709c6c88b5ea686c13e", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 2, 2182 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who were born before 2182?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2182\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "were", "born", "before", "2182", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2182\"" ], "answer": [ "45037" ] }, { "key": "0c553b22210b5ad96a9a01680ef22091", "format": { "table": [ 0 ], "cond": [ [ 0, 19, 4, 2180.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients who passed away in or before the year 2180.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2180.0\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "who", "passed", "away", "in", "or", "before", "the", "year", "2180", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2180.0\"" ], "answer": [ "12342" ] }, { "key": "8232941afbee51d5e20e7dcf879ee83f", "format": { "table": [ 0 ], "cond": [ [ 0, 19, 4, 2132.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients who were born in or before 2132.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2132.0\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "who", "were", "born", "in", "or", "before", "2132", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2132.0\"" ], "answer": [ "4820" ] }, { "key": "bb19be85af3e917061a124154ac4818b", "format": { "table": [ 0 ], "cond": [ [ 0, 19, 4, 2111.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the total number of patients who died in or before the year 2111?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2111.0\"", "question_refine_tok": [ "What", "is", "the", "total", "number", "of", "patients", "who", "died", "in", "or", "before", "the", "year", "2111", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2111.0\"" ], "answer": [ "1531" ] }, { "key": "0d326c2914714602a81cd8d61f8e9ac6", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "V4364" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who have v4364 diagnoses icd9 code?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"V4364\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "have", "v4364", "diagnoses", "icd9", "code", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"V4364\"" ], "answer": [ "706" ] }, { "key": "101713b242bbc2a546b1dcc3dea29920", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 2, 0, "2875" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who have diagnoses icd9 code 2875?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"2875\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "have", "diagnoses", "icd9", "code", "2875", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2875\"" ], "answer": [ "2807" ] }, { "key": "9c185af46be35cab5c7f0bc760c202b5", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Pseudomonas infect NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have been diagnosed with unspecified pseudomonas infection?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Pseudomonas infect NOS\"", "question_refine_tok": [ "how", "many", "patients", "have", "been", "diagnosed", "with", "unspecified", "pseudomonas", "infection", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Pseudomonas", "infect", "NOS\"" ], "answer": [ "376" ] }, { "key": "93b1013135b3f8b94446490eb23a4ccc", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Subarachnoid hemorrhage" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose diagnosis short title is subarachnoid hemorrhage.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Subarachnoid hemorrhage\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "diagnosis", "short", "title", "is", "subarachnoid", "hemorrhage", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Subarachnoid", "hemorrhage\"" ], "answer": [ "647" ] }, { "key": "9e33f7987cb3bdf5b47e8b870d28d06e", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Urinary incontinence NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were diagnosed with urinary incontinence nos?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Urinary incontinence NOS\"", "question_refine_tok": [ "how", "many", "patients", "were", "diagnosed", "with", "urinary", "incontinence", "nos", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Urinary", "incontinence", "NOS\"" ], "answer": [ "293" ] }, { "key": "ab3f3d61bd231c11a4f22dce7af58d02", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Crbl art ocl NOS w infrc" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients who were diagnosed with unspecified cerebral artery occlusion with cerebral infarction.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Crbl art ocl NOS w infrc\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "who", "were", "diagnosed", "with", "unspecified", "cerebral", "artery", "occlusion", "with", "cerebral", "infarction", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Crbl", "art", "ocl", "NOS", "w", "infrc\"" ], "answer": [ "728" ] }, { "key": "86700c0eae00722e324e12c3ebb72980", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 3, 0, "Secundum atrial sept def" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with secundum atrial septum defect?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Secundum atrial sept def\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "secundum", "atrial", "septum", "defect", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Secundum", "atrial", "sept", "def\"" ], "answer": [ "621" ] }, { "key": "0d3a0c773b794768a307800f42bed3ae", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 4, 0, "Other shock without mention of trauma" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients had other shock without mention of trauma?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Other shock without mention of trauma\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "had", "other", "shock", "without", "mention", "of", "trauma", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Other", "shock", "without", "mention", "of", "trauma\"" ], "answer": [ "530" ] }, { "key": "870f671294fda99c32cc17f92aad78a8", "format": { "table": [ 0, 1 ], "cond": [ [ 1, 4, 0, "Hemochromatosis due to repeated red blood cell transfusions" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had the diagnosis long title hemochromatosis due to repeated red blood cell transfusions?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Hemochromatosis due to repeated red blood cell transfusions\"", "question_refine_tok": [ "how", "many", "patients", "had", "the", "diagnosis", "long", "title", "hemochromatosis", "due", "to", "repeated", "red", "blood", "cell", "transfusions", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Hemochromatosis", "due", "to", "repeated", "red", "blood", "cell", "transfusions\"" ], "answer": [ "2" ] }, { "key": "809481545e7a77fa4c823f05ba51741b", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 4105 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "specify the total number of patients who had icd9 code 4105", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"4105\"", "question_refine_tok": [ "specify", "the", "total", "number", "of", "patients", "who", "had", "icd9", "code", "4105" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4105\"" ], "answer": [ "29" ] }, { "key": "05c5dbad2999a021a98bc80262a523d1", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 4601 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the total number of patients who had icd9 code 4601", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"4601\"", "question_refine_tok": [ "what", "is", "the", "total", "number", "of", "patients", "who", "had", "icd9", "code", "4601" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4601\"" ], "answer": [ "73" ] }, { "key": "931575a48b183cfef6810a7748886f1c", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 2, 0, 3804 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get the number of patients who have procedure icd9 code 3804.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"3804\"", "question_refine_tok": [ "get", "the", "number", "of", "patients", "who", "have", "procedure", "icd9", "code", "3804", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"3804\"" ], "answer": [ "10" ] }, { "key": "a601dcef90267006aea6385d22fd36d3", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "Cardiac rhythm conv NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose procedure short title is cardiac rhythm conv nec.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"Cardiac rhythm conv NEC\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "whose", "procedure", "short", "title", "is", "cardiac", "rhythm", "conv", "nec", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Cardiac", "rhythm", "conv", "NEC\"" ], "answer": [ "90" ] }, { "key": "0d4c35f952b8d4ff9c7b0b736d1556f1", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "Abdomen artery incision" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the total number of patients who had abdomen artery incision.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"Abdomen artery incision\"", "question_refine_tok": [ "calculate", "the", "total", "number", "of", "patients", "who", "had", "abdomen", "artery", "incision", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Abdomen", "artery", "incision\"" ], "answer": [ "32" ] }, { "key": "90c61fa47e6f3ee70f1d5a5262acea5b", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "Radical cystectomy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who underwent radical cystectomy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"Radical cystectomy\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "underwent", "radical", "cystectomy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Radical", "cystectomy\"" ], "answer": [ "55" ] }, { "key": "a74c0d773d66fce959ed3490677faac0", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 3, 0, "Opn lft hemicolectmy NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients had open and other left hemicolectomy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"SHORT_TITLE\" = \"Opn lft hemicolectmy NEC\"", "question_refine_tok": [ "which", "patients", "had", "open", "and", "other", "left", "hemicolectomy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Opn", "lft", "hemicolectmy", "NEC\"" ], "answer": [ "117" ] }, { "key": "9ce7d4ba8e33f5a9bb87ec0199c5fcd2", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 4, 0, "Creation of conduit between left ventricle and aorta" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had procedure creation of conduit between left ventricle and aorta?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"LONG_TITLE\" = \"Creation of conduit between left ventricle and aorta\"", "question_refine_tok": [ "how", "many", "patients", "had", "procedure", "creation", "of", "conduit", "between", "left", "ventricle", "and", "aorta", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Creation", "of", "conduit", "between", "left", "ventricle", "and", "aorta\"" ], "answer": [ "4" ] }, { "key": "8a2e0e54555d64dde3f63958cea24cc7", "format": { "table": [ 0, 2 ], "cond": [ [ 2, 4, 0, "Drug detoxification" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who underwent drug detoxification.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE PROCEDURES.\"LONG_TITLE\" = \"Drug detoxification\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "underwent", "drug", "detoxification", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Drug", "detoxification\"" ], "answer": [ "35" ] }, { "key": "86f305efdfde01b908615d3b271a35ad", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Diltiazem" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were treated with diltiazem?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Diltiazem\"", "question_refine_tok": [ "how", "many", "patients", "were", "treated", "with", "diltiazem", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Diltiazem\"" ], "answer": [ "3476" ] }, { "key": "abba3e287b6c32380cd3174ef6088b7f", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Hydrocortisone Oint 0.5%" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had the drug name hydrocortisone oint 0.5%?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Hydrocortisone Oint 0.5%\"", "question_refine_tok": [ "how", "many", "patients", "had", "the", "drug", "name", "hydrocortisone", "oint", "0.5", "%", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Hydrocortisone", "Oint", "0.5%\"" ], "answer": [ "13" ] }, { "key": "02984008762913113973753bce29760d", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Spironolactone" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have prescription for spironolactone medication?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Spironolactone\"", "question_refine_tok": [ "which", "patients", "have", "prescription", "for", "spironolactone", "medication", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Spironolactone\"" ], "answer": [ "1738" ] }, { "key": "82d3695ec5d890238e93c72e3a314ced", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Nitroglycerin Ointment 2%" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how any patients have been given nitroglycerin ointment 2%?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Nitroglycerin Ointment 2%\"", "question_refine_tok": [ "how", "any", "patients", "have", "been", "given", "nitroglycerin", "ointment", "2", "%", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Nitroglycerin", "Ointment", "", "2%\"" ], "answer": [ "571" ] }, { "key": "04e11bc1fccec154a83252f26868c437", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Tizanidine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "specify the total number of patients treated with tizanidine", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Tizanidine\"", "question_refine_tok": [ "specify", "the", "total", "number", "of", "patients", "treated", "with", "tizanidine" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Tizanidine\"" ], "answer": [ "187" ] }, { "key": "07e8317bfc6823eb329bd116ced86994", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 4, 0, "Ferrous Gluconate" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were given the drug ferrous gluconate?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"DRUG\" = \"Ferrous Gluconate\"", "question_refine_tok": [ "how", "many", "patients", "were", "given", "the", "drug", "ferrous", "gluconate", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Ferrous", "Gluconate\"" ], "answer": [ "523" ] }, { "key": "909508f96947421e68d99c31bd253ef0", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "PRED1" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have been prescribed the drug with code pred1?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"PRED1\"", "question_refine_tok": [ "how", "many", "patients", "have", "been", "prescribed", "the", "drug", "with", "code", "pred1", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"PRED1\"" ], "answer": [ "215" ] }, { "key": "a5d9467737164f47007345c4893d763f", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "BACTSS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have drug code bactss?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"BACTSS\"", "question_refine_tok": [ "which", "patients", "have", "drug", "code", "bactss", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"BACTSS\"" ], "answer": [ "851" ] }, { "key": "a8dc0bd5c32a5391be47e8cfd979667e", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "ATRO1I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had drug code atro1i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"ATRO1I\"", "question_refine_tok": [ "how", "many", "patients", "had", "drug", "code", "atro1i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"ATRO1I\"" ], "answer": [ "3500" ] }, { "key": "06221a83812b03cacce79b7404bb3785", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 5, 0, "PANT40I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have the drug code pant40i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"PANT40I\"", "question_refine_tok": [ "how", "many", "patients", "have", "the", "drug", "code", "pant40i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"PANT40I\"" ], "answer": [ "13973" ] }, { "key": "9e98c86301154d7baf44b1654b51c1f0", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 6, 0, "REPLACE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with replaced route of drug administration?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"ROUTE\" = \"REPLACE\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "replaced", "route", "of", "drug", "administration", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"REPLACE\"" ], "answer": [ "800" ] }, { "key": "9dc0838fea8ceebde01fd608c434210c", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 6, 0, "BUCCAL" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have buccal route of drug administration?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"ROUTE\" = \"BUCCAL\"", "question_refine_tok": [ "which", "patients", "have", "buccal", "route", "of", "drug", "administration", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"BUCCAL\"" ], "answer": [ "3" ] }, { "key": "ab6f89b00da40c7ecc26b6864d460588", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 6, 0, "IV DRIP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had iv drip drug route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"ROUTE\" = \"IV DRIP\"", "question_refine_tok": [ "how", "many", "patients", "had", "iv", "drip", "drug", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"IV", "DRIP\"" ], "answer": [ "25780" ] }, { "key": "9638fb767e2ce81c243568cce6a0d6fe", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 6, 0, "TP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Which patients are medicated via tp route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"ROUTE\" = \"TP\"", "question_refine_tok": [ "Which", "patients", "are", "medicated", "via", "tp", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"TP\"" ], "answer": [ "12600" ] }, { "key": "971abf094f9ae07758205567a0bcc5f1", "format": { "table": [ 0, 3 ], "cond": [ [ 3, 6, 0, "DWELL" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose drug route is dwell?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PRESCRIPTIONS.\"ROUTE\" = \"DWELL\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "drug", "route", "is", "dwell", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"DWELL\"" ], "answer": [ "966" ] }, { "key": "9374426f7a7a5514195f42d67b10ae3a", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51200 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "which patients have lab test item id 51200?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51200\"", "question_refine_tok": [ "which", "patients", "have", "lab", "test", "item", "i", "d", "51200", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51200\"" ], "answer": [ "35491" ] }, { "key": "860df604232ec2b6f7612f44a1acd583", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51214 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "look for the number of patients who have lab test item id 51214.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51214\"", "question_refine_tok": [ "look", "for", "the", "number", "of", "patients", "who", "have", "lab", "test", "item", "i", "d", "51214", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51214\"" ], "answer": [ "15268" ] }, { "key": "0ce185e197a73df5c7d1d28e8b208096", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51218 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose item id is 51218.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51218\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "whose", "item", "i", "d", "is", "51218", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51218\"" ], "answer": [ "1180" ] }, { "key": "96160962e5c4e848fcc6d8436019e9a1", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51229 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who have lab test item id 51229.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51229\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "have", "lab", "test", "item", "i", "d", "51229", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51229\"" ], "answer": [ "254" ] }, { "key": "a6efda66101f5ee356834b8d407f433a", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51245 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find out the number of patients with lab test item id 51245.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51245\"", "question_refine_tok": [ "find", "out", "the", "number", "of", "patients", "with", "lab", "test", "item", "i", "d", "51245", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51245\"" ], "answer": [ "416" ] }, { "key": "934102ea4b2c1a74fa970bf8adf637c9", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51256 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose item id is 51256.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51256\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "item", "i", "d", "is", "51256", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51256\"" ], "answer": [ "35492" ] }, { "key": "a042f037d40f6ca5ddaa6b3b1cd2d4fb", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "Triiodothyronine (T3)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were tested for triiodothyronine (t3)?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"Triiodothyronine (T3)\"", "question_refine_tok": [ "how", "many", "patients", "were", "tested", "for", "triiodothyronine", "(", "t3", ")", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"Triiodothyronine", "(T3)\"" ], "answer": [ "1137" ] }, { "key": "80d9900f94b580302de4a0266ed25d48", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "RBC, CSF" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Which patients were ordered a rbc csf lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"RBC, CSF\"", "question_refine_tok": [ "Which", "patients", "were", "ordered", "a", "rbc", "csf", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"RBC,", "CSF\"" ], "answer": [ "2445" ] }, { "key": "060151fe7a66f01cf5811b6efdc73538", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "Alanine Aminotransferase (ALT)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who were ordered alanine aminotransferase (alt) lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"Alanine Aminotransferase (ALT)\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "were", "ordered", "alanine", "aminotransferase", "(", "alt", ")", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"Alanine", "Aminotransferase", "(ALT)\"" ], "answer": [ "26917" ] }, { "key": "8ee312bcaee5fe43732e1d6afd1f8e50", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 6, 0, "Mesothelial cells" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had their lab test name as mesothelial cells?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"LABEL\" = \"Mesothelial cells\"", "question_refine_tok": [ "how", "many", "patients", "had", "their", "lab", "test", "name", "as", "mesothelial", "cells", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"LABEL\"", "=", "\"Mesothelial", "cells\"" ], "answer": [ "397" ] }, { "key": "a0900dc344330df7b6a46d5c347d108d", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 7, 0, "Cerebrospinal Fluid (CSF)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients for whom csf lab test was ordered.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"FLUID\" = \"Cerebrospinal Fluid (CSF)\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "for", "whom", "csf", "lab", "test", "was", "ordered", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"FLUID\"", "=", "\"Cerebrospinal", "Fluid", "(CSF)\"" ], "answer": [ "2478" ] }, { "key": "00648dbdd1cf6863da5597366c79a6f0", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 12, 0, "WHITE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the unmarried patients belonged to white ethnic origin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\"", "question_refine_tok": [ "how", "many", "of", "the", "unmarried", "patients", "belonged", "to", "white", "ethnic", "origin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"" ], "answer": [ "6512" ] }, { "key": "81732889ea775ce54e8a3a2ba1d6ddcf", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "DIVORCED" ], [ 0, 12, 0, "BLACK/AFRICAN AMERICAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients are of divorced marital status and with black/african american ethnicity?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"DIVORCED\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/AFRICAN AMERICAN\"", "question_refine_tok": [ "How", "many", "patients", "are", "of", "divorced", "marital", "status", "and", "with", "black/african", "american", "ethnicity", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"DIVORCED\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/AFRICAN", "AMERICAN\"" ], "answer": [ "209" ] }, { "key": "a7dfb5cb643686fde165b81208a5780f", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 12, 0, "ASIAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients whose marital status is married and ethnicity is asian", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "whose", "marital", "status", "is", "married", "and", "ethnicity", "is", "asian" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"" ], "answer": [ "389" ] }, { "key": "885d89607152d4e994c2d3ea430b4cde", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "DIVORCED" ], [ 0, 22, 2, 2120 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of divorced patients who were admitted before 2120?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"DIVORCED\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2120\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "divorced", "patients", "who", "were", "admitted", "before", "2120", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"DIVORCED\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2120\"" ], "answer": [ "464" ] }, { "key": "9126eb002106d4c790c7ca9f1745106d", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 22, 2, 2198 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of total number of patients admitted before 2198, how many of them were married.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2198\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "admitted", "before", "2198", ",", "how", "many", "of", "them", "were", "married", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2198\"" ], "answer": [ "17934" ] }, { "key": "00ef3ee46331250704baf2033dad4b10", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "DIVORCED" ], [ 1, 2, 0, "25541" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients diagnosed under icd9 code 25541 were divorced?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"DIVORCED\" AND DIAGNOSES.\"ICD9_CODE\" = \"25541\"", "question_refine_tok": [ "how", "many", "patients", "diagnosed", "under", "icd9", "code", "25541", "were", "divorced", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"DIVORCED\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"25541\"" ], "answer": [ "12" ] }, { "key": "003f53e7bc7442b9768eadd55de1419d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "DIVORCED" ], [ 1, 3, 0, "Ocl crtd art wo infrct" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of divorced patients who were diagnosed with occlusion and stenosis of carotid artery without mention of cerebral infarction.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"DIVORCED\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Ocl crtd art wo infrct\"", "question_refine_tok": [ "provide", "the", "number", "of", "divorced", "patients", "who", "were", "diagnosed", "with", "occlusion", "and", "stenosis", "of", "carotid", "artery", "without", "mention", "of", "cerebral", "infarction", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"DIVORCED\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Ocl", "crtd", "art", "wo", "infrct\"" ], "answer": [ "42" ] }, { "key": "ade0c7463c725d9219e5712adb45de85", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 1, 3, 0, "AMI inferolateral, init" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of married patients who have acute myocardial infarction of inferolateral wall, initial episode of care diagnoses.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DIAGNOSES.\"SHORT_TITLE\" = \"AMI inferolateral, init\"", "question_refine_tok": [ "count", "the", "number", "of", "married", "patients", "who", "have", "acute", "myocardial", "infarction", "of", "inferolateral", "wall", ",", "initial", "episode", "of", "care", "diagnoses", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"AMI", "inferolateral,", "init\"" ], "answer": [ "71" ] }, { "key": "a90ecf2fa6bc7c4af1d8fc44eb09a881", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 1, 4, 0, "Pyelonephritis, unspecified" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who are married and have been diagnosed with pyelonephritis, unspecified.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DIAGNOSES.\"LONG_TITLE\" = \"Pyelonephritis, unspecified\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "are", "married", "and", "have", "been", "diagnosed", "with", "pyelonephritis", ",", "unspecified", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Pyelonephritis,", "unspecified\"" ], "answer": [ "40" ] }, { "key": "01f05a65bd07aa9348e2de5f77103144", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 2, 2, 0, 4523 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find me the number of unmarried patients who have 4523 procedure icd9 code.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND PROCEDURES.\"ICD9_CODE\" = \"4523\"", "question_refine_tok": [ "find", "me", "the", "number", "of", "unmarried", "patients", "who", "have", "4523", "procedure", "icd9", "code", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4523\"" ], "answer": [ "165" ] }, { "key": "0ce126ae4e9cb93b9ebe1d771b4b4026", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 2, 2, 0, 8968 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of unmarried patients who have procedure icd9 code 8968?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND PROCEDURES.\"ICD9_CODE\" = \"8968\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "unmarried", "patients", "who", "have", "procedure", "icd9", "code", "8968", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8968\"" ], "answer": [ "41" ] }, { "key": "0ef1bd0f34de8289d8b8043c9600dbb9", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 2, 3, 0, "Tonsil&adenoid biopsy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get me the number of unmarried patients who had tonsil and adenoid biopsy.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND PROCEDURES.\"SHORT_TITLE\" = \"Tonsil&adenoid biopsy\"", "question_refine_tok": [ "Get", "me", "the", "number", "of", "unmarried", "patients", "who", "had", "tonsil", "and", "adenoid", "biopsy", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Tonsil&adenoid", "biopsy\"" ], "answer": [ "1" ] }, { "key": "a91aca91e611cc00d88e4830e527aef7", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 2, 3, 0, "Opn mitral valvuloplasty" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Tell me the number of married patients who underwent a procedure called open heart valvuloplasty of mitral valve without replacement.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND PROCEDURES.\"SHORT_TITLE\" = \"Opn mitral valvuloplasty\"", "question_refine_tok": [ "Tell", "me", "the", "number", "of", "married", "patients", "who", "underwent", "a", "procedure", "called", "open", "heart", "valvuloplasty", "of", "mitral", "valve", "without", "replacement", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Opn", "mitral", "valvuloplasty\"" ], "answer": [ "251" ] }, { "key": "a03591944cbd372c579f85a8601246d7", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 4, 8, 0, "Hematology" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Provide the number of unmarried patients who have a hematology lab test category.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND LAB.\"CATEGORY\" = \"Hematology\"", "question_refine_tok": [ "Provide", "the", "number", "of", "unmarried", "patients", "who", "have", "a", "hematology", "lab", "test", "category", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Hematology\"" ], "answer": [ "9751" ] }, { "key": "9d2768cf17e0425da16f63997f9008fe", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 9, 0, "ELECTIVE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of female patients who had elective hospital admission.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "female", "patients", "who", "had", "elective", "hospital", "admission", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"" ], "answer": [ "2957" ] }, { "key": "085ccd570886bbdcecbbfb4b9f8b8644", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 9, 0, "EMERGENCY" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients had an emergency admission type?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\"", "question_refine_tok": [ "how", "many", "female", "patients", "had", "an", "emergency", "admission", "type", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"" ], "answer": [ "14324" ] }, { "key": "a0340437a3e0b41ee288ee4688e73caf", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 9, 0, "URGENT" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among the total number of urgent admissions, how many of them were male patients?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\"", "question_refine_tok": [ "among", "the", "total", "number", "of", "urgent", "admissions", ",", "how", "many", "of", "them", "were", "male", "patients", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"" ], "answer": [ "720" ] }, { "key": "891114d2fc4e33a1bf1fb2afb806f51a", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 11, 0, "Self Pay" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients had the insurance self pay?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\"", "question_refine_tok": [ "how", "many", "female", "patients", "had", "the", "insurance", "self", "pay", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"" ], "answer": [ "153" ] }, { "key": "bb9cac96e684f7a261332a1fadbed50c", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 11, 0, "Medicare" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had medicare insurance?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "medicare", "insurance", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"" ], "answer": [ "10923" ] }, { "key": "8c4094b14f138bbe58b72af518b7ad1c", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 12, 0, "WHITE - RUSSIAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many female patients iare of white russian ethnicity?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE - RUSSIAN\"", "question_refine_tok": [ "How", "many", "female", "patients", "iare", "of", "white", "russian", "ethnicity", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE", "-", "RUSSIAN\"" ], "answer": [ "66" ] }, { "key": "830f85be4c94fd358f0fdaf278230176", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 12, 0, "WHITE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many female patients belonged to the white ethnic origin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\"", "question_refine_tok": [ "How", "many", "female", "patients", "belonged", "to", "the", "white", "ethnic", "origin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"" ], "answer": [ "14007" ] }, { "key": "a580e307f344b684c0ce9e8900d41c72", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 14, 0, "CLINIC REFERRAL/PREMATURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who are male and their admission location is clinic referral/premature.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"CLINIC REFERRAL/PREMATURE\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "are", "male", "and", "their", "admission", "location", "is", "clinic", "referral", "/", "premature", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"CLINIC", "REFERRAL/PREMATURE\"" ], "answer": [ "5782" ] }, { "key": "87ad79f94d27a4728ad5359025e0f862", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 15, 0, "DEAD/EXPIRED" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "look for the number of female patients who were discharged dead/expired.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DEAD/EXPIRED\"", "question_refine_tok": [ "look", "for", "the", "number", "of", "female", "patients", "who", "were", "discharged", "dead", "/", "expired", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DEAD/EXPIRED\"" ], "answer": [ "2690" ] }, { "key": "a49ba67979f1038a46a665478bcb7a0c", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 16, 0, "VENTRICULAR TACHYCARDIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose diagnoses is lap surg convert to open and they are female.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"VENTRICULAR TACHYCARDIA\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "diagnoses", "is", "lap", "surg", "convert", "to", "open", "and", "they", "are", "female", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"VENTRICULAR", "TACHYCARDIA\"" ], "answer": [ "6" ] }, { "key": "04f70250fa8b8c71fcf64afe5f04935c", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 16, 0, "TRANSIENT ISCHEMIC ATTACK" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find .the number of patients who are female and were diagnosed with transient ischemic attack?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"TRANSIENT ISCHEMIC ATTACK\"", "question_refine_tok": [ "find", ".the", "number", "of", "patients", "who", "are", "female", "and", "were", "diagnosed", "with", "transient", "ischemic", "attack", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"TRANSIENT", "ISCHEMIC", "ATTACK\"" ], "answer": [ "6" ] }, { "key": "0865ad637ad2259ebb61c689e98b06cd", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 16, 0, "COPD EXACERBATION" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients have copd exacerbation as their primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"COPD EXACERBATION\"", "question_refine_tok": [ "how", "many", "male", "patients", "have", "copd", "exacerbation", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"COPD", "EXACERBATION\"" ], "answer": [ "24" ] }, { "key": "aa024c1b63b3b5033195044b8dbbfee1", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 4, 2, 43 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many female patients are aged below 43 years?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"AGE\" < \"43\"", "question_refine_tok": [ "How", "many", "female", "patients", "are", "aged", "below", "43", "years", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"" ], "answer": [ "5669" ] }, { "key": "051e15109d31eca3af6d4a47486cb036", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 4, 2, 44 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of female patients who are less than 44 years of age.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"AGE\" < \"44\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "female", "patients", "who", "are", "less", "than", "44", "years", "of", "age", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"44\"" ], "answer": [ "5803" ] }, { "key": "9bebc7e80c1afd55faaf99cb972caf61", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 4, 2, 77 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the male patients were aged below 77?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"AGE\" < \"77\"", "question_refine_tok": [ "how", "many", "of", "the", "male", "patients", "were", "aged", "below", "77", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"77\"" ], "answer": [ "21059" ] }, { "key": "017e1f21141e43d53c4f9311a23b0607", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 4, 2, 79 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients are less than 79 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"AGE\" < \"79\"", "question_refine_tok": [ "how", "many", "male", "patients", "are", "less", "than", "79", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"79\"" ], "answer": [ "21997" ] }, { "key": "005126389e203de74cbb8935f6c7a256", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 4, 2, 24 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients are below 24 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"AGE\" < \"24\"", "question_refine_tok": [ "how", "many", "male", "patients", "are", "below", "24", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"24\"" ], "answer": [ "4850" ] }, { "key": "07409693de111b6d37ed0372f74f0e7a", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 18, 2, 1846 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of male patients who were born before 1846.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1846\"", "question_refine_tok": [ "count", "the", "number", "of", "male", "patients", "who", "were", "born", "before", "1846", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1846\"" ], "answer": [ "306" ] }, { "key": "ac915e25dd47cc485ec186e545c86b48", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 2, 0, "3572" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of female patients who have diagnosis icd9 code 3572.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"ICD9_CODE\" = \"3572\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "female", "patients", "who", "have", "diagnosis", "icd9", "code", "3572", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"3572\"" ], "answer": [ "461" ] }, { "key": "96afc2a274c9bac2d9765759a64957fd", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 2, 0, "99813" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients have diagnoses icd9 code 99813?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"ICD9_CODE\" = \"99813\"", "question_refine_tok": [ "how", "many", "female", "patients", "have", "diagnoses", "icd9", "code", "99813", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"99813\"" ], "answer": [ "37" ] }, { "key": "accc81fb75df97d7563cbae8ec618d90", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 6, 0, "F" ], [ 1, 3, 0, "Staph pneumonia NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "show me the number of female patients who have been diagnosed with unspecified pneumonia due to staphylococcus.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Staph pneumonia NEC\"", "question_refine_tok": [ "show", "me", "the", "number", "of", "female", "patients", "who", "have", "been", "diagnosed", "with", "unspecified", "pneumonia", "due", "to", "staphylococcus", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Staph", "pneumonia", "NEC\"" ], "answer": [ "5" ] }, { "key": "064bdfb8075ddf916996b79432d9e188", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "F" ], [ 2, 2, 0, 5771 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients had the procedure icd9 code 5771?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PROCEDURES.\"ICD9_CODE\" = \"5771\"", "question_refine_tok": [ "how", "many", "female", "patients", "had", "the", "procedure", "icd9", "code", "5771", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5771\"" ], "answer": [ "6" ] }, { "key": "a4411125b5abe68f2d0eb36a12677a73", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "M" ], [ 2, 2, 0, 8842 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many male patients had icd9 code 8842?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PROCEDURES.\"ICD9_CODE\" = \"8842\"", "question_refine_tok": [ "How", "many", "male", "patients", "had", "icd9", "code", "8842", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8842\"" ], "answer": [ "432" ] }, { "key": "95c238a02d6882fc2c6d323fde3f7631", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "M" ], [ 2, 2, 0, 9703 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had the procedure icd9 code 9703?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PROCEDURES.\"ICD9_CODE\" = \"9703\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "the", "procedure", "icd9", "code", "9703", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9703\"" ], "answer": [ "25" ] }, { "key": "a5b952dae5761a673041cb3e4c9b2fd4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "F" ], [ 2, 3, 0, "Drug detoxification" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many female patients have undergone drug detoxification as their procedure short title?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PROCEDURES.\"SHORT_TITLE\" = \"Drug detoxification\"", "question_refine_tok": [ "how", "many", "female", "patients", "have", "undergone", "drug", "detoxification", "as", "their", "procedure", "short", "title", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Drug", "detoxification\"" ], "answer": [ "14" ] }, { "key": "0dde689bf72ef9edd183eb73843dba07", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 6, 0, "M" ], [ 2, 4, 0, "Open and other replacement of aortic valve with tissue graft" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had open and other replacement of aortic valve with tissue graft procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PROCEDURES.\"LONG_TITLE\" = \"Open and other replacement of aortic valve with tissue graft\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "open", "and", "other", "replacement", "of", "aortic", "valve", "with", "tissue", "graft", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Open", "and", "other", "replacement", "of", "aortic", "valve", "with", "tissue", "graft\"" ], "answer": [ "816" ] }, { "key": "93f1c2203790abf5e19f70304d9fa6cb", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 6, 0, "F" ], [ 3, 4, 0, "Amitriptyline" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among patients treated with amitriptyline, calculate the number of female patients.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PRESCRIPTIONS.\"DRUG\" = \"Amitriptyline\"", "question_refine_tok": [ "among", "patients", "treated", "with", "amitriptyline", ",", "calculate", "the", "number", "of", "female", "patients", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Amitriptyline\"" ], "answer": [ "154" ] }, { "key": "9b581dcd0f727ee14875356de70bafdd", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 6, 0, "F" ], [ 3, 4, 0, "Theophylline SR" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many female patients use a drug named theophylline sr?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND PRESCRIPTIONS.\"DRUG\" = \"Theophylline SR\"", "question_refine_tok": [ "How", "many", "female", "patients", "use", "a", "drug", "named", "theophylline", "sr", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Theophylline", "SR\"" ], "answer": [ "41" ] }, { "key": "9b5243d9114f907596a4a8362e169688", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 6, 0, "M" ], [ 3, 5, 0, "ARIP10" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find out the number of male patients who have an arip10 drug code.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"ARIP10\"", "question_refine_tok": [ "Find", "out", "the", "number", "of", "male", "patients", "who", "have", "an", "arip10", "drug", "code", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"ARIP10\"" ], "answer": [ "50" ] }, { "key": "93b9e31884f67490542d6aaf4d6b8108", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 2, 0, 51146 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients have lab test item id 51146?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"ITEMID\" = \"51146\"", "question_refine_tok": [ "how", "many", "male", "patients", "have", "lab", "test", "item", "i", "d", "51146", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"ITEMID\"", "=", "\"51146\"" ], "answer": [ "19368" ] }, { "key": "95467eb799726ac08b222ad6b2fa9fc8", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 2, 0, 51148 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Specify the total number of male patients with item id 51148", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"ITEMID\" = \"51148\"", "question_refine_tok": [ "Specify", "the", "total", "number", "of", "male", "patients", "with", "item", "id", "51148" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"ITEMID\"", "=", "\"51148\"" ], "answer": [ "183" ] }, { "key": "9624197cdfc232272226b8d1716d3cf9", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 6, 0, "Amylase" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had the lab test for amylase?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"LABEL\" = \"Amylase\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "the", "lab", "test", "for", "amylase", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"LABEL\"", "=", "\"Amylase\"" ], "answer": [ "9441" ] }, { "key": "8528bb359cc39d7ad4fc795461677553", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 6, 0, "PTT" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of male patients whose lab test name is ptt.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"LABEL\" = \"PTT\"", "question_refine_tok": [ "give", "me", "the", "number", "of", " ", "male", "patients", "whose", "lab", "test", "name", "is", "ptt", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"LABEL\"", "=", "\"PTT\"" ], "answer": [ "21266" ] }, { "key": "abd26d62b8557ca1e9111eb9ffe88c4a", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 6, 0, "M" ], [ 4, 6, 0, "Potassium, Whole Blood" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many male patients had the lab test name potassium, whole blood?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND LAB.\"LABEL\" = \"Potassium, Whole Blood\"", "question_refine_tok": [ "how", "many", "male", "patients", "had", "the", "lab", "test", "name", "potassium", ",", "whole", "blood", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "LAB.\"LABEL\"", "=", "\"Potassium,", "Whole", "Blood\"" ], "answer": [ "14770" ] }, { "key": "03e7efbd099cefdb084900589681e2d1", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "RUSS" ], [ 0, 15, 0, "DISC-TRAN CANCER/CHLDRN H" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of paitents whose language is russian and discharge location is disc-tran cancer/chldrn h.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"RUSS\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISC-TRAN CANCER/CHLDRN H\"", "question_refine_tok": [ "give", "the", "number", "of", "paitents", "whose", "language", "is", "russian", "and", "discharge", "location", "is", "disc", "-", "tran", "cancer", "/", "chldrn", "h." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"RUSS\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISC-TRAN", "CANCER/CHLDRN", "H\"" ], "answer": [ "10" ] }, { "key": "86a048bee4d60ed30b32964f9a48eac9", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "CAPE" ], [ 0, 4, 2, 67 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients under the gae of 67 speak the language cape?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"CAPE\" AND DEMOGRAPHIC.\"AGE\" < \"67\"", "question_refine_tok": [ "what", "number", "of", "patients", "under", "the", "gae", "of", "67", "speak", "the", "language", "cape", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"CAPE\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"67\"" ], "answer": [ "102" ] }, { "key": "0bc3359131c7aaca9aa7f660a3b3a40e", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "CAPE" ], [ 0, 4, 2, 71 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients speak cape language and are under 71 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"CAPE\" AND DEMOGRAPHIC.\"AGE\" < \"71\"", "question_refine_tok": [ "how", "many", "patients", "speak", "cape", "language", "and", "are", "under", "71", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"CAPE\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"71\"" ], "answer": [ "115" ] }, { "key": "87c1857d7148bcb00305e281fadd20e7", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "SPAN" ], [ 0, 4, 2, 76 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients aged below 76 years whose language is spanish.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"SPAN\" AND DEMOGRAPHIC.\"AGE\" < \"76\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "aged", "below", "76", "years", "whose", "language", "is", "spanish", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"SPAN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"76\"" ], "answer": [ "664" ] }, { "key": "adf20b60a1fb5b796f72b749bee0e696", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "ENGL" ], [ 0, 4, 2, 31 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients younger than 31 years who prefer english?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"ENGL\" AND DEMOGRAPHIC.\"AGE\" < \"31\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "younger", "than", "31", "years", "who", "prefer", "english", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"ENGL\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"31\"" ], "answer": [ "1364" ] }, { "key": "acc6b4b35378ea998962887cae1e1139", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "PORT" ], [ 0, 10, 1, 3 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many portuguese speaking patients stayed in hospital for more than 3 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"PORT\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"3\"", "question_refine_tok": [ "how", "many", "portuguese", "speaking", "patients", "stayed", "in", "hospital", "for", "more", "than", "3", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"PORT\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"3\"" ], "answer": [ "226" ] }, { "key": "045c5269cdae83454d68e393e12c8658", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "SPAN" ], [ 0, 18, 2, 2071 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give me the list of patients born before 2071 who prefer spanish.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"SPAN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2071\"", "question_refine_tok": [ "Give", "me", "the", "list", "of", "patients", "born", "before", "2071", "who", "prefer", "spanish", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"SPAN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2071\"" ], "answer": [ "233" ] }, { "key": "08dd582acefd6cc3ce501b04fb54a915", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "PTUN" ], [ 0, 18, 2, 2066 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients born before the year 2066 speaks the language ptun?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"PTUN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2066\"", "question_refine_tok": [ "how", "many", "patients", "born", "before", "the", "year", "2066", "speaks", "the", "language", "ptun", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"PTUN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2066\"" ], "answer": [ "194" ] }, { "key": "9193cd16f584ed1da7296d33599c77c1", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "PTUN" ], [ 0, 19, 4, 2138.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients whose language is ptun died in or before 2138?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"PTUN\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2138.0\"", "question_refine_tok": [ "How", "many", "patients", "whose", "language", "is", "ptun", "died", "in", "or", "before", "2138", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"PTUN\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2138.0\"" ], "answer": [ "99" ] }, { "key": "066126e662a3003e041bd6974df0cc98", "format": { "table": [ 0 ], "cond": [ [ 0, 8, 0, "CATHOLIC" ], [ 0, 4, 2, 45 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the catholic patients were aged below 45?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"RELIGION\" = \"CATHOLIC\" AND DEMOGRAPHIC.\"AGE\" < \"45\"", "question_refine_tok": [ "how", "many", "of", "the", "catholic", "patients", "were", "aged", "below", "45", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"CATHOLIC\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"45\"" ], "answer": [ "3680" ] }, { "key": "a7c671e965437f33b28e21cf6bfe9e89", "format": { "table": [ 0 ], "cond": [ [ 0, 8, 0, "GREEK ORTHODOX" ], [ 0, 18, 2, 2085 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of greek orthodox religious background patients who were born before 2085.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"RELIGION\" = \"GREEK ORTHODOX\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2085\"", "question_refine_tok": [ "find", "the", "number", "of", "greek", "orthodox", "religious", "background", "patients", "who", "were", "born", "before", "2085", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"GREEK", "ORTHODOX\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2085\"" ], "answer": [ "158" ] }, { "key": "82715ac803ef686d617d271292dcf551", "format": { "table": [ 0 ], "cond": [ [ 0, 8, 0, "CATHOLIC" ], [ 0, 18, 2, 1846 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients born before the year 1846 followed the catholic religion?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"RELIGION\" = \"CATHOLIC\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1846\"", "question_refine_tok": [ "how", "many", "patients", "born", "before", "the", "year", "1846", "followed", "the", "catholic", "religion", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"RELIGION\"", "=", "\"CATHOLIC\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1846\"" ], "answer": [ "198" ] }, { "key": "93e5a26d56fc80b963506bc71b380d70", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 11, 0, "Government" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of government health insurance patients who had elective hospital admission.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Government\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "government", "health", "insurance", "patients", "who", "had", "elective", "hospital", "admission", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"" ], "answer": [ "135" ] }, { "key": "815b0971ecad8500060f8ad3fc3df9a9", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 11, 0, "Medicaid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many elective hospital admission patients have medicaid health insurance?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\"", "question_refine_tok": [ "how", "many", "elective", "hospital", "admission", "patients", "have", "medicaid", "health", "insurance", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"" ], "answer": [ "393" ] }, { "key": "ac75d8f182635ee20767a8e379757555", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "NEWBORN" ], [ 0, 11, 0, "Self Pay" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of newborn admitted patients who have self pay insurance.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"NEWBORN\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "newborn", "admitted", "patients", "who", "have", "self", "pay", "insurance", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"" ], "answer": [ "36" ] }, { "key": "0e8fd2d722e37743ae80d2f8b9c7a3f0", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 12, 0, "HISPANIC/LATINO - PUERTO RICAN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted under emergency admission type are of hispanic/latino - puertorican ethnicity?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"HISPANIC/LATINO - PUERTO RICAN\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "under", "emergency", "admission", "type", "are", "of", "hispanic/latino", "-", "puertorican", "ethnicity", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"HISPANIC/LATINO", "-", "PUERTO", "RICAN\"" ], "answer": [ "128" ] }, { "key": "a918a0036b56f9087c0676932fa13024", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 15, 0, "HOME HEALTH CARE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with an elective admission type were discharged at home health care?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME HEALTH CARE\"", "question_refine_tok": [ "How", "many", "patients", "with", "an", "elective", "admission", "type", "were", "discharged", "at", "home", "health", "care", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME", "HEALTH", "CARE\"" ], "answer": [ "3327" ] }, { "key": "88918368bee11a289ddd9a04f1958b6b", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 16, 0, "CORONARY ARTERY DISEASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of elective hospital admission patients who had coronary artery primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"CORONARY ARTERY DISEASE\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "elective", "hospital", "admission", "patients", "who", "had", "coronary", "artery", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CORONARY", "ARTERY", "DISEASE\"" ], "answer": [ "9" ] }, { "key": "806722d7337a441a746d2477d440c867", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 16, 0, "ABDOMINAL ABSCESS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose admission type is elective and primary disease is abdominal abscess.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"ABDOMINAL ABSCESS\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "whose", "admission", "type", "is", "elective", "and", "primary", "disease", "is", "abdominal", "abscess", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ABDOMINAL", "ABSCESS\"" ], "answer": [ "0" ] }, { "key": "a667eb8609a76490ddbf55b5c12e3695", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 16, 0, "GANGRENE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of emergency hospital admission patients who have gangrene primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"GANGRENE\"", "question_refine_tok": [ "count", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "have", "gangrene", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GANGRENE\"" ], "answer": [ "6" ] }, { "key": "84c856c06f729524fdc4905b0fd4a68b", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 16, 0, "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT WITH MVR; ? MAZE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted under emergency and diagnosed with primary disease coronary artery disease or coronary artery bypass graft with mvr maze?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT WITH MVR; ? MAZE\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "under", "emergency", "and", "diagnosed", "with", "primary", "disease", "coronary", "artery", "disease", "or", "coronary", "artery", "bypass", "graft", "with", "mvr", "maze", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CORONARY", "ARTERY", "DISEASE\\CORONARY", "ARTERY", "BYPASS", "GRAFT", "WITH", "MVR;", "?", "MAZE\"" ], "answer": [ "0" ] }, { "key": "935237d31f785ead710a5b2124d19370", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "NEWBORN" ], [ 0, 10, 1, 10 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of newborn admission patients who have more than 10 days of hospital stay.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"NEWBORN\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"10\"", "question_refine_tok": [ "count", "the", "number", "of", "newborn", "admission", "patients", "who", "have", "more", "than", "10", "days", "of", "hospital", "stay", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"10\"" ], "answer": [ "1816" ] }, { "key": "83d2f2439a19c3bac564156d4d7f0f20", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 0, 18, 2, 2074 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients admitted in urgent care who were born before 2074.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2074\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "admitted", "in", "urgent", "care", "who", "were", "born", "before", "2074", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2074\"" ], "answer": [ "492" ] }, { "key": "8284b2149ec8c5df761d2ceca3c5ba18", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 18, 2, 2076 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many elective hospital admission patients were born before the year 2076?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2076\"", "question_refine_tok": [ "how", "many", "elective", "hospital", "admission", "patients", "were", "born", "before", "the", "year", "2076", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2076\"" ], "answer": [ "2811" ] }, { "key": "94fac89f564ff4ef5cafb4d446f7035d", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 18, 2, 2066 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose admission type is emergency and born before 2066?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2066\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "admission", "type", "is", "emergency", "and", "born", "before", "2066", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2066\"" ], "answer": [ "10497" ] }, { "key": "840d704cc763acd72fab4ae0efe35a9f", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 0, 22, 2, 2190 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose admission type is urgent and who were admitted before 2190.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2190\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "admission", "type", "is", "urgent", "and", "who", "were", "admitted", "before", "2190", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2190\"" ], "answer": [ "1167" ] }, { "key": "0516cfb3db509987e51368563ba0504e", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 0, 22, 2, 2194 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": " find the number of urgent hospital admission patients before the year 2194.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2194\"", "question_refine_tok": [ " ", "find", "the", "number", "of", "urgent", "hospital", "admission", "patients", "before", "the", "year", "2194", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2194\"" ], "answer": [ "1223" ] }, { "key": "9cfe1b1262ebc011c0cd636a6bd1b9f7", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 22, 2, 2108 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the total number of patients on elective admission before the year 2108", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2108\"", "question_refine_tok": [ "Calculate", "the", "total", "number", "of", "patients", "on", "elective", "admission", "before", "the", "year", "2108" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2108\"" ], "answer": [ "531" ] }, { "key": "04f2d8289f6c164c281c05e3fc7f3940", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 22, 2, 2163 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted in emergency and admitted before the year 2163?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2163\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "in", "emergency", "and", "admitted", "before", "the", "year", "2163", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2163\"" ], "answer": [ "20197" ] }, { "key": "89473cb3b3eaa62d3a19fba9185e42e7", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 1, 2, 0, "E8798" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of emergency room admitted patients who have diagnosis icd9 code e8798?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DIAGNOSES.\"ICD9_CODE\" = \"E8798\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "emergency", "room", "admitted", "patients", "who", "have", "diagnosis", "icd9", "code", "e8798", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"E8798\"" ], "answer": [ "1235" ] }, { "key": "9de47dece6861ec239f5b445048e5d34", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 1, 2, 0, "V453" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of elective hospital admission patients who have diagnoses icd9 code v453?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DIAGNOSES.\"ICD9_CODE\" = \"V453\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "elective", "hospital", "admission", "patients", "who", "have", "diagnoses", "icd9", "code", "v453", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"V453\"" ], "answer": [ "20" ] }, { "key": "0e8f81d1242cdc9c96139d18dd974c45", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 1, 2, 0, "2948" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted on urgent basis have diagnoses icd9 code 2948?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DIAGNOSES.\"ICD9_CODE\" = \"2948\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "on", "urgent", "basis", "have", "diagnoses", "icd9", "code", "2948", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2948\"" ], "answer": [ "14" ] }, { "key": "8069c7ebf4da69cc765ce168571b8678", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 1, 4, 0, "Acute salpingitis and oophoritis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of urgent hospital admission patients who have acute salpingitis and oophoritis diagnoses.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DIAGNOSES.\"LONG_TITLE\" = \"Acute salpingitis and oophoritis\"", "question_refine_tok": [ "find", "the", "number", "of", "urgent", "hospital", "admission", "patients", "who", "have", "acute", "salpingitis", "and", "oophoritis", "diagnoses", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Acute", "salpingitis", "and", "oophoritis\"" ], "answer": [ "1" ] }, { "key": "006ea048ce601c09ed3c998b3cbd55c7", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 1, 4, 0, "Ostium secundum type atrial septal defect" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients on urgent admission were diagnosed with ostium secundum type atrial septal defect?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DIAGNOSES.\"LONG_TITLE\" = \"Ostium secundum type atrial septal defect\"", "question_refine_tok": [ "how", "many", "patients", "on", "urgent", "admission", "were", "diagnosed", "with", "ostium", "secundum", "type", "atrial", "septal", "defect", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Ostium", "secundum", "type", "atrial", "septal", "defect\"" ], "answer": [ "14" ] }, { "key": "a6ad761e37a208e191433f57667b024c", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 2, 2, 0, 17 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose admission type is urgent and procedure icd9 code is 17.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PROCEDURES.\"ICD9_CODE\" = \"17\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "admission", "type", "is", "urgent", "and", "procedure", "icd9", "code", "is", "17", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"17\"" ], "answer": [ "0" ] }, { "key": "975738dc9e601e98b319b82487686ed4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 2, 2, 0, 540 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients with elective admission type under procedure icd9 code 540.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND PROCEDURES.\"ICD9_CODE\" = \"540\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "with", "elective", "admission", "type", "under", "procedure", "icd9", "code", "540", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"540\"" ], "answer": [ "16" ] }, { "key": "86960807966ab11fb4a31cae186af57a", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 2, 2, 0, 331 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of emergency hospital admission patients who had procedure icd9 code 331.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PROCEDURES.\"ICD9_CODE\" = \"331\"", "question_refine_tok": [ "count", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "had", "procedure", "icd9", "code", "331", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"331\"" ], "answer": [ "3" ] }, { "key": "025b440ef65e624fc7920b8ac9bc6519", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 2, 3, 0, "Abdomen artery incision" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients had abdomen artery incision on urgent admission?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PROCEDURES.\"SHORT_TITLE\" = \"Abdomen artery incision\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "had", "abdomen", "artery", "incision", "on", "urgent", "admission", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Abdomen", "artery", "incision\"" ], "answer": [ "0" ] }, { "key": "0b17981f6cdd40e964a9ba229f5ea2db", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 2, 3, 0, "Form cutan ileoureterost" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients were admitted urgently and had the formation of cutaneous uretero-ileostomy procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PROCEDURES.\"SHORT_TITLE\" = \"Form cutan ileoureterost\"", "question_refine_tok": [ "How", "many", "patients", "were", "admitted", "urgently", "and", "had", "the", "formation", "of", "cutaneous", "uretero-ileostomy", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Form", "cutan", "ileoureterost\"" ], "answer": [ "0" ] }, { "key": "02327044ff1e866a680fa88cc4de37af", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 2, 3, 0, "Percu gastrojejunostomy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted under urgent admission type and underwent percu gastrojejunostomy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PROCEDURES.\"SHORT_TITLE\" = \"Percu gastrojejunostomy\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "under", "urgent", "admission", "type", "and", "underwent", "percu", "gastrojejunostomy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Percu", "gastrojejunostomy\"" ], "answer": [ "9" ] }, { "key": "a619d5854b9eb9d0df34539f613cafc4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 2, 3, 0, "Insert 2 vascular stents" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of emergency hospital admission patients who had insertion of 2 vascular stents.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PROCEDURES.\"SHORT_TITLE\" = \"Insert 2 vascular stents\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "had", "insertion", "of", "2", "vascular", "stents", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Insert", "2", "vascular", "stents\"" ], "answer": [ "374" ] }, { "key": "a61b003ff5bafba8ea45aa2853f939f7", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 2, 4, 0, "Venous catheterization for renal dialysis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "specify the total number of patients who had urgent admission due to venous catheterization for renal dialysis", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PROCEDURES.\"LONG_TITLE\" = \"Venous catheterization for renal dialysis\"", "question_refine_tok": [ "specify", "the", "total", "number", "of", "patients", "who", "had", "urgent", "admission", "due", "to", "venous", "catheterization", "for", "renal", "dialysis" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Venous", "catheterization", "for", "renal", "dialysis\"" ], "answer": [ "45" ] }, { "key": "b9ddbce5fe38a4b01105bb7fdc218772", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 2, 4, 0, "Attachment of pedicle or flap graft to other sites" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose admission type is elective and procedure long title is attachment of pedicle or flap graft to other sites.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND PROCEDURES.\"LONG_TITLE\" = \"Attachment of pedicle or flap graft to other sites\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "admission", "type", "is", "elective", "and", "procedure", "long", "title", "is", "attachment", "of", "pedicle", "or", "flap", "graft", "to", "other", "sites", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Attachment", "of", "pedicle", "or", "flap", "graft", "to", "other", "sites\"" ], "answer": [ "48" ] }, { "key": "045957f351a876adb124b29b739d0638", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 2, 4, 0, "Other operations on heart and pericardium" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with elective admission type had the procedure titled other operations on heart and pericardium?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND PROCEDURES.\"LONG_TITLE\" = \"Other operations on heart and pericardium\"", "question_refine_tok": [ "how", "many", "patients", "with", " ", "elective", "admission", "type", "had", "the", "procedure", "titled", "other", "operations", "on", "heart", "and", "pericardium", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Other", "operations", "on", "heart", "and", "pericardium\"" ], "answer": [ "30" ] }, { "key": "8314ff25189b1cf1389172288628eccb", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 3, 3, 0, "MAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of emergency hospital admission patients who are taking main drug type prescription.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"MAIN\"", "question_refine_tok": [ "count", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "are", "taking", "main", "drug", "type", "prescription", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"MAIN\"" ], "answer": [ "30393" ] }, { "key": "ad0c2ee55406703b73c20f92102a868d", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 3, 4, 0, "Docusate Sodium" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "let me know the number of emergency hospital admission patients who have docusate sodium prescription.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PRESCRIPTIONS.\"DRUG\" = \"Docusate Sodium\"", "question_refine_tok": [ "let", "me", "know", "the", "number", "of", "emergency", "hospital", "admission", "patients", "who", "have", "docusate", "sodium", "prescription", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Docusate", "Sodium\"" ], "answer": [ "18946" ] }, { "key": "a59c2fe7f918bb9e3f87dfd11186b2e7", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 3, 4, 0, "D5W (EXCEL BAG)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "To how many patients on urgent admission were d5w (excel bag) administered?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PRESCRIPTIONS.\"DRUG\" = \"D5W (EXCEL BAG)\"", "question_refine_tok": [ "To", "how", "many", "patients", "on", "urgent", "admission", "were", "d5w", "(", "excel", "bag", ")", "administered", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"D5W", "(EXCEL", "BAG)\"" ], "answer": [ "64" ] }, { "key": "8186696c78815c25591204220af03a90", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 3, 5, 0, "GLYC1R" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients admitted in emergency whose drug code is glyc1r.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"GLYC1R\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "admitted", "in", "emergency", "whose", "drug", "code", "is", "glyc1r", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"GLYC1R\"" ], "answer": [ "8" ] }, { "key": "a9235e22c8d073812cd26d2c8f638814", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 3, 5, 0, "ENOX80I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients admitted in emergency had drug code enox80i?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"ENOX80I\"", "question_refine_tok": [ "what", "number", "of", "patients", "admitted", "in", "emergency", "had", "drug", "code", "enox80i", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"ENOX80I\"" ], "answer": [ "703" ] }, { "key": "ab77dd480b1dc0b7cb1da0caf15a9068", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 3, 6, 0, "IVPCA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients admitted in urgent care had their route mentioned as ivpca?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PRESCRIPTIONS.\"ROUTE\" = \"IVPCA\"", "question_refine_tok": [ "what", "number", "of", "patients", "admitted", "in", "urgent", "care", "had", "their", "route", "mentioned", "as", "ivpca", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"IVPCA\"" ], "answer": [ "76" ] }, { "key": "91c5218be91466059b6ab55b5c9a214b", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 3, 6, 0, "NEB" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the patients on urgent admission had Neb drug route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PRESCRIPTIONS.\"ROUTE\" = \"NEB\"", "question_refine_tok": [ "How", "many", "of", "the", "patients", "on", "urgent", "admission", "had", "Neb", "drug", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"NEB\"" ], "answer": [ "21" ] }, { "key": "814b08ced5bf2cfc63c311dd93979199", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 3, 6, 0, "REPLACE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of urgent hospital admission patients who have replaced route of drug administration.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND PRESCRIPTIONS.\"ROUTE\" = \"REPLACE\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "urgent", "hospital", "admission", "patients", "who", "have", "replaced", "route", "of", "drug", "administration", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"REPLACE\"" ], "answer": [ "17" ] }, { "key": "07e91d222ec295e0af62c05e46fa5dc2", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 4, 2, 0, 51257 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients on elective admission had item id 51257?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND LAB.\"ITEMID\" = \"51257\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "on", "elective", "admission", "had", "item", "i", "d", "51257", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "LAB.\"ITEMID\"", "=", "\"51257\"" ], "answer": [ "149" ] }, { "key": "a67acde1ffdd89fb4002c394789b52e8", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 4, 6, 0, "Magnesium" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients admitted to emergency had a lab test for magnesium level?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND LAB.\"LABEL\" = \"Magnesium\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "admitted", "to", "emergency", "had", "a", "lab", "test", "for", "magnesium", "level", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "LAB.\"LABEL\"", "=", "\"Magnesium\"" ], "answer": [ "31782" ] }, { "key": "a839ed0e465ef114e44b38b91da01604", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 4, 7, 0, "Joint Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of urgent hospital admission patients for whom joint fluid lab test was ordered?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND LAB.\"FLUID\" = \"Joint Fluid\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "urgent", "hospital", "admission", "patients", "for", "whom", "joint", "fluid", "lab", "test", "was", "ordered", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "LAB.\"FLUID\"", "=", "\"Joint", "Fluid\"" ], "answer": [ "6" ] }, { "key": "0ff56098d8e667560ad6010a2bd49309", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose admission type is urgent and lab test category is chemistry.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "admission", "type", "is", "urgent", "and", "lab", "test", "category", "is", "chemistry", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "1246" ] }, { "key": "0e6c9aa4ec70962176e94cd1b787f404", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Private" ], [ 0, 14, 0, "PHYS REFERRAL/NORMAL DELI" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of private insurance patients who had phys referral/normal deli admission.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"PHYS REFERRAL/NORMAL DELI\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "private", "insurance", "patients", "who", "had", "phys", "referral", "/", "normal", "deli", "admission", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"PHYS", "REFERRAL/NORMAL", "DELI\"" ], "answer": [ "8090" ] }, { "key": "8752c40e2f19d9e0a8756d1c3c0d1e07", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 0, 16, 0, "BRADYCARDIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of medicaid patients who have bradycardia primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRADYCARDIA\"", "question_refine_tok": [ "count", "the", "number", "of", "medicaid", "patients", "who", "have", "bradycardia", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRADYCARDIA\"" ], "answer": [ "7" ] }, { "key": "09fd10713c941eab173ad347aa3286fb", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 0, 10, 1, 23 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of self pay insurance patients who were hospitalized for more than 23 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"23\"", "question_refine_tok": [ "provide", "the", "number", "of", "self", "pay", "insurance", "patients", "who", "were", "hospitalized", "for", "more", "than", "23", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"23\"" ], "answer": [ "22" ] }, { "key": "01be4c9c27f9397745f08c89be7c083a", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 0, 10, 1, 27 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of self pay insurance patients who were hospitalized for more than 27 days in hospital.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"27\"", "question_refine_tok": [ "count", "the", "number", "of", "self", "pay", "insurance", "patients", "who", "were", "hospitalized", "for", "more", "than", "27", "days", "in", "hospital", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"27\"" ], "answer": [ "14" ] }, { "key": "81b9fd8d1b452898ca8a528fc428fa72", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 0, 10, 1, 29 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of patients with self pay health insurance who were hospitalized for more than 29 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"29\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "patients", "with", "self", "pay", "health", "insurance", "who", "were", "hospitalized", "for", "more", "than", "29", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"29\"" ], "answer": [ "11" ] }, { "key": "0cbcd863e94c9c26d432776eda767c8d", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Private" ], [ 0, 18, 2, 1887 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with private insurance and born before 1887?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1887\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "private", "insurance", "and", "born", "before", "1887", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1887\"" ], "answer": [ "60" ] }, { "key": "871063e662639cce420193023a6c7f6b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 1, 2, 0, "4168" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients have a medicare insurance policy and diagnosis icd9 code is 4168?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND DIAGNOSES.\"ICD9_CODE\" = \"4168\"", "question_refine_tok": [ "how", "many", "patients", "have", "a", "medicare", "insurance", "policy", "and", "diagnosis", "icd9", "code", "is", "4168", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"4168\"" ], "answer": [ "1276" ] }, { "key": "bb226002b8be8b3696ff60e0ab444621", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 1, 2, 0, "430" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose insurance is self pay and with diagnosis icd9 code 430?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DIAGNOSES.\"ICD9_CODE\" = \"430\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "insurance", "is", "self", "pay", "and", "with", "diagnosis", "icd9", "code", "430", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"430\"" ], "answer": [ "13" ] }, { "key": "adc966b0bf7912a76c52b14c5f0fb98d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Private" ], [ 1, 2, 0, "2769" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients whose insurance is private and diagnoses icd9 code is 2769.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DIAGNOSES.\"ICD9_CODE\" = \"2769\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "whose", "insurance", "is", "private", "and", "diagnoses", "icd9", "code", "is", "2769", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2769\"" ], "answer": [ "29" ] }, { "key": "012f63ae067eacd6c0e4afa9dae1aa7b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 1, 2, 0, "33829" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "let me know the number of patients who have self pay insurance with diagnoses icd9 code 33829.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DIAGNOSES.\"ICD9_CODE\" = \"33829\"", "question_refine_tok": [ "let", "me", "know", "the", "number", "of", "patients", "who", "have", "self", "pay", "insurance", "with", "diagnoses", "icd9", "code", "33829", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"33829\"" ], "answer": [ "3" ] }, { "key": "81b7536d96f8c6d71d6411b29f3e4531", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 1, 3, 0, "Hx of GI malignancy NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose insurance is self pay and whose diagnosis short title is hx of gi malignancy nos.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Hx of GI malignancy NOS\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "insurance", "is", "self", "pay", "and", "whose", "diagnosis", "short", "title", "is", "hx", "of", "gi", "malignancy", "nos", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Hx", "of", "GI", "malignancy", "NOS\"" ], "answer": [ "0" ] }, { "key": "082284313a19eb529220fdbbf1676c91", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 1, 3, 0, "Crnry athrscl natve vssl" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients on self pay had coronary athrscl natve vessel?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Crnry athrscl natve vssl\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "on", "self", "pay", "had", "coronary", "athrscl", "natve", "vessel", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Crnry", "athrscl", "natve", "vssl\"" ], "answer": [ "48" ] }, { "key": "808b921081a21617d1d649e86c33894e", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Private" ], [ 1, 4, 0, "Infectious mononucleosis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of private health insurance patients who have infectious mononucleosis diagnoses.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DIAGNOSES.\"LONG_TITLE\" = \"Infectious mononucleosis\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "private", "health", "insurance", "patients", "who", "have", "infectious", "mononucleosis", "diagnoses", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Infectious", "mononucleosis\"" ], "answer": [ "6" ] }, { "key": "a8c9ccd4513aa68a86ef56e05609224e", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Government" ], [ 1, 4, 0, "Tietze's disease" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with tietze's disease are insured by the government?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND DIAGNOSES.\"LONG_TITLE\" = \"Tietze's disease\"", "question_refine_tok": [ "how", "many", "patients", "with", "tietze", "'s", "disease", "are", "insured", "by", "the", "government", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Tietze's", "disease\"" ], "answer": [ "1" ] }, { "key": "a56bfe2c679c02acf5a3018461748064", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Private" ], [ 1, 4, 0, "Hematoma complicating a procedure" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose insurance is private and diagnosis long title is hematoma complicating a procedure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DIAGNOSES.\"LONG_TITLE\" = \"Hematoma complicating a procedure\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "insurance", "is", "private", "and", "diagnosis", "long", "title", "is", "hematoma", "complicating", "a", "procedure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Hematoma", "complicating", "a", "procedure\"" ], "answer": [ "346" ] }, { "key": "9114d1b703187b9a91eb49802885ee40", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 1, 4, 0, "Acute on chronic systolic heart failure" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of medicaid patients who are diagnosed with acute on chronic systolic heart failure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND DIAGNOSES.\"LONG_TITLE\" = \"Acute on chronic systolic heart failure\"", "question_refine_tok": [ "find", "the", "number", "of", "medicaid", "patients", "who", "are", "diagnosed", "with", "acute", "on", "chronic", "systolic", "heart", "failure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Acute", "on", "chronic", "systolic", "heart", "failure\"" ], "answer": [ "47" ] }, { "key": "bba8daf0dc3f5b30121ab621a4fd9572", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 1, 4, 0, "Blood in stool" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients posses self pay insurance and were diagnosed with blood in stool?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND DIAGNOSES.\"LONG_TITLE\" = \"Blood in stool\"", "question_refine_tok": [ "how", "many", "patients", "posses", "self", "pay", "insurance", "and", "were", "diagnosed", "with", "blood", "in", "stool", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Blood", "in", "stool\"" ], "answer": [ "3" ] }, { "key": "0bbcf8d324631dbcb4695ecf9f9355d6", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 11, 0, "Private" ], [ 1, 4, 0, "Paraplegia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with a private insurance had the diagnosis long title paraplegia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND DIAGNOSES.\"LONG_TITLE\" = \"Paraplegia\"", "question_refine_tok": [ "how", "many", "patients", "with", "a", "private", "insurance", "had", "the", "diagnosis", "long", "title", "paraplegia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Paraplegia\"" ], "answer": [ "46" ] }, { "key": "8a203c76dc335931b4d7ea505187d743", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Private" ], [ 2, 2, 0, 8960 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of private insurance patients who have procedure icd9 code 8960.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND PROCEDURES.\"ICD9_CODE\" = \"8960\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "private", "insurance", "patients", "who", "have", "procedure", "icd9", "code", "8960", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8960\"" ], "answer": [ "98" ] }, { "key": "09b90c671f009a51f4e731381bad6f2a", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Private" ], [ 2, 2, 0, 8847 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients posses private insurance and followed the procedure icd9 code 8847?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND PROCEDURES.\"ICD9_CODE\" = \"8847\"", "question_refine_tok": [ "how", "many", "patients", "posses", "private", "insurance", "and", "followed", "the", "procedure", "icd9", "code", "8847", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8847\"" ], "answer": [ "208" ] }, { "key": "9282ac3a193e0216224ba0aa27a09e60", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Government" ], [ 2, 2, 0, 2219 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients on government insurance had icd9 code 2219?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND PROCEDURES.\"ICD9_CODE\" = \"2219\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "on", "government", "insurance", "had", "icd9", "code", "2219", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"2219\"" ], "answer": [ "0" ] }, { "key": "95e21d3f8a09445ab0200ce36a3bb911", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 2, 2, 0, 331 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients on medicaid insurance had icd9 code 331?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND PROCEDURES.\"ICD9_CODE\" = \"331\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "on", "medicaid", "insurance", "had", "icd9", "code", "331", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"331\"" ], "answer": [ "0" ] }, { "key": "04ff81516b8b19802dbcca87e803a124", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 2, 2, 0, 7761 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of medicaid patients who have procedure icd9 code 7761?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND PROCEDURES.\"ICD9_CODE\" = \"7761\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "medicaid", "patients", "who", "have", "procedure", "icd9", "code", "7761", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"7761\"" ], "answer": [ "6" ] }, { "key": "842458dd6b3386bf8dd16f590c85bc37", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 2, 2, 0, 9703 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of medicare patients who have procedure icd9 code 9703?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND PROCEDURES.\"ICD9_CODE\" = \"9703\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "medicare", "patients", "who", "have", "procedure", "icd9", "code", "9703", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9703\"" ], "answer": [ "29" ] }, { "key": "0415c705636a594e54167a885bafecb1", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Private" ], [ 2, 3, 0, "Abdomen artery incision" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of private insurance patients who had incision of abdomen artery.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND PROCEDURES.\"SHORT_TITLE\" = \"Abdomen artery incision\"", "question_refine_tok": [ "provide", "the", "number", "of", "private", "insurance", "patients", "who", "had", "incision", "of", "abdomen", "artery", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Abdomen", "artery", "incision\"" ], "answer": [ "9" ] }, { "key": "0e642608874d252c87210c63bfff9aba", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Private" ], [ 2, 3, 0, "Remov biliary/liver tube" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose insurance is private and procedure short title is remov biliary/liver tube.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND PROCEDURES.\"SHORT_TITLE\" = \"Remov biliary/liver tube\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "insurance", "is", "private", "and", "procedure", "short", "title", "is", "remov", "biliary", "/", "liver", "tube", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Remov", "biliary/liver", "tube\"" ], "answer": [ "18" ] }, { "key": "02359f7d8f1cd2a818f4de4f9d1a3fab", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Private" ], [ 2, 4, 0, "Single internal mammary-coronary artery bypass" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of private health insurance patients who have had single internal mammary-coronary artery bypass.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND PROCEDURES.\"LONG_TITLE\" = \"Single internal mammary-coronary artery bypass\"", "question_refine_tok": [ "provide", "the", "number", "of", "private", "health", "insurance", "patients", "who", "have", "had", "single", "internal", "mammary", "-", "coronary", "artery", "bypass", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Single", "internal", "mammary-coronary", "artery", "bypass\"" ], "answer": [ "1616" ] }, { "key": "aa81098d9bbd712002641a023ad9c2ed", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Government" ], [ 2, 4, 0, "Laryngoscopy and other tracheoscopy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of government health insurance patients who had laryngoscopy and other tracheoscopy procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND PROCEDURES.\"LONG_TITLE\" = \"Laryngoscopy and other tracheoscopy\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "government", "health", "insurance", "patients", "who", "had", "laryngoscopy", "and", "other", "tracheoscopy", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Laryngoscopy", "and", "other", "tracheoscopy\"" ], "answer": [ "19" ] }, { "key": "90caf4ef19c39af73c6c6a3f0c443dac", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Government" ], [ 2, 4, 0, "Other percutaneous procedures on biliary tract" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of government health insurance patients who have other percutaneous procedures on biliary tract.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND PROCEDURES.\"LONG_TITLE\" = \"Other percutaneous procedures on biliary tract\"", "question_refine_tok": [ "provide", "the", "number", "of", "government", "health", "insurance", "patients", "who", "have", "other", "percutaneous", "procedures", "on", "biliary", "tract", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Other", "percutaneous", "procedures", "on", "biliary", "tract\"" ], "answer": [ "3" ] }, { "key": "875d499905399fac8bee24c2c3b53ad0", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 2, 4, 0, "Automatic implantable cardioverter/defibrillator (AICD) check" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of medicaid patients who have an automatic implantable cardioverter/defibrillator (aicd) check procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND PROCEDURES.\"LONG_TITLE\" = \"Automatic implantable cardioverter/defibrillator (AICD) check\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "medicaid", "patients", "who", "have", "an", "automatic", "implantable", "cardioverter/defibrillator", "(", "aicd", ")", "check", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Automatic", "implantable", "cardioverter/defibrillator", "(AICD)", "check\"" ], "answer": [ "4" ] }, { "key": "00ff7a671d3e218eaf9811d9294a2df5", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Government" ], [ 4, 6, 0, "Thyroid Stimulating Hormone" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients posses government insurance and are tested for thyroid stimulating hormone in lab?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND LAB.\"LABEL\" = \"Thyroid Stimulating Hormone\"", "question_refine_tok": [ "how", "many", "patients", "posses", "government", "insurance", "and", "are", "tested", "for", "thyroid", "stimulating", "hormone", "in", "lab", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "LAB.\"LABEL\"", "=", "\"Thyroid", "Stimulating", "Hormone\"" ], "answer": [ "325" ] }, { "key": "b9f1e03f8008107335da5fbe1f8b604f", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 4, 6, 0, "RBC, CSF" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get me the number of self pay insurance patients who had an rbc csf lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND LAB.\"LABEL\" = \"RBC, CSF\"", "question_refine_tok": [ "Get", "me", "the", "number", "of", "self", "pay", "insurance", "patients", "who", "had", "an", "rbc", "csf", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "LAB.\"LABEL\"", "=", "\"RBC,", "CSF\"" ], "answer": [ "33" ] }, { "key": "829b1b9874d4849cb5c8f0fbabd0373e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Government" ], [ 4, 6, 0, "WBC, Joint Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of government health insurance patients who had wbc, joint fluid lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND LAB.\"LABEL\" = \"WBC, Joint Fluid\"", "question_refine_tok": [ "count", "the", "number", "of", "government", "health", "insurance", "patients", "who", "had", "wbc", ",", "joint", "fluid", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "LAB.\"LABEL\"", "=", "\"WBC,", "Joint", "Fluid\"" ], "answer": [ "8" ] }, { "key": "019e08d2917352c1c6a6a5e59af70736", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Government" ], [ 4, 6, 0, "Hemoglobin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of government health insurance patients who had a hemoglobin lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND LAB.\"LABEL\" = \"Hemoglobin\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "government", "health", "insurance", "patients", "who", "had", "a", "hemoglobin", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "LAB.\"LABEL\"", "=", "\"Hemoglobin\"" ], "answer": [ "1558" ] }, { "key": "03b293f7978766e73fdfb4285a540bd0", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 4, 6, 0, "Granular Casts" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many self pay insurance patients had granular casts lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND LAB.\"LABEL\" = \"Granular Casts\"", "question_refine_tok": [ "how", "many", "self", "pay", "insurance", "patients", "had", "granular", "casts", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "LAB.\"LABEL\"", "=", "\"Granular", "Casts\"" ], "answer": [ "47" ] }, { "key": "05cbfa2dbd0e6f14a3b99380a97d21e0", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Self Pay" ], [ 4, 6, 0, "Fibrin Degradation Products" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients had the lab test named fibrin degradation products and self paid the costs?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\" AND LAB.\"LABEL\" = \"Fibrin Degradation Products\"", "question_refine_tok": [ "what", "number", "of", "patients", "had", "the", "lab", "test", "named", "fibrin", "degradation", "products", "and", "self", "paid", "the", "costs", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"", "AND", "LAB.\"LABEL\"", "=", "\"Fibrin", "Degradation", "Products\"" ], "answer": [ "29" ] }, { "key": "04dcc9195c39d775a4c8e4bbca95655d", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Government" ], [ 4, 6, 0, "NTproBNP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "let me know the number of government health insurance patients who have ntprobnp lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND LAB.\"LABEL\" = \"NTproBNP\"", "question_refine_tok": [ "let", "me", "know", "the", "number", "of", "government", "health", "insurance", "patients", "who", "have", "ntprobnp", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "LAB.\"LABEL\"", "=", "\"NTproBNP\"" ], "answer": [ "61" ] }, { "key": "07163adde9ae1793367db811d58fcbd0", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Private" ], [ 4, 6, 0, "Ferritin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients who have private insurance policy and who have had lab test ferritin done.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\" AND LAB.\"LABEL\" = \"Ferritin\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "who", "have", "private", "insurance", "policy", "and", "who", "have", "had", "lab", "test", "ferritin", "done", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"", "AND", "LAB.\"LABEL\"", "=", "\"Ferritin\"" ], "answer": [ "2134" ] }, { "key": "aac606c3fa8dda9c93ac0bf472a23557", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Medicare" ], [ 4, 6, 0, "Amylase, Body Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find me the number of medicare patients for whome amylase a body fluid lab test was ordered.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicare\" AND LAB.\"LABEL\" = \"Amylase, Body Fluid\"", "question_refine_tok": [ "Find", "me", "the", "number", "of", "medicare", "patients", "for", "whome", "amylase", "a", "body", "fluid", "lab", "test", "was", "ordered", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicare\"", "AND", "LAB.\"LABEL\"", "=", "\"Amylase,", "Body", "Fluid\"" ], "answer": [ "233" ] }, { "key": "8e437a1d5319bc89ef8672cf6621f812", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 11, 0, "Government" ], [ 4, 6, 0, "Ammonia" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients having government insurance have had ammonia lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND LAB.\"LABEL\" = \"Ammonia\"", "question_refine_tok": [ "how", "many", "patients", "having", "government", "insurance", "have", "had", "ammonia", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "LAB.\"LABEL\"", "=", "\"Ammonia\"" ], "answer": [ "61" ] }, { "key": "0248a48a1f8756d259a4bd33b86768dc", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/CAPE VERDEAN" ], [ 0, 16, 0, "COLANGITIS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients of black/cape verdean ethnicity were primarily diagnosed with the disease colangitis", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/CAPE VERDEAN\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"COLANGITIS\"", "question_refine_tok": [ "How", "many", "patients", "of", "black/cape", "verdean", "ethnicity", "were", "primarily", "diagnosed", "with", "the", "disease", "colangitis" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/CAPE", "VERDEAN\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"COLANGITIS\"" ], "answer": [ "0" ] }, { "key": "9c0e1d982d6a14ff908ec2ba2546d3f1", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/CAPE VERDEAN" ], [ 0, 16, 0, "FEMORAL ARTERY THROMBOSIS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients of black/cape verdean ethnicity are primary diagnosed with femoral artery thrombosis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/CAPE VERDEAN\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"FEMORAL ARTERY THROMBOSIS\"", "question_refine_tok": [ "how", "many", "patients", "of", "black/cape", "verdean", "ethnicity", "are", "primary", "diagnosed", "with", "femoral", "artery", "thrombosis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/CAPE", "VERDEAN\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"FEMORAL", "ARTERY", "THROMBOSIS\"" ], "answer": [ "0" ] }, { "key": "a82c32dbfebc44c734653dbb104baeef", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 0, 16, 0, "OVERDOSE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many white patients had overdose as the primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"OVERDOSE\"", "question_refine_tok": [ "how", "many", "white", "patients", "had", "overdose", "as", "the", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"OVERDOSE\"" ], "answer": [ "139" ] }, { "key": "10aa4541cd78d8f064a7a61f4407dd95", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "AMERICAN INDIAN/ALASKA NATIVE" ], [ 0, 16, 0, "FEMORAL ARTERY THROMBOSIS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose ethnicity is american indian/alaska native and primary disease is femoral artery thrombosis.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"AMERICAN INDIAN/ALASKA NATIVE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"FEMORAL ARTERY THROMBOSIS\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "ethnicity", "is", "american", "indian", "/", "alaska", "native", "and", "primary", "disease", "is", "femoral", "artery", "thrombosis", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"AMERICAN", "INDIAN/ALASKA", "NATIVE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"FEMORAL", "ARTERY", "THROMBOSIS\"" ], "answer": [ "0" ] }, { "key": "8762eb0a5667497e60e00c3d154d04a5", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "AMERICAN INDIAN/ALASKA NATIVE" ], [ 0, 16, 0, "INFECTED RIGHT THIGH GRAFT" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with infected right thigh graft were of american indian/alaska native ethnicty?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"AMERICAN INDIAN/ALASKA NATIVE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"INFECTED RIGHT THIGH GRAFT\"", "question_refine_tok": [ "how", "many", "patients", "with", "infected", "right", "thigh", "graft", "were", "of", "american", "indian", "/", "alaska", "native", "ethnicty", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"AMERICAN", "INDIAN/ALASKA", "NATIVE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"INFECTED", "RIGHT", "THIGH", "GRAFT\"" ], "answer": [ "0" ] }, { "key": "9719acc7d60a861e34e62a3ce13af41a", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 16, 0, "PNEUMONIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many asian patients have pneumonia as their primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"PNEUMONIA\"", "question_refine_tok": [ "How", "many", "asian", "patients", "have", "pneumonia", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PNEUMONIA\"" ], "answer": [ "38" ] }, { "key": "add9568e43f767016e132a36afb7ccdd", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 16, 0, "LIVER TRANSPLANT" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many asian patients had liver transplant as their primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"LIVER TRANSPLANT\"", "question_refine_tok": [ "how", "many", "asian", "patients", "had", "liver", "transplant", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"LIVER", "TRANSPLANT\"" ], "answer": [ "1" ] }, { "key": "0b6038dee288554b4be4cbc7318d978e", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 4, 2, 50 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with icd9 code 9600 have an additive drug type?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"AGE\" < \"50\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "icd9", "code", "9600", "have", "an", "additive", "drug", "type", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"50\"" ], "answer": [ "877" ] }, { "key": "089d4aad2ec39bb2d761af30e107414a", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE - RUSSIAN" ], [ 0, 18, 2, 2103 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get me the number of white russian patients born before year 2103.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE - RUSSIAN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2103\"", "question_refine_tok": [ "Get", "me", "the", "number", "of", "white", "russian", "patients", "born", "before", "year", "2103", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE", "-", "RUSSIAN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2103\"" ], "answer": [ "94" ] }, { "key": "827507e01ab3afc178dc211fd3c77e6e", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "AMERICAN INDIAN/ALASKA NATIVE" ], [ 0, 18, 2, 2129 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with an american indian/alaska native ethnic background were born before 2129?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"AMERICAN INDIAN/ALASKA NATIVE\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2129\"", "question_refine_tok": [ "How", "many", "patients", "with", "an", "american", "indian/alaska", "native", "ethnic", "background", "were", "born", "before", "2129", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"AMERICAN", "INDIAN/ALASKA", "NATIVE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2129\"" ], "answer": [ "25" ] }, { "key": "033c6bc31c1e87fc2bd294982f5fe319", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "AMERICAN INDIAN/ALASKA NATIVE" ], [ 0, 22, 2, 2148 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many american indian/alaska native ethnic background patients were born before 2148?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"AMERICAN INDIAN/ALASKA NATIVE\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2148\"", "question_refine_tok": [ "how", "many", "american", "indian", "/", "alaska", "native", "ethnic", "background", "patients", "were", "born", "before", "2148", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"AMERICAN", "INDIAN/ALASKA", "NATIVE\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2148\"" ], "answer": [ "28" ] }, { "key": "94d0be30fd59acfdb250295d59e23a84", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 0, 22, 2, 2123 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many black/haitian patients were admitted in hospital before 2123?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2123\"", "question_refine_tok": [ "how", "many", "black", "/", "haitian", "patients", "were", "admitted", "in", "hospital", "before", "2123", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2123\"" ], "answer": [ "18" ] }, { "key": "0f769f9a7f2c3f0370a0819fc352f161", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 0, 22, 2, 2124 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me the number of black/haitian patients who were admitted before the year 2124.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2124\"", "question_refine_tok": [ "provide", "me", "the", "number", "of", "black", "/", "haitian", "patients", "who", "were", "admitted", "before", "the", "year", "2124", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2124\"" ], "answer": [ "18" ] }, { "key": "0dec664e1cf98dc3fc384816c4c72c8e", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 0, 22, 2, 2110 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients of asian ethnicity are admitted before the year 2110?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2110\"", "question_refine_tok": [ "how", "many", "patients", "of", "asian", "ethnicity", "are", "admitted", "before", "the", "year", "2110", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2110\"" ], "answer": [ "125" ] }, { "key": "05343cc69204da73ce2ac4ac4d8295bb", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 1, 2, 0, "2948" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Show me the number of black /haitian patients who were diagnosed under the diagnoses cicd9 code 2948.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND DIAGNOSES.\"ICD9_CODE\" = \"2948\"", "question_refine_tok": [ "Show", "me", "the", "number", "of", "black", "/", "haitian", "patients", "who", "were", "diagnosed", "under", "the", "diagnoses", "cicd9", "code", "2948", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"2948\"" ], "answer": [ "2" ] }, { "key": "060b7c924b230b79b3935a795cfaf37d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 1, 4, 0, "Neutropenia, unspecified" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the asian patients had unspecified neutropenia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND DIAGNOSES.\"LONG_TITLE\" = \"Neutropenia, unspecified\"", "question_refine_tok": [ "how", "many", "of", "the", "asian", "patients", "had", "unspecified", "neutropenia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Neutropenia,", "unspecified\"" ], "answer": [ "2" ] }, { "key": "92780cb99869641eda47bd51e2817ff3", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 2, 2, 0, 8854 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients belonging to black/haitian ethnic background hav ethe procedure icd9 code 8854?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND PROCEDURES.\"ICD9_CODE\" = \"8854\"", "question_refine_tok": [ "how", "many", "patients", "belonging", "to", "black", "/", "haitian", "ethnic", "background", "hav", "ethe", "procedure", "icd9", "code", "8854", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8854\"" ], "answer": [ "1" ] }, { "key": "ad8ddc87b6f78351e61ae2c8eb6d84c7", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 2, 4, 0, "Open and other replacement of aortic valve with tissue graft" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many asian patients underwent open and other replacement of aortic valve with tissue graft procedure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND PROCEDURES.\"LONG_TITLE\" = \"Open and other replacement of aortic valve with tissue graft\"", "question_refine_tok": [ "how", "many", "asian", "patients", "underwent", "open", "and", "other", "replacement", "of", "aortic", "valve", "with", "tissue", "graft", "procedure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Open", "and", "other", "replacement", "of", "aortic", "valve", "with", "tissue", "graft\"" ], "answer": [ "2" ] }, { "key": "0c9f6eae00f98d18ac9f50768c7c5a86", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many asian patients had a base drug type?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "how", "many", "asian", "patients", "had", "a", "base", "drug", "type", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "814" ] }, { "key": "81246894ba88abc13f0ae732be0ae33f", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ], [ 3, 4, 0, "Phenylephrine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many black/haitian patients have phenylephrine medication prescription?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\" AND PRESCRIPTIONS.\"DRUG\" = \"Phenylephrine\"", "question_refine_tok": [ "how", "many", "black", "/", "haitian", "patients", "have", "phenylephrine", "medication", "prescription", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Phenylephrine\"" ], "answer": [ "7" ] }, { "key": "0c8330f32031377d2d0f4c9c05d1adae", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 12, 0, "ASIAN" ], [ 3, 4, 0, "GlyBURIDE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of asian patients who are taking glyburide medication.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\" AND PRESCRIPTIONS.\"DRUG\" = \"GlyBURIDE\"", "question_refine_tok": [ "provide", "the", "number", "of", "asian", "patients", "who", "are", "taking", "glyburide", "medication", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"GlyBURIDE\"" ], "answer": [ "6" ] }, { "key": "96963b619664c6cb69c86c26538c79da", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 12, 0, "WHITE - RUSSIAN" ], [ 3, 6, 0, "NEB" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Get the list of white-russian patients with a neb route of drug administration.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE - RUSSIAN\" AND PRESCRIPTIONS.\"ROUTE\" = \"NEB\"", "question_refine_tok": [ "Get", "the", "list", "of", "white-russian", "patients", "with", "a", "neb", "route", "of", "drug", "administration", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE", "-", "RUSSIAN\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"NEB\"" ], "answer": [ "0" ] }, { "key": "0d1708a4f7f49d7baab81dc4dcb63832", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 4, 6, 0, "Protein/Creatinine Ratio" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many white ethnic background patients had a protein/creatinine ratio lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND LAB.\"LABEL\" = \"Protein/Creatinine Ratio\"", "question_refine_tok": [ "How", "many", "white", "ethnic", "background", "patients", "had", "a", "protein/creatinine", "ratio", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "LAB.\"LABEL\"", "=", "\"Protein/Creatinine", "Ratio\"" ], "answer": [ "1432" ] }, { "key": "860ca98fdc1c9de35d4d8efdcef583ec", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 16, 0, "T5 FRACTURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients whose death status is 1 and primary disease is t5 fracture.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"T5 FRACTURE\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "whose", "death", "status", "is", "1", "and", "primary", "disease", "is", "t5", "fracture", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"T5", "FRACTURE\"" ], "answer": [ "0" ] }, { "key": "a098cd2cff8c0c939b8ee19c13e38c43", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 16, 0, "ST ELEVATED MYOCARDIAL INFARCTION\\CARDIAC CATH" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Provide the number of patients that died and had a primary disease of ST elevated myocardial infarction/cardiac cath.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"ST ELEVATED MYOCARDIAL INFARCTION\\CARDIAC CATH\"", "question_refine_tok": [ "Provide", "the", "number", "of", "patients", "that", "died", "and", "had", "a", "primary", "disease", "of", "ST", "elevated", "myocardial", "infarction/cardiac", "cath", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ST", "ELEVATED", "MYOCARDIAL", "INFARCTION\\CARDIAC", "CATH\"" ], "answer": [ "1" ] }, { "key": "8671bf636d2e0104446bd24670fb7189", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 16, 0, "BRAIN MASS;INTRACRANIAL HEMORRHAGE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of dead patients who had brain mass intracranial hemorrhage?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRAIN MASS;INTRACRANIAL HEMORRHAGE\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "dead", "patients", "who", "had", "brain", "mass", "intracranial", "hemorrhage", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRAIN", "MASS;INTRACRANIAL", "HEMORRHAGE\"" ], "answer": [ "1" ] }, { "key": "898baa9cfc011b6284b24d2cbc29209a", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 16, 0, "LEFT FEMUR FRACTURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many dead patients had left femur fracture primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"LEFT FEMUR FRACTURE\"", "question_refine_tok": [ "how", "many", "dead", "patients", "had", "left", "femur", "fracture", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"LEFT", "FEMUR", "FRACTURE\"" ], "answer": [ "7" ] }, { "key": "88309c7f731812aac8c0784535361b4e", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 16, 0, "PITUITARY BLEED" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who died of pituatary bleed.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"PITUITARY BLEED\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "died", "of", "pituatary", "bleed", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PITUITARY", "BLEED\"" ], "answer": [ "1" ] }, { "key": "02ba408e52f64f06bc6b48bee70f2bda", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 10, 1, 2 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are died and stayed in hospital above 2 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"2\"", "question_refine_tok": [ "how", "many", "patients", "are", "died", "and", "stayed", "in", "hospital", "above", "2", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"2\"" ], "answer": [ "13411" ] }, { "key": "05b45f4c6bb925d5091172692b926676", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 1 ], [ 0, 18, 2, 1837 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients born before the year 1837 who are no longer alive.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1837\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "born", "before", "the", "year", "1837", "who", "are", "no", "longer", "alive", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1837\"" ], "answer": [ "519" ] }, { "key": "a599dd4808509b599117b9956c19739c", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 2, 0, "5712" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give the number of patients that survived and have a diagnosis icd9 code of 5712.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"ICD9_CODE\" = \"5712\"", "question_refine_tok": [ "Give", "the", "number", "of", "patients", "that", "survived", "and", "have", "a", "diagnosis", "icd9", "code", "of", "5712", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"5712\"" ], "answer": [ "350" ] }, { "key": "88bd504917d82cccd38ba49d6ab39d9d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 2, 0, "29570" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients diagnosed with icd9 code 29570 whose death status is unspecified", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"ICD9_CODE\" = \"29570\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "diagnosed", "with", "icd9", "code", "29570", "whose", "death", "status", "is", "unspecified" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"29570\"" ], "answer": [ "101" ] }, { "key": "8902a02099712a8189d8bcf54a6d94de", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 1 ], [ 1, 2, 0, "5680" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients survived and were diagnosed with icd9 code 5680?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DIAGNOSES.\"ICD9_CODE\" = \"5680\"", "question_refine_tok": [ "how", "many", "patients", "survived", "and", "were", "diagnosed", "with", "icd9", "code", "5680", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"5680\"" ], "answer": [ "147" ] }, { "key": "87193d8860bf45c98f1c716149f06cb5", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 1 ], [ 1, 2, 0, "5733" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of dead patients who had 5733 diagnoses icd9 code.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DIAGNOSES.\"ICD9_CODE\" = \"5733\"", "question_refine_tok": [ "find", "the", "number", "of", "dead", "patients", "who", "had", "5733", "diagnoses", "icd9", "code", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"5733\"" ], "answer": [ "55" ] }, { "key": "ac4859e6d068b8942b9b9fe02883dde2", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 1 ], [ 1, 3, 0, "Fall NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients diagnosed with fall nos who have died", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Fall NOS\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "diagnosed", "with", "fall", "nos", "who", "have", "died" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Fall", "NOS\"" ], "answer": [ "558" ] }, { "key": "06bbd920c4191e622346b9c33d8b0f43", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 4, 0, "Suicide and self-inflicted poisoning by analgesics, antipyretics, and antirheumatics" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of living patients diagnosed with suicide and self-inflicted poisoning by analgesics, antipyretics, and antirheumatics?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"LONG_TITLE\" = \"Suicide and self-inflicted poisoning by analgesics, antipyretics, and antirheumatics\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "living", "patients", "diagnosed", "with", "suicide", "and", "self", "-", "inflicted", "poisoning", "by", "analgesics", ",", "antipyretics", ",", "and", "antirheumatics", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Suicide", "and", "self-inflicted", "poisoning", "by", "analgesics,", "antipyretics,", "and", "antirheumatics\"" ], "answer": [ "158" ] }, { "key": "93769bf5b268fb4f529260ca8fc17c57", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 13, 0, 0 ], [ 1, 4, 0, "Chronic diastolic heart failure" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are with death status 0 and with diagnosis chronic diastolic heart failure?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DIAGNOSES.\"LONG_TITLE\" = \"Chronic diastolic heart failure\"", "question_refine_tok": [ "how", "many", "patients", "are", "with", "death", "status", "0", "and", "with", "diagnosis", "chronic", "diastolic", "heart", "failure", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Chronic", "diastolic", "heart", "failure\"" ], "answer": [ "532" ] }, { "key": "a8f8dda2d780d61747aee2d99f50e9fe", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 2, 0, 4610 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me with the number of alive patients who have procedure icd9 code 4610.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"ICD9_CODE\" = \"4610\"", "question_refine_tok": [ "provide", "me", "with", "the", "number", "of", "alive", "patients", "who", "have", "procedure", "icd9", "code", "4610", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4610\"" ], "answer": [ "41" ] }, { "key": "021ebbc73156e10c78d02f72ff647325", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 2, 0, 331 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Count the number of patients that survived and had a procedure icd9 code of 331.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"ICD9_CODE\" = \"331\"", "question_refine_tok": [ "Count", "the", "number", "of", "patients", "that", "survived", "and", "had", "a", "procedure", "icd9", "code", "of", "331", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"331\"" ], "answer": [ "0" ] }, { "key": "9d0a02bc7f100ba107192d6e44a9e695", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 2, 0, 5012 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with 5012 as the procedure icd9 code survived?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"ICD9_CODE\" = \"5012\"", "question_refine_tok": [ "How", "many", "patients", "with", "5012", "as", "the", "procedure", "icd9", "code", "survived", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5012\"" ], "answer": [ "52" ] }, { "key": "9debb2f0f6c08e2c0b547c27502c36b4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 3, 0, "Int insert lead in vent" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "For how many patients with int insert lead in vent was the death status left unspecified?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"SHORT_TITLE\" = \"Int insert lead in vent\"", "question_refine_tok": [ "For", "how", "many", "patients", "with", "int", "insert", "lead", "in", "vent", "was", "the", "death", "status", "left", "unspecified", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Int", "insert", "lead", "in", "vent\"" ], "answer": [ "28" ] }, { "key": "0a997753f9229f659e7e05d541190484", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 3, 0, "Suture bladder lacerat" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Specify the total number of patients who had suture bladder lacerat and a death status of unspecified", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"SHORT_TITLE\" = \"Suture bladder lacerat\"", "question_refine_tok": [ "Specify", "the", "total", "number", "of", "patients", "who", "had", "suture", "bladder", "lacerat", "and", "a", "death", "status", "of", "unspecified" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Suture", "bladder", "lacerat\"" ], "answer": [ "14" ] }, { "key": "061d620cdd89282af1d48f9a0f2d3931", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 13, 0, 0 ], [ 2, 4, 0, "Open biopsy of soft tissue" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get the number of alive patients who underwent open biopsy of soft tissue.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND PROCEDURES.\"LONG_TITLE\" = \"Open biopsy of soft tissue\"", "question_refine_tok": [ "get", "the", "number", "of", "alive", "patients", "who", "underwent", "open", "biopsy", "of", "soft", "tissue", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Open", "biopsy", "of", "soft", "tissue\"" ], "answer": [ "47" ] }, { "key": "aa87e8e508f6984831876860be1761df", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 13, 0, 1 ], [ 3, 4, 0, "Pantoprazole Sodium" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of dead patients who had a prescription for pantoprazole sodium medication?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"1\" AND PRESCRIPTIONS.\"DRUG\" = \"Pantoprazole Sodium\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "dead", "patients", "who", "had", "a", "prescription", "for", "pantoprazole", "sodium", "medication", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"1\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Pantoprazole", "Sodium\"" ], "answer": [ "5871" ] }, { "key": "08f97d12862b1090fe02850b15e4b5b9", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRANSFER FROM HOSP/EXTRAM" ], [ 0, 15, 0, "DISC-TRAN CANCER/CHLDRN H" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admission location is transfer from hosp/extram and were discharged to disc-tran cancer/chldrn h?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRANSFER FROM HOSP/EXTRAM\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISC-TRAN CANCER/CHLDRN H\"", "question_refine_tok": [ "how", "many", "patients", "admission", "location", "is", "transfer", "from", "hosp/extram", "and", "were", "discharged", "to", "disc-tran", "cancer/chldrn", "h", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRANSFER", "FROM", "HOSP/EXTRAM\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISC-TRAN", "CANCER/CHLDRN", "H\"" ], "answer": [ "129" ] }, { "key": "806f6052bc99c1f5f8cb8a3215d3f8b2", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRANSFER FROM HOSP/EXTRAM" ], [ 0, 15, 0, "DEAD/EXPIRED" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients admitted or transfer from hosp/extram were dead or expired on discharge?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRANSFER FROM HOSP/EXTRAM\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DEAD/EXPIRED\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "admitted", "or", "transfer", "from", "hosp", "/", "extram", "were", "dead", "or", "expired", "on", "discharge", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRANSFER", "FROM", "HOSP/EXTRAM\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DEAD/EXPIRED\"" ], "answer": [ "1137" ] }, { "key": "81d4b16c544ec88c25ad79af7eae050e", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRSF WITHIN THIS FACILITY" ], [ 0, 15, 0, "HOME" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who were transferred within the facility and were discharged to home.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRSF WITHIN THIS FACILITY\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "were", "transferred", "within", "the", "facility", "and", "were", "discharged", "to", "home", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRSF", "WITHIN", "THIS", "FACILITY\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"" ], "answer": [ "0" ] }, { "key": "0625a832abfe55a8682577eedb38b824", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 0, 16, 0, "T5 FRACTURE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose admission location is emergency room admit and with primary disease t5 fracture?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"T5 FRACTURE\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "admission", "location", "is", "emergency", "room", "admit", "and", "with", "primary", "disease", "t5", "fracture", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"T5", "FRACTURE\"" ], "answer": [ "0" ] }, { "key": "050ed27881bce414cfd05ba83a22a4d4", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 0, 10, 1, 4 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of emergency room admitted patients who were hospitalized for more than 4 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"4\"", "question_refine_tok": [ "provide", "the", "number", "of", "emergency", "room", "admitted", "patients", "who", "were", "hospitalized", "for", "more", "than", "4", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"4\"" ], "answer": [ "11750" ] }, { "key": "0bc26b6c69c9bf3628430b1e23d18007", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "TRSF WITHIN THIS FACILITY" ], [ 0, 18, 2, 1879 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients born before 1879 ere tranferred within the facility.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"TRSF WITHIN THIS FACILITY\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1879\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "born", "before", "1879", "ere", "tranferred", "within", "the", "facility", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"TRSF", "WITHIN", "THIS", "FACILITY\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1879\"" ], "answer": [ "0" ] }, { "key": "015ae8de2f7597f3308e719345bd99de", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 1, 3, 0, "Mixed acid-base bal dis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted under emergency room and diagnosed with mixed acid-base bal dis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Mixed acid-base bal dis\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "under", "emergency", "room", "and", "diagnosed", "with", "mixed", "acid", "-", "base", "bal", "dis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Mixed", "acid-base", "bal", "dis\"" ], "answer": [ "195" ] }, { "key": "a5daeaab175913c300dbbbb1206a9c4e", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 2, 2, 0, 3799 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients admitted in emergency room had the procedure under procedure icd9 code 3799?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND PROCEDURES.\"ICD9_CODE\" = \"3799\"", "question_refine_tok": [ "what", "number", "of", "patients", "admitted", "in", "emergency", "room", "had", "the", "procedure", "under", "procedure", "icd9", "code", "3799", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"3799\"" ], "answer": [ "5" ] }, { "key": "87d8d820fb592e6d775688ce8e9e1e64", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 14, 0, "EMERGENCY ROOM ADMIT" ], [ 2, 3, 0, "Arthrocentesis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients were admitted in emergency room for arthrocentesis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"EMERGENCY ROOM ADMIT\" AND PROCEDURES.\"SHORT_TITLE\" = \"Arthrocentesis\"", "question_refine_tok": [ "what", "number", "of", "patients", "were", "admitted", "in", "emergency", "room", "for", "arthrocentesis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"EMERGENCY", "ROOM", "ADMIT\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Arthrocentesis\"" ], "answer": [ "156" ] }, { "key": "abc509430b1d8d81c516286d740587c4", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SNF" ], [ 0, 16, 0, "HYPOXIA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients discharged to snf had hypoxia primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SNF\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPOXIA\"", "question_refine_tok": [ "how", "many", "patients", "discharged", "to", "snf", "had", "hypoxia", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SNF\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPOXIA\"" ], "answer": [ "25" ] }, { "key": "a772fe669af1ccf30732303ee43d3e8e", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SNF" ], [ 0, 16, 0, "ABDOMINAL PAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients with abdominal pain as their primary disease who were discharged to snf?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SNF\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"ABDOMINAL PAIN\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "with", "abdominal", "pain", "as", "their", "primary", "disease", "who", "were", "discharged", "to", "snf", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SNF\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ABDOMINAL", "PAIN\"" ], "answer": [ "98" ] }, { "key": "a684318d4cd02c2bb51bcd7d668f7cc9", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SNF" ], [ 0, 16, 0, "COPD EXACERBATION" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients with copd exacerbation primary disease who have been discharged to skilled nursing facility.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SNF\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"COPD EXACERBATION\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "with", "copd", "exacerbation", "primary", "disease", "who", "have", "been", "discharged", "to", "skilled", "nursing", "facility", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SNF\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"COPD", "EXACERBATION\"" ], "answer": [ "11" ] }, { "key": "1042fd78503d5845278fe1b06f681b2a", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "DISCH-TRAN TO PSYCH HOSP" ], [ 0, 16, 0, "RUQ PAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients discharge location is disch-tran to psych hosp and primary diagnosis is ruq pain?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISCH-TRAN TO PSYCH HOSP\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"RUQ PAIN\"", "question_refine_tok": [ "How", "many", "patients", "discharge", "location", "is", "disch-tran", "to", "psych", "hosp", "and", "primary", "diagnosis", "is", "ruq", "pain", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISCH-TRAN", "TO", "PSYCH", "HOSP\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"RUQ", "PAIN\"" ], "answer": [ "0" ] }, { "key": "00aeb9c1a1c154237887e8f3557273c0", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "HOME HEALTH CARE" ], [ 0, 4, 2, 27 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 27 year had a discharge locaiton home health?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME HEALTH CARE\" AND DEMOGRAPHIC.\"AGE\" < \"27\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "27", "year", "had", "a", "discharge", "locaiton", "home", "health", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME", "HEALTH", "CARE\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"27\"" ], "answer": [ "1599" ] }, { "key": "8c509179c969a1bd8f152a3124083f4f", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SHORT TERM HOSPITAL" ], [ 0, 4, 2, 64 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are discharged due to short term hospital and are under the age 64?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SHORT TERM HOSPITAL\" AND DEMOGRAPHIC.\"AGE\" < \"64\"", "question_refine_tok": [ "how", "many", "patients", "are", "discharged", "due", "to", "short", "term", "hospital", "and", "are", "under", "the", "age", "64", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SHORT", "TERM", "HOSPITAL\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"64\"" ], "answer": [ "1274" ] }, { "key": "0ce7ffc2b0832d683b0873a75983ee3b", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "HOME" ], [ 0, 10, 1, 20 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who were hospitalized for more than 20 days and were later discharged home?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"20\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "were", "hospitalized", "for", "more", "than", "20", "days", "and", "were", "later", "discharged", "home", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"20\"" ], "answer": [ "548" ] }, { "key": "0ee5fc38f74c5504524928e78a4f7e06", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "LONG TERM CARE HOSPITAL" ], [ 0, 18, 2, 2058 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients discharged to long term care hospital were born before 2058?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"LONG TERM CARE HOSPITAL\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2058\"", "question_refine_tok": [ "how", "many", "patients", "discharged", "to", "long", "term", "care", "hospital", "were", "born", "before", "2058", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"LONG", "TERM", "CARE", "HOSPITAL\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2058\"" ], "answer": [ "577" ] }, { "key": "0dc83447bac46f820dda4a5f23a89502", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "SHORT TERM HOSPITAL" ], [ 0, 18, 2, 2078 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients born before 2078 are discharged to short term hospital?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SHORT TERM HOSPITAL\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2078\"", "question_refine_tok": [ "how", "many", "patients", "born", "before", "2078", "are", "discharged", "to", "short", "term", "hospital", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SHORT", "TERM", "HOSPITAL\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2078\"" ], "answer": [ "175" ] }, { "key": "bb293bd6de2390ea5296f80618672cc4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 15, 0, "DISC-TRAN CANCER/CHLDRN H" ], [ 2, 2, 0, 8604 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients who were transfered to a cancer/chlidren hospital who had icd9 code 8604?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISC-TRAN CANCER/CHLDRN H\" AND PROCEDURES.\"ICD9_CODE\" = \"8604\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "who", "were", "transfered", "to", "a", "cancer/chlidren", "hospital", "who", "had", "icd9", "code", "8604", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISC-TRAN", "CANCER/CHLDRN", "H\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8604\"" ], "answer": [ "0" ] }, { "key": "032ce153e9f7fd9bb58d2381e7473a96", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 15, 0, "LONG TERM CARE HOSPITAL" ], [ 2, 2, 0, 9229 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients with icd9 code 9229 were discharged for long term care hospital?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"LONG TERM CARE HOSPITAL\" AND PROCEDURES.\"ICD9_CODE\" = \"9229\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "with", "icd9", "code", "9229", "were", "discharged", "for", "long", "term", "care", "hospital", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"LONG", "TERM", "CARE", "HOSPITAL\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9229\"" ], "answer": [ "16" ] }, { "key": "0bac3adfb0214ec24e28eb8a60c823a6", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 15, 0, "HOME" ], [ 2, 3, 0, "Contrast arteriogram-leg" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients are treated for contrast arteriogram-leg and have their discharge location as home?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\" AND PROCEDURES.\"SHORT_TITLE\" = \"Contrast arteriogram-leg\"", "question_refine_tok": [ "How", "many", "patients", "are", "treated", "for", "contrast", "arteriogram-leg", "and", "have", "their", "discharge", "location", "as", "home", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Contrast", "arteriogram-leg\"" ], "answer": [ "93" ] }, { "key": "04f6025046849b72bcf92ac808479159", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 15, 0, "HOME" ], [ 2, 3, 0, "Skin closure NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were discharged to home after skin closure nec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\" AND PROCEDURES.\"SHORT_TITLE\" = \"Skin closure NEC\"", "question_refine_tok": [ "how", "many", "patients", "were", "discharged", "to", "home", "after", "skin", "closure", "nec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Skin", "closure", "NEC\"" ], "answer": [ "234" ] }, { "key": "a84dd2cf945be1cd6281de749bbe8da4", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA" ], [ 0, 4, 2, 89 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients whose primary disease is coronary artery disease/coronary artery bypass graft/sda and who were aged below 89 years.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CORONARY ARTERY DISEASE\\CORONARY ARTERY BYPASS GRAFT /SDA\" AND DEMOGRAPHIC.\"AGE\" < \"89\"", "question_refine_tok": [ "give", " ", "the", "number", "of", "patients", "whose", "primary", "disease", "is", "coronary", "artery", "disease", "/", "coronary", "artery", "bypass", "graft", "/", "sda", "and", "who", "were", "aged", "below", "89", "years", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CORONARY", "ARTERY", "DISEASE\\CORONARY", "ARTERY", "BYPASS", "GRAFT", "/SDA\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"89\"" ], "answer": [ "579" ] }, { "key": "8647b4ed3acbcdf65b6a3e4a003a5b5b", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "FEMORAL ARTERY THROMBOSIS" ], [ 0, 4, 2, 89 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients less than 89 years who are suffering from femoral artery thrombosis primaray disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"FEMORAL ARTERY THROMBOSIS\" AND DEMOGRAPHIC.\"AGE\" < \"89\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "less", "than", "89", "years", "who", "are", "suffering", "from", "femoral", "artery", "thrombosis", "primaray", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"FEMORAL", "ARTERY", "THROMBOSIS\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"89\"" ], "answer": [ "1" ] }, { "key": "aafae9c30494946bbd7ac56453a627b2", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "OVERDOSE" ], [ 0, 4, 2, 50 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with primary disease overdose were less than 50 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"OVERDOSE\" AND DEMOGRAPHIC.\"AGE\" < \"50\"", "question_refine_tok": [ "how", "many", "patients", "with", "primary", "disease", "overdose", "were", "less", "than", "50", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"OVERDOSE\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"50\"" ], "answer": [ "162" ] }, { "key": "03e1872fa9f2244d449f2a0055cc0b8e", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "UPPER GI BLEED" ], [ 0, 4, 2, 51 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients less than 51 years who have upper gi bleed primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"UPPER GI BLEED\" AND DEMOGRAPHIC.\"AGE\" < \"51\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "less", "than", "51", "years", "who", "have", "upper", "gi", "bleed", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"UPPER", "GI", "BLEED\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"51\"" ], "answer": [ "106" ] }, { "key": "06e87f96c060a82f8f490899e8cd2b2e", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "ACIDOSIS" ], [ 0, 4, 2, 79 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with primary disease acidosis and are below 79 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"ACIDOSIS\" AND DEMOGRAPHIC.\"AGE\" < \"79\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "primary", "disease", "acidosis", "and", "are", "below", "79", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"ACIDOSIS\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"79\"" ], "answer": [ "7" ] }, { "key": "884dc26a6654afe0e49736753edf0841", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "STEMI" ], [ 0, 4, 2, 20 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients younger than 20 years who have stemi primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"STEMI\" AND DEMOGRAPHIC.\"AGE\" < \"20\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "younger", "than", "20", "years", "who", "have", "stemi", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"STEMI\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"20\"" ], "answer": [ "0" ] }, { "key": "9567d248d6d501760e7ebd8b722cb088", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CELO-VESSICLE FISTULA" ], [ 0, 4, 2, 27 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients who are aged below 27 years had celo-vessicle fistula as the primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CELO-VESSICLE FISTULA\" AND DEMOGRAPHIC.\"AGE\" < \"27\"", "question_refine_tok": [ "how", "many", "patients", "who", "are", "aged", "below", "27", "years", "had", "celo", "-", "vessicle", "fistula", "as", "the", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CELO-VESSICLE", "FISTULA\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"27\"" ], "answer": [ "0" ] }, { "key": "80aa8850eba943696abe768a98fb73a3", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SQUAMOUS CELL CARCINOMA ORAL TONGUE/SDA" ], [ 0, 4, 2, 54 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients who are less than 54 years and have squamous cell carcinoma of oral tongue/sda.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SQUAMOUS CELL CARCINOMA ORAL TONGUE/SDA\" AND DEMOGRAPHIC.\"AGE\" < \"54\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "who", "are", "less", "than", "54", "years", "and", "have", "squamous", "cell", "carcinoma", "of", "oral", "tongue", "/", "sda", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SQUAMOUS", "CELL", "CARCINOMA", "ORAL", "TONGUE/SDA\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"54\"" ], "answer": [ "0" ] }, { "key": "871de8f4f83e7d3c523502445f3264de", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "HYPERGLYCEMIA" ], [ 0, 4, 2, 56 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients less than 56 years who have hyperglycemia primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPERGLYCEMIA\" AND DEMOGRAPHIC.\"AGE\" < \"56\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "less", "than", "56", "years", "who", "have", "hyperglycemia", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPERGLYCEMIA\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"56\"" ], "answer": [ "30" ] }, { "key": "804d61ea251779e8ec9d8f758e134a6d", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CELO-VESSICLE FISTULA" ], [ 0, 4, 2, 45 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 45 years had celo-vessicle fistula?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CELO-VESSICLE FISTULA\" AND DEMOGRAPHIC.\"AGE\" < \"45\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "45", "years", "had", "celo", "-", "vessicle", "fistula", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CELO-VESSICLE", "FISTULA\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"45\"" ], "answer": [ "0" ] }, { "key": "95729f0dfd914c9590bd8c1e29b1c9b9", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "LIVER TRANSPLANT" ], [ 0, 4, 2, 85 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients less than 85 years who have liver transplant as their primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"LIVER TRANSPLANT\" AND DEMOGRAPHIC.\"AGE\" < \"85\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "less", "than", "85", "years", "who", "have", "liver", "transplant", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"LIVER", "TRANSPLANT\"", "AND", "DEMOGRAPHIC.\"AGE\"", "<", "\"85\"" ], "answer": [ "20" ] }, { "key": "02c3ab63ce702e2e06cc08185f7d8025", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CONGESTIVE HEART FAILURE" ], [ 0, 10, 1, 13 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with congestive heart failure stayed in the hospital for more than 13 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CONGESTIVE HEART FAILURE\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"13\"", "question_refine_tok": [ "how", "many", "patients", "with", "congestive", "heart", "failure", "stayed", "in", "the", "hospital", "for", "more", "than", "13", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CONGESTIVE", "HEART", "FAILURE\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"13\"" ], "answer": [ "205" ] }, { "key": "06028c07e07182afdd1e9c62a1543c56", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "NEWBORN" ], [ 0, 10, 1, 29 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients diagnosed as newborn stayed in the hospital for more than 29 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"NEWBORN\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"29\"", "question_refine_tok": [ "How", "many", "patients", "diagnosed", "as", "newborn", "stayed", "in", "the", "hospital", "for", "more", "than", "29", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"29\"" ], "answer": [ "809" ] }, { "key": "88d8bcd981e64d9f4392bbe153ef2896", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CHEST PAIN" ], [ 0, 18, 2, 1837 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients diagnosed primarily for chest pain were born before the year 1837?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CHEST PAIN\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"1837\"", "question_refine_tok": [ "what", "number", "of", "patients", "diagnosed", "primarily", "for", "chest", "pain", "were", "born", "before", "the", "year", "1837", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CHEST", "PAIN\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1837\"" ], "answer": [ "18" ] }, { "key": "83587912882a86d7dca07f32f4e56949", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CEREBRAL ANEURYSM/SDA" ], [ 0, 18, 2, 2126 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with cerebral aneurysm/sda as their primary disease were born before the year 2126?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CEREBRAL ANEURYSM/SDA\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2126\"", "question_refine_tok": [ "How", "many", "patients", "with", "cerebral", "aneurysm/sda", "as", "their", "primary", "disease", "were", "born", "before", "the", "year", "2126", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CEREBRAL", "ANEURYSM/SDA\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2126\"" ], "answer": [ "42" ] }, { "key": "8b3f3fcfe4d5fcfe1568a36890cfc580", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "UPPER GI BLEED" ], [ 0, 18, 2, 2076 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of patients with upper gi bleed who were born before 2076?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"UPPER GI BLEED\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2076\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "patients", "with", "upper", "gi", "bleed", "who", "were", "born", "before", "2076", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"UPPER", "GI", "BLEED\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2076\"" ], "answer": [ "234" ] }, { "key": "0d83c52fc4822a82a4ebf2428e18c0fa", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "HYPERGLYCEMIA" ], [ 0, 18, 2, 2167 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients born before the year 2167 were primarily diagnosed for hyperglycemia?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPERGLYCEMIA\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2167\"", "question_refine_tok": [ "how", "many", "patients", "born", "before", "the", "year", "2167", "were", "primarily", "diagnosed", "for", "hyperglycemia", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPERGLYCEMIA\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2167\"" ], "answer": [ "59" ] }, { "key": "0a884e78aa02a74579bcb18489ef1b06", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "S/P HANGING" ], [ 0, 18, 2, 2123 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Provide the number of patients born before 2123 who have s/p hanging as their primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"S/P HANGING\" AND DEMOGRAPHIC.\"DOB_YEAR\" < \"2123\"", "question_refine_tok": [ "Provide", "the", "number", "of", "patients", "born", "before", "2123", "who", "have", "s/p", "hanging", "as", "their", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"S/P", "HANGING\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2123\"" ], "answer": [ "6" ] }, { "key": "0a3dc5c21d8ffc3c23a92fb8702dc0d3", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "COPD EXACERBATION" ], [ 0, 19, 4, 2158.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find out the number of patients with copd exacerbation as their primary disease who died in or before 2158.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"COPD EXACERBATION\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2158.0\"", "question_refine_tok": [ "Find", "out", "the", "number", "of", "patients", "with", "copd", "exacerbation", "as", "their", "primary", "disease", "who", "died", "in", "or", "before", "2158", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"COPD", "EXACERBATION\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2158.0\"" ], "answer": [ "25" ] }, { "key": "072772efb616023608b5eb3921bc36bb", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "NEWBORN" ], [ 0, 19, 4, 2122.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the newborn patients died in or before the year 2122?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"NEWBORN\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2122.0\"", "question_refine_tok": [ "How", "many", "of", "the", "newborn", "patients", "died", "in", "or", "before", "the", "year", "2122", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"NEWBORN\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2122.0\"" ], "answer": [ "13" ] }, { "key": "844e56db40ebdffe688da456b2860342", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "LEFT INTERNAL JUGULAR VEIN THROMBOSIS;LEFT ARM EDEMA" ], [ 0, 19, 4, 2179.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Provide me the number of patients born in or before 2179 who have left internal jugular vein thrombosis; left arm edema primary disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"LEFT INTERNAL JUGULAR VEIN THROMBOSIS;LEFT ARM EDEMA\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2179.0\"", "question_refine_tok": [ "Provide", "me", "the", "number", "of", "patients", "born", "in", "or", "before", "2179", "who", "have", "left", "internal", "jugular", "vein", "thrombosis", ";", "left", "arm", "edema", "primary", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"LEFT", "INTERNAL", "JUGULAR", "VEIN", "THROMBOSIS;LEFT", "ARM", "EDEMA\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2179.0\"" ], "answer": [ "1" ] }, { "key": "867a534f015f32479c12b96fb31876a8", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "FEMORAL ARTERY THROMBOSIS" ], [ 0, 19, 4, 2154.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients who passed away in or before the year 2154 had femoral artery thrombosis.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"FEMORAL ARTERY THROMBOSIS\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2154.0\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "who", "passed", "away", "in", "or", "before", "the", "year", "2154", "had", "femoral", "artery", "thrombosis", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"FEMORAL", "ARTERY", "THROMBOSIS\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2154.0\"" ], "answer": [ "0" ] }, { "key": "0be50e80b5be87e0c4395c5608c9d39f", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SYNCOPE;TELEMETRY" ], [ 0, 19, 4, 2158.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Look for the number of patients with the primary disease syncope telemetry who died in or before 2158.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SYNCOPE;TELEMETRY\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2158.0\"", "question_refine_tok": [ "Look", "for", "the", "number", "of", "patients", "with", "the", "primary", "disease", "syncope", "telemetry", "who", "died", "in", "or", "before", "2158", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SYNCOPE;TELEMETRY\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2158.0\"" ], "answer": [ "20" ] }, { "key": "009aa4759afa218e175bb02341f17f70", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SYNCOPE;TELEMETRY" ], [ 0, 19, 4, 2179.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients whose primary disease was syncope;telemetry died in or before year 2179?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SYNCOPE;TELEMETRY\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2179.0\"", "question_refine_tok": [ "how", "many", "patients", "whose", "primary", "disease", "was", "syncope;telemetry", "died", "in", "or", "before", "year", "2179", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SYNCOPE;TELEMETRY\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2179.0\"" ], "answer": [ "41" ] }, { "key": "09984e6569fc8c58f0b5fc16e38e3dd6", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CONGESTIVE HEART FAILURE" ], [ 0, 19, 4, 2115.0 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Among patients who died in or before the year 2115, how many had congestive heart failure as primary disease?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CONGESTIVE HEART FAILURE\" AND DEMOGRAPHIC.\"DOD_YEAR\" <= \"2115.0\"", "question_refine_tok": [ "Among", "patients", "who", "died", "in", "or", "before", "the", "year", "2115", ",", "how", "many", "had", "congestive", "heart", "failure", "as", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CONGESTIVE", "HEART", "FAILURE\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2115.0\"" ], "answer": [ "57" ] }, { "key": "a75e1aa8b393a93c5a51986d68dc15a6", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CEREBRAL ANEURYSM/SDA" ], [ 0, 22, 2, 2200 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give the number of patients whose primary disease is cerebral aneurysm/sda and were admitted before the year 2200.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CEREBRAL ANEURYSM/SDA\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2200\"", "question_refine_tok": [ "Give", "the", "number", "of", "patients", "whose", "primary", "disease", "is", "cerebral", "aneurysm/sda", "and", "were", "admitted", "before", "the", "year", "2200", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CEREBRAL", "ANEURYSM/SDA\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2200\"" ], "answer": [ "55" ] }, { "key": "9bcb8fd398ac5be28718b9fb311c354e", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "CEREBRAL ANEURYSM/SDA" ], [ 0, 22, 2, 2173 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Among patients with cerebral aneurysm/sda as their primary disease, calculate the total number of those born before the year 2173.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"CEREBRAL ANEURYSM/SDA\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2173\"", "question_refine_tok": [ "Among", "patients", "with", "cerebral", "aneurysm/sda", "as", "their", "primary", "disease", ",", "calculate", "the", "total", "number", "of", "those", "born", "before", "the", "year", "2173", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CEREBRAL", "ANEURYSM/SDA\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2173\"" ], "answer": [ "36" ] }, { "key": "8404478c3a267757514125bb690cca23", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "RUQ PAIN" ], [ 0, 22, 2, 2146 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted after year 2146 had ruq pain?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"RUQ PAIN\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2146\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "after", "year", "2146", "had", "ruq", "pain", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"RUQ", "PAIN\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2146\"" ], "answer": [ "3" ] }, { "key": "9e3324b9e4876efdcca381640e060400", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "SEPSIS" ], [ 0, 22, 2, 2187 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with primary disease sepsis and admitted before the year 2187?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SEPSIS\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2187\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "primary", "disease", "sepsis", "and", "admitted", "before", "the", "year", "2187", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SEPSIS\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2187\"" ], "answer": [ "954" ] }, { "key": "ac913a6b3e1ac8c1578d0b6f9f3788f8", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 16, 0, "SEPSIS" ], [ 2, 2, 0, 9960 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients with sepsis as primary disease had icd9 code 9960?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"SEPSIS\" AND PROCEDURES.\"ICD9_CODE\" = \"9960\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "with", "sepsis", "as", "primary", "disease", "had", "icd9", "code", "9960", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SEPSIS\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9960\"" ], "answer": [ "19" ] }, { "key": "10b32134252a1f771d87a3886090cfb9", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 16, 0, "GANGRENE" ], [ 3, 6, 0, "PO/NG" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients with gangrene as primary disease received po/ng therapy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GANGRENE\" AND PRESCRIPTIONS.\"ROUTE\" = \"PO/NG\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "with", "gangrene", "as", "primary", "disease", "received", "po", "/", "ng", "therapy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GANGRENE\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"PO/NG\"" ], "answer": [ "6" ] }, { "key": "82eff879cba7ff7e99b9425a450d16e3", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 16, 0, "NEWBORN" ], [ 4, 7, 0, "Pleural" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with newborn primary disease who had pleural lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"NEWBORN\" AND LAB.\"FLUID\" = \"Pleural\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "newborn", "primary", "disease", "who", "had", "pleural", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"NEWBORN\"", "AND", "LAB.\"FLUID\"", "=", "\"Pleural\"" ], "answer": [ "8" ] }, { "key": "96a65966374941a10a74e3436a43aadd", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 16, 0, "NEWBORN" ], [ 4, 7, 0, "Blood" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Count the number of newborn patients whose lab test fluid is blood", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"NEWBORN\" AND LAB.\"FLUID\" = \"Blood\"", "question_refine_tok": [ "Count", "the", "number", "of", "newborn", "patients", "whose", "lab", "test", "fluid", "is", "blood" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"NEWBORN\"", "AND", "LAB.\"FLUID\"", "=", "\"Blood\"" ], "answer": [ "7577" ] }, { "key": "84cdf16ce9ced3807228663939f35f2c", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 16, 0, "S/P FALL" ], [ 4, 7, 0, "Ascites" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with s/p fall as their primary disease had ascitic fluid lab test?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"S/P FALL\" AND LAB.\"FLUID\" = \"Ascites\"", "question_refine_tok": [ "How", "many", "patients", "with", "s/p", "fall", "as", "their", "primary", "disease", "had", "ascitic", "fluid", "lab", "test", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"S/P", "FALL\"", "AND", "LAB.\"FLUID\"", "=", "\"Ascites\"" ], "answer": [ "3" ] }, { "key": "09d912da854c13b02cbfc618578853a1", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 36 ], [ 0, 10, 1, 14 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 36 years have stayed in the hospital for more than 14 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"36\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"14\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "36", "years", "have", "stayed", "in", "the", "hospital", "for", "more", "than", "14", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"36\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"14\"" ], "answer": [ "2007" ] }, { "key": "aa8fea62a1049793a19a00bdb81275c3", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 24 ], [ 0, 10, 1, 11 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients less than 24 years of age were hospitalized for more than 11 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"24\" AND DEMOGRAPHIC.\"DAYS_STAY\" > \"11\"", "question_refine_tok": [ "how", "many", "patients", "less", "than", "24", "years", "of", "age", "were", "hospitalized", "for", "more", "than", "11", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"24\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"11\"" ], "answer": [ "1942" ] }, { "key": "088bfde60ac975ad3850f459ad47cfef", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 48 ], [ 0, 22, 2, 2138 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "bring the number of patients younger than 48 years who were admitted before 2138.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"48\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2138\"", "question_refine_tok": [ "bring", "the", "number", "of", "patients", "younger", "than", "48", "years", "who", "were", "admitted", "before", "2138", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"48\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2138\"" ], "answer": [ "5643" ] }, { "key": "aa9d08c1a7ed4cdd6bf2b289a54a6cc1", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 49 ], [ 0, 22, 2, 2198 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are below 49 years of age and admitted under the year 2198?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"49\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2198\"", "question_refine_tok": [ "how", "many", "patients", "are", "below", "49", "years", "of", "age", "and", "admitted", "under", "the", "year", "2198", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"49\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2198\"" ], "answer": [ "14882" ] }, { "key": "87d2e624239a23f89bfbb0fcc952c3f7", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 2, 58 ], [ 0, 22, 2, 2107 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients less than 58 years who were admitted to hospital before 2107.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" < \"58\" AND DEMOGRAPHIC.\"ADMITYEAR\" < \"2107\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "less", "than", "58", "years", "who", "were", "admitted", "to", "hospital", "before", "2107", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"58\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2107\"" ], "answer": [ "1368" ] }, { "key": "bb7026d14a730065b59a010540dc5904", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 31 ], [ 1, 2, 0, "V140" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide me the number of patients younger than 31 years with diagnosis icd9 code v140.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"31\" AND DIAGNOSES.\"ICD9_CODE\" = \"V140\"", "question_refine_tok": [ "provide", "me", "the", "number", "of", "patients", "younger", "than", "31", "years", "with", "diagnosis", "icd9", "code", "v140", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"31\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"V140\"" ], "answer": [ "2" ] }, { "key": "833b7bc32d5e845e94f9a99e0700998d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 50 ], [ 1, 2, 0, "32723" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who have diagnoses icd9 code 32723 and are less than 50 years of age.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"50\" AND DIAGNOSES.\"ICD9_CODE\" = \"32723\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "have", "diagnoses", "icd9", "code", "32723", "and", "are", "less", "than", "50", "years", "of", "age", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"50\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"32723\"" ], "answer": [ "285" ] }, { "key": "a71971647b210e967ef858d5cdc770bd", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 31 ], [ 1, 2, 0, "70721" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients younger than 31 with a diagnoses icd9 code 70721?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"31\" AND DIAGNOSES.\"ICD9_CODE\" = \"70721\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "younger", "than", "31", "with", "a", "diagnoses", "icd9", "code", "70721", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"31\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"70721\"" ], "answer": [ "2" ] }, { "key": "06fbe5c6c99bc3f7cd0a53249b2de3dd", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 43 ], [ 1, 3, 0, "Prob-head/neck/trunk NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients aged below 43 years old are diagnosed with prob-head/neck/trunk nos?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"43\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Prob-head/neck/trunk NOS\"", "question_refine_tok": [ "How", "many", "patients", "aged", "below", "43", "years", "old", "are", "diagnosed", "with", "prob-head/neck/trunk", "nos", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Prob-head/neck/trunk", "NOS\"" ], "answer": [ "0" ] }, { "key": "0253fe7f06bcba29a5a6dc7342278218", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 4, 2, 50 ], [ 1, 4, 0, "Acute vascular insufficiency of intestine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients with acute vascular insufficiency of intestine who are less than 50 years of age?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"50\" AND DIAGNOSES.\"LONG_TITLE\" = \"Acute vascular insufficiency of intestine\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "with", "acute", "vascular", "insufficiency", "of", "intestine", "who", "are", "less", "than", "50", "years", "of", "age", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"50\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Acute", "vascular", "insufficiency", "of", "intestine\"" ], "answer": [ "68" ] }, { "key": "a59ccd6f537695b771a09217857ef583", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 64 ], [ 2, 2, 0, 4311 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find the patients aged less than 64 years old with procedure icd9 code 4311.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"64\" AND PROCEDURES.\"ICD9_CODE\" = \"4311\"", "question_refine_tok": [ "Find", "the", "patients", "aged", "less", "than", "64", "years", "old", "with", "procedure", "icd9", "code", "4311", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"64\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4311\"" ], "answer": [ "570" ] }, { "key": "827f8123c25ca3f714d96faaa00d1b84", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 77 ], [ 2, 2, 0, 4632 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many pateints aged below 77 had undergone the procedure with icd9 code 4632?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"77\" AND PROCEDURES.\"ICD9_CODE\" = \"4632\"", "question_refine_tok": [ "How", "many", "pateints", "aged", "below", "77", "had", "undergone", "the", "procedure", "with", "icd9", "code", "4632", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"77\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4632\"" ], "answer": [ "84" ] }, { "key": "0c28285998ef7cdb124d0fb46b890993", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 61 ], [ 2, 2, 0, 8619 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are under 61 years of age have procedure icd9 code 8619?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"61\" AND PROCEDURES.\"ICD9_CODE\" = \"8619\"", "question_refine_tok": [ "how", "many", "patients", "are", "under", "61", "years", "of", "age", "have", "procedure", "icd9", "code", "8619", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"61\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"8619\"" ], "answer": [ "0" ] }, { "key": "043f05af1ac261f3d6e8467b8a421629", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 77 ], [ 2, 3, 0, "Percu endosc gastrostomy" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients below 77 years of age have undergone the procedure with short title percu endosc gastrostomy?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"77\" AND PROCEDURES.\"SHORT_TITLE\" = \"Percu endosc gastrostomy\"", "question_refine_tok": [ "how", "many", "patients", "below", "77", "years", "of", "age", "have", "undergone", "the", "procedure", "with", "short", "title", "percu", "endosc", "gastrostomy", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"77\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Percu", "endosc", "gastrostomy\"" ], "answer": [ "989" ] }, { "key": "9b8c4d8881a36278282467b567588435", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 70 ], [ 2, 3, 0, "Percutan liver aspirat" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find the number of patients less than 70 years of age who had a percutaneous liver aspiration procedure.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"70\" AND PROCEDURES.\"SHORT_TITLE\" = \"Percutan liver aspirat\"", "question_refine_tok": [ "Find", "the", "number", "of", "patients", "less", "than", "70", "years", "of", "age", "who", "had", "a", "percutaneous", "liver", "aspiration", "procedure", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"70\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Percutan", "liver", "aspirat\"" ], "answer": [ "34" ] }, { "key": "87828dccf954b593285952f9e05285b4", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 61 ], [ 2, 4, 0, "Percutaneous abdominal drainage" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of the total number of patients with percutaneous abdominal drainage, how many of them were aged below 61?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"61\" AND PROCEDURES.\"LONG_TITLE\" = \"Percutaneous abdominal drainage\"", "question_refine_tok": [ "Out", "of", "the", "total", "number", "of", "patients", "with", "percutaneous", "abdominal", "drainage", ",", "how", "many", "of", "them", "were", "aged", "below", "61", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"61\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Percutaneous", "abdominal", "drainage\"" ], "answer": [ "715" ] }, { "key": "085c097c30ee27375d301af1413d2f6a", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 4, 2, 45 ], [ 2, 4, 0, "Endoscopic insertion of stent (tube) into bile duct" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "out of total number of patients who had endoscopic insertion of stent (tube) into bile duct, calculate the number of those aged below 45", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"45\" AND PROCEDURES.\"LONG_TITLE\" = \"Endoscopic insertion of stent (tube) into bile duct\"", "question_refine_tok": [ "out", "of", "total", "number", "of", "patients", "who", "had", "endoscopic", "insertion", "of", "stent", "(", "tube", ")", "into", "bile", "duct", ",", "calculate", "the", "number", "of", "those", "aged", "below", "45" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"45\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Endoscopic", "insertion", "of", "stent", "(tube)", "into", "bile", "duct\"" ], "answer": [ "29" ] }, { "key": "804ca29d119c7ae443c69c0e0f4bee74", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 51 ], [ 3, 4, 0, "Metoprolol Tartrate" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what number of patients under the age of 51 were given the drug metoprolol tartrate?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"51\" AND PRESCRIPTIONS.\"DRUG\" = \"Metoprolol Tartrate\"", "question_refine_tok": [ "what", "number", "of", "patients", "under", "the", "age", "of", "51", "were", "given", "the", "drug", "metoprolol", "tartrate", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"51\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Metoprolol", "Tartrate\"" ], "answer": [ "1136" ] }, { "key": "9c05a565ee5d9c64aaf12d921d02d4c9", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 72 ], [ 3, 4, 0, "Pravastatin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among the patients who were treated with pravastatin, how many of them were aged below 72?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"72\" AND PRESCRIPTIONS.\"DRUG\" = \"Pravastatin\"", "question_refine_tok": [ "among", "the", "patients", "who", "were", "treated", "with", "pravastatin", ",", "how", "many", "of", "them", "were", "aged", "below", "72", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"72\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Pravastatin\"" ], "answer": [ "555" ] }, { "key": "969b372fc589d8b0734db3c70b6eb4fc", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 81 ], [ 3, 4, 0, "Critic-Aid Clear AF" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients less than 81 years who were prescribed critic-aid clear af drug.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"81\" AND PRESCRIPTIONS.\"DRUG\" = \"Critic-Aid Clear AF\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "less", "than", "81", "years", "who", "were", "prescribed", "critic", "-", "aid", "clear", "af", "drug", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"81\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Critic-Aid", "Clear", "AF\"" ], "answer": [ "3" ] }, { "key": "aa253b41030e5c298e4ceb1c7aef9028", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 56 ], [ 3, 4, 0, "Voriconazole" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients below the age of 56 were given voriconazole?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"56\" AND PRESCRIPTIONS.\"DRUG\" = \"Voriconazole\"", "question_refine_tok": [ "how", "many", "patients", "below", "the", "age", "of", "56", "were", "given", "voriconazole", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"56\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Voriconazole\"" ], "answer": [ "125" ] }, { "key": "0850adcaf50adb3f7a89eb56b2f1104a", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 59 ], [ 3, 5, 0, "TACRSUSP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients less than 59 years who have drug code tacrsusp.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"59\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"TACRSUSP\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "less", "than", "59", "years", "who", "have", "drug", "code", "tacrsusp", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"59\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"TACRSUSP\"" ], "answer": [ "213" ] }, { "key": "84d545e92b1a3cabb755523ca1f95bd4", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 62 ], [ 3, 5, 0, "MORP2I" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Show the number of patients who are less than 60 years of age and have the drug code morp2i.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"62\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"MORP2I\"", "question_refine_tok": [ "Show", "the", "number", "of", "patients", "who", "are", "less", "than", "60", "years", "of", "age", "and", "have", "the", "drug", "code", "morp2i", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"62\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"MORP2I\"" ], "answer": [ "5465" ] }, { "key": "ada73b5096f28b24b79cb30cc513b751", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 43 ], [ 3, 5, 0, "HEPBASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who are less than 43 years of age and their drug code is hepbase.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"43\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"HEPBASE\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "are", "less", "than", "43", "years", "of", "age", "and", "their", "drug", "code", "is", "hepbase", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"HEPBASE\"" ], "answer": [ "526" ] }, { "key": "9b2fd5dc21a28a480871e22effce3a33", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 43 ], [ 3, 6, 0, "DIALYS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 43 year had the drug route dialysis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"43\" AND PRESCRIPTIONS.\"ROUTE\" = \"DIALYS\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "43", "year", "had", "the", "drug", "route", "dialysis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"DIALYS\"" ], "answer": [ "103" ] }, { "key": "8436a88896b36ac22a1de03c526e42a1", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 31 ], [ 3, 6, 0, "SC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients aged below 31 years had sc as the drug route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"31\" AND PRESCRIPTIONS.\"ROUTE\" = \"SC\"", "question_refine_tok": [ "how", "many", "patients", "aged", "below", "31", "years", "had", "sc", "as", "the", "drug", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"31\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"SC\"" ], "answer": [ "1873" ] }, { "key": "97a709030d581ebe37d34fa3d33e7349", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 83 ], [ 3, 6, 0, "DIALYS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients whose drug route is dialys and age under 83 years.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"83\" AND PRESCRIPTIONS.\"ROUTE\" = \"DIALYS\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "whose", "drug", "route", "is", "dialys", "and", "age", "under", "83", "years", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"83\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"DIALYS\"" ], "answer": [ "938" ] }, { "key": "8a54ab08858b40c96c758520cd5309ac", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 58 ], [ 3, 6, 0, "NEB" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients less than 58 years on neb route of drug administration.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"58\" AND PRESCRIPTIONS.\"ROUTE\" = \"NEB\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "less", "than", "58", "years", "on", "neb", "route", "of", "drug", "administration", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"58\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"NEB\"" ], "answer": [ "283" ] }, { "key": "a098490776ade92f9d0c247ccfb1eb73", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 4, 2, 70 ], [ 3, 6, 0, "INHALATION" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "get me the number of patients less than 70 years who take drug via inhalation.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"70\" AND PRESCRIPTIONS.\"ROUTE\" = \"INHALATION\"", "question_refine_tok": [ "get", "me", "the", "number", "of", "patients", "less", "than", "70", "years", "who", "take", "drug", "via", "inhalation", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"70\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"INHALATION\"" ], "answer": [ "72" ] }, { "key": "82fe69e357204798f6fa15a9b66761ff", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 70 ], [ 4, 7, 0, "Cerebrospinal Fluid (CSF)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients younger than 70 years have got the cerebrospinal fluid (csf) lab test done?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"70\" AND LAB.\"FLUID\" = \"Cerebrospinal Fluid (CSF)\"", "question_refine_tok": [ "how", "many", "patients", "younger", "than", "70", "years", "have", "got", "the", "cerebrospinal", "fluid", "(", "csf", ")", "lab", "test", "done", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"70\"", "AND", "LAB.\"FLUID\"", "=", "\"Cerebrospinal", "Fluid", "(CSF)\"" ], "answer": [ "1988" ] }, { "key": "0b478e939f03f13b46bdf4e3d449a6ae", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 41 ], [ 4, 7, 0, "Joint Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are below 41 years of age and tested with joint fluid in lab?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"41\" AND LAB.\"FLUID\" = \"Joint Fluid\"", "question_refine_tok": [ "how", "many", "patients", "are", "below", "41", "years", "of", "age", "and", "tested", "with", "joint", "fluid", "in", "lab", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"41\"", "AND", "LAB.\"FLUID\"", "=", "\"Joint", "Fluid\"" ], "answer": [ "28" ] }, { "key": "85c64a20b4ee9ba7566059a53b6fcdb3", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 41 ], [ 4, 7, 0, "Blood" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Bring the list of patients younger than 41 years of age who had a blood lab test done.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"41\" AND LAB.\"FLUID\" = \"Blood\"", "question_refine_tok": [ "Bring", "the", "list", "of", "patients", "younger", "than", "41", "years", "of", "age", "who", "had", "a", "blood", "lab", "test", "done", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"41\"", "AND", "LAB.\"FLUID\"", "=", "\"Blood\"" ], "answer": [ "11962" ] }, { "key": "93df86655ac888bcf620e06e7b7e5f80", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 43 ], [ 4, 7, 0, "Ascites" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among patients aged below 43, how many of them had a lab test for ascites?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"43\" AND LAB.\"FLUID\" = \"Ascites\"", "question_refine_tok": [ "among", "patients", "aged", "below", "43", ",", "how", "many", "of", "them", "had", "a", "lab", "test", "for", "ascites", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"", "AND", "LAB.\"FLUID\"", "=", "\"Ascites\"" ], "answer": [ "189" ] }, { "key": "a6ebd440c78317b1d6a84ca93eabf13e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 43 ], [ 4, 7, 0, "Pleural" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients below 43 years of age tested in lab for pleural fluid?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"43\" AND LAB.\"FLUID\" = \"Pleural\"", "question_refine_tok": [ "how", "many", "patients", "below", "43", "years", "of", "age", "tested", "in", "lab", "for", "pleural", "fluid", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"43\"", "AND", "LAB.\"FLUID\"", "=", "\"Pleural\"" ], "answer": [ "144" ] }, { "key": "aa94e974b8ee66950b649251ba9090dc", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 31 ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are less than 31 year old with a chemistry lab test category?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"31\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "how", "many", "patients", "are", "less", "than", "31", "year", "old", "with", "a", "chemistry", "lab", "test", "category", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"31\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "8679" ] }, { "key": "926a345db323823260da99f203e0010e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 41 ], [ 4, 8, 0, "Blood Gas" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients who are below the age of 41 and lab test category is blood gas.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"41\" AND LAB.\"CATEGORY\" = \"Blood Gas\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "who", "are", "below", "the", "age", "of", "41", "and", "lab", "test", "category", "is", "blood", "gas", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"41\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Blood", "Gas\"" ], "answer": [ "5688" ] }, { "key": "86ed722adeb715c537f8251884abffca", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 4, 2, 61 ], [ 4, 8, 0, "Hematology" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "find the number of patients whose lab test category is hematology and age is under 61 years.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"AGE\" < \"61\" AND LAB.\"CATEGORY\" = \"Hematology\"", "question_refine_tok": [ "find", "the", "number", "of", "patients", "whose", "lab", "test", "category", "is", "hematology", "and", "age", "is", "under", "61", "years", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"AGE\"", "<", "\"61\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Hematology\"" ], "answer": [ "22171" ] }, { "key": "9dbca995af6b0989abc114cc3d1b3fb7", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 4 ], [ 1, 2, 0, "99681" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the nymber of patients with diagnosis icd9 code 99681 who stayed in hospital for more than 4 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"4\" AND DIAGNOSES.\"ICD9_CODE\" = \"99681\"", "question_refine_tok": [ "give", "me", "the", "nymber", "of", "patients", "with", "diagnosis", "icd9", "code", "99681", "who", "stayed", "in", "hospital", "for", "more", "than", "4", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"4\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"99681\"" ], "answer": [ "255" ] }, { "key": "0c8f33538cf6d53181d3b2f39f69baf8", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 34 ], [ 1, 2, 0, "317" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients with diagnoses icd9 code 317 who were admitted for more than 34 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"34\" AND DIAGNOSES.\"ICD9_CODE\" = \"317\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "with", "diagnoses", "icd9", "code", "317", "who", "were", "admitted", "for", "more", "than", "34", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"34\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"317\"" ], "answer": [ "2" ] }, { "key": "88af406053b45485750b8981010e88e9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 6 ], [ 1, 3, 0, "Orthostatic hypotension" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients stayed in hospital for more than 6 days and were diagnosed with orthostatic hypertension?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"6\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Orthostatic hypotension\"", "question_refine_tok": [ "how", "many", "patients", "stayed", "in", "hospital", "for", "more", "than", "6", "days", "and", "were", "diagnosed", "with", "orthostatic", "hypertension", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"6\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Orthostatic", "hypotension\"" ], "answer": [ "134" ] }, { "key": "a7f0f51a1b7298fc9b7c2f8214ee4b19", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 30 ], [ 1, 3, 0, "Chr diastolic hrt fail" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients diagnosed with chronic diastolic heart failure were hospitalized for more than 30 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"30\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Chr diastolic hrt fail\"", "question_refine_tok": [ "how", "many", "patients", "diagnosed", "with", "chronic", "diastolic", "heart", "failure", "were", "hospitalized", "for", "more", "than", "30", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"30\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Chr", "diastolic", "hrt", "fail\"" ], "answer": [ "33" ] }, { "key": "0b5fc111d80c2e60438458ddb5979cf1", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 10, 1, 5 ], [ 1, 3, 0, "Personality disorder NOS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "calculate the number of patients with personality disorder nos who had a hospital stay for more than 5 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"5\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Personality disorder NOS\"", "question_refine_tok": [ "calculate", "the", "number", "of", "patients", "with", "personality", "disorder", "nos", "who", "had", "a", "hospital", "stay", "for", "more", "than", "5", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"5\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Personality", "disorder", "NOS\"" ], "answer": [ "11" ] }, { "key": "0dd083c0247abcf28d92f74623eae302", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 10, 1, 3 ], [ 2, 2, 0, 5451 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients who stayed in the hospital for more than 3 days had procedure icd9 code 5451?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"3\" AND PROCEDURES.\"ICD9_CODE\" = \"5451\"", "question_refine_tok": [ "how", "many", "patients", "who", "stayed", "in", "the", "hospital", "for", "more", "than", "3", "days", "had", "procedure", "icd9", "code", "5451", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"3\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5451\"" ], "answer": [ "24" ] }, { "key": "86095463f2ab22007d32c028f0efe69c", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 10, 1, 1 ], [ 2, 2, 0, 5198 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted under procedure icd9 code 5198 stayed in the hospital for more than 1 day?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"1\" AND PROCEDURES.\"ICD9_CODE\" = \"5198\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "under", "procedure", "icd9", "code", "5198", "stayed", "in", "the", "hospital", "for", "more", "than", "1", "day", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"1\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5198\"" ], "answer": [ "147" ] }, { "key": "838ee5f862ddd3c0a19da04e62ab6735", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 5 ], [ 3, 3, 0, "ADDITIVE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the patients who are prescribed additive drugs that have stayed in the hospital for more than 5 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"5\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"ADDITIVE\"", "question_refine_tok": [ "Calculate", "the", "patients", "who", "are", "prescribed", "additive", "drugs", "that", "have", "stayed", "in", "the", "hospital", "for", "more", "than", "5", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"5\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"ADDITIVE\"" ], "answer": [ "3381" ] }, { "key": "b9d328373ac5aa2bb7d84ee3fa0cee44", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 9 ], [ 3, 4, 0, "Ibuprofen Suspension" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients stayed in hospital for more than 9 days and used the drug ibuprofen suspension?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"9\" AND PRESCRIPTIONS.\"DRUG\" = \"Ibuprofen Suspension\"", "question_refine_tok": [ "how", "many", "patients", "stayed", "in", "hospital", "for", "more", "than", "9", "days", "and", "used", "the", "drug", "ibuprofen", "suspension", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"9\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Ibuprofen", "Suspension\"" ], "answer": [ "278" ] }, { "key": "080127e8abd81701f88e49d4a966b56d", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 43 ], [ 3, 4, 0, "Alteplase (Catheter Clearance)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients on prescription of alteplase (catheter clearance) who had to stay for more than 43 days in hospital.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"43\" AND PRESCRIPTIONS.\"DRUG\" = \"Alteplase (Catheter Clearance)\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "on", "prescription", "of", "alteplase", "(", "catheter", "clearance", ")", "who", "had", "to", "stay", "for", "more", "than", "43", "days", "in", "hospital", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"43\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Alteplase", "(Catheter", "Clearance)\"" ], "answer": [ "358" ] }, { "key": "b9e6f14f784427e612f5e8259145fe67", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 10, 1, 34 ], [ 3, 4, 0, "NEO*PO*MCT Oil" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who stayed in the hospital for more than 34 days and have been prescribed the drug neo*po*mct oil?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"34\" AND PRESCRIPTIONS.\"DRUG\" = \"NEO*PO*MCT Oil\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "stayed", "in", "the", "hospital", "for", "more", "than", "34", "days", "and", "have", "been", "prescribed", "the", "drug", "neo*po*mct", "oil", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"34\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"NEO*PO*MCT", "Oil\"" ], "answer": [ "374" ] }, { "key": "089a137d1d773bd6f945b3accb8eb318", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 16 ], [ 4, 2, 0, 50976 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients with item id 50976 remained admitted in hospital for more than 16 days?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"16\" AND LAB.\"ITEMID\" = \"50976\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "with", "item", "i", "d", "50976", "remained", "admitted", "in", "hospital", "for", "more", "than", "16", "days", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"16\"", "AND", "LAB.\"ITEMID\"", "=", "\"50976\"" ], "answer": [ "1243" ] }, { "key": "00263ad8de751999af6aa3a7cf5276ad", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 14 ], [ 4, 6, 0, "Methemoglobin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose hospital stay is above 14 days and with lab test methemoglobin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"14\" AND LAB.\"LABEL\" = \"Methemoglobin\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "hospital", "stay", "is", "above", "14", "days", "and", "with", "lab", "test", "methemoglobin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"14\"", "AND", "LAB.\"LABEL\"", "=", "\"Methemoglobin\"" ], "answer": [ "475" ] }, { "key": "03581613dae97e5ca2785224b80c6222", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 26 ], [ 4, 6, 0, "24 hr Creatinine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "bring the number of patients who have had 24 hr creatinine lab test and stayed in hospital for more than 26 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"26\" AND LAB.\"LABEL\" = \"24 hr Creatinine\"", "question_refine_tok": [ "bring", "the", "number", "of", "patients", "who", "have", "had", "24", "hr", "creatinine", "lab", "test", "and", "stayed", "in", "hospital", "for", "more", "than", "26", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"26\"", "AND", "LAB.\"LABEL\"", "=", "\"24", "hr", "Creatinine\"" ], "answer": [ "98" ] }, { "key": "09836ee89fd684d22d1fd39b5efb7692", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 1 ], [ 4, 7, 0, "Urine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give the number of patients who have stayed in the hospital for more than one day whose lab test fluid is urine.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"1\" AND LAB.\"FLUID\" = \"Urine\"", "question_refine_tok": [ "give", "the", "number", "of", "patients", "who", "have", "stayed", "in", "the", "hospital", "for", "more", "than", "one", "day", "whose", "lab", "test", "fluid", "is", "urine", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"1\"", "AND", "LAB.\"FLUID\"", "=", "\"Urine\"" ], "answer": [ "28742" ] }, { "key": "859d3b545592e6d48f57a1a061efee5c", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 2 ], [ 4, 7, 0, "Urine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted for more than 2 days had a lab test for urine", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"2\" AND LAB.\"FLUID\" = \"Urine\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "for", "more", "than", "2", "days", "had", "a", "lab", "test", "for", "urine" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"2\"", "AND", "LAB.\"FLUID\"", "=", "\"Urine\"" ], "answer": [ "27171" ] }, { "key": "85aa76ce561a87a6edc0d482804be238", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 2 ], [ 4, 7, 0, "Other Body Fluid" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients who had other body fluid lab test and were hospitalized for more than 2 days.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"2\" AND LAB.\"FLUID\" = \"Other Body Fluid\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "who", "had", "other", "body", "fluid", "lab", "test", "and", "were", "hospitalized", "for", "more", "than", "2", "days", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"2\"", "AND", "LAB.\"FLUID\"", "=", "\"Other", "Body", "Fluid\"" ], "answer": [ "2430" ] }, { "key": "0733b1bb3d1aa461500203a4d62a5b57", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 10, 1, 5 ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who were admitted for more than 5 days in hospital and had chemistry lab test category.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DAYS_STAY\" > \"5\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "were", "admitted", "for", "more", "than", "5", "days", "in", "hospital", "and", "had", "chemistry", "lab", "test", "category", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", ">", "\"5\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "25971" ] }, { "key": "0396aa6c389fbd125085ebc36a4135c6", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 18, 2, 2024 ], [ 1, 3, 0, "Chronic liver dis NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients born before 2024 diagnosed with other chronic nonalcoholic liver disease.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2024\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Chronic liver dis NEC\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "born", "before", "2024", "diagnosed", "with", "other", "chronic", "nonalcoholic", "liver", "disease", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2024\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Chronic", "liver", "dis", "NEC\"" ], "answer": [ "1" ] }, { "key": "0ea47d14ad9c8eb5f88da2a93f2a6b8d", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 18, 2, 2065 ], [ 2, 2, 0, 46 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose year of birth is before 2065 and procedure icd9 code 46?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2065\" AND PROCEDURES.\"ICD9_CODE\" = \"46\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "year", "of", "birth", "is", " ", "before", "2065", "and", "procedure", "icd9", "code", "46", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2065\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"46\"" ], "answer": [ "0" ] }, { "key": "03a4061b29e9397f573c8fc2412dcf06", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 18, 2, 2065 ], [ 2, 2, 0, 9604 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give the number of patients who were born before the year 2065 and have a procedure icd9 code as 9604?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2065\" AND PROCEDURES.\"ICD9_CODE\" = \"9604\"", "question_refine_tok": [ "Give", "the", "number", "of", "patients", "who", "were", "born", "before", "the", "year", "2065", "and", "have", "a", "procedure", "icd9", "code", "as", "9604", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2065\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"9604\"" ], "answer": [ "2438" ] }, { "key": "04fec7017bec275d4bc47df53bb90b78", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 18, 2, 2121 ], [ 2, 4, 0, "Biopsy of tonsils and adenoids" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are born before 2121 and followed the procedure biopsy of tonsils and adenoids?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2121\" AND PROCEDURES.\"LONG_TITLE\" = \"Biopsy of tonsils and adenoids\"", "question_refine_tok": [ "how", "many", "patients", "are", "born", "before", "2121", "and", "followed", "the", "procedure", "biopsy", "of", "tonsils", "and", "adenoids", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2121\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Biopsy", "of", "tonsils", "and", "adenoids\"" ], "answer": [ "2" ] }, { "key": "819886e34e7e0c9516caa63edcf8fa0d", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 18, 2, 2065 ], [ 2, 4, 0, "Prophylactic administration of vaccine against other diseases" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients born before 2065 who had prophylactic administration of vaccine against other diseases.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2065\" AND PROCEDURES.\"LONG_TITLE\" = \"Prophylactic administration of vaccine against other diseases\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "born", "before", "2065", "who", "had", "prophylactic", "administration", "of", "vaccine", "against", "other", "diseases", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2065\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Prophylactic", "administration", "of", "vaccine", "against", "other", "diseases\"" ], "answer": [ "5" ] }, { "key": "80778e877d3c5ed5efa2155fccdcc2ec", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 18, 2, 2109 ], [ 2, 4, 0, "Coronary arteriography using two catheters" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who had coronary arteriography using two catheters and were born before 2109?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2109\" AND PROCEDURES.\"LONG_TITLE\" = \"Coronary arteriography using two catheters\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "had", "coronary", "arteriography", "using", "two", "catheters", "and", "were", "born", "before", "2109", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2109\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Coronary", "arteriography", "using", "two", "catheters\"" ], "answer": [ "3715" ] }, { "key": "821b43f632853ed712026a1d2d0d8313", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 18, 2, 2104 ], [ 3, 3, 0, "ADDITIVE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients on additive type drug prescription who were born before 2104.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2104\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"ADDITIVE\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "on", "additive", "type", "drug", "prescription", "who", "were", "born", "before", "2104", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2104\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"ADDITIVE\"" ], "answer": [ "1613" ] }, { "key": "94d03397b2b5cc027c508ab22c8e216e", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 18, 2, 2104 ], [ 3, 4, 0, "Vancomycin" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients born before the year 2104 were given the drug vancomycin?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2104\" AND PRESCRIPTIONS.\"DRUG\" = \"Vancomycin\"", "question_refine_tok": [ "how", "many", "patients", "born", "before", "the", "year", "2104", "were", "given", "the", "drug", "vancomycin", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2104\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"Vancomycin\"" ], "answer": [ "7388" ] }, { "key": "0ef4e32954ca70a4dbc73fedfa9a6ba8", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 18, 2, 2109 ], [ 3, 4, 0, "NORepinephrine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients on norepinephrine prescription who were born before the year 2109.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2109\" AND PRESCRIPTIONS.\"DRUG\" = \"NORepinephrine\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "on", "norepinephrine", "prescription", "who", "were", "born", "before", "the", "year", "2109", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2109\"", "AND", "PRESCRIPTIONS.\"DRUG\"", "=", "\"NORepinephrine\"" ], "answer": [ "915" ] }, { "key": "01978ff062145f6b9b95e252b3bab2b0", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 18, 2, 2053 ], [ 3, 6, 0, "IVPCA" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients born before 2053 who are taking drug via ivpca route.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2053\" AND PRESCRIPTIONS.\"ROUTE\" = \"IVPCA\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "born", "before", "2053", "who", "are", "taking", "drug", "via", "ivpca", "route", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2053\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"IVPCA\"" ], "answer": [ "560" ] }, { "key": "070960a090aa476250fdbf3a9ddc3350", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 18, 2, 2071 ], [ 4, 2, 0, 50953 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were born before the year 2071 with an item id 50953?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2071\" AND LAB.\"ITEMID\" = \"50953\"", "question_refine_tok": [ "how", "many", "patients", "were", "born", "before", "the", "year", "2071", "with", "an", "item", "i", "d", "50953", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2071\"", "AND", "LAB.\"ITEMID\"", "=", "\"50953\"" ], "answer": [ "2885" ] }, { "key": "81b4faef3515b239d74fcabdef8c1a42", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 18, 2, 2170 ], [ 4, 6, 0, "Other Cells" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients born before the year 2170 had a lab test named other cells?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2170\" AND LAB.\"LABEL\" = \"Other Cells\"", "question_refine_tok": [ "How", "many", "patients", "born", "before", "the", "year", "2170", "had", "a", "lab", "test", "named", "other", "cells", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2170\"", "AND", "LAB.\"LABEL\"", "=", "\"Other", "Cells\"" ], "answer": [ "512" ] }, { "key": "ad68c7f37e76a07bb9df8bbd457cb210", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 18, 2, 1821 ], [ 4, 6, 0, "Lactate Dehydrogenase, CSF" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients year of birth is before 1821 with lab test lactate dehydrogenase csf?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"1821\" AND LAB.\"LABEL\" = \"Lactate Dehydrogenase, CSF\"", "question_refine_tok": [ "how", "many", "patients", "year", "of", "birth", "is", "before", "1821", "with", "lab", "test", "lactate", "dehydrogenase", "csf", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"1821\"", "AND", "LAB.\"LABEL\"", "=", "\"Lactate", "Dehydrogenase,", "CSF\"" ], "answer": [ "3" ] }, { "key": "ace7d9f8651d4d512565d6be3b6a9a6c", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 18, 2, 2089 ], [ 4, 7, 0, "Pleural" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Out of total number of patients who had a lab test for pleural fluid, how many of them were born before 2089?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2089\" AND LAB.\"FLUID\" = \"Pleural\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "who", "had", "a", "lab", "test", "for", "pleural", "fluid", ",", "how", "many", "of", "them", "were", "born", "before", "2089", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2089\"", "AND", "LAB.\"FLUID\"", "=", "\"Pleural\"" ], "answer": [ "879" ] }, { "key": "a8ed9d698cc466a86e52507edcf4e5df", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 18, 2, 2120 ], [ 4, 7, 0, "Urine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "What is the number of patients born before 2120 who had urine lab tests?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOB_YEAR\" < \"2120\" AND LAB.\"FLUID\" = \"Urine\"", "question_refine_tok": [ "What", "is", "the", "number", "of", "patients", "born", "before", "2120", "who", "had", "urine", "lab", "tests", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", "<", "\"2120\"", "AND", "LAB.\"FLUID\"", "=", "\"Urine\"" ], "answer": [ "24817" ] }, { "key": "893e04ea869a527c2f9efc37d8ac617d", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 19, 4, 2115.0 ], [ 2, 4, 0, "Other endoscopy of small intestine" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who had other endoscopy of small intestine and died on or before 2115?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2115.0\" AND PROCEDURES.\"LONG_TITLE\" = \"Other endoscopy of small intestine\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "had", "other", "endoscopy", "of", "small", "intestine", "and", "died", "on", "or", "before", "2115", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2115.0\"", "AND", "PROCEDURES.\"LONG_TITLE\"", "=", "\"Other", "endoscopy", "of", "small", "intestine\"" ], "answer": [ "165" ] }, { "key": "b9b1e272af0cd9a909d5b78a51ebf792", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 19, 4, 2122.0 ], [ 3, 5, 0, "BETH5" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients with drug code beth5 died in or before the year 2122?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2122.0\" AND PRESCRIPTIONS.\"FORMULARY_DRUG_CD\" = \"BETH5\"", "question_refine_tok": [ "How", "many", "patients", "with", "drug", "code", "beth5", "died", "in", "or", "before", "the", "year", "2122", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2122.0\"", "AND", "PRESCRIPTIONS.\"FORMULARY_DRUG_CD\"", "=", "\"BETH5\"" ], "answer": [ "1" ] }, { "key": "a73e048daa3b63ac4a41d7c267a48d31", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 19, 4, 2131.0 ], [ 4, 6, 0, "White Blood Cells" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients had white blood cells test and died in or before 2131?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"DOD_YEAR\" <= \"2131.0\" AND LAB.\"LABEL\" = \"White Blood Cells\"", "question_refine_tok": [ "how", "many", "patients", "had", "white", "blood", "cells", "test", "and", "died", "in", "or", "before", "2131", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<=", "\"2131.0\"", "AND", "LAB.\"LABEL\"", "=", "\"White", "Blood", "Cells\"" ], "answer": [ "4619" ] }, { "key": "935442d35e0d989f39b12cfeb80688d2", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2157 ], [ 1, 2, 0, "78039" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients who were admitted before the year 2157 with 78039 as their diagnosis icd9 code", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2157\" AND DIAGNOSES.\"ICD9_CODE\" = \"78039\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "who", "were", "admitted", "before", "the", "year", "2157", "with", "78039", "as", "their", "diagnosis", "icd9", "code" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2157\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"78039\"" ], "answer": [ "958" ] }, { "key": "acffd8d07f8a0ebff45d316bdad79292", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2112 ], [ 1, 2, 0, "56212" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients admitted before 2112 had icd9 code 56212?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2112\" AND DIAGNOSES.\"ICD9_CODE\" = \"56212\"", "question_refine_tok": [ "How", "many", "patients", "admitted", "before", "2112", "had", "icd9", "code", "56212", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2112\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"56212\"" ], "answer": [ "38" ] }, { "key": "8793d7722bc0a33c0337714fb51f5a3b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2200 ], [ 1, 2, 0, "E8791" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted before the year 2200 and diagnosed with icd9 code e8791?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2200\" AND DIAGNOSES.\"ICD9_CODE\" = \"E8791\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "before", "the", "year", "2200", "and", "diagnosed", "with", "icd9", "code", "e8791", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2200\"", "AND", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"E8791\"" ], "answer": [ "147" ] }, { "key": "0bc9f228d063f921a03fbc029e61db03", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2173 ], [ 1, 3, 0, "Ac salpingo-oophoritis" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the patients admitted before the year 2173 were diagnosed with ac salpingo-oophoritis?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2173\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Ac salpingo-oophoritis\"", "question_refine_tok": [ "How", "many", "of", "the", "patients", "admitted", "before", "the", "year", "2173", "were", "diagnosed", "with", "ac", "salpingo-oophoritis", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2173\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Ac", "salpingo-oophoritis\"" ], "answer": [ "5" ] }, { "key": "8412f1e49973d10caff572e2e132ff72", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2112 ], [ 1, 3, 0, "Chest pain NEC" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many of the patients admitted before 2112 were diagnosed with chest pain nec?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2112\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Chest pain NEC\"", "question_refine_tok": [ "How", "many", "of", "the", "patients", "admitted", "before", "2112", "were", "diagnosed", "with", "chest", "pain", "nec", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2112\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Chest", "pain", "NEC\"" ], "answer": [ "25" ] }, { "key": "877f04eb9833f04f2862fc716b001395", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2154 ], [ 1, 3, 0, "Full incontinence-feces" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "tell me the number of patients with a diagnoses of full incontinence of feces who were admitted before the year 2154.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2154\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Full incontinence-feces\"", "question_refine_tok": [ "tell", "me", "the", "number", "of", "patients", "with", "a", "diagnoses", "of", "full", "incontinence", "of", "feces", "who", "were", "admitted", "before", "the", "year", "2154", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2154\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Full", "incontinence-feces\"" ], "answer": [ "10" ] }, { "key": "9fa8ef22b161a69988711ef9cb37abc9", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2145 ], [ 1, 3, 0, "Syncope and collapse" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are admitted before the year 2145 and diagnosed with syncope and collapse?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2145\" AND DIAGNOSES.\"SHORT_TITLE\" = \"Syncope and collapse\"", "question_refine_tok": [ "how", "many", "patients", "are", "admitted", "before", "the", "year", "2145", "and", "diagnosed", "with", "syncope", "and", "collapse", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2145\"", "AND", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Syncope", "and", "collapse\"" ], "answer": [ "181" ] }, { "key": "8214f3889146d612348c9eb4d86ce408", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2138 ], [ 1, 4, 0, "Unspecified schizophrenia, unspecified" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Find the number of patients admitted before 2138 who had unspecified schizophrenia and unspecified diagnoses.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2138\" AND DIAGNOSES.\"LONG_TITLE\" = \"Unspecified schizophrenia, unspecified\"", "question_refine_tok": [ "Find", "the", "number", "of", "patients", "admitted", "before", "2138", "who", "had", "unspecified", "schizophrenia", "and", "unspecified", "diagnoses", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2138\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Unspecified", "schizophrenia,", "unspecified\"" ], "answer": [ "72" ] }, { "key": "86e5e1517891514bdb1d0018f85f9a34", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 22, 2, 2112 ], [ 1, 4, 0, "Retained plastic fragments" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients admitted before 2112 are diagnosed with retained plastic fragments?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2112\" AND DIAGNOSES.\"LONG_TITLE\" = \"Retained plastic fragments\"", "question_refine_tok": [ "How", "many", "patients", "admitted", "before", "2112", "are", "diagnosed", "with", "retained", "plastic", "fragments", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2112\"", "AND", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Retained", "plastic", "fragments\"" ], "answer": [ "0" ] }, { "key": "00c91f40bec29a121a7c95c4a3a4fa87", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2137 ], [ 2, 2, 0, 3972 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose admission year is before 2137 with procedure icd9 code 3972?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2137\" AND PROCEDURES.\"ICD9_CODE\" = \"3972\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "admission", "year", "is", "before", "2137", "with", "procedure", "icd9", "code", "3972", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2137\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"3972\"" ], "answer": [ "111" ] }, { "key": "8385c7828a91dfb287c01c8c00c801d6", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2103 ], [ 2, 2, 0, 93 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients were admitted before the year 2103 and underwent procedure under icd9 code 93?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2103\" AND PROCEDURES.\"ICD9_CODE\" = \"93\"", "question_refine_tok": [ "how", "many", "patients", "were", "admitted", "before", "the", "year", "2103", "and", "underwent", "procedure", "under", "icd9", "code", "93", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2103\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"93\"" ], "answer": [ "0" ] }, { "key": "8905a4c9ce097875ed1f8db4c3ff14bd", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2166 ], [ 2, 2, 0, 5011 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients admitted before 2166 with procedure icd9 code 5011?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2166\" AND PROCEDURES.\"ICD9_CODE\" = \"5011\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "admitted", "before", "2166", "with", "procedure", "icd9", "code", "5011", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2166\"", "AND", "PROCEDURES.\"ICD9_CODE\"", "=", "\"5011\"" ], "answer": [ "177" ] }, { "key": "87689c7809bf255181fa07418161d05b", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 22, 2, 2167 ], [ 2, 3, 0, "Adm inhal nitric oxide" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "How many patients were admitted to the hospital before year 2167 with procedure short title adm inhal nitric oxide?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2167\" AND PROCEDURES.\"SHORT_TITLE\" = \"Adm inhal nitric oxide\"", "question_refine_tok": [ "How", "many", "patients", "were", "admitted", "to", "the", "hospital", "before", "year", "2167", "with", "procedure", "short", "title", "adm", "inhal", "nitric", "oxide", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2167\"", "AND", "PROCEDURES.\"SHORT_TITLE\"", "=", "\"Adm", "inhal", "nitric", "oxide\"" ], "answer": [ "23" ] }, { "key": "9573ec5367c02c9833ccab2080693edf", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 22, 2, 2154 ], [ 3, 6, 0, "DIALYS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients who have dialys route of drug administration and were admitted before 2154?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2154\" AND PRESCRIPTIONS.\"ROUTE\" = \"DIALYS\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "who", "have", "dialys", "route", "of", "drug", "administration", "and", "were", "admitted", "before", "2154", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2154\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"DIALYS\"" ], "answer": [ "541" ] }, { "key": "81b5be8c3f3f6d80a55a59f385e43659", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 22, 2, 2167 ], [ 3, 6, 0, "TP" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "what is the number of patients whose drug route is tp and admission year is before 2167?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2167\" AND PRESCRIPTIONS.\"ROUTE\" = \"TP\"", "question_refine_tok": [ "what", "is", "the", "number", "of", "patients", "whose", "drug", "route", "is", "tp", "and", "admission", "year", "is", "before", "2167", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2167\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"TP\"" ], "answer": [ "8318" ] }, { "key": "a8f454b305ca58863f8acb1e275043cd", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2156 ], [ 4, 2, 0, 51383 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "among patients admitted in the year less than 2156, how many had item id 51383?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2156\" AND LAB.\"ITEMID\" = \"51383\"", "question_refine_tok": [ "among", "patients", "admitted", "in", "the", "year", "less", "than", "2156", ",", "how", "many", "had", "item", "i", "d", "51383", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2156\"", "AND", "LAB.\"ITEMID\"", "=", "\"51383\"" ], "answer": [ "151" ] }, { "key": "a931fe64ae8d250a39e2aab3a9ca6d35", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2120 ], [ 4, 2, 0, 51044 ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients admitted before the year 2120 had the lab test item id 51044?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2120\" AND LAB.\"ITEMID\" = \"51044\"", "question_refine_tok": [ "how", "many", "patients", "admitted", "before", "the", "year", "2120", "had", "the", "lab", "test", "item", "i", "d", "51044", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2120\"", "AND", "LAB.\"ITEMID\"", "=", "\"51044\"" ], "answer": [ "7" ] }, { "key": "8e4ac03622a29fc33cb3db508067755b", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2129 ], [ 4, 6, 0, "RBC, Pleural" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Give me the number of patients admitted before the year 2129 and whose lab test name is rbc, pleural.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2129\" AND LAB.\"LABEL\" = \"RBC, Pleural\"", "question_refine_tok": [ "Give", "me", "the", "number", "of", "patients", "admitted", "before", "the", "year", "2129", "and", "whose", "lab", "test", "name", "is", "rbc", ",", "pleural", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2129\"", "AND", "LAB.\"LABEL\"", "=", "\"RBC,", "Pleural\"" ], "answer": [ "418" ] }, { "key": "0782eff13b2a6fe1c1f0fb94270bb9c4", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2158 ], [ 4, 6, 0, "Thyroxine (T4)" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "count the number of patients who were admitted before 2158 and had thyroxine (t4) lab test.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2158\" AND LAB.\"LABEL\" = \"Thyroxine (T4)\"", "question_refine_tok": [ "count", "the", "number", "of", "patients", "who", "were", "admitted", "before", "2158", "and", "had", "thyroxine", "(", "t4", ")", "lab", "test", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2158\"", "AND", "LAB.\"LABEL\"", "=", "\"Thyroxine", "(T4)\"" ], "answer": [ "923" ] }, { "key": "0210d3905a34c79042a4d7e986f358a5", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2123 ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Calculate the total number of patients admitted before 2123, who had a lab test for clinical chemistry.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2123\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "Calculate", "the", "total", "number", "of", "patients", "admitted", "before", "2123", ",", "who", "had", "a", "lab", "test", "for", "clinical", "chemistry", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2123\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "10078" ] }, { "key": "836465719f3fb798cb45b66ac582843f", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 22, 2, 2124 ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Count the number of patients admitted before 2124 categorized under chemistry lab tests.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"ADMITYEAR\" < \"2124\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "Count", "the", "number", "of", "patients", "admitted", "before", "2124", "categorized", "under", "chemistry", "lab", "tests", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"ADMITYEAR\"", "<", "\"2124\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "10521" ] }, { "key": "a4bede9ac4d227fba14b6e58ffee4fe8", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 2, 0, "4464" ], [ 3, 3, 0, "BASE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many of the patients diagnosed with icd9 code 4464 were treated with base drug?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"4464\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"BASE\"", "question_refine_tok": [ "how", "many", "of", "the", "patients", "diagnosed", "with", "icd9", "code", "4464", "were", "treated", "with", "base", "drug", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"4464\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"BASE\"" ], "answer": [ "30" ] }, { "key": "8e6282194cccfa0e8fc65e02a9e1a47f", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 2, 0, "53190" ], [ 4, 4, 0, "delta" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with diagnoses icd9 code 53190 have had delta abnormal lab test status?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"53190\" AND LAB.\"FLAG\" = \"delta\"", "question_refine_tok": [ "how", "many", "patients", "with", "diagnoses", "icd9", "code", "53190", "have", "had", "delta", "abnormal", "lab", "test", "status", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"53190\"", "AND", "LAB.\"FLAG\"", "=", "\"delta\"" ], "answer": [ "42" ] }, { "key": "879e430064f5011919b19ba70a193bc9", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 2, 0, "76528" ], [ 4, 8, 0, "Chemistry" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "give me the number of patients who were diagnosed under icd9 code 76528 and also their lab test category is chemistry.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"ICD9_CODE\" = \"76528\" AND LAB.\"CATEGORY\" = \"Chemistry\"", "question_refine_tok": [ "give", "me", "the", "number", "of", "patients", "who", "were", "diagnosed", "under", "icd9", "code", "76528", "and", "also", "their", "lab", "test", "category", "is", "chemistry", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"ICD9_CODE\"", "=", "\"76528\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Chemistry\"" ], "answer": [ "810" ] }, { "key": "0889b8c37decb7cd8458fd44dc8b8bb5", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Polycythemia vera" ], [ 3, 3, 0, "MAIN" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients with polycythemia were treated with main drug?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Polycythemia vera\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"MAIN\"", "question_refine_tok": [ "how", "many", "patients", "with", "polycythemia", "were", "treated", "with", "main", "drug", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Polycythemia", "vera\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"MAIN\"" ], "answer": [ "83" ] }, { "key": "a9d3922a87c08a9303cca4b529bb1bdc", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 3, 0, "Adv eff antineoplastic" ], [ 3, 6, 0, "PR" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "report the number of patients on pr route of drug administration who were diagnosed with antineoplastic and immunosuppressive drugs causing adverse effects in therapeutic use.", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"Adv eff antineoplastic\" AND PRESCRIPTIONS.\"ROUTE\" = \"PR\"", "question_refine_tok": [ "report", "the", "number", "of", "patients", "on", "pr", "route", "of", "drug", "administration", "who", "were", "diagnosed", "with", "antineoplastic", "and", "immunosuppressive", "drugs", "causing", "adverse", "effects", "in", "therapeutic", "use", "." ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"Adv", "eff", "antineoplastic\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"PR\"" ], "answer": [ "211" ] }, { "key": "823634609ee30ffe023353e3f58c68ad", "format": { "table": [ 0, 1, 4 ], "cond": [ [ 1, 3, 0, "History of tobacco use" ], [ 4, 8, 0, "Blood Gas" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with the history of tobacco use and tested under the lab category blood gas?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DIAGNOSES.\"SHORT_TITLE\" = \"History of tobacco use\" AND LAB.\"CATEGORY\" = \"Blood Gas\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "the", "history", "of", "tobacco", "use", "and", "tested", "under", "the", "lab", "category", "blood", "gas", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DIAGNOSES.\"SHORT_TITLE\"", "=", "\"History", "of", "tobacco", "use\"", "AND", "LAB.\"CATEGORY\"", "=", "\"Blood", "Gas\"" ], "answer": [ "2151" ] }, { "key": "0cf005065d0b57f881548f2a461ceaa9", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 4, 0, "Other and unspecified coagulation defects" ], [ 3, 3, 0, "ADDITIVE" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with unspecified coagulation defects and used the additive drug type?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Other and unspecified coagulation defects\" AND PRESCRIPTIONS.\"DRUG_TYPE\" = \"ADDITIVE\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "unspecified", "coagulation", "defects", "and", "used", "the", "additive", "drug", "type", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Other", "and", "unspecified", "coagulation", "defects\"", "AND", "PRESCRIPTIONS.\"DRUG_TYPE\"", "=", "\"ADDITIVE\"" ], "answer": [ "83" ] }, { "key": "ade3038af3cee4bf7d6dad698f9a4b7b", "format": { "table": [ 0, 1, 3 ], "cond": [ [ 1, 4, 0, "Opioid type dependence, unspecified" ], [ 3, 6, 0, "TD" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "how many patients are diagnosed with opioid type dependence (unspecified) with td drug route?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DIAGNOSES.\"LONG_TITLE\" = \"Opioid type dependence, unspecified\" AND PRESCRIPTIONS.\"ROUTE\" = \"TD\"", "question_refine_tok": [ "how", "many", "patients", "are", "diagnosed", "with", "opioid", "type", "dependence", "(", "unspecified", ")", "with", "td", "drug", "route", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DIAGNOSES.\"LONG_TITLE\"", "=", "\"Opioid", "type", "dependence,", "unspecified\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"TD\"" ], "answer": [ "33" ] }, { "key": "0c2ef79ee5525ce0ca1b3136fba43436", "format": { "table": [ 0, 2, 3 ], "cond": [ [ 2, 2, 0, 4576 ], [ 3, 6, 0, "IV BOLUS" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "provide the number of patients whose procedure icd9 code is 4576 and drug route is iv bolus", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE PROCEDURES.\"ICD9_CODE\" = \"4576\" AND PRESCRIPTIONS.\"ROUTE\" = \"IV BOLUS\"", "question_refine_tok": [ "provide", "the", "number", "of", "patients", "whose", "procedure", "icd9", "code", "is", "4576", "and", "drug", "route", "is", "iv", "bolus" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "PROCEDURES.\"ICD9_CODE\"", "=", "\"4576\"", "AND", "PRESCRIPTIONS.\"ROUTE\"", "=", "\"IV", "BOLUS\"" ], "answer": [ "25" ] }, { "key": "95c9f21405c27dccc93ef6c419bf3626", "format": { "table": [ 0, 4 ], "cond": [ [ 4, 2, 0, 51255 ], [ 4, 4, 0, "abnormal" ] ], "agg_col": [ [ 0, 0 ] ], "sel": 1 }, "question_refine": "Which patients have an abnormal test with lab test item id 51255?", "sql": "SELECT COUNT ( DISTINCT DEMOGRAPHIC.\"SUBJECT_ID\" ) FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE LAB.\"ITEMID\" = \"51255\" AND LAB.\"FLAG\" = \"abnormal\"", "question_refine_tok": [ "Which", "patients", "have", "an", "abnormal", "test", "with", "lab", "test", "item", "id", "51255", "?" ], "sql_tok": [ "SELECT", "COUNT", "(", "DISTINCT", "DEMOGRAPHIC.\"SUBJECT_ID\"", ")", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "LAB.\"ITEMID\"", "=", "\"51255\"", "AND", "LAB.\"FLAG\"", "=", "\"abnormal\"" ], "answer": [ "4073" ] }, { "key": "8f55194c343ff824217a7b21628ce8df", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 8 ] ], "sel": 0 }, "question_refine": "find the religion of subject id 2560.", "sql": "SELECT DEMOGRAPHIC.\"RELIGION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "find", "the", "religion", "of", "subject", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"RELIGION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NOT SPECIFIED" ] }, { "key": "90ee181da18bcfa8845875faca250b0b", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "specify the admission type of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "specify", "the", "admission", "type", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NEWBORN" ] }, { "key": "a4df1c06ae50974eb35454fea26ee559", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 12 ] ], "sel": 0 }, "question_refine": "specify ethnic origin of patient id 2560", "sql": "SELECT DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "specify", "ethnic", "origin", "of", "patient", "i", "d", "2560" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "BLACK/AFRICAN AMERICAN" ] }, { "key": "9ac0e0d4bfb323232d30e9ed3deaec6f", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 14 ] ], "sel": 0 }, "question_refine": "what is the admission location of subject id 2560?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "admission", "location", "of", "subject", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "96386b9da21f0970e7a61190fe3ea6e1", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 20 ] ], "sel": 0 }, "question_refine": "At what time was the patient with patient id 2560 admitted in the hospital?", "sql": "SELECT DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "At", "what", "time", "was", "the", "patient", "with", "patient", "id", "2560", "admitted", "in", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "2182-04-24 21:20:00" ] }, { "key": "0300bf805faa92cd8547894672e7dc4f", "format": { "table": [ 3 ], "cond": [ [ 3, 0, 0, 2560 ] ], "agg_col": [ [ 3, 2 ] ], "sel": 0 }, "question_refine": "tell me the icu stay id of the patient with patient id 2560.", "sql": "SELECT PRESCRIPTIONS.\"ICUSTAY_ID\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "icu", "stay", "i", "d", "of", "the", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"ICUSTAY_ID\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "201579", "201579", "201579", "201579" ] }, { "key": "85b8122d33f83e2e347667f686b01923", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 2560 ] ], "agg_col": [ [ 4, 6 ] ], "sel": 0 }, "question_refine": "bring me the lab test name of the patient with patient id 2560.", "sql": "SELECT LAB.\"LABEL\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "bring", "me", "the", "lab", "test", "name", "of", "the", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "LAB.\"LABEL\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "Bilirubin, Total", "Basophils", "Eosinophils", "Hematocrit", "Hemoglobin", "Lymphocytes", "MCH", "MCHC", "MCV", "Monocytes", "Neutrophils", "Platelet Count", "RDW", "Red Blood Cells", "White Blood Cells", "Atypical Lymphocytes", "Bands", "Metamyelocytes", "Myelocytes", "Nucleated Red Cells", "Bilirubin, Direct", "Bilirubin, Indirect" ] }, { "key": "0aa9447c3469cd02b865dfa7719d49fc", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 2 ], [ 0, 4 ] ], "sel": 0 }, "question_refine": "let me know the age and name of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"AGE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "let", "me", "know", "the", "age", "and", "name", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"AGE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "Shawn Green" ] }, { "key": "8f18423f8d3275ea02e399fc8ac60b11", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 2 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "tell me the gender and name of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "gender", "and", "name", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "Shawn Green" ] }, { "key": "9c392d2c88c6189f9251d0bd435033a9", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 2 ], [ 0, 20 ] ], "sel": 0 }, "question_refine": "tell me the time of admission and name of the patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "time", "of", "admission", "and", "name", "of", "the", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\",DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "Shawn Green" ] }, { "key": "0e56b87b438922c7950eeb5d9058c983", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 4 ], [ 0, 12 ] ], "sel": 0 }, "question_refine": "what is the age and ethnicity of the patient id 2560?", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "age", "and", "ethnicity", "of", "the", "patient", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "0" ] }, { "key": "90edf3709e8df1784f2d3fda1a16252c", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 4 ], [ 0, 14 ] ], "sel": 0 }, "question_refine": "tell me the age and location of admission for the patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "age", "and", "location", "of", "admission", "for", "the", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "0" ] }, { "key": "019e8cc13b5a6753a90808feb7e87e1b", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 4 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "what is the age and diagnosis icd9 code of subject id 2560?", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "age", "and", "diagnosis", "icd9", "code", "of", "subject", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "0", "0", "0", "0", "0" ] }, { "key": "a72b27d87f1604c13e39e7d4e5b4ff46", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 4 ], [ 3, 4 ] ], "sel": 0 }, "question_refine": "Specify the age of patient id 2560 and drug he was treated with", "sql": "SELECT DEMOGRAPHIC.\"AGE\",PRESCRIPTIONS.\"DRUG\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "Specify", "the", "age", "of", "patient", "id", "2560", "and", "drug", "he", "was", "treated", "with" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",PRESCRIPTIONS.\"DRUG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "0", "0", "0", "0" ] }, { "key": "841e216a58a14d3c9464750a1b9b112a", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 5 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "let me know the gender and birth date of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "let", "me", "know", "the", "gender", "and", "birth", "date", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "2182-04-24 00:00:00" ] }, { "key": "013f6c92a36d259b5c0c379312966415", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "let me know the gender and days for which patient with patient id 2560 was admitted.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "let", "me", "know", "the", "gender", "and", "days", "for", "which", "patient", "with", "patient", "i", "d", "2560", "was", "admitted", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M" ] }, { "key": "0865071639569180742a822ef4d6ec79", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "what is the gender and diagnosis icd9 code of the patient id 2560?", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "gender", "and", "diagnosis", "icd9", "code", "of", "the", "patient", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M", "M", "M", "M" ] }, { "key": "01e495e69e3444418dd0a16b3dbc3827", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 1, 3 ] ], "sel": 0 }, "question_refine": "let me know the gender and short title of diagnoses for patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "let", "me", "know", "the", "gender", "and", "short", "title", "of", "diagnoses", "for", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M", "M", "M", "M" ] }, { "key": "0df0d1bfc8c469daedeb651e5ca26919", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "tell me the gender and procedure icd9 code of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "gender", "and", "procedure", "icd9", "code", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M" ] }, { "key": "9c1c99acd4928c03d0fe9b39e929e3d2", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 4, 2 ] ], "sel": 0 }, "question_refine": "for patient id 2560, specify gender and item id. ", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",LAB.\"ITEMID\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "for", "patient", "i", "d", "2560", ",", "specify", "gender", "and", "item", "i", "d", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",LAB.\"ITEMID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M" ] }, { "key": "90ea3f943491a9110aa016d6d613cba8", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 4, 4 ] ], "sel": 0 }, "question_refine": "let me know the gender and lab test abnormal status of patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",LAB.\"FLAG\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "let", "me", "know", "the", "gender", "and", "lab", "test", "abnormal", "status", "of", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",LAB.\"FLAG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M" ] }, { "key": "8b3b7d60621a3316c1c33500b8f4243d", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 6 ], [ 4, 6 ] ], "sel": 0 }, "question_refine": "Get me the gender and lab test name for patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\",LAB.\"LABEL\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "Get", "me", "the", "gender", "and", "lab", "test", "name", "for", "patient", "with", "patient", "id", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\",LAB.\"LABEL\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M" ] }, { "key": "aa022b1cc5c7397eb610009350ab2fe2", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 9 ], [ 0, 13 ] ], "sel": 0 }, "question_refine": "mention the admission type and death status of the patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "mention", "the", "admission", "type", "and", "death", "status", "of", "the", "patient", "with", "patient", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"EXPIRE_FLAG\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NEWBORN" ] }, { "key": "8769210e7e36fb15bd7f3441ac74704f", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 9 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "tell me the admission type and primary disease of subject id 2560.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "tell", "me", "the", "admission", "type", "and", "primary", "disease", "of", "subject", "i", "d", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NEWBORN" ] }, { "key": "9da49c29363fd75f4415f0a45bc818e7", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 9 ], [ 2, 2 ] ], "sel": 0 }, "question_refine": "Let me know the type of admission and procedure ic9 code for the patient with patient id 2560.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "Let", "me", "know", "the", "type", "of", "admission", "and", "procedure", "ic9", "code", "for", "the", "patient", "with", "patient", "id", "2560", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",PROCEDURES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NEWBORN", "NEWBORN" ] }, { "key": "89a92f1bd2e74cecb90195b6d5cd860f", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 9 ], [ 4, 6 ] ], "sel": 0 }, "question_refine": "what is the admission type and lab test name for the patient id 2560?", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"LABEL\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "admission", "type", "and", "lab", "test", "name", "for", "the", "patient", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\",LAB.\"LABEL\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN", "NEWBORN" ] }, { "key": "0f8f5ea7b7f14f7015f7442d242c547d", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 10 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "What is the primary disease and days of hospital stay for patient id 2560", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "What", "is", "the", "primary", "disease", "and", "days", "of", "hospital", "stay", "for", "patient", "id", "2560" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "4" ] }, { "key": "0c6330427069e970ee4be464f3c99c48", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 2560 ] ], "agg_col": [ [ 0, 10 ], [ 0, 17 ] ], "sel": 0 }, "question_refine": "what is the days of hospital stay and date of death of subject id 2560?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DOD\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"2560\"", "question_refine_tok": [ "what", "is", "the", "days", "of", "hospital", "stay", "and", "date", "of", "death", "of", "subject", "i", "d", "2560", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\",DEMOGRAPHIC.\"DOD\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"2560\"" ], "answer": [ "4" ] }, { "key": "0002b22d84bc01ecf68cc95c5b6a28d8", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 2 ] ], "sel": 0 }, "question_refine": "what is the subject name of subject id 6983?", "sql": "SELECT DEMOGRAPHIC.\"NAME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "what", "is", "the", "subject", "name", "of", "subject", "i", "d", "6983", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"NAME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "Edward Castillo", "Edward Castillo" ] }, { "key": "86eddf5b63dee431e8e258e630341a7d", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 6 ] ], "sel": 0 }, "question_refine": "find the gender of subject id 6983.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "find", "the", "gender", "of", "subject", "i", "d", "6983", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "M", "M" ] }, { "key": "896df25f5b715ec49f1df5714593388a", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 8 ] ], "sel": 0 }, "question_refine": "to which religious background does the patient with patient id 6983 belong to?", "sql": "SELECT DEMOGRAPHIC.\"RELIGION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "to", "which", "religious", "background", "does", "the", "patient", "with", "patient", "i", "d", "6983", "belong", "to", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"RELIGION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "JEWISH", "JEWISH" ] }, { "key": "8e6fc76db9d8db496cef372a27ead890", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 17 ] ], "sel": 0 }, "question_refine": "on which date did the patient with patient id 6983 die?", "sql": "SELECT DEMOGRAPHIC.\"DOD\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "on", "which", "date", "did", "the", "patient", "with", "patient", "i", "d", "6983", "die", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOD\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "2179-07-02 00:00:00", "2179-07-02 00:00:00" ] }, { "key": "a668f0e1f166ac29ff6af5bb677710a8", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 6983 ] ], "agg_col": [ [ 0, 21 ] ], "sel": 0 }, "question_refine": "find the discharge time for subject id 6983.", "sql": "SELECT DEMOGRAPHIC.\"DISCHTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "find", "the", "discharge", "time", "for", "subject", "i", "d", "6983", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "2177-08-06 15:16:00", "2177-08-21 13:30:00" ] }, { "key": "83657431596bda1d0854362f6a0df459", "format": { "table": [ 3 ], "cond": [ [ 3, 0, 0, 6983 ] ], "agg_col": [ [ 3, 6 ] ], "sel": 0 }, "question_refine": "How is the drug administered to patient with patient id 6983?", "sql": "SELECT PRESCRIPTIONS.\"ROUTE\" FROM PRESCRIPTIONS WHERE PRESCRIPTIONS.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "How", "is", "the", "drug", "administered", "to", "patient", "with", "patient", "id", "6983", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"ROUTE\"", "FROM", "PRESCRIPTIONS", "WHERE", "PRESCRIPTIONS.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "PO", "PO", "PO", "PO", "IV", "IV", "IV", "IV", "PO", "SC", "IV", "PO", "IV", "IV", "PO", "IV", "PO", "PO", "IV", "IV", "PO", "PO", "TP", "PO", "PO", "IV", "IV", "TP", "PO", "PO", "PO", "IV", "PO", "IV", "IV", "IV", "IV", "IV", "IV", "SC", "SC", "PO", "PO", "IV", "IV", "IV", "IV", "PO", "PO", "PO", "PO", "PO", "IV", "PO", "PO", "IV", "PO", "PO", "PO", "SC", "SC", "SC", "PO", "PO", "PO", "PO", "SC", "PO", "TP", "PO", "SC", "PO", "IV", "IV", "PO", "SC", "SC", "SC", "SC", "PO", "PO", "PO" ] }, { "key": "9af42f48310450fb7dec8a50ffe328fa", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 6983 ] ], "agg_col": [ [ 4, 6 ] ], "sel": 0 }, "question_refine": "what is the lab test name of the patient id 6983?", "sql": "SELECT LAB.\"LABEL\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "what", "is", "the", "lab", "test", "name", "of", "the", "patient", "i", "d", "6983", "?" ], "sql_tok": [ "SELECT", "LAB.\"LABEL\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Creatine Kinase (CK)", "Creatine Kinase (CK)", "Creatine Kinase (CK)", "Creatine Kinase, MB Isoenzyme", "Creatine Kinase, MB Isoenzyme", "Creatine Kinase, MB Isoenzyme", "Creatine Kinase, MB Isoenzyme", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Alkaline Phosphatase", "Alkaline Phosphatase", "Alkaline Phosphatase", "Asparate Aminotransferase (AST)", "Asparate Aminotransferase (AST)", "Asparate Aminotransferase (AST)", "Bilirubin, Total", "Bilirubin, Total", "Bilirubin, Total", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Basophils", "Basophils", "Eosinophils", "Eosinophils", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Lymphocytes", "Lymphocytes", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "Monocytes", "Monocytes", "Neutrophils", "Neutrophils", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PTT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "PT", "Alanine Aminotransferase (ALT)", "Alanine Aminotransferase (ALT)", "Alanine Aminotransferase (ALT)", "Albumin", "Albumin", "Amylase", "Amylase", "Fibrinogen, Functional", "Fibrinogen, Functional", "Fibrinogen, Functional", "Glucose", "Potassium, Whole Blood", "Calculated Bicarbonate, Whole Blood", "Bilirubin", "Bilirubin", "Blood", "Blood", "Epithelial Cells", "Epithelial Cells", "Glucose", "Glucose", "Ketone", "Ketone", "pH", "pH", "Protein", "Protein", "RBC", "RBC", "Specific Gravity", "Specific Gravity", "Urobilinogen", "Urobilinogen", "WBC", "WBC", "Osmolality, Measured", "Osmolality, Measured", "Lactate Dehydrogenase (LD)", "Protein, Total", "Troponin T", "Troponin T", "Troponin T", "Troponin T", "Creatinine, Urine", "Sodium, Urine", "Ammonia", "Ammonia", "Ammonia", "Ammonia", "Ammonia", "Ammonia", "Ammonia", "Ammonia", "D-Dimer" ] }, { "key": "90b82b03ca23ee905266d83b2d929e5b", "format": { "table": [ 4 ], "cond": [ [ 4, 0, 0, 6983 ] ], "agg_col": [ [ 4, 8 ] ], "sel": 0 }, "question_refine": "provide the lab test category of subject id 6983.", "sql": "SELECT LAB.\"CATEGORY\" FROM LAB WHERE LAB.\"SUBJECT_ID\" = \"6983\"", "question_refine_tok": [ "provide", "the", "lab", "test", "category", "of", "subject", "i", "d", "6983", "." ], "sql_tok": [ "SELECT", "LAB.\"CATEGORY\"", "FROM", "LAB", "WHERE", "LAB.\"SUBJECT_ID\"", "=", "\"6983\"" ], "answer": [ "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", 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"Hematology" ] }, { "key": "a9e960146f15dc78dfdf7778cf79c3ba", "format": { "table": [ 0 ], "cond": [ [ 0, 0, 0, 3343 ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "what is the primary disease of the patient id 3343?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"SUBJECT_ID\" = \"3343\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "of", "the", "patient", "i", "d", "3343", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"SUBJECT_ID\"", "=", "\"3343\"" ], "answer": [ "NEWBORN" ] }, { "key": "81e957f6baa421e0530996027bcba9e4", "format": { "table": [ 1 ], "cond": [ [ 1, 0, 0, 3343 ] ], "agg_col": [ [ 1, 4 ] ], "sel": 0 }, "question_refine": "find out the long title diagnosis of patient with patient id 3343.", "sql": "SELECT DIAGNOSES.\"LONG_TITLE\" FROM DIAGNOSES WHERE DIAGNOSES.\"SUBJECT_ID\" = \"3343\"", "question_refine_tok": [ "find", "out", "the", "long", "title", "diagnosis", "of", "patient", "with", "patient", "i", "d", "3343", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"LONG_TITLE\"", "FROM", "DIAGNOSES", "WHERE", "DIAGNOSES.\"SUBJECT_ID\"", "=", "\"3343\"" ], "answer": [ "Single liveborn, born in hospital, delivered by cesarean section", "Observation for suspected genetic or metabolic condition", "Need for prophylactic vaccination and inoculation against viral hepatitis", "Observation for suspected infectious condition" ] }, { "key": "a6ac3a97bbdef6c2de3b7385495aa9c6", "format": { "table": [ 2 ], "cond": [ [ 2, 0, 0, 3343 ] ], "agg_col": [ [ 2, 2 ] ], "sel": 0 }, "question_refine": "what is the procedure icd9 code for the patient id 3343?", "sql": "SELECT PROCEDURES.\"ICD9_CODE\" FROM PROCEDURES WHERE PROCEDURES.\"SUBJECT_ID\" = \"3343\"", "question_refine_tok": [ "what", "is", "the", "procedure", "icd9", "code", "for", "the", "patient", "i", "d", "3343", "?" ], "sql_tok": [ "SELECT", "PROCEDURES.\"ICD9_CODE\"", "FROM", "PROCEDURES", "WHERE", "PROCEDURES.\"SUBJECT_ID\"", "=", "\"3343\"" ], "answer": [ "9955" ] }, { "key": "bb33d9ea342c4d53171831ac967d5204", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 9 ] ], "sel": 0 }, "question_refine": "find out the type of admission patient jerry deberry had.", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_TYPE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "find", "out", "the", "type", "of", "admission", "patient", "jerry", "deberry", "had", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY", "EMERGENCY" ] }, { "key": "8b566538fbaf86ce837bf39a65f2a86e", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "How many days did the patient Jerry Deberry stay in the hospital?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "How", "many", "days", "did", "the", "patient", "Jerry", "Deberry", "stay", "in", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "6", "18", "3", "4", "20", "13", "11" ] }, { "key": "09a0bef7bbe0368bdd3ecdcf037d3927", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 11 ] ], "sel": 0 }, "question_refine": "what is the insurance of the patient name jerry deberry?", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "what", "is", "the", "insurance", "of", "the", "patient", "name", "jerry", "deberry", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare", "Medicare" ] }, { "key": "885fc05dd9e2816d96606e43d38a8e31", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "what is the primary disease of the patient name jerry deberry?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "what", "is", "the", "primary", "disease", "of", "the", "patient", "name", "jerry", "deberry", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "CONGESTIVE HEART FAILURE", "CONGESTIVE HEART FAILURE", "SHORTNESS OF BREATH", "CONGESTIVE HEART FAILURE", "S/P FALL", "SEPSIS", "HEPATITIS" ] }, { "key": "0c4acbfcf0acf32880529f8b2adcc64d", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 1, 2 ] ], "sel": 0 }, "question_refine": "let me know the diagnoses icd9 code of patient jerry deberry.", "sql": "SELECT DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "let", "me", "know", "the", "diagnoses", "icd9", "code", "of", "patient", "jerry", "deberry", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "25000", "2859", "2869", "4019", "41401", "4280", "42823", "496", "51881", "0413", "25000", "2720", "2761", "2767", "4019", "41401", "4254", "4271", "42731", "42741", "4280", "42823", "45989", "496", "5119", "570", "5849", "5990", "78551", "V5861", "25000", "2720", "2859", "4019", "41401", "4168", "42731", "4280", "42823", "49121", "V1582", "V4502", "25000", "2724", "27541", "2762", "4019", "42731", "4280", "42823", "486", "496", "5939", "V1251", "V1581", "V1582", "V4502", "V5861", "25082", "2639", "2724", "2761", "2763", "2767", "34831", "4019", "41400", "4271", "42731", "4280", "42843", "4580", "5070", "51881", "5849", "6959", "73300", "78720", "78909", "E8497", "E9323", "V4502", "V4581", "V5867", "1103", "1122", "25050", "25060", "2639", "2720", "3572", "36201", "40390", "4271", "42731", "4280", "42823", "45382", "48282", "496", "5070", "51884", "5859", "7994", "99674", "V1251", "V1271", "V5861", "V5867", "04149", "25000", "2724", "2762", "3970", "4019", "41401", "4254", "4271", "42731", "4280", "42823", "452", "45829", "496", "5119", "53085", "570", "5722", "5730", "5848", "5959", "6988", "70703", "70722", "78097", "7904", "79092", "E9342", "V1253", "V1582", "V4502", "V4986", "V551", "V5867", "V667" ] }, { "key": "92135f23237f33782c87fc215ea43e54", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "let me know the short title of procedure that the patient jerry deberry underwent.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "let", "me", "know", "the", "short", "title", "of", "procedure", "that", "the", "patient", "jerry", "deberry", "underwent", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "Cont inv mec ven <96 hrs", "Insert endotracheal tube", "Implt/repl carddefib tot", "Rev/reloc card dev pockt", "Thoracentesis", "Venous cath NEC", "CV cath plcmt w guidance", "Arterial catheterization", "CV cath plcmt w guidance", "Cont inv mec ven <96 hrs", "Entral infus nutrit sub", "Insert endotracheal tube", "Percu endosc gastrostomy", "Venous cath NEC", "CV cath plcmt w guidance", "Cont inv mec ven 96+ hrs", "Entral infus nutrit sub", "Other perm tracheostomy", "Parent infus nutrit sub", "Percu endosc gastrostomy", "Entral infus nutrit sub", "Heart countershock NEC", "Venous cath NEC" ] }, { "key": "964051ea9739d5463dc623efb7016c1e", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 4, 8 ] ], "sel": 0 }, "question_refine": "what is the lab category forJerry Deberry?", "sql": "SELECT LAB.\"CATEGORY\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "what", "is", "the", "lab", "category", "forJerry", "Deberry", "?" ], "sql_tok": [ "SELECT", "LAB.\"CATEGORY\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", 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"899be5c31a9c59c33a7a448c4c224976", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 4 ], [ 0, 6 ] ], "sel": 0 }, "question_refine": "mention the age and gender of subject named jerry deberry?", "sql": "SELECT DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "mention", "the", "age", "and", "gender", "of", "subject", "named", "jerry", "deberry", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"AGE\",DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "69", "71", "71", "72", "72", "72", "72" ] }, { "key": "0a77605bec326cf6c78fbd27644ee60d", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 5 ], [ 0, 10 ] ], "sel": 0 }, "question_refine": "find the date of birth and number of days of hospital stay of jerry deberry.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "find", "the", "date", "of", "birth", "and", "number", "of", "days", "of", "hospital", "stay", "of", "jerry", "deberry", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00" ] }, { "key": "0159c2d55484e5e69db037e3092ea43d", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 5 ], [ 0, 12 ] ], "sel": 0 }, "question_refine": "look for the birth date and ethnic background of patient jerry deberry.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "look", "for", "the", "birth", "date", "and", "ethnic", "background", "of", "patient", "jerry", "deberry", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00" ] }, { "key": "9de792fe2a88120b9c4b104e3ef20a27", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 5 ], [ 0, 16 ] ], "sel": 0 }, "question_refine": "mention the disease that jerry deberry is primarily suffering from and his date of birth as well.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "mention", "the", "disease", "that", "jerry", "deberry", "is", "primarily", "suffering", "from", "and", "his", "date", "of", "birth", "as", "well", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00" ] }, { "key": "0817c025e046b7be84ef289caead5837", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 5 ], [ 1, 2 ] ], "sel": 0 }, "question_refine": "Give me the date of birth and diagnoses icd9 code of Jerry Deberry.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",DIAGNOSES.\"ICD9_CODE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "Give", "me", "the", "date", "of", "birth", "and", "diagnoses", "icd9", "code", "of", "Jerry", "Deberry", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",DIAGNOSES.\"ICD9_CODE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00" ] }, { "key": "0e597171d8f49a56ee59fb5598fd6322", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Jerry Deberry" ] ], "agg_col": [ [ 0, 5 ], [ 2, 4 ] ], "sel": 0 }, "question_refine": "give the birthdate and procedure title of jerry deberry.", "sql": "SELECT DEMOGRAPHIC.\"DOB\",PROCEDURES.\"LONG_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Jerry Deberry\"", "question_refine_tok": [ "give", "the", "birthdate", "and", "procedure", "title", "of", "jerry", "deberry", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\",PROCEDURES.\"LONG_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Jerry", "Deberry\"" ], "answer": [ "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00", "2043-02-28 00:00:00" ] }, { "key": "06f15c6be771186668997528e52270cb", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 0, 6 ] ], "sel": 0 }, "question_refine": "tell me the gender of patient stephanie suchan.", "sql": "SELECT DEMOGRAPHIC.\"GENDER\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "tell", "me", "the", "gender", "of", "patient", "stephanie", "suchan", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"GENDER\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "F" ] }, { "key": "8620eaa43239b46cc9bde99b6286773a", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 0 }, "question_refine": "For how many days Stephanie Sechan stayed in the hospital?", "sql": "SELECT DEMOGRAPHIC.\"DAYS_STAY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "For", "how", "many", "days", "Stephanie", "Sechan", "stayed", "in", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DAYS_STAY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "5" ] }, { "key": "9f46ec724f05eabbc56834aac5d8c551", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 0, 12 ] ], "sel": 0 }, "question_refine": "Specify the ethnic origin of the subject named Stephanie Suchan", "sql": "SELECT DEMOGRAPHIC.\"ETHNICITY\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "Specify", "the", "ethnic", "origin", "of", "the", "subject", "named", "Stephanie", "Suchan" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ETHNICITY\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "WHITE" ] }, { "key": "ac5ff199a31192f91afcf9220dbdb50b", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 0, 21 ] ], "sel": 0 }, "question_refine": "when did the patient stephanie suchan get discharged?", "sql": "SELECT DEMOGRAPHIC.\"DISCHTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "when", "did", "the", "patient", "stephanie", "suchan", "get", "discharged", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DISCHTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "2145-08-09 17:50:00" ] }, { "key": "a46d3d925c662de7a83922c62ca97e98", "format": { "table": [ 0, 1 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 1, 3 ] ], "sel": 0 }, "question_refine": "tell me the short title of diagnoses for patient stephanie suchan.", "sql": "SELECT DIAGNOSES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN DIAGNOSES on DEMOGRAPHIC.HADM_ID = DIAGNOSES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "tell", "me", "the", "short", "title", "of", "diagnoses", "for", "patient", "stephanie", "suchan", "." ], "sql_tok": [ "SELECT", "DIAGNOSES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "DIAGNOSES", "on", "DEMOGRAPHIC.HADM_ID", "=", "DIAGNOSES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "Ac posthemorrhag anemia", "Mv collision NOS-driver", "Myalgia and myositis NOS", "Pleural effusion NOS", "Rheumatoid arthritis", "T1-t6 fx-cl/cord inj NEC" ] }, { "key": "100bb3105ffdcb4cfd369197eb54f0f3", "format": { "table": [ 0, 2 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 2, 3 ] ], "sel": 0 }, "question_refine": "mention the procedure short title of subject name stephanie suchan.", "sql": "SELECT PROCEDURES.\"SHORT_TITLE\" FROM DEMOGRAPHIC INNER JOIN PROCEDURES on DEMOGRAPHIC.HADM_ID = PROCEDURES.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "mention", "the", "procedure", "short", "title", "of", "subject", "name", "stephanie", "suchan", "." ], "sql_tok": [ "SELECT", "PROCEDURES.\"SHORT_TITLE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PROCEDURES", "on", "DEMOGRAPHIC.HADM_ID", "=", "PROCEDURES.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "Drsl/dslmb fus post/post", "Fus/refus 4-8 vertebrae", "Spinal canal explor NEC" ] }, { "key": "aa270f02ccb751ae8d962d0ebb685aa1", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 3, 3 ] ], "sel": 0 }, "question_refine": "what is the drug type of patient name stephanie suchan?", "sql": "SELECT PRESCRIPTIONS.\"DRUG_TYPE\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "what", "is", "the", "drug", "type", "of", "patient", "name", "stephanie", "suchan", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"DRUG_TYPE\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "BASE", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN", "MAIN" ] }, { "key": "891ff71c0291fb8c625b26a05cf602d9", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 3, 4 ] ], "sel": 0 }, "question_refine": "what is the drug name used by the patient stephanie suchan?", "sql": "SELECT PRESCRIPTIONS.\"DRUG\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "what", "is", "the", "drug", "name", "used", "by", "the", "patient", "stephanie", "suchan", "?" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"DRUG\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "0.9% Sodium Chloride", "5% Dextrose", "Amitriptyline", "Amitriptyline", "Amlodipine", "Bag", "Bag", "Bag", "Bisacodyl", "Bisacodyl", "Bisacodyl", "Calcium Carbonate", "Calcium Gluconate", "Calcium Gluconate", "Calcium Gluconate", "Dexamethasone", "Dexamethasone", "Dexamethasone", "Dextrose 50%", "Dextrose 50%", "Diazepam", "Docusate Sodium", "Docusate Sodium", "Estrogens Conjugated", "Estrogens Conjugated", "Famc", "Famotidine", "Famvir", "Furosemide", "Gabapentin", "Gabapentin", "Gabapentin", "Gabapentin", "Glucagon", "Glucagon", "HYDROmorphone", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "HYDROmorphone (Dilaudid)", "Heparin", "Heparin", "Heparin", "Insulin", "Insulin", "Insulin", "Iso-Osmotic Sodium Chloride", "Lorazepam", "Magnesium Sulfate", "Magnesium Sulfate", "Magnesium Sulfate", "Morphine Sulfate", "Omeprazole", "Pantoprazole", "Pantoprazole", "Potassium Chl 20 mEq / 1000 mL NS", "Potassium Chloride", "Potassium Chloride", "Potassium Chloride", "Potassium Phosphate", "PredniSONE", "PredniSONE", "PredniSONE", "SW", "Scopolamine Patch", "Senna", "Senna", "Sodium Chloride 0.9% Flush", "Sodium Chloride 0.9% Flush", "Sodium Chloride 0.9% Flush", "Sodium Chloride Nasal", "Vancomycin", "Vial", "Vial" ] }, { "key": "01e59ed775997881d7cc02d7305220f7", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 4, 6 ] ], "sel": 0 }, "question_refine": "what is the lab test name that the patient stephanie suchan underwent?", "sql": "SELECT LAB.\"LABEL\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "what", "is", "the", "lab", "test", "name", "that", "the", "patient", "stephanie", "suchan", "underwent", "?" ], "sql_tok": [ "SELECT", "LAB.\"LABEL\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Anion Gap", "Base Excess", "Basophils", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Bicarbonate", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calcium, Total", "Calculated Bicarbonate, Whole Blood", "Calculated Bicarbonate, Whole Blood", "Calculated Total CO2", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride", "Chloride, Whole Blood", "Chloride, Whole Blood", "Creatine Kinase, MB Isoenzyme", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Creatinine", "Eosinophils", "Epithelial Cells", "Fibrinogen, Functional", "Free Calcium", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Glucose", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit", "Hematocrit, Calculated", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hemoglobin", "Hyaline Casts", "Lactate", "Lipase", "Lymphocytes", "MCH", "MCH", "MCH", "MCH", "MCH", "MCH", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCHC", "MCV", "MCV", "MCV", "MCV", "MCV", "MCV", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Magnesium", "Monocytes", "Neutrophils", "O2 Flow", "Oxygen", "Oxygen Saturation", "PT", "PT", "PT", "PT", "PTT", "PTT", "PTT", "PTT", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Phosphate", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Platelet Count", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium", "Potassium, Whole Blood", "Potassium, Whole Blood", "Protein", "RBC", "RDW", "RDW", "RDW", "RDW", "RDW", "RDW", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Red Blood Cells", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium", "Sodium, Whole Blood", "Sodium, Whole Blood", "Specific Gravity", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urea Nitrogen", "Urobilinogen", "WBC", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "White Blood Cells", "pCO2", "pH", "pH", "pO2" ] }, { "key": "9052ed7f485f07e69a4872d7bf18bb45", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Stephanie Suchan" ] ], "agg_col": [ [ 4, 8 ] ], "sel": 0 }, "question_refine": "find out the category of lab test for patient stephanie suchan.", "sql": "SELECT LAB.\"CATEGORY\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Stephanie Suchan\"", "question_refine_tok": [ "find", "out", "the", "category", "of", "lab", "test", "for", "patient", "stephanie", "suchan", "." ], "sql_tok": [ "SELECT", "LAB.\"CATEGORY\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Stephanie", "Suchan\"" ], "answer": [ "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Blood Gas", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Chemistry", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology", "Hematology" ] }, { "key": "10822f7eec6c3aa7af2078923e5b8148", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 0, 7 ] ], "sel": 0 }, "question_refine": "which language does patient paul edwards speak?", "sql": "SELECT DEMOGRAPHIC.\"LANGUAGE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "which", "language", "does", "patient", "paul", "edwards", "speak", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"LANGUAGE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "ENGL" ] }, { "key": "a6b824de0e783a5f6eded81625061bbe", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 0, 11 ] ], "sel": 0 }, "question_refine": "paul edwards is covered under which health insurance?", "sql": "SELECT DEMOGRAPHIC.\"INSURANCE\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "paul", "edwards", "is", "covered", "under", "which", "health", "insurance", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"INSURANCE\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "Private" ] }, { "key": "a7285ffa3213ab37d2c756b87b37babf", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "which primary disease is the patient paul edwards suffering from?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "which", "primary", "disease", "is", "the", "patient", "paul", "edwards", "suffering", "from", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "HYPERGLYCEMIA;HYPONATREMIA" ] }, { "key": "0055629048450c85a45c53fcb015c8bf", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 0, 20 ] ], "sel": 0 }, "question_refine": "what is the admission time of the Paul Edwards?", "sql": "SELECT DEMOGRAPHIC.\"ADMITTIME\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "what", "is", "the", "admission", "time", "of", "the", "Paul", "Edwards", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMITTIME\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "2125-03-19 23:04:00" ] }, { "key": "9de102f878a21d71b64badbf34ba36af", "format": { "table": [ 0, 3 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 3, 2 ] ], "sel": 0 }, "question_refine": "Specify the ICU stay id for the subject named Paul Edwards", "sql": "SELECT PRESCRIPTIONS.\"ICUSTAY_ID\" FROM DEMOGRAPHIC INNER JOIN PRESCRIPTIONS on DEMOGRAPHIC.HADM_ID = PRESCRIPTIONS.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "Specify", "the", "ICU", "stay", "id", "for", "the", "subject", "named", "Paul", "Edwards" ], "sql_tok": [ "SELECT", "PRESCRIPTIONS.\"ICUSTAY_ID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "PRESCRIPTIONS", "on", "DEMOGRAPHIC.HADM_ID", "=", "PRESCRIPTIONS.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861", "206861" ] }, { "key": "83412574faf1462aa5aee780eaa94ca6", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Paul Edwards" ] ], "agg_col": [ [ 4, 7 ] ], "sel": 0 }, "question_refine": "specify the lab test fluid of patient paul edwards", "sql": "SELECT LAB.\"FLUID\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Paul Edwards\"", "question_refine_tok": [ "specify", "the", "lab", "test", "fluid", "of", "patient", "paul", "edwards" ], "sql_tok": [ "SELECT", "LAB.\"FLUID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Paul", "Edwards\"" ], "answer": [ "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Urine", "Urine", "Urine", "Urine", "Urine", "Urine", "Urine" ] }, { "key": "9115b8182d191e8ccf47ad6e721c9742", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 0, 5 ] ], "sel": 0 }, "question_refine": "let me know the birth date of patient kelly gallardo.", "sql": "SELECT DEMOGRAPHIC.\"DOB\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "let", "me", "know", "the", "birth", "date", "of", "patient", "kelly", "gallardo", "." ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DOB\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "2184-09-06 00:00:00" ] }, { "key": "9377ea7a9532e2f0a0509c75c086c8be", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 0, 8 ] ], "sel": 0 }, "question_refine": "What is the religion of Kelley Gallardo?", "sql": "SELECT DEMOGRAPHIC.\"RELIGION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "What", "is", "the", "religion", "of", "Kelley", "Gallardo", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"RELIGION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "UNOBTAINABLE" ] }, { "key": "8f0dceb4e87c48e94403f2207c5c1f90", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 0, 14 ] ], "sel": 0 }, "question_refine": "specify the admission location of patient kelly gallardo", "sql": "SELECT DEMOGRAPHIC.\"ADMISSION_LOCATION\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "specify", "the", "admission", "location", "of", "patient", "kelly", "gallardo" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "PHYS REFERRAL/NORMAL DELI" ] }, { "key": "0d78e61ca912d643a9233b60b95f4b40", "format": { "table": [ 0 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 0, 16 ] ], "sel": 0 }, "question_refine": "What is the primary disease of Kelly Gallardo?", "sql": "SELECT DEMOGRAPHIC.\"DIAGNOSIS\" FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "What", "is", "the", "primary", "disease", "of", "Kelly", "Gallardo", "?" ], "sql_tok": [ "SELECT", "DEMOGRAPHIC.\"DIAGNOSIS\"", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "NEWBORN" ] }, { "key": "0a1afd3f6a8a58a11490424176d9f026", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 4, 2 ] ], "sel": 0 }, "question_refine": "find the item id of kelly gallardo.", "sql": "SELECT LAB.\"ITEMID\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "find", "the", "item", "i", "d", "of", "kelly", "gallardo", "." ], "sql_tok": [ "SELECT", "LAB.\"ITEMID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "50868", "50882", "50883", "50883", "50884", "50884", "50885", "50885", "50902", "50971", "50983", "51143", "51144", "51146", "51200", "51221", "51222", "51244", "51248", "51249", "51250", "51251", "51254", "51255", "51256", "51257", "51265", "51277", "51279", "51301" ] }, { "key": "8ad4b7b39df3ac2ccb2e85d1956e8ad3", "format": { "table": [ 0, 4 ], "cond": [ [ 0, 2, 0, "Kelly Gallardo" ] ], "agg_col": [ [ 4, 7 ] ], "sel": 0 }, "question_refine": "find the lab test fluid of kelly gallardo.", "sql": "SELECT LAB.\"FLUID\" FROM DEMOGRAPHIC INNER JOIN LAB on DEMOGRAPHIC.HADM_ID = LAB.HADM_ID WHERE DEMOGRAPHIC.\"NAME\" = \"Kelly Gallardo\"", "question_refine_tok": [ "find", "the", "lab", "test", "fluid", "of", "kelly", "gallardo", "." ], "sql_tok": [ "SELECT", "LAB.\"FLUID\"", "FROM", "DEMOGRAPHIC", "INNER", "JOIN", "LAB", "on", "DEMOGRAPHIC.HADM_ID", "=", "LAB.HADM_ID", "WHERE", "DEMOGRAPHIC.\"NAME\"", "=", "\"Kelly", "Gallardo\"" ], "answer": [ "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood", "Blood" ] }, { "key": "9382a7fab8590394cd3d4db8b932aace", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "what is the maximum days of hospital stay for female patients ?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\"", "question_refine_tok": [ "what", "is", "the", "maximum", "days", "of", "hospital", "stay", "for", "female", "patients", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"" ], "answer": [ "181" ] }, { "key": "07431ff7a6c6bd3c08e6a26a84e600b3", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "what is the maximum days of hospital stay of patients whose gender is male?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\"", "question_refine_tok": [ "what", "is", "the", "maximum", "days", "of", "hospital", "stay", "of", "patients", "whose", "gender", "is", "male", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"" ], "answer": [ "294" ] }, { "key": "8a2f27186a6f9174f5f9346999f666f2", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "URGENT" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "what is the minimum days of hospital stay of patients whose admission type is urgent?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\"", "question_refine_tok": [ "what", "is", "the", "minimum", "days", "of", "hospital", "stay", "of", "patients", "whose", "admission", "type", "is", "urgent", "?" ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"" ], "answer": [ "-1" ] }, { "key": "05bac85c2939f9bbec8d57102c7b6156", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "NEWBORN" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "find the minimum days of hospital stay for newborns.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"NEWBORN\"", "question_refine_tok": [ "find", "the", "minimum", "days", "of", "hospital", "stay", "for", "newborns", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"NEWBORN\"" ], "answer": [ "-1" ] }, { "key": "0264eb2e7e0075c9cfef5cec114f92df", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Private" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "calculate the maximum days for which patients with private health insurance have been hospitalized.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Private\"", "question_refine_tok": [ "calculate", "the", "maximum", "days", "for", "which", "patients", "with", "private", "health", "insurance", "have", "been", "hospitalized", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"" ], "answer": [ "206" ] }, { "key": "a862cb556c8a303b9fd05ffbc3866738", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "BLACK/HAITIAN" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "What is the minimum days of hospital stay for patients who are of black/haitian ethnicity?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/HAITIAN\"", "question_refine_tok": [ "What", "is", "the", "minimum", "days", "of", "hospital", "stay", "for", "patients", "who", "are", "of", "black/haitian", "ethnicity", "?" ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/HAITIAN\"" ], "answer": [ "0" ] }, { "key": "0e366fd23450de6fce0205772c03c7d8", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "ASIAN" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "give the average duration of hospital stay for asian patients.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"ASIAN\"", "question_refine_tok": [ "give", "the", "average", "duration", "of", "hospital", "stay", "for", "asian", "patients", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"ASIAN\"" ], "answer": [ "8.216699801192844" ] }, { "key": "026b31c845468f221e7fa3ce74c7ca5f", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "HISPANIC OR LATINO" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "calculate the average days for which hispanic or latino patients have stayed in hospital.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"HISPANIC OR LATINO\"", "question_refine_tok": [ "calculate", "the", "average", "days", "for", "which", "hispanic", "or", "latino", "patients", "have", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"HISPANIC", "OR", "LATINO\"" ], "answer": [ "9.577240566037736" ] }, { "key": "07dd887d78325747ddf8d7f6a4cc952b", "format": { "table": [ 0 ], "cond": [ [ 0, 14, 0, "CLINIC REFERRAL/PREMATURE" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "For how long the patients admitted to clinic referral (premature) stayed in the hospital?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"CLINIC REFERRAL/PREMATURE\"", "question_refine_tok": [ "For", "how", "long", "the", "patients", "admitted", "to", "clinic", "referral", "(", "premature", ")", "stayed", "in", "the", "hospital", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"CLINIC", "REFERRAL/PREMATURE\"" ], "answer": [ "206" ] }, { "key": "a6cecf07aa5066f7bc97d4afef5e4767", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "BRAIN MASS;INTRACRANIAL HEMORRHAGE" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "what is the minimum days for which patients with brain mass; intracranial hemorrhage were hospitalized?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRAIN MASS;INTRACRANIAL HEMORRHAGE\"", "question_refine_tok": [ "what", "is", "the", "minimum", "days", "for", "which", "patients", "with", "brain", "mass", ";", "intracranial", "hemorrhage", "were", "hospitalized", "?" ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRAIN", "MASS;INTRACRANIAL", "HEMORRHAGE\"" ], "answer": [ "4" ] }, { "key": "099986280545b8297552cdfa2b1f8f88", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "VENTRICULAR TACHYCARDIA" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "calculate the minimum duration of hospital stay for patients who had ventricular tachycardia as primary disease.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"VENTRICULAR TACHYCARDIA\"", "question_refine_tok": [ "calculate", "the", "minimum", "duration", "of", "hospital", "stay", "for", "patients", "who", "had", "ventricular", "tachycardia", "as", "primary", "disease", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"VENTRICULAR", "TACHYCARDIA\"" ], "answer": [ "0" ] }, { "key": "0e6e157150b6804faa15e113bdd34edd", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "S/P HANGING" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "calculate the maximum days of hospitalization for patients with s/p hanging primary disease.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"S/P HANGING\"", "question_refine_tok": [ "calculate", "the", "maximum", "days", "of", "hospitalization", "for", "patients", "with", "s", "/", "p", "hanging", "primary", "disease", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"S/P", "HANGING\"" ], "answer": [ "163" ] }, { "key": "0505b2e7a406ecc63693aa9f33c0af26", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "S/P FALL" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "what is the average days of hospital stay of patients whose primary disease is s/p fall?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"S/P FALL\"", "question_refine_tok": [ "what", "is", "the", "average", "days", "of", "hospital", "stay", "of", "patients", "whose", "primary", "disease", "is", "s", "/", "p", "fall", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"S/P", "FALL\"" ], "answer": [ "9.004504504504505" ] }, { "key": "075dfde202da217a38664c06dfb7fc1d", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "HYPERTENSION;RULE OUT CORONARY ARTERY DISEASE\\CARDIAC CATH" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "what is the maximum number of days of hospital stay for patients with hypertension but not coronary artery disease/cardiac cath?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPERTENSION;RULE OUT CORONARY ARTERY DISEASE\\CARDIAC CATH\"", "question_refine_tok": [ "what", "is", "the", "maximum", "number", "of", "days", "of", "hospital", "stay", "for", "patients", "with", "hypertension", "but", "not", "coronary", "artery", "disease", "/", "cardiac", "cath", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPERTENSION;RULE", "OUT", "CORONARY", "ARTERY", "DISEASE\\CARDIAC", "CATH\"" ], "answer": [ "4" ] }, { "key": "07a359a1b5b143af812f602a0f4efc3b", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "PITUITARY BLEED" ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "what is the maximum days of hospital stay of patients whose primary disease is pituitary bleed?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"PITUITARY BLEED\"", "question_refine_tok": [ "what", "is", "the", "maximum", "days", "of", "hospital", "stay", "of", "patients", "whose", "primary", "disease", "is", "pituitary", "bleed", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PITUITARY", "BLEED\"" ], "answer": [ "1" ] }, { "key": "a09e87b1a123bd380b2c2cce58c57df5", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 3, 68 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "Calculate the maximum days for which patients of 68 years of age or older stayed in hospital.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" >= \"68\"", "question_refine_tok": [ "Calculate", "the", "maximum", "days", "for", "which", "patients", "of", "68", "years", "of", "age", "or", "older", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", ">=", "\"68\"" ], "answer": [ "191" ] }, { "key": "bbbbcdd36fc4c67e7dc5d9127a958509", "format": { "table": [ 0 ], "cond": [ [ 0, 4, 3, 20 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "calculate the minimum days for which patients aged 20 years or older were hospitalized.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"AGE\" >= \"20\"", "question_refine_tok": [ "calculate", "the", "minimum", "days", "for", "which", "patients", "aged", "20", "years", "or", "older", "were", "hospitalized", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"AGE\"", ">=", "\"20\"" ], "answer": [ "-1" ] }, { "key": "0367a0f03bb46a2d3edf35a1ce8632f3", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 1, 2180 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "what is the average days of hospital stay for the patients born after 2180?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" > \"2180\"", "question_refine_tok": [ "what", "is", "the", "average", "days", "of", "hospital", "stay", "for", "the", "patients", "born", "after", "2180", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2180\"" ], "answer": [ "11.461634435433561" ] }, { "key": "876d21e0b155dacd669c5089a1f6b66e", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 1, 2071 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "Average out the duration of hospital stay for patients born after the year 2071", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" > \"2071\"", "question_refine_tok": [ "Average", "out", "the", "duration", "of", "hospital", "stay", "for", "patients", "born", "after", "the", "year", "2071" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2071\"" ], "answer": [ "9.83391865301751" ] }, { "key": "0f85a50055cfb411dd0b95a57d97191f", "format": { "table": [ 0 ], "cond": [ [ 0, 18, 1, 2200 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 3 }, "question_refine": "find the minimum number of days of hospital stay for patients born before the year 2200.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOB_YEAR\" > \"2200\"", "question_refine_tok": [ "find", "the", "minimum", "number", "of", "days", "of", "hospital", "stay", "for", "patients", "born", "before", "the", "year", "2200", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2200\"" ], "answer": [ "2" ] }, { "key": "8cb9d9cd9777cb7de0f280d81e661f92", "format": { "table": [ 0 ], "cond": [ [ 0, 19, 2, 2154.0 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 4 }, "question_refine": "what is the average days of hospital stay of patients who died before year 2154?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOD_YEAR\" < \"2154.0\"", "question_refine_tok": [ "what", "is", "the", "average", "days", "of", "hospital", "stay", "of", "patients", "who", "died", "before", "year", "2154", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<", "\"2154.0\"" ], "answer": [ "10.69376670402621" ] }, { "key": "8758789c5295576a106780e5c140c9bd", "format": { "table": [ 0 ], "cond": [ [ 0, 19, 2, 2164.0 ] ], "agg_col": [ [ 0, 10 ] ], "sel": 2 }, "question_refine": "calculate the maximum days for which patients who died before 2164 stayed in hospital.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"DAYS_STAY\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DOD_YEAR\" < \"2164.0\"", "question_refine_tok": [ "calculate", "the", "maximum", "days", "for", "which", "patients", "who", "died", "before", "2164", "stayed", "in", "hospital", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"DAYS_STAY\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DOD_YEAR\"", "<", "\"2164.0\"" ], "answer": [ "294" ] }, { "key": "a01adcfe9f808af2f0964d8e7bea89c4", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 6, 0, "F" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of married female patients.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"GENDER\" = \"F\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "married", "female", "patients", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"" ], "answer": [ "63.56269226036668" ] }, { "key": "96f280508885ff11a9f9b6cbfbc3ff0b", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "DIVORCED" ], [ 0, 6, 0, "F" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of female divorced patients.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"DIVORCED\" AND DEMOGRAPHIC.\"GENDER\" = \"F\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "female", "divorced", "patients", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"DIVORCED\"", "AND", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"" ], "answer": [ "94" ] }, { "key": "9fc4764cc38d024d1682c51ce690b975", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 6, 0, "M" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of unmarried male patients.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"GENDER\" = \"M\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "unmarried", "male", "patients", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"" ], "answer": [ "94" ] }, { "key": "043f8f8307b509641e9efc3a7189cd0a", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 9, 0, "ELECTIVE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "calculate the minimum age of married patients who had elective type hospital admission.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\"", "question_refine_tok": [ "calculate", "the", "minimum", "age", "of", "married", "patients", "who", "had", "elective", "type", "hospital", "admission", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"" ], "answer": [ "21" ] }, { "key": "86d137b429120508a500a6853e984c09", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 11, 0, "Self Pay" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of married patients admitted on self pay status", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "married", "patients", "admitted", "on", "self", "pay", "status" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"" ], "answer": [ "77" ] }, { "key": "00942a70682dd4a711f87a01a76f6f4b", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 14, 0, "CLINIC REFERRAL/PREMATURE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of patient with single as marital status and admitted under clinic referral/premature?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"ADMISSION_LOCATION\" = \"CLINIC REFERRAL/PREMATURE\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "patient", "with", "single", "as", "marital", "status", "and", "admitted", "under", "clinic", "referral", "/", "premature", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"ADMISSION_LOCATION\"", "=", "\"CLINIC", "REFERRAL/PREMATURE\"" ], "answer": [ "53.28832487309645" ] }, { "key": "04ab9977c1bb2580994bec34d2bf7e89", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 15, 0, "SNF" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of patients whose marital status is married and discharge location is snf?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SNF\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "patients", "whose", "marital", "status", "is", "married", "and", "discharge", "location", "is", "snf", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SNF\"" ], "answer": [ "76.0259086002159" ] }, { "key": "025adce7a3b46ed090cf77e5dcc9c5ec", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 4, 3, 41 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "Calculate the maximum age of married patients who are 41 years or older.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"AGE\" >= \"41\"", "question_refine_tok": [ "Calculate", "the", "maximum", "age", "of", "married", "patients", "who", "are", "41", "years", "or", "older", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"41\"" ], "answer": [ "100" ] }, { "key": "013a940a6c002ff9dac66a9c19992514", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 4, 3, 44 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "What is the average age of patients whose marital status is married and are aged 44 years or older?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"AGE\" >= \"44\"", "question_refine_tok": [ "What", "is", "the", "average", "age", "of", "patients", "whose", "marital", "status", "is", "married", "and", "are", "aged", "44", "years", "or", "older", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"44\"" ], "answer": [ "67.74338718267353" ] }, { "key": "817fe7ae70c2b5623a475f9d9081d340", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "MARRIED" ], [ 0, 4, 3, 47 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of married patients aged 47 years or more?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"MARRIED\" AND DEMOGRAPHIC.\"AGE\" >= \"47\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "married", "patients", "aged", "47", "years", "or", "more", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"MARRIED\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"47\"" ], "answer": [ "100" ] }, { "key": "9da3b03e4f367ed866072b9f7c825921", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 18, 1, 2087 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of unmarried patients born after 2087.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"DOB_YEAR\" > \"2087\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "unmarried", "patients", "born", "after", "2087", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2087\"" ], "answer": [ "44.61355174981385" ] }, { "key": "91e4268fef7e4c6940983b195523dd3d", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 18, 1, 2097 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "Calculate the average age of unmarried patients born after the year 2097", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"DOB_YEAR\" > \"2097\"", "question_refine_tok": [ "Calculate", "the", "average", "age", "of", "unmarried", "patients", "born", "after", "the", "year", "2097" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2097\"" ], "answer": [ "43.05845972610808" ] }, { "key": "a936b3862b737cd672397efa1a7ea9b0", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 18, 1, 2073 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of patients whose marital status is single and who were born before the year 2073?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"DOB_YEAR\" > \"2073\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "patients", "whose", "marital", "status", "is", "single", "and", "who", "were", "born", "before", "the", "year", "2073", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2073\"" ], "answer": [ "89" ] }, { "key": "adae5e26acd2cff0c947689a1e07525e", "format": { "table": [ 0 ], "cond": [ [ 0, 3, 0, "SINGLE" ], [ 0, 22, 3, 2156 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "Specify the average age of unmarried patients admitted in or after the year 2156", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"MARITAL_STATUS\" = \"SINGLE\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2156\"", "question_refine_tok": [ "Specify", "the", "average", "age", "of", "unmarried", "patients", "admitted", "in", "or", "after", "the", "year", "2156" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"MARITAL_STATUS\"", "=", "\"SINGLE\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2156\"" ], "answer": [ "51.47936772046589" ] }, { "key": "8a8314389b88631016bc7ce9cefe7351", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 11, 0, "Medicaid" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of male patients with medicaid insurance?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "male", "patients", "with", "medicaid", "insurance", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"" ], "answer": [ "38.32910609341169" ] }, { "key": "0e5bbc6f42fc88135fb495c1a3303902", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 11, 0, "Private" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of male patients with a private insurance policy?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Private\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "male", "patients", "with", "a", "private", "insurance", "policy", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Private\"" ], "answer": [ "40.005622133451695" ] }, { "key": "fffdd25c4b1fd2c10864a81fa85fd02e", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 12, 0, "WHITE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "find the minimum age of white female patients .", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\"", "question_refine_tok": [ "find", "the", "minimum", "age", "of", "white", "female", "patients", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"" ], "answer": [ "0" ] }, { "key": "a741e084792d0b494db1b7f806b144d5", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 12, 0, "HISPANIC OR LATINO" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "how many male patients are of hispanic or latino ethnicity?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"HISPANIC OR LATINO\"", "question_refine_tok": [ "how", "many", "male", "patients", "are", "of", "hispanic", "or", "latino", "ethnicity", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"HISPANIC", "OR", "LATINO\"" ], "answer": [ "40.97273612463486" ] }, { "key": "00b8efccccac56dfadd92400425b33fa", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 13, 0, 0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of female patients who died of death status 0?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "female", "patients", "who", "died", "of", "death", "status", "0", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"" ], "answer": [ "98" ] }, { "key": "907eb0304115dca64c1217427151d675", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 13, 0, 0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of male patients who are still alive.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "male", "patients", "who", "are", "still", "alive", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"" ], "answer": [ "100" ] }, { "key": "046dedd9201c79ad138cee000f7e9354", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 15, 0, "LONG TERM CARE HOSPITAL" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of female patients who were discharged to long term care hospital.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"LONG TERM CARE HOSPITAL\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "female", "patients", "who", "were", "discharged", "to", "long", "term", "care", "hospital", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"LONG", "TERM", "CARE", "HOSPITAL\"" ], "answer": [ "68.70277777777778" ] }, { "key": "88e7d0489a8a25e29d2d72fe43c208e8", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 15, 0, "SNF" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "find the maximum age of male patients whose discharge location is snf.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"SNF\"", "question_refine_tok": [ "find", "the", "maximum", "age", "of", "male", "patients", "whose", "discharge", "location", "is", "snf", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"SNF\"" ], "answer": [ "100" ] }, { "key": "07f9e5ea7ba538b73cce9e2446522bf8", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 16, 0, "GASTROINTESTINAL BLEED" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "Calculate the minimum age of female patients who had gastrointestinal bleed as their primary disease?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"GASTROINTESTINAL BLEED\"", "question_refine_tok": [ "Calculate", "the", "minimum", "age", "of", "female", "patients", "who", "had", "gastrointestinal", "bleed", "as", "their", "primary", "disease", "?" ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GASTROINTESTINAL", "BLEED\"" ], "answer": [ "28" ] }, { "key": "a04053b65b4e0a526f0eb2e1b027f139", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 16, 0, "OVERDOSE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of male patients diagnosed with primary disease overdose?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"OVERDOSE\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "male", "patients", "diagnosed", "with", "primary", "disease", "overdose", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"OVERDOSE\"" ], "answer": [ "73" ] }, { "key": "95715270fb6291a1bc4411e87f316243", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 4, 3, 24 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "Find out the average age of male patients that are 24 years old or older.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"AGE\" >= \"24\"", "question_refine_tok": [ "Find", "out", "the", "average", "age", "of", "male", "patients", "that", "are", "24", "years", "old", "or", "older", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"24\"" ], "answer": [ "63.599656234333594" ] }, { "key": "02147b1f44bdb370c58befcdb779f4f6", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 4, 3, 54 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "Calculate the minimum age of male patients who are 54 years or older.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"AGE\" >= \"54\"", "question_refine_tok": [ "Calculate", "the", "minimum", "age", "of", "male", "patients", "who", "are", "54", "years", "or", "older", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"54\"" ], "answer": [ "54" ] }, { "key": "0d6939ea7e7229353b55c8e51e27e242", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "F" ], [ 0, 10, 0, 1 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of female patients who were admitted to hospital for a day.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"F\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"1\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "female", "patients", "who", "were", "admitted", "to", "hospital", "for", "a", "day", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"F\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"1\"" ], "answer": [ "100" ] }, { "key": "ac4878fcb21e4703a73ca747ce9bd819", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 10, 0, 5 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of male patients who stayed in hospital for 5 days?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"5\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "male", "patients", "who", "stayed", "in", "hospital", "for", "5", "days", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"5\"" ], "answer": [ "97" ] }, { "key": "0e952b08f68237025d354d7f78002818", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 10, 0, 20 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "specify the maximum age of male patients who remained admitted in hospital for 20 days. ", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"20\"", "question_refine_tok": [ "specify", "the", "maximum", "age", "of", "male", "patients", "who", "remained", "admitted", "in", "hospital", "for", "20", "days", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"20\"" ], "answer": [ "90" ] }, { "key": "bb32861221acb7493b42a12fce4769b6", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 10, 0, 27 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of male patients who have stayed in hospital for 27 days.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"27\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "male", "patients", "who", "have", "stayed", "in", "hospital", "for", "27", "days", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"27\"" ], "answer": [ "55.25595238095238" ] }, { "key": "822832e2d35ed42025ec20b201dd7eef", "format": { "table": [ 0 ], "cond": [ [ 0, 6, 0, "M" ], [ 0, 18, 1, 2078 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "calculate the minimum age of male patients who were born after 2078.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"GENDER\" = \"M\" AND DEMOGRAPHIC.\"DOB_YEAR\" > \"2078\"", "question_refine_tok": [ "calculate", "the", "minimum", "age", "of", "male", "patients", "who", "were", "born", "after", "2078", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"GENDER\"", "=", "\"M\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2078\"" ], "answer": [ "0" ] }, { "key": "8c182c6e8b8ec7c9edf817d41ad093ae", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "SPAN" ], [ 0, 16, 0, "OVERDOSE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "Calculate the average age of spanish speaking patients who have overdose as the primary disease.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"SPAN\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"OVERDOSE\"", "question_refine_tok": [ "Calculate", "the", "average", "age", "of", "spanish", "speaking", "patients", "who", "have", "overdose", "as", "the", "primary", "disease", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"SPAN\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"OVERDOSE\"" ], "answer": [ "39.666666666666664" ] }, { "key": "925b64a7b970e5a56de55e7db18fbd8f", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "CAPE" ], [ 0, 16, 0, "HYPERGLYCEMIA" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of patients whose language is cape and primary disease is hyperglycemia?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"CAPE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPERGLYCEMIA\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "patients", "whose", "language", "is", "cape", "and", "primary", "disease", "is", "hyperglycemia", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"CAPE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPERGLYCEMIA\"" ], "answer": [ "49.0" ] }, { "key": "a7d6a83b8b3aaf21dafd25bcee27258e", "format": { "table": [ 0 ], "cond": [ [ 0, 7, 0, "ENGL" ], [ 0, 16, 0, "SEPSIS" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of english speaking patients who have sepsis primary disease.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"LANGUAGE\" = \"ENGL\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"SEPSIS\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "english", "speaking", "patients", "who", "have", "sepsis", "primary", "disease", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"LANGUAGE\"", "=", "\"ENGL\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"SEPSIS\"" ], "answer": [ "99" ] }, { "key": "ae1f244625f4fdea70dbcfc038f2a2ed", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "URGENT" ], [ 0, 11, 0, "Self Pay" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of self pay insurance patients who had urgent hospital admission.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"URGENT\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Self Pay\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "self", "pay", "insurance", "patients", "who", "had", "urgent", "hospital", "admission", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"URGENT\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Self", "Pay\"" ], "answer": [ "34.0" ] }, { "key": "928495bf6e5d07038672946ee7801428", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "ELECTIVE" ], [ 0, 11, 0, "Medicaid" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "what is the maximum age of patients whose admission type is elective and insurance is medicaid?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"ELECTIVE\" AND DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\"", "question_refine_tok": [ "what", "is", "the", "maximum", "age", "of", "patients", "whose", "admission", "type", "is", "elective", "and", "insurance", "is", "medicaid", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"ELECTIVE\"", "AND", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"" ], "answer": [ "89" ] }, { "key": "007b736a7e85c0d907a1aa0574bcd582", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 16, 0, "BRAIN MASS;INTRACRANIAL HEMORRHAGE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "how many patients were admitted in emergency primarily for brain mass; intracranial hemorrhage ?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"BRAIN MASS;INTRACRANIAL HEMORRHAGE\"", "question_refine_tok": [ "how", "many", "patients", "were", "admitted", "in", "emergency", "primarily", "for", "brain", "mass", ";", "intracranial", "hemorrhage", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BRAIN", "MASS;INTRACRANIAL", "HEMORRHAGE\"" ], "answer": [ "71.0" ] }, { "key": "935565ac3f8101d1f13fc0393a9f8e6f", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 16, 0, "T5 FRACTURE" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "how many patients were admitted in emergency primarily for t5 fracture?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"T5 FRACTURE\"", "question_refine_tok": [ "how", "many", "patients", "were", "admitted", "in", "emergency", "primarily", "for", "t5", "fracture", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"T5", "FRACTURE\"" ], "answer": [ "56.0" ] }, { "key": "043f09d41386cd759fd9242478d6e6a9", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 22, 3, 2173 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "what is the minimum age of patients whose admission type is emergency and admitted in the year 2173 or after?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2173\"", "question_refine_tok": [ "what", "is", "the", "minimum", "age", "of", "patients", "whose", "admission", "type", "is", "emergency", "and", "admitted", "in", "the", "year", "2173", "or", "after", "?" ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2173\"" ], "answer": [ "0" ] }, { "key": "a91f19e15d1efa55a1fee067b317778e", "format": { "table": [ 0 ], "cond": [ [ 0, 9, 0, "EMERGENCY" ], [ 0, 22, 3, 2175 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "find the minimum age of patients who were admitted in emergency in or after the year 2175.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ADMISSION_TYPE\" = \"EMERGENCY\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2175\"", "question_refine_tok": [ "find", "the", "minimum", "age", "of", "patients", "who", "were", "admitted", "in", "emergency", "in", "or", "after", "the", "year", "2175", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ADMISSION_TYPE\"", "=", "\"EMERGENCY\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2175\"" ], "answer": [ "0" ] }, { "key": "0f06b77b423037f77d9cf551771a846d", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 0, 12, 0, "BLACK/CAPE VERDEAN" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of medicaid patients who belong to black/cape verdean ethnic background.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND DEMOGRAPHIC.\"ETHNICITY\" = \"BLACK/CAPE VERDEAN\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "medicaid", "patients", "who", "belong", "to", "black", "/", "cape", "verdean", "ethnic", "background", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"BLACK/CAPE", "VERDEAN\"" ], "answer": [ "88" ] }, { "key": "0c4724e628885e5157f1df2895d68640", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Medicaid" ], [ 0, 16, 0, "CEREBRAL ANEURYSM/SDA" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "calculate the minimum age of medicaid insurance patients who have cerebral aneurysm/sda primary disease.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Medicaid\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"CEREBRAL ANEURYSM/SDA\"", "question_refine_tok": [ "calculate", "the", "minimum", "age", "of", "medicaid", "insurance", "patients", "who", "have", "cerebral", "aneurysm", "/", "sda", "primary", "disease", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Medicaid\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"CEREBRAL", "ANEURYSM/SDA\"" ], "answer": [ "38" ] }, { "key": "a5ed08bdcb4c1e8be442640558d76f49", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Government" ], [ 0, 10, 0, 1 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of government health insurance patients who were admitted in hospital for a day.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"1\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "government", "health", "insurance", "patients", "who", "were", "admitted", "in", "hospital", "for", "a", "day", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"1\"" ], "answer": [ "27.01290322580645" ] }, { "key": "ad0222178143c1561a0a8a027757997f", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Government" ], [ 0, 19, 2, 2154.0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "find the maximum age of patients with government insurance who expired before the year 2154.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND DEMOGRAPHIC.\"DOD_YEAR\" < \"2154.0\"", "question_refine_tok": [ "find", "the", "maximum", "age", "of", "patients", "with", "government", "insurance", "who", "expired", "before", "the", "year", "2154", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<", "\"2154.0\"" ], "answer": [ "89" ] }, { "key": "0af601deae0ffdd1c1ffcfb2b892150c", "format": { "table": [ 0 ], "cond": [ [ 0, 11, 0, "Government" ], [ 0, 22, 3, 2177 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "Out of total number of patients admitted in or after 2177, calculate the maximum age of patients on government insurance", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"INSURANCE\" = \"Government\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2177\"", "question_refine_tok": [ "Out", "of", "total", "number", "of", "patients", "admitted", "in", "or", "after", "2177", ",", "calculate", "the", "maximum", "age", "of", "patients", "on", "government", "insurance" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"INSURANCE\"", "=", "\"Government\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2177\"" ], "answer": [ "84" ] }, { "key": "032b7fd8d2d178537cac4b13edbb0d02", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 0, 10, 0, 2 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "calculate the average age of white ethnic background patients who stayed in hospital for 2 days.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"2\"", "question_refine_tok": [ "calculate", "the", "average", "age", "of", "white", "ethnic", "background", "patients", "who", "stayed", "in", "hospital", "for", "2", "days", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"2\"" ], "answer": [ "44.04178044784271" ] }, { "key": "00a69fd54e5ae5eb444fc1cc6c67a71f", "format": { "table": [ 0 ], "cond": [ [ 0, 12, 0, "WHITE" ], [ 0, 22, 3, 2120 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "how many patients belonging to white ethnic origin were admitted in the year less than or equal to 2120?", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"ETHNICITY\" = \"WHITE\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2120\"", "question_refine_tok": [ "how", "many", "patients", "belonging", "to", "white", "ethnic", "origin", "were", "admitted", "in", "the", "year", "less", "than", "or", "equal", "to", "2120", "?" ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"ETHNICITY\"", "=", "\"WHITE\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2120\"" ], "answer": [ "100" ] }, { "key": "0c5abc6a996b56827cc5e3c820f9fc6e", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 0 ], [ 0, 15, 0, "DISC-TRAN CANCER/CHLDRN H" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "tell me the minimum age of patients with death status as 0 and discharge location as disc-tran cancer chldrn h.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"DISC-TRAN CANCER/CHLDRN H\"", "question_refine_tok": [ "tell", "me", "the", "minimum", "age", "of", "patients", "with", "death", "status", "as", "0", "and", "discharge", "location", "as", "disc", "-", "tran", "cancer", "chldrn", "h." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"DISC-TRAN", "CANCER/CHLDRN", "H\"" ], "answer": [ "0" ] }, { "key": "0c99cbdfd068bcf1ca99f14d7e69b1fc", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 0 ], [ 0, 16, 0, "COPD EXACERBATION" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "What is average age of patients that survived and had a primary disease of COPD exacerbation?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"COPD EXACERBATION\"", "question_refine_tok": [ "What", "is", "average", "age", "of", "patients", "that", "survived", "and", "had", "a", "primary", "disease", "of", "COPD", "exacerbation", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"COPD", "EXACERBATION\"" ], "answer": [ "66.3529411764706" ] }, { "key": "0f6b59272b612f8e29af1fcd07b26294", "format": { "table": [ 0 ], "cond": [ [ 0, 13, 0, 0 ], [ 0, 22, 3, 2121 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "Calculate the average age of living patients admitted to the hospital on or after 2121.", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"EXPIRE_FLAG\" = \"0\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2121\"", "question_refine_tok": [ "Calculate", "the", "average", "age", "of", "living", "patients", "admitted", "to", "the", "hospital", "on", "or", "after", "2121", "." ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"EXPIRE_FLAG\"", "=", "\"0\"", "AND", "DEMOGRAPHIC.\"ADMITYEAR\"", ">=", "\"2121\"" ], "answer": [ "46.00821757667446" ] }, { "key": "0f749a69b07f78a4c26f1deaff3d9478", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "HOME" ], [ 0, 16, 0, "POSTERIOR COMMUNICATING ANEURYSM/SDA" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "Calculate the minimum age of patients who have posterior communicating aneurysm/sda and were discharged home.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"POSTERIOR COMMUNICATING ANEURYSM/SDA\"", "question_refine_tok": [ "Calculate", "the", "minimum", "age", "of", "patients", "who", "have", "posterior", "communicating", "aneurysm/sda", "and", "were", "discharged", "home", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"POSTERIOR", "COMMUNICATING", "ANEURYSM/SDA\"" ], "answer": [ "48" ] }, { "key": "9c1019a7798259f92a6b8ff6f856cc7c", "format": { "table": [ 0 ], "cond": [ [ 0, 15, 0, "HOME HEALTH CARE" ], [ 0, 16, 0, "GASTROINTESTINAL BLEED" ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is the average age of patients who are discharged due to home health care and diagnosed with primary disease gastrointestinal bleed?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DISCHARGE_LOCATION\" = \"HOME HEALTH CARE\" AND DEMOGRAPHIC.\"DIAGNOSIS\" = \"GASTROINTESTINAL BLEED\"", "question_refine_tok": [ "what", "is", "the", "average", "age", "of", "patients", "who", "are", "discharged", "due", "to", "home", "health", "care", "and", "diagnosed", "with", "primary", "disease", "gastrointestinal", "bleed", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DISCHARGE_LOCATION\"", "=", "\"HOME", "HEALTH", "CARE\"", "AND", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GASTROINTESTINAL", "BLEED\"" ], "answer": [ "70.93" ] }, { "key": "87e3e952f4c6888eca35ce87b6a82e7d", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "BOWEL OBSTRUCTION" ], [ 0, 4, 3, 71 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 4 }, "question_refine": "what is average age of patients whose primary disease is bowel obstruction and who are aged equal or more than 71 years?", "sql": "SELECT AVG ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"BOWEL OBSTRUCTION\" AND DEMOGRAPHIC.\"AGE\" >= \"71\"", "question_refine_tok": [ "what", "is", "average", "age", "of", "patients", "whose", "primary", "disease", "is", "bowel", "obstruction", "and", "who", "are", "aged", "equal", "or", "more", "than", "71", "years", "?" ], "sql_tok": [ "SELECT", "AVG", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"BOWEL", "OBSTRUCTION\"", "AND", "DEMOGRAPHIC.\"AGE\"", ">=", "\"71\"" ], "answer": [ "80.89473684210526" ] }, { "key": "0df82d3e22799b2179485006b810705b", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "PNEUMONIA" ], [ 0, 10, 0, 30 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of patients who have pneumonia primary disease and were hospitalized for 30 days.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"PNEUMONIA\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"30\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "patients", "who", "have", "pneumonia", "primary", "disease", "and", "were", "hospitalized", "for", "30", "days", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"PNEUMONIA\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"30\"" ], "answer": [ "78" ] }, { "key": "8188575c168485955174dd92b0caf881", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "GASTROINTESTINAL BLEED" ], [ 0, 10, 0, 17 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "calculate the minimum age of patients who have gastrointestinal bleed primary disease and were hospitalized for 17 days.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"GASTROINTESTINAL BLEED\" AND DEMOGRAPHIC.\"DAYS_STAY\" = \"17\"", "question_refine_tok": [ "calculate", "the", "minimum", "age", "of", "patients", "who", "have", "gastrointestinal", "bleed", "primary", "disease", "and", "were", "hospitalized", "for", "17", "days", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"GASTROINTESTINAL", "BLEED\"", "AND", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"17\"" ], "answer": [ "44" ] }, { "key": "867cf2582e1a2e8d3334cc3214b69472", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "TRANSIENT ISCHEMIC ATTACK" ], [ 0, 18, 1, 2095 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "Calculate the minimum age of patients born after 2095 who have transient ischemic attack as their primary disease.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"TRANSIENT ISCHEMIC ATTACK\" AND DEMOGRAPHIC.\"DOB_YEAR\" > \"2095\"", "question_refine_tok": [ "Calculate", "the", "minimum", "age", "of", "patients", "born", "after", "2095", "who", "have", "transient", "ischemic", "attack", "as", "their", "primary", "disease", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"TRANSIENT", "ISCHEMIC", "ATTACK\"", "AND", "DEMOGRAPHIC.\"DOB_YEAR\"", ">", "\"2095\"" ], "answer": [ "50" ] }, { "key": "a64d7ee4e6048464ae58bbd5755b176b", "format": { "table": [ 0 ], "cond": [ [ 0, 16, 0, "HYPOXIA" ], [ 0, 19, 2, 2155.0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "provide the minimum age of patients primarily diagnosed for hypoxia and expired before the year 2155.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DIAGNOSIS\" = \"HYPOXIA\" AND DEMOGRAPHIC.\"DOD_YEAR\" < \"2155.0\"", "question_refine_tok": [ "provide", "the", "minimum", "age", "of", "patients", "primarily", "diagnosed", "for", "hypoxia", "and", "expired", "before", "the", "year", "2155", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DIAGNOSIS\"", "=", "\"HYPOXIA\"", "AND", 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19, 2, 2131.0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 2 }, "question_refine": "calculate the maximum age of patients who were hospitalized for 20 days and died before 2131.", "sql": "SELECT MAX ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DAYS_STAY\" = \"20\" AND DEMOGRAPHIC.\"DOD_YEAR\" < \"2131.0\"", "question_refine_tok": [ "calculate", "the", "maximum", "age", "of", "patients", "who", "were", "hospitalized", "for", "20", "days", "and", "died", "before", "2131", "." ], "sql_tok": [ "SELECT", "MAX", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"20\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<", "\"2131.0\"" ], "answer": [ "90" ] }, { "key": "06fdfc5ab31f978981e3b81b323b4d0a", "format": { "table": [ 0 ], "cond": [ [ 0, 10, 0, 20 ], [ 0, 19, 2, 2186.0 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "find the minimum age of patients who stayed in the hospital for 20 days and died before the year 2186.", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DAYS_STAY\" = \"20\" AND DEMOGRAPHIC.\"DOD_YEAR\" < \"2186.0\"", "question_refine_tok": [ "find", "the", "minimum", "age", "of", "patients", "who", "stayed", "in", "the", "hospital", "for", "20", "days", "and", "died", "before", "the", "year", "2186", "." ], "sql_tok": [ "SELECT", "MIN", "(", "DEMOGRAPHIC.\"AGE\"", ")", "FROM", "DEMOGRAPHIC", "WHERE", "DEMOGRAPHIC.\"DAYS_STAY\"", "=", "\"20\"", "AND", "DEMOGRAPHIC.\"DOD_YEAR\"", "<", "\"2186.0\"" ], "answer": [ "20" ] }, { "key": "8367cefd0993d59dc5c70209c60326a5", "format": { "table": [ 0 ], "cond": [ [ 0, 10, 0, 4 ], [ 0, 22, 3, 2177 ] ], "agg_col": [ [ 0, 4 ] ], "sel": 3 }, "question_refine": "what is the minimum age of patients who stayed in hospital for 4 days and were admitted in or after the year 2177?", "sql": "SELECT MIN ( DEMOGRAPHIC.\"AGE\" ) FROM DEMOGRAPHIC WHERE DEMOGRAPHIC.\"DAYS_STAY\" = \"4\" AND DEMOGRAPHIC.\"ADMITYEAR\" >= \"2177\"", 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