AndreaBozzo/ceres-open-data-index huggingface dataset:
Hospital Inpatient Discharges (SPARCS De-Identified): Inpatient Quality Indicators (IQI) Area Measures by Patient County: Calendar Year 2015

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ). The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality. All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures. The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.
Hospital Inpatient Discharges (SPARCS De-Identified): Inpatient Quality Indicators (IQI) Area Measures by Patient County: Beginning 2009

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ). The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality. All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures. The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.
Hospital Inpatient Discharges (SPARCS De-Identified): In-Hospital/30-Day Acute Stroke Mortality Rates by Hospital: Beginning 2013

The dataset contains hospital stroke designation and Coverdell registry participation status, acute stroke discharges counts (numerators, denominators), observed, expected and risk-adjusted acute stroke in-hospital/30-day post admission mortality rates with corresponding 95% confidence intervals. Mortality rates risk adjustment was based on the methodology developed by the New York State Department of Health. The purpose of this data set is reporting of hospital-specific risk adjusted acute stroke mortality rates (RAMR) to inform hospitals, to aid initiatives to improve hospital quality performance and measurement, and to identify performance outliers for public reporting.
Hospital Inpatient Discharges (SPARCS De-Identified): Cost Transparency: Beginning 2009

This dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The file contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge.
Hospital Inpatient Discharges (SPARCS De-Identified): Adult Prevention Quality Indicators (PQI) by Zip Code: Calendar Year 2015

This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for calendar year 2015. This dataset is at the zip code level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
Hospital Inpatient Discharges (SPARCS De-Identified): Adult Prevention Quality Indicators (PQI) by Zip Code: Beginning 2009

This dataset is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
Hospital Inpatient Discharges (SPARCS De-Identified): Adult Prevention Quality Indicators (PQI) by County: Beginning 2009

This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. This dataset is at the county level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
Hospital Inpatient Discharges (SPARCS De-Identified): 2024

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. For more information visit: [https://www.health.ny.gov/statistics/sparcs/]
Hospital Inpatient Discharges (SPARCS De-Identified): 2023

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. For more information visit: https://www.health.ny.gov/statistics/sparcs/
Hospital Inpatient Discharges (SPARCS De-Identified): 2022

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. For more information visit: [https://www.health.ny.gov/statistics/sparcs/]
Hospital Inpatient Discharges (SPARCS De-Identified): 2021

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. Note: The full dataset may be downloaded in a smaller, compressed file format from the attachments section.
Hospital Inpatient Discharges (SPARCS De-Identified): 2020

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. Note: The full dataset may be downloaded in a smaller, compressed file format from the attachments section.
Hospital Inpatient Discharges (SPARCS De-Identified): 2019

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. Note: This dataset may be downloaded from the attachments section of this page in a smaller, compressed format.
Hospital Inpatient Discharges (SPARCS De-Identified): 2018

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed. Note: This dataset may be downloaded from the attachments section of this page in a smaller, compressed format.
Hospital Inpatient Discharges (SPARCS De-Identified): 2017

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2016

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2015

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2014

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2013

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2012

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-Identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however, the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2011

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges, and costs.This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2010

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges, and costs. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges (SPARCS De-Identified): 2009

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges and costs. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Hospital Inpatient Discharges by Patient County of Residence (SPARCS De-Identified): Beginning 2009

This dataset is a summary of hospital inpatient discharges from every hospital including Article 28 facilities; Ambulatory Surgery and Emergency Department visits, from the Statewide Planning and Research Cooperative System (SPARCS). The data is rolled up by patient county of residence. This dataset was modified in September 2013 to be in sync with the release of the Hospital Inpatient Discharges (SPARCS De-Identified) datasets. Please refer to the data dictionary for information on the current data available. The SPARCS data has been divided into two distinct datasets: Hospital Discharges by Patient County of Residence and Hospital Discharges by Facility. This is to preserve the confidentiality of identifiable individual information.This dataset does not include facility names.
Hospital Inpatient Discharges by Facility (SPARCS De-Identified): Beginning 2009

The Statewide Planning and Research Cooperative System (SPARCS) is a comprehensive data reporting system which collects patient level detail on patient characteristics, diagnoses, treatments, services, and charges for every hospital discharge from an Article 28 facility; ambulatory surgery discharges from hospital-based ambulatory surgery centers and all other facilities providing ambulatory surgery services; and emergency department visits in New York State. This dataset is a summary of the SPARCS inpatient discharge data.
Hospital Emergency Department Discharges (SPARCS De-Identified): Potentially Preventable Emergency Visit (PPV) Rates by Patient Zip Code: Beginning 2011

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.
Hospital Emergency Department Discharges (SPARCS De-Identified): Potentially Preventable Emergency Visit (PPV) Rates by Patient County: Beginning 2011

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up. The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient and outpatient data and Claritas population information. The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
Hospital Emergency Department Discharges (SPARCS De-Identified): Emergency Department Encounters by Facility: Beginning 2018

This dataset is a summary of the emergency department (ED) encounters reported in SPARCS data, summarized by facility and quarter of visit. ED encounters are classified according to the claim type associated with the SPARCS record into treat and release ED visits, ED visits that required ambulatory surgery, and ED visits that resulted in an inpatient admission.
Hospital-Acquired Infections: Beginning 2008

All acute care hospitals are required to report certain hospital-acquired infections (HAIs) to the New York State Department of Health (NYSDOH). This includes central line-associated blood stream infections; surgical site infections following colon, hip replacement/revision, coronary artery bypass graft, and hysterectomy; Clostridium difficile infections; and carbapenem-resistant Enterobacteriaceae infections.
Home Care Registry Training Data: Beginning 2009

The dataset provides training information extracted from Home Care Registry (HCR) application. HCR is a web-based registry of all personal care and home health aides who have successfully completed a personal care or home health aide training program approved by either the New York State Department of Health (NYSDOH) or the New York State Education Department (NYSED). This registry is the central repository of the individuals who have successfully completed State-approved education or training programs for Home Health Aides and Personal Care Aides. The Training Programs are the sources for most of the training information available in HCR. This dataset is refreshed on monthly basis.
Home Care Registry Summary Of Training Certificates Issued: Beginning 2009

The dataset contains information extracted from Home Care Registry (HCR) application. HCR is a web-based registry of all personal care aides and home health aides who have successfully completed a personal care aide or home health aide training program approved by either the New York State Department of Health (NYSDOH) or the New York State Education Department (NYSED). The dataset provides information about the training certificates issued in a specific region within the State of New York based on Certificate Type, Methodology, Language and the State Agency that approved the Training program that issued the Certificate. This dataset is refreshed on monthly basis. For more information, visit https://apps.health.ny.gov/professionals/home_care/registry/home.action.