DOI: 10.5061/dryad.7sqv9s55x
title: Antimicrobial Resistance Microbiological Dataset (ARMD-ECUH): A deidentified collection of electronic health records from a rural academic health system for antimicrobial resistance research

description: As antimicrobial resistance is increasingly becoming an emergent public
 health issue, quality, real-world electronic health record-based data sets
 available for research are lacking. To help remedy this, we have developed
 the Antimicrobial Resistance Microbiological Dataset: East Carolina
 University Health (ARMD-ECUH), which includes microbiological culture and
 susceptibility results for 261,217 patients from ECU Health from 2015 to
 2025. Additionally, the inclusion of longitudinal data such as
 patient demographics, prior medical histories, medications, and procedures
 adds to the significance of the data set. Clinically relevant data, such
 as the locations where the cultures were gathered, recent laboratory
 values, and vitals taken during the respective encounters, are also
 included. The deidentified ARMD: ECUH data set, with standardized data
 values to minimize the need for data transformations, will allow
 researchers across the globe to improve patient outcomes and increase
 awareness and understanding of antimicrobial resistance.
description: Our Antimicrobial Resistance Microbiological Dataset - East
 Carolina University Health (ARMD-ECUH) data set is a longitudinal
 collection of Epic-based EHR from the ECU Health (ECUH) health system of
 adults (≥18 years old) from 2015 to 2025 (prior to date jittering for
 deidentification purposes). The data set includes deidentified
 microbiological laboratory results for blood, urine, and respiratory
 cultures. Encounter-based vitals, patient demographics, comorbidities,
 socioeconomic factors quantified by the Area Deprivation Index (ADI), and
 prior exposures to medications and procedures are included in the data
 set. All data were collected via a Microsoft Fabric-supported data
 warehouse, which contains daily updates from ECUH’s Epic Clarity database.
 The data were queried using Spark SQL in Fabric notebooks.
 In similar methods described by both ARMD and ARMD-UTSW, all raw data were standardized to assist with future research applications. This standardization includes identifying gender into two anonymized values of “0” or “1” (Null was used for missing gender data), patient ages at the time when the culture was taken were divided into age ranges such as 18-24, 25-34, 35-44, etc. Medication names were also standardized by using generic names. To account for the various reporting methods used by different microbiology laboratories, susceptibility results were consolidated to the values of “susceptible”, “intermediate”, “resistant”, “synergism”, and “inconclusive.” Binary indicators of “0” or “1” were used to designate culture positivity as determined by the inclusion of susceptibility results for positive cultures. Patients with possible active infections were identified by having multiple cultures within the previous two weeks from the encounter and were thus excluded from the data set. Safe Harbor regulations were utilized for the deidentification process, including removing or anonymizing all patient identifiers. This includes identifiers such as patient ID numbers, encounter ID numbers, and culture order ID numbers, which were anonymized through a process that produced randomized identification numbers consistent between all individual patient records. Socioeconomic factors were identified using the ADI, which requires the use of patient zip codes. Zip codes were removed after the identification of the ADI values. All datetime information has been offset by a randomly assigned number of days per patient, while keeping possible temporal relationships intact. Age and gender for patients were deidentified using the methods described previously.
description: # Antimicrobial Resistance Microbiological Dataset (ARMD-ECUH): A
 deidentified collection of electronic health records from a rural academic
 health system for antimicrobial resistance research Dataset DOI:
 [10.5061/dryad.7sqv9s55x](https://doi.org/10.5061/dryad.7sqv9s55x) ##
 Description of the data and file structure *Data Description* Our data set
 is comprised of longitudinal electronic health records from ECU Health.
 This collection includes deidentified urine, respiratory, and blood-based
 microbiological culture results and susceptibilities from a cohort of
 adult patients (≥18 years old) regardless of culture positivity.
 Additional data included in the data set consists of prior medical
 histories such as comorbidities, socioeconomic indicators, prior
 medications, prior infections, and prior medical procedures. Vitals were
 collected for the encounter in which the culture was taken. The data set
 includes 14 .csv files that can be used for future analyses. All
 identifying personal information has been removed or anonymized according
 to the deidentification methods mentioned below. All files are joined by
 the following identifiers: * anon_id: the deidentified patient number *
 pat_enc_csn_id_coded: the deidentified patient encounter number *
 order_proc_id_coded: the deidentified unique culture order number *
 order_time_jittered: the jittered timestamp for the unique culture order
 All missing values have been replaced with “Null” values.
 *Deidentification Methods* The data set is deidentified to comply with the
 Health Insurance Portability and Accountability Act (HIPAA) and the
 National Institute of Standards and Technology (NIST) Safe Harbor
 regulations.  * All identifying patient information has been removed from
 the data set.  * Any patient, encounter, or culture order identification
 numbers have been anonymized. The anon_id was created by giving each
 patient an identification number, a random pair of letters, accompanied by
 a random set of numbers. The pat_enc_csn_id_coded and order_proc_id_coded
 values were created by giving each encounter number or culture order a
 prefix (3 for pat_enc_csn_id_coded and 4 for order_proc_id_coded),
 accompanied by a serialized value based on the initial randomization of
 the accompanying anon_id. This allows for each patient’s encounter and
 culture order identifiers to be linked to the appropriate patient, but
 remain anonymized.  * Demographic information has been removed except for
 age and gender. Age has been bucketed into age ranges such as 18-24,
 25-34, etc., and gender (male or female) has been adapted to a binary
 indicator of 0 or 1 without indication of which gender is represented by 0
 or 1. * Dates and times have been offset (jittered) by a random number of
 days within two months while keeping consistent temporal relationships.
 ### Files and variables *Files and Variables* 1.
 00_microbiology_cultures_cohort.csv 1. The comprehensive listing of
 culture types, organisms, and susceptibility testing results 2. Key
 Columns: 1. ordering_mode: The mode of the culture order (Inpatient or
 Outpatient) 2. culture_description: The type of culture ordered (Blood,
 Respiratory, or Urine) 3. was_positive: Binary indicator of a positive
 culture result (0 or 1) 4. organism: Name of organism 5. antibiotic: Name
 of antibiotic tested 6. susceptibility: Susceptibility results such as
 susceptible, intermediate, or resistant per antibiotic 2.
 01_microbiology_cultures_adi_scores.csv 1. Area Deprivation Index (ADI)
 information for both national and state ranks that was mapped to patient
 nine-digit (where available, otherwise five-digit) zip codes. 2. Key
 Columns: 1. adi_score: ADI percentile score at the national level; higher
 values indicate higher levels of deprivation 2. adi_state_rank: ADI decile
 rankings at the state (North Carolina, USA) level; higher values indicate
 higher levels of deprivation 3.
 02_microbiology_cultures_antibiotic_class_exposure.csv 1. Prior exposure
 to various antibiotic classes 2. Key Columns: 1. medication_name: Name of
 antibiotic 2. antibiotic_class: Class of antibiotic 3.
 time_to_culturetime: Days between culture order and antibiotic exposure 4.
 03_microbiology_cultures_antibiotic_subtype_exposure.csv 1. Prior exposure
 to antibiotic subclasses 2. Key Columns: 1. medication_name: Name of
 antibiotic 2. antibiotic_subtype: Subclass of antibiotic 3.
 antibiotic_subtype_category: Categorical name of antibiotic subclass 4.
 medication_time_to_culturetime: Days between culture order and antibiotic
 exposure 5. 04_microbiology_cultures_comorbidity.csv 1. Comorbidity
 information for each patient in the cohort 2. Key Columns: 1.
 comorbidity_component: Comorbidity component type based on either the AHRQ
 CCSR diagnosis or Elixhauser Comorbidity Index 2.
 comorbidity_component_start_days_culture: Days between the start of
 comorbidity and the culture order 3.
 comorbidity_component_end_days_culture: Days between the end of the
 comorbidity and the culture order, with “Null” indicating an ongoing
 comorbidity and negative values indicating comorbidities that ended after
 the culture order 6. 05_microbiology_cultures_demographics.csv 1. Basic
 demographic information for each patient in the cohort 2. Key columns: 1.
 age: The age range of the patient with values such as 18-24, 25-24, and
 above 90 2. gender: Binary indicator of 0 or 1 to indicate a particular
 gender. The indicators are purposely not identified for deidentification
 purposes. 7. 06_microbiology_cultures_labs.csv 1. Laboratory results
 recorded for the following: 1. wbc: White blood cell count (k/μL) 2.
 neutrophils: Neutrophils (%) 3. lymphocytes: Lymphocytes (%) 4. hgb:
 Hemoglobin (mg/dL) 5. plt: Platelets (k/μL) 6. na: sodium (mmol/L) 7.
 hco3: bicarbonate (mmol/L) 8. bun: blood urea nitrogen (mg/dL) 9.
 procalcitonin: Procalcitonin (ng/mL) 2. Key columns: 1. Period_Day: Days
 between the culture order and the time range in which the laboratory
 values were measured 2. Q25_xx: Lower quartile laboratory values for
 listed measurements 3. median_xx: Median laboratory values for listed
 measurements 4. Q75_xx: Upper quartile laboratory values for listed
 measurements 5. first_xx: First laboratory value for listed measurements
 6. last_xx: Last laboratory value for listed measurements 8.
 07_microbiology_cultures_microbial_resistance.csv 1. Microbial resistance
 information for each culture ordered 2. Key columns: 1. organism: Name of
 organism 2. antibiotic: Name of antibiotic 3.
 Resistant_time_to_culturetime: Days between the culture order and the
 susceptibility result 9. 08_microbiology_cultures_nursing_home_visits.csv
 1. Information about visits to nursing facilities prior to the date of the
 culture order 2. Key Columns: 1. nursing_home_visit_culture: Days between
 the culture order and nursing facility visit 10.
 09_microbiology_cultures_prior_infecting_organism.csv 1. Information on
 identified organisms prior to the culture order 2. Key columns: 1\.
 prior_organism: Name of organism 2\.
 prior_infecting_organism_days_to_culture: Days between the culture order
 and prior infection 11. 010_microbiology_cultures_prior_med.csv 1.
 Information regarding medications used prior to the culture order 2. Key
 columns: 1\. medication_name: Name of prior medication used 2\.
 medication_time_to_culturetime: Days between the culture order and prior
 medication start 3\. medication_category: Name of medication category 12.
 011_microbiology_cultures_prior_procedures.csv 1. Information on
 procedures such as mechanical ventilation, parenteral nutrition, surgical
 procedures, dialysis, or catheterization (central venous and urethral)
 prior to culture order 2. Key columns: 1\. procedure_description: Name of
 procedure 2\. procedure_time_to_culturetime: Days between the prior
 procedure and the culture order 13.
 012_microbiology_cultures_ward_info.csv 1. Location of the ward in which
 the culture was taken, such as the intensive care unit, the emergency
 department, an inpatient setting, or an outpatient setting 2. Key columns:
 1\. hosp_ward_IP: Binary indicator of the culture location in an inpatient
 setting 2\. hosp_ward_OP: Binary indicator of the culture location in an
 outpatient setting 3\. hosp_ward_ER: Binary indicator of the culture
 location in the emergency department 4\. hosp_ward_ICU: Binary indicator
 of the culture location in the intensive care unit 14.
 013_microbiology_cultures_vitals.csv 1. Vitals recorded for the following:
 1. heartrate: Heart Rate (Pulse) 2. resprate: Respiratory Rate 3. temp:
 Temperature in Fahrenheit 4. sysbp: Systolic Blood Pressure 5. diasbp:
 Diastolic Blood Pressure 2. Key columns: 1\. Period_Day: Days between the
 culture order and the time range in which the laboratory values were
 measured 2\. Q25_xx: Lower quartile laboratory values for listed
 measurements 3\. median_xx: Median laboratory values for listed
 measurements 4\. Q75_xx: Upper quartile laboratory values for listed
 measurements 5\. first_xx: First laboratory value for listed measurements
 6\. last_xx: Last laboratory value for listed measurements ##
 Code/software *Code/Software* * No special software is needed to access
 the data set. The data files are all .csv (comma-separated value) files,
 which can be used with standard statistical methods such as SAS, R, and
 Python. * No additional scripts or software are provided with the data
 set. ## Access information *Sharing/Access* * No other publicly accessible
 locations are available to download the data set * The data were sourced
 from the Epic-based electronic health records system of ECU Health in
 Greenville, NC, USA. ## Human subjects data This study was approved by the
 IRB committee at East Carolina University (UMCIRB 24-001121). Patient
 consent was not required as all data will be deidentified and is for
 secondary use in nature. The data set is deidentified to comply with the
 Health Insurance Portability and Accountability Act (HIPAA) and the
 National Institute of Standards and Technology (NIST) Safe Harbor
 regulations. • All identifying patient information has been removed from
 the data set. • Any patient, encounter, or culture order identification
 numbers have been anonymized. The anon_id was created by giving each
 patient an identification number, a random pair of letters, accompanied by
 a random set of numbers. The pat_enc_csn_id_coded and order_proc_id_coded
 values were created by giving each encounter number or culture order a
 prefix (3 for pat_enc_csn_id_coded and 4 for order_proc_id_coded),
 accompanied by a serialized value based on the initial randomization of
 the accompanying anon_id. This allows for each patient’s encounter and
 culture order identifiers to be linked to the appropriate patient, but
 remain anonymized. • Demographic information has been removed except for
 age and gender. Age has been bucketed into age ranges such as 18-24,
 25-34, etc., and gender (male or female) has been adapted to a binary
 indicator of 0 or 1 without indication of which gender is represented by 0
 or 1. • Dates and times have been offset (jittered) by a random number of
 days within two months while keeping consistent temporal relationships.