Antimicrobial Resistance Microbiological Dataset (ARMD-ECUH): A deidentified collection of electronic health records from a rural academic health system for antimicrobial resistance research

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 aware..., 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 i..., # 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 i..., 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 ...

随着抗菌耐药性日益成为突发公共卫生问题，可用于科研的高质量真实世界电子健康记录（Electronic Health Record, EHR）数据集仍存在缺口。为填补这一空白，我们构建了**东卡罗来纳大学健康系统抗菌耐药性微生物数据集（Antimicrobial Resistance Microbiological Dataset: East Carolina University Health, ARMD-ECUH）**，涵盖2015年至2025年来自ECU Health的261217名患者的微生物培养与药敏检测结果。此外，数据集纳入了患者人口统计学信息、既往病史、用药史及诊疗操作等纵向数据，进一步提升了其科研价值；同时还包含与临床紧密相关的附加信息，如标本采集部位、近期实验室检验指标及对应就诊时采集的生命体征数据。本去标识化数据集采用标准化数据格式，以最大限度减少后续数据转换工作，将助力全球研究者优化患者诊疗结局、提升抗菌耐药性认知……

我们的抗菌耐药性微生物数据集——东卡罗来纳大学健康系统版（ARMD-ECUH），是2015年至2025年（用于去标识化的日期扰动前）来自ECU Health医疗系统的成年患者（≥18岁）的纵向基于Epic的电子健康记录集合。数据集包含去标识化的血液、尿液及呼吸道标本的微生物实验室检验结果。此外，数据集还纳入了基于就诊的生命体征、患者人口统计学信息、合并症、通过区域剥夺指数（Area Deprivation Index, ADI）量化的社会经济因素，以及既往用药史与诊疗操作史。所有数据通过微软Fabric支持的数据仓库采集，该仓库每日同步ECU Health的Epic Clarity数据库数据，并在Fabric笔记本中通过Spark SQL完成数据查询。

参考ARMD与ARMD-UTSW的标准化方法，我们对所有原始数据进行了标准化处理，以支撑后续科研应用。该标准化流程包括性别标识的统一……

# 抗菌耐药性微生物数据集（ARMD-ECUH）：来自农村学术医疗系统的去标识化电子健康记录集合，用于抗菌耐药性研究
数据集数字对象标识符（DOI）：[10.5061/dryad.7sqv9s55x](https://doi.org/10.5061/dryad.7sqv9s55x)

## 数据与文件结构说明
### *数据描述*
本数据集由来自ECU Health的纵向电子健康记录组成，涵盖≥18岁成年患者群体的去标识化尿液、呼吸道及血液标本的微生物培养与药敏结果，无论培养结果呈阳性与否。数据集额外包含的信息包括：既往病史（如合并症）、社会经济指标、既往用药史、既往感染史及既往诊疗操作史；同时采集了标本采集当次就诊的生命体征数据。本数据集包含14个.csv格式文件，可用于后续各类分析。所有可识别的个人信息……

本研究已通过东卡罗来纳大学机构审查委员会（Institutional Review Board, IRB）审批（UMCIRB 24-001121）。由于所有数据均已完成去标识化且仅用于二次研究，因此无需获得患者知情同意。

本数据集已完成去标识化处理，符合《健康保险流通与责任法案》（Health Insurance Portability and Accountability Act, HIPAA）及美国国家标准与技术研究院（National Institute of Standards and Technology, NIST）的安全港法规要求：
- 已移除数据集中所有可识别患者的个人信息；
- 所有患者、就诊或培养订单的标识编号均已完成匿名化处理：通过为每位患者分配一个由随机字母组合与随机数字串组成的anon_id实现匿名；pat_enc_csn_id_coded与order_proc_id_coded字段则通过为每条就诊编号或培养订单编号添加前缀（pat_enc_csn_id_coded前缀为3，order_proc_id_coded前缀为4），并结合基于anon_id初始随机化生成的序列化值生成，以此实现……