Unique biases in electronic health records data for research: a systematic review
Hsu, Frances; Weiskopf, Nicole
2023

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Abstract

Observational data fill in knowledge gaps when randomized controlled trials (RCTs) are not ethical or feasible. Electronic health records (EHRs) provide a source of observational data from diverse patient samples that reflect real-world settings. However, observational data are susceptible to biases and EHR data contain new forms of bias(es) because they were collected for clinical and not research purposes.

Details

Title Unique biases in electronic health records data for research: a systematic review
Creator Hsu, Frances : Oregon Health and Science University
Weiskopf, Nicole : Oregon Health and Science University
Meeting Name Research Week, Oregon Health and Science University, 2023
Publisher Oregon Health and Science University
Date 2023-08-15
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Keywords
DOI https://doi.org/10.6083/bpxhc41528
Language English
Content Type Abstract
Department Department of Medical Informatics and Clinical Epidemiology
School School of Medicine
Copyright Status
In copyright - joint owners
Usage Statement
Record ID 41528
Record Created 2023-08-15
Record Appears in Organizations > Departments and Divisions > School of Medicine Clinical Sciences Departments and Divisions > Department of Medical Informatics and Clinical Epidemiology
Organizations > Schools > School of Medicine
OHSU Works > Events > Research Week
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