Cited by 619Electronic Health Records SystemsMedical Coding and Health InformationMachine Learning in Healthcare

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Using Electronic Health Records for Population Health Research: A Review of Methods and Applications

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Casey, Joan A., Schwartz, Brian S., Stewart, Walter F., Adler, Nancy E.·2016·Annual Review of Public Health

DOI 10.1146/annurev-publhealth-032315-021353PMC PMC6724703

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Abstract

The use and functionality of electronic health records (EHRs) have increased rapidly in the past decade. Although the primary purpose of EHRs is clinical, researchers have used them to conduct epidemiologic investigations, ranging from cross-sectional studies within a given hospital to longitudinal studies on geographically distributed patients. Herein, we describe EHRs, examine their use in population health research, and compare them with traditional epidemiologic methods. We describe diverse research applications that benefit from the large sample sizes and generalizable patient populations afforded by EHRs. These have included reevaluation of prior findings, a range of diseases and subgroups, environmental and social epidemiology, stigmatized conditions, predictive modeling, and evaluation of natural experiments. Although studies using primary data collection methods may have more reliable data and better population retention, EHR-based studies are less expensive and require less time to complete. Future EHR epidemiology with enhanced collection of social/behavior measures, linkage with vital records, and integration of emerging technologies such as personal sensing could improve clinical care and population health.

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See all 619

Authors: Casey, J. A., Schwartz, B. S., Stewart, W. F., & Adler, N. E.
Affiliations: University of California, San Francisco (US)
Johns Hopkins University (US)
Sutter Health (US)
ORCID: Casey, Joan A.
Schwartz, Brian S.
Stewart, Walter F.
Adler, Nancy E.
Venue: Annual Review of Public Health
Publisher: Annual Reviews
Published: 2016-03-18
Volume: 37
Issue: 1
Pages: 61-81
ISSN: 0163-7525 (ISSN-L)
1545-2093
DOI: 10.1146/annurev-publhealth-032315-021353
PMC: PMC6724703
OpenAlex: W2140302476
Cited by: 590
References: 132
Citations by year: 2026: 64 · 2025: 62 · 2024: 76 · 2023: 75 · 2022: 75 · 2021: 70 · 2020: 70 · 2019: 47 · 2018: 28 · 2017: 19 · 2016: 3
FWCI: 1.80
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Annual Review of Public Health (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Institute of Environmental Health Sciences (K99ES027023, R00ES027023)
Topics: Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords: electronic health records, population health research, epidemiological study design, predictive modeling, natural experiment, digital phenotyping
MeSH terms: Age Factors, Data Collection, Environment, Humans, Models, Theoretical, Sex Factors, Social Environment, Socioeconomic Factors, Reproducibility of Results, Epidemiologic Research Design, Health Behavior, Diagnostic Techniques and Procedures, Vital Signs, Electronic Health Records

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Using Electronic Health Records for Population Health Research: A Review of Methods and Applications

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