The utility of EMR address histories for assessing neighborhood exposures
Open accessAbstract
Purpose Electronic medical records (EMRs) include residential address histories, which may alleviate exposure misclassification caused by exclusion of patient spatiotemporal location. EMR data are increasingly available but rarely leveraged as a measure of cumulative environmental exposure, in part due to limited understanding of the validity of EMR-derived address histories. Methods We compared EMR address histories to self-reported histories among 100 patients of a safety-net health care system completing a telephone survey. We assessed agreement and compared seven neighborhood-level environmental exposures as assessed using both data sources. Results While 17.1% of respondents did not live at the most recent EMR-derived address during the survey, nearly all (98%) lived there at some point. For respondents with more than one EMR-derived address (N = 64), 87.5% had once lived at the previous EMR address. Of these, 30.4% lived at 1 or more additional residences between the two most recent EMR address. For all measures, neighborhood-level environmental exposures did not differ when using EMR-derived versus self-report addresses. Conclusions More recent EMR-derived addresses are more accurate, and differences compared to self-reported addresses in neighborhood-level exposures are negligible. EMR-derived address histories are incomplete and likely suffer from collection bias; future research should further assess their validity and reliability.
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Three studies concluded that a single patient address was sufficient when patients may have moved several times over the study period.
“When confronted with data from patients who may have moved several times over the study period, 3 studies concluded that a single patient address was sufficient;15,56,57”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [56]
The Introduction (page unavailable) says life-course neighborhood exposures cannot be fully assessed through a single measurement in space and time. The Discussion (page unavailable) also cautions that exposure misclassification may be greater over longer periods or with more moves. This paper does not conclude that one address is sufficient for patients who may have moved several times. (LLM, conf=0.88)
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Experimental — accuracy not yet measuredOne study recommended using the most recent address.
“one study recommended using the most recent address,56”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [56]
The Discussion (page unavailable) finds that more recent EMR address entries are more accurate, which supports the rationale for using the most recent address. The paper does not explicitly recommend using only that address; its Conclusions instead describe the value of address histories for longitudinal exposure research. (LLM, conf=0.84)
Experimental — accuracy not yet measuredFour (80%) of the included articles explored the impact of residential mobility on exposure assessment.
“Four (80%) of the included articles explored the impact of residential mobility on exposure assessment; that is, whether patients’ moving impacted the results of studies looking at environmental outcomes.15,16,56,57”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [56]
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Background
- Authors
- Hughes, A. E., & Pruitt, S. L.
- Affiliations
- The University of Texas Southwestern Medical Center (US)
- Harold C. Simmons Comprehensive Cancer Center (US)
- Corresponding author
- Hughes, Amy E.
- Venue
- Annals of Epidemiology
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 27
- Issue
- 1
- Pages
- 20-26
- ISSN
- 1047-2797 (ISSN-L)
- PMC
- PMC5482357
- OpenAlex
- W2513067231
- Cited by
- 18
- References
- 48
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 4 · 2022: 1 · 2021: 3 · 2020: 3 · 2018: 1 · 2017: 1 · 2016: 1
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annals of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Cancer Prevention Research Institute of Texas (CPRIT R1208)
- National Cancer Institute (U54CA163308, 5P30CA142543)
- National Center for Advancing Translational Sciences (UL1TR001105)
- NIH (R25 CA57712)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Social Sciences › Sociology and Political Science › Environmental Justice and Health Disparities
- Keywords
- electronic health records, cumulative environmental exposure, exposure misclassification, data source agreement, data collection bias, safety net health care
- MeSH terms
- Air Pollution, Cross-Sectional Studies, Environmental Exposure, Female, Humans, Male, Population Dynamics, Residence Characteristics, United States, Reproducibility of Results, Bias, Geographic Information Systems, Electronic Health Records, Self Report
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