ArticleHealth services research2025
Comparing imputation approaches for immigration status in ED visits: Implications for using electronic medical records.
Article in Health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- T2D Management Among a Community Clinic Patient Sample After California's May 2022 Medicaid Expansion.Diabetes, obesity & metabolism · 2026Article
- Self-Pay Emergency Department Visits by Undocumented Patients After 2018 Public Charge Announcement.JAMA network open · 2026Article
- Changes in Type 2 Diabetes Medications Among Primary Care Patients After California's 2022 Medicaid Expansion.Diabetes care · 2026Article
- Examining Emergency Department Utilization and Hospital Admissions Among Older Undocumented Immigrants: Insights From a Primary Care County Program.The Gerontologist · 2025Article
- Comparing imputation approaches for immigration status in ED visits: Implications for using electronic medical records.Health services research · 2025Article
- Undocumented Patients with Access to Primary Care and Avoidable Emergency Department Visits: Evidence from a Safety-Net System.Journal of health care for the poor and underserved · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveThis study aimed to compare imputation approaches to identify the likely undocumented patient population in electronic health record (EHRs). EHR are a promising source of information on undocumented immigrants' medical needs and care utilization, but there is no verified way to identify immigration status in the data. Different approaches to approximating immigration status in EHR introduce unique biases, which in turn has major implications on our understanding of undocumented immigrant patients. STUDY SETTING AND
designWe used a dataset of all emergency department (ED) visits from 2016 to 2019 in the Los Angeles Department of Health Services (LADHS) merged across patient medical records, demographic data, and claims data. We included all ED visits from our patient groups of interest and limited to patients at or over the age of 18 years at the time of their ED visit and excluded empty encounter records (n = 1,106,086 ED encounters). DATA SOURCES AND ANALYTIC SAMPLE: We created three patient groups: (1) US-born, (2) foreign-born documented, and (3) undocumented using two different imputation approaches: a logical approach versus statistical assignment. We compared predicted probabilities for two outcomes: an ED visit related to a behavioral health (BH) disorder and inpatient admission/transfer to another facility. PRINCIPAL
findingsBoth approaches provide comparable estimates among the three patient groups for ED encounters for a BH disorder and inpatient admission/transfer to another facility. Undocumented immigrants are less likely to have a BH diagnosis in the ED and are less likely to be admitted or transferred compared to the US-born.
conclusionsResearchers should consider expanding EHR with administrative data when studying the undocumented patient population and may prefer a logical approach to estimate immigration status. Researchers who rely on payer status alone (i.e., restricted Medicaid) as a proxy for undocumented immigrants in EHR should consider how this may bias their results. As Medicaid expands for undocumented immigrants, statistical assignment may become the preferred method.
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