ArticleAnnals of epidemiology2021
Inverse probability weighting for selection bias in a Delaware community health center electronic medical record study of community deprivation and hepatitis C prevalence.
Article in Annals of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Area deprivation and hepatitis C infection in Korea: a multilevel case-control study using the National Health Insurance Database.BMJ public health · 2026Article
- Evaluating bias in electronic health record data: using agent-based models to examine whether geographic disparities in community-acquired methicillin-resistant Staphylococcus aureus are due to differential health care-seeking behaviors.American journal of epidemiology · 2025Article
- Are Aggregated Electronic Health Record Datasets Good for Research?Journal of general internal medicine · 2025Article
- Changes in accelerated aging and risk of cardiovascular disease and mortality: three cohort studies.BMC medicine · 2025Article
- TriNetX and Real-World Evidence: A Critical Review of Its Strengths, Limitations, and Bias Considerations in Clinical Research.ASIDE internal medicine · 2025Article
- Inferring Population HIV Viral Load From a Single HIV Clinic's Electronic Health Record: Simulation Study With a Real-World Example.Online journal of public health informatics · 2024Article
- Challenges in and Opportunities for Electronic Health Record-Based Data Analysis and Interpretation.Gut and liver · 2024Review
- Design, implementation, and inferential issues associated with clinical trials that rely on data in electronic medical records: a narrative review.BMC medical research methodology · 2023Review
- A catchment and location-allocation analysis of mammography access in Delaware, US: implications for disparities in geographic access to breast cancer screening.Breast cancer research : BCR · 2023Article
- A Catchment and Location-Allocation Analysis of Mammography Access in Delaware, US: Implications for disparities in geographic access to breast cancer screening.Research square · 2023Article
- Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.Frontiers in public health · 2023Article
- A narrative review on the validity of electronic health record-based research in epidemiology.BMC medical research methodology · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
purposeTo demonstrate how selection into a healthcare facility can induce bias in an electronic medical record-based study of community deprivation and chronic hepatitis C virus infection, in order to more accurately identify local risk factors and prevalence.
methodsWe created a catchment model that attempted to define the probability of selection into a retrospective cohort. Then using the inverse of this probability, we compared naïve unweighted and weighted models to demonstrate the impact of selection bias.
resultsZIP code-level ecological plots of the cohort demonstrated that there was a pattern of the community deprivation, hepatitis C outcome, and distance to the health center (an intuitive proxy for being within catchments). The naïve multilevel analysis found that living in an area with greater deprivation resulted in 1.25 times greater odds of HCV (95% CI: 1.06, 1.48), whereas the weighted analysis found less certainty of this effect due to a selection bias.
conclusionsWe observed that selection into the catchment area of the studied healthcare facility may bias the association of community deprivation and hepatitis C. This may be mitigated through inverse probability weighting.
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