ArticleContemporary clinical trials2023
Equity and bias in electronic health records data.
Article in Contemporary clinical trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Spatial bias in quality of estimated delivery date records in the electronic health record.JAMIA open · 2026Article
- Nurses' Ethical Reasoning About Digital Ethical Risks: A Vignette-Elicited Qualitative Study.International nursing review · 2026Article
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- Article
- Functional outcomes of children after SARS-CoV-2 infection: An EHR-based cohort study.Journal of pediatric rehabilitation medicine · 2026Article
- A Microsimulation-Based Approach for Mitigating Societal Bias in Chronic Kidney Disease Data.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- From Scale to Situated: Sociotechnical Imaginaries and the Configuration of Algorithmic Health Research.Sociology of health & illness · 2026Article
- The potential, perils and pitfalls of Artificial intelligence (AI) in Assisted Reproductive Technologies (ART).Reproductive biology and endocrinology : RB&E · 2026Review
- Sex differences in cardiovascular disease and associated factors in people living with HIV: Evidence from All of Us program.HIV medicine · 2026Article
- Training the next-generation of biomedical scientists through artificial intelligence-driven education and research in pharmacology and pharmaceutical sciences.Experimental biology and medicine (Maywood, N.J.) · 2026Review
- Connecting biospecimens and data: a scoping review-informed conceptual framework for digital infrastructure in biobanking and genomic research in low- and middle-income countries.Frontiers in public health · 2026Article
- A microsimulation-based framework for mitigating societal bias in primary care data.medRxiv : the preprint server for health sciences · 2025Article
- Incompleteness of Electronic Health Records: An Impending Process Problem Within Healthcare.Healthcare (Basel, Switzerland) · 2025Article
- The Lifecycle of Electronic Health Record Data in HIV-Related Big Data Studies: Qualitative Study of Bias Instances and Potential Opportunities for Minimization.Journal of medical Internet research · 2025Article
- Collection of Patient-Reported Outcome Measures in Rural and Underserved Populations.Applied clinical informatics · 2025Article
- Impact of electronic health record updates and changes on the delivery and monitoring of interventions in embedded pragmatic clinical trials.Contemporary clinical trials · 2025Article
- Evaluating EHR-Integrated Digital Technologies for Medication-Related Outcomes and Health Equity in Hospitalised Adults: A Scoping Review.Journal of medical systems · 2024Article
- On the evaluation of synthetic longitudinal electronic health records.BMC medical research methodology · 2024Article
- Recurring and Emerging Ethical Issues in Pragmatic Clinical Trials.Circulation. Cardiovascular quality and outcomes · 2024Article
- Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
Abstract
Embedded pragmatic clinical trials (ePCTs) are conducted during routine clinical care and have the potential to increase knowledge about the effectiveness of interventions under real world conditions. However, many pragmatic trials rely on data from the electronic health record (EHR) data, which are subject to bias from incomplete data, poor data quality, lack of representation from people who are medically underserved, and implicit bias in EHR design. This commentary examines how the use of EHR data might exacerbate bias and potentially increase health inequities. We offer recommendations for how to increase generalizability of ePCT results and begin to mitigate bias to promote health equity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.