ArticleApplied clinical informatics2021
Validating the Matching of Patients in the Linkage of a Large Hospital System's EHR with State and National Death Databases.
Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Linking Electronic Health Records for Multiple Sclerosis Research: Comparative Study of Deterministic, Probabilistic, and Machine Learning Linkage Methods.JMIR medical informatics · 2026Article
- Molecularly Targeted Cancer Medications and Kidney Health.JAMA network open · 2025Article
- Recovering missing electronic health record mortality data with a machine learning-enhanced data linkage process.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Validation of Mortality Data Sources Compared to the National Death Index in the Healthcare Integrated Research Database.Pragmatic and observational research · 2025Article
- Patient characteristics and health system encounters of decedents not marked deceased in the electronic health record.JAMIA open · 2024Article
- Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets.Applied clinical informatics · 2024Article
- A Mortality Surveillance Collaboration Between a Health System and Public Health Department.American journal of public health · 2023Article
- A lifecycle framework illustrates eight stages necessary for realizing the benefits of patient-centered clinical decision support.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Engaging Patients and Other Stakeholders in "Designing for Dissemination" of Record Linkage Methods and Tools.Applied clinical informatics · 2023Article
- Evaluating novel methods of outcome assessment following cardiac arrest.Resuscitation · 2022Article
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4 authors.
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Abstract
backgroundThough electronic health record (EHR) data have been linked to national and state death registries, such linkages have rarely been validated for an entire hospital system's EHR.
objectivesThe aim of the study is to validate West Virginia University Medicine's (WVU Medicine) linkage of its EHR to three external death registries: the Social Security Death Masterfile (SSDMF), the national death index (NDI), the West Virginia Department of Health and Human Resources (DHHR).
methodsProbabilistic matching was used to link patients to NDI and deterministic matching for the SSDMF and DHHR vital statistics records (WVDMF). In subanalysis, we used deaths recorded in Epic (
resultsOf the deaths captured by the SSDMF, 59.8 and 68.5% were captured by NDI and WVDMF, respectively; for deaths captured by NDI this co-capture rate was 80 and 78%, respectively, for the SSDMF and WVDMF. Kappa statistics were strongest for NDI and WVDMF (61.2%) and NDI and SSDMF (60.6%) and weakest for SSDMF and WVDMF (27.9%). Of deaths recorded in Epic, 84.3, 85.5, and 84.4% were captured by SSDMF, NDI, and WVDMF, respectively. Less than 2% of patients' deaths recorded in Epic were not found in any of the death registries. Finally, approximately 0.2% of "decedents" in any death registry re-emerged in Epic at least 6 months after their death date, a very small percentage and thus further validating the linkages.
conclusionNDI had greatest validity in capturing deaths in our EHR. As a similar, though slightly less capture and agreement rate in identifying deaths is observed for SSDMF and state vital statistics records, these registries may be reasonable alternatives to NDI for research and quality assurance studies utilizing entire EHRs from large hospital systems. Investigators should also be aware that there will be a very tiny fraction of "dead" patients re-emerging in the EHR.
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