CC BY-NC-ND 4.0 · Appl Clin Inform 2021; 12(01): 082-089
DOI: 10.1055/s-0040-1722220
Research Article

Validating the Matching of Patients in the Linkage of a Large Hospital System's EHR with State and National Death Databases

Rebecca B. N. Conway
1  Department of Community Health, University of Texas Health Science Center at Tyler, Tyler, Texas, United States
Matthew G. Armistead
2  Department of Biomedical Informatics, West Virginia Clinical and Translational Science Institute, Morgantown, West Virginia, United States
Michael J. Denney
2  Department of Biomedical Informatics, West Virginia Clinical and Translational Science Institute, Morgantown, West Virginia, United States
Gordon S. Smith
3  Department of Epidemiology, West Virginia University, Morgantown, West Virginia, United States
› Author Affiliations
Funding This study was funded by National Institute of General Medical Sciences, grants: 1U54GM104942-02, 2U54GM104942-02 and National Institute on Drug Abuse, grants: 1UG3DA044825, R21DA040187.


Background Though 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.

Objectives The 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).

Methods Probabilistic 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 (n = 30,217) to further validate a subset of deaths captured by the SSDMF, NDI, and WVDMF.

Results Of 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.

Conclusion NDI 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.

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by WVU University Institutional Review Board.

Former affiliation: University of Texas Health Science Center at Tyler, School of Community and Rural Health, Tyler, Texas, United States.

Supplementary Material

Publication History

Received: 02 July 2020

Accepted: 16 November 2020

Publication Date:
10 February 2021 (online)

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (

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