Evidence map›Paper›PMID 41945635›Full record

Observational studyJMIR medical informatics2026

Concordance of Death Information Between Two Health Systems Serving the Same Region and the Social Security Administration Death Master File: Retrospective Observational Study.

Zhan Wang, Mahanaz Syed, Shweta Bansal, Meredith Nahm Zozus, Eric Eisenstein, Muayad Hamidi

Abstract readObservational Study
In one paragraph

Observational study in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhan WangClinical Research Informatics Division, Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States, 1 2105624107.ORCID 0009-0002-6748-6263
Mahanaz SyedClinical Research Informatics Division, Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States, 1 2105624107.ORCID 0000-0002-8978-1565
Shweta BansalDivision of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States.ORCID 0000-0002-3306-2799
Meredith Nahm ZozusClinical Research Informatics Division, Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States, 1 2105624107.ORCID 0000-0002-9332-1684
Eric EisensteinDepartment of Medicine, Duke University, Durham, NC, United States.ORCID 0000-0003-0216-428X
Muayad HamidiClinical Research Informatics Division, Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States, 1 2105624107.ORCID 0009-0005-9825-4993

Funding

Institute for Integration of Medicine & Science: A Partnership to Improve HealthUM1TR004538 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI ROBERT A CLARK, Kenneth M Hargreaves · 2023 to 2026
$22.3M
NCATS NIH HHS UM1 TR004538
6 · The paper itself

Abstract

Background: There are multiple sources that document the date of a person's death in the United States. Unfortunately, this seemingly simple information is either incomplete or costly to obtain. Nevertheless, information on such events is critical for both health systems and clinical studies to assess the outcomes of operational and therapeutic interventions. Objective: As part of a larger assessment of the quality of multisource death information, we compared the death data from two health systems serving the same region and the Social Security Administration Death Master File (SSADMF). Methods: This study linked death records for patients seen in either health system with the SSADMF from 2007 to 2020 to identify concordant and discordant death data among sources. Analyses included cross-system matching, classification of death records by overlap, and calculation of agreement using the Fleiss κ. Results: Among 904,581 matched patients, only 209 (0.02%) deaths were confirmed by all 3 sources. Large proportions of deaths were uniquely recorded by a single source: 54.32% (10,697/19,691) by health system A, 5.16% (1017/19,691) by health system B, and 20.17% (3972/19,691) by the SSADMF. The Fleiss κ was negative (-0.312), reflecting less agreement than expected by chance. Conclusions: While this study is not generalizable, it showed that, without processes in place to obtain external data regarding patient deaths, health care facility death information should not be relied upon as a complete list of those who have died. The discordances observed highlight the potential for significant gaps in death reporting within health care systems, which could impact the accuracy of mortality-based analyses and quality assessments.

Indexed as

Death CertificatesUnited States Social Security AdministrationHumansRetrospective StudiesUnited Statesdeath record concordanceEHR data qualityelectronic health record data qualityhealth systemsmortality data qualitySocial Security Administration Death Master File

Identifiers

PMID41945635
PMCPMC13055938

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Registered trials

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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.