Evidence map›Paper›PMID 39473881›Full record

ArticleJAMIA open2024

Patient characteristics and health system encounters of decedents not marked deceased in the electronic health record.

Fernando Javier Sanz Vidorreta, Michael T Dudley, Anne M Walling, Chi-Hong Tseng, Michael Hogarth, Neil S Wenger

Abstract read
In one paragraph

Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Fernando Javier Sanz VidorretaBiomedical Informatics Program at UCLA Clinical and Translational Science Institute, University of California, Los Angeles, CA 90095, United States.
Michael T DudleyUCLA Office of Health Informatics and Analytics, University of California, Los Angeles, CA 90095, United States.
Anne M WallingUCLA Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, CA 90024, United States.
Chi-Hong TsengUCLA Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, CA 90024, United States.ORCID https://orcid.org/0000-0002-2549-6167
Michael HogarthDivision of Biomedical Informatics, Department of Medicine, University of California, San Diego, CA 92093, United States.
Neil S WengerUCLA Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, CA 90024, United States.ORCID https://orcid.org/0000-0002-9884-3967

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Health systems are increasingly accountable for patients and require accurate electronic health record (EHR) vital status. We recently demonstrated that 19% of seriously ill primary care patients in one system were not marked dead in the EHR and 80% of these decedents had an encounter or appointment outstanding after death. Herein we describe the mechanism of identifying decedents whose death is not captured at the level of the EHR, characterize these decedents, and describe medications refilled after death. Materials and Methods: Description of multistep process to identify deceased patients not marked dead in the EHR among a cohort of seriously ill primary care patients including public death file matching, utilization analysis, and chart abstraction. We compared decedents not marked dead in the EHR to known decedents and described pharmacy requests and refills. Results: Nearly 90% of encounters and appointments occurred because the health system EHR did not record the death although 11% of these encounters contained condolences or death notifications. Decedents not marked dead in the EHR were older and lived in more vulnerable areas than those marked dead. Of 146 refill requests after death, 88 medications were authorized. Discussion and Conclusion: Matching with a limited public death file is an inadequate solution to inaccurate vital status. Better workflows are needed to capture deaths about which clinicians and staff are aware, but will identify only a fraction of the decedents inaccurately listed as alive. Efforts are needed to connect EHRs with more specific sources of linkable decedent information.

Indexed as

electronic health recordfact-of-deathpatient deathvital status

Identifiers

PMID39473881
PMCPMC11521374

What OpenQuestion holds

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LicenceCC BY
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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.