Organizational Intent, Organizational Structures, and Reviewer Mental Models Influence Mortality Review Processes.


Journal

Mayo Clinic proceedings. Innovations, quality & outcomes
ISSN: 2542-4548
Titre abrégé: Mayo Clin Proc Innov Qual Outcomes
Pays: Netherlands
ID NLM: 101728275

Informations de publication

Date de publication:
Dec 2023
Historique:
medline: 16 11 2023
pubmed: 16 11 2023
entrez: 16 11 2023
Statut: epublish

Résumé

To identify the factors that influence the mortality review process at health systems, including how mortality review is conducted, cases are adjudicated, and results are used. We conducted a qualitative analysis of the mortality review processes of 6 US health systems from February 1, 2021 to June 31, 2021. The data sources included individual and small-group semi-structured interviews with mortality review team members and a content analysis of site artifacts (eg, guiding principles, chart abstraction forms, review workflows, and clinical pathways developed from past mortality reviews). We analyzed each site's mortality review process, goals and incentives for mortality review, historical and evolving aspects of mortality review, personnel involved, and post-review use of findings. Across the 6 systems, we interviewed a total of 24 mortality review experts and analyzed 26 site documents. We identified 3 thematic factors that influence mortality review processes: organizational intent, organizational structures for mortality review, and the mental models of individuals involved in the review process. Two subthemes emerged within organizational intent: (1) identifying preventable deaths to lower (clinical or financial) risk and (2) using death cases to guide system improvement. Sites varied in governance and decision rights concerning mortality review and adjudication, with 2 subthemes within organizational structures: (1) centralized-hierarchical and (2) decentralized or multidisciplinary. The analysis of mental models of participating reviewers revealed 2 themes: (1) confirmation of preventability and (2) identification of patterns or "signals." Understanding the factors that influence mortality review allows health systems to better leverage mortality review for institutional improvement and to develop training that builds shared mental models to enhance the review process.

Identifiants

pubmed: 37969423
doi: 10.1016/j.mayocpiqo.2023.09.004
pii: S2542-4548(23)00062-0
pmc: PMC10632187
doi:

Types de publication

Journal Article

Langues

eng

Pagination

515-523

Informations de copyright

© 2023 The Authors.

Déclaration de conflit d'intérêts

The authors have no conflict of interest to disclose.

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Auteurs

Inas S Khayal (IS)

Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH.
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH.
Department of Computer Science, Dartmouth College, Hanover, NH.

Rebecca L Butcher (RL)

Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH.
Center for Program Design and Evaluation, Geisel School of Medicine at Dartmouth, Lebanon, NH.

Colin H McLeish (CH)

Geisel School of Medicine at Dartmouth, Hanover, NH.
Tuck School of Business, Hanover, NH.

Yujia Shentu (Y)

Geisel School of Medicine at Dartmouth, Hanover, NH.
Department of Neurosurgery, The University of Texas McGovern Medical School, Houston.

Amber E Barnato (AE)

Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH.
Section of Palliative Care, Department of Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH.

Classifications MeSH