Academic Journal
Application of a Systems Theory-Based Accident Analysis Technique to Perioperative Safety Reports From the COVID-19 Pandemic.
| Τίτλος: | Application of a Systems Theory-Based Accident Analysis Technique to Perioperative Safety Reports From the COVID-19 Pandemic. |
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| Συγγραφείς: | Samost-Williams AL; Department of Anesthesiology, Critical Care, and Pain Medicine, McGovern Medical School, University of Texas Health Science Center in Houston, Houston, TX., Sinyard RD; Department of Surgery, Vanderbilt University, Nashville, TN., Tabayoyong LL; Department of Pharmacy, Massachusetts General Hospital, Boston, MA., Fogarty JR; University of New England College of Osteopathic Medicine, Biddeford, ME., Minehart RD; Department of Anesthesiology, Brown University School of Medicine, Providence, RI., Nanji KC; Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital.; Department of Anesthesia, Harvard Medical School, Boston, MA. |
| Πηγή: | Journal of patient safety [J Patient Saf] 2025 Oct 01; Vol. 21 (7), pp. 445-451. Date of Electronic Publication: 2025 Jun 06. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 101233393 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-8425 (Electronic) Linking ISSN: 15498417 NLM ISO Abbreviation: J Patient Saf Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Philadelphia, Pa. : Lippincott Williams & Wilkins, c2005- |
| Ιατρικοί όροι (MeSH): | COVID-19*/epidemiology , Systems Theory* , Patient Safety* , Systems Analysis* , Safety Management* , Perioperative Care*, Humans ; Pandemics ; Retrospective Studies ; SARS-CoV-2 |
| Περίληψη: | Objectives: Nonlinear retrospective analytic techniques can allow for in-depth understanding of accidents and their causes, yet they are infrequently used in health care. The purpose of this study was to provide an example, using Causal Analysis based on Systems Theory (CAST) together with an inductive thematic analysis to understand the contextual factors contributing to one hospital's perioperative safety events. Methods: We created a hierarchical control structure of the hospital's perioperative system with input from a multidisciplinary group. We then analyzed safety events that were self-reported during a COVID surge (April 2020) using CAST to understand their contributing factors. Next, we analyzed the contributing factors using inductive qualitative thematic coding to identify system-level safety risks. We mapped each system-level safety risk to a recommendation for future mitigation. Results: We screened 122 safety reports and found 19 safety events that met inclusion criteria. The analysis revealed 245 contributing factors represented by 22 subthemes corresponding to 3 major themes: (1) vulnerable processes, being problems with workflows or communication channels; (2) personnel challenges including challenges with staff redeployment as well as cognitive and behavioural challenges; and (3) poorly designed or unavailable equipment. Each subtheme corresponded to a prevention strategy, such as creation of a central protocol hub. Conclusions: Using a nonlinear accident analysis technique together with thematic analysis, we were able to identify system-wide contributing factors to safety events. These contributing factors led to recommendations for future pandemics or crises characterized by scarce resources, limited data, and a rapidly changing environment. (Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.) |
| Competing Interests: | K.C.N. reports author royalties from UpToDate Inc (Waltham MA), equity from Guided Clinical Solutions (Boston MA), consulting fees from NORC at the University of Chicago and research grants from the Agency for Healthcare Research & Quality and the Doris Duke Charitable Foundation. The remaining authors disclose no conflict of interest. |
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| Grant Information: | K12 TR004908 United States TR NCATS NIH HHS |
| Contributed Indexing: | Keywords: COVID-19; accident analysis; systems modeling; systems theory |
| Entry Date(s): | Date Created: 20250605 Date Completed: 20250923 Latest Revision: 20260813 |
| Update Code: | 20260813 |
| PubMed Central ID: | PMC13003508 |
| DOI: | 10.1097/PTS.0000000000001372 |
| PMID: | 40470886 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1549-8425 |
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| DOI: | 10.1097/PTS.0000000000001372 |