Academic Journal
Stakeholders' Attitudes on Automating Data Abstraction in a Surgical Quality Improvement Program.
| Τίτλος: | Stakeholders' Attitudes on Automating Data Abstraction in a Surgical Quality Improvement Program. |
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| Συγγραφείς: | Haltom TM, Rosen T, Chen PV, Petersen LA, Harris AHS, Massarweh NN |
| Πηγή: | Joint Commission journal on quality and patient safety [Jt Comm J Qual Patient Saf] 2026 Aug; Vol. 52 (8), pp. 342-349. Date of Electronic Publication: 2026 Apr 24. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101238023 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1938-131X (Electronic) Linking ISSN: 15537250 NLM ISO Abbreviation: Jt Comm J Qual Patient Saf Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2017- : Amsterdam : Elsevier Original Publication: Oakbrook Terrace, IL : Joint Commission Resources, c2005- |
| Ιατρικοί όροι (MeSH): | Quality Improvement*/organization & administration , Data Collection*/methods , Surgical Procedures, Operative*/standards , Attitude of Health Personnel*, Humans ; United States ; United States Department of Veterans Affairs ; Workflow ; Interviews as Topic ; Qualitative Research |
| Περίληψη: | Background: National surgical quality improvement programs rely on a labor-intensive process of manual data abstraction. There have been few efforts to understand stakeholders' attitudes on programmatic workflows, data collection processes, or identification of modifications to workflows that might enhance efficiency. Given contemporary data science methods, the attitudes of stakeholders regarding data collection automation could have implications for future national quality program modernization efforts. Methods: Qualitative interviews were conducted with US Department of Veterans Affairs (VA) surgical quality nurses (SQNs) and researchers who use VA Surgical Quality Improvement (VASQIP) data from a national integrated health system. All transcripts were analyzed using thematic analysis. Results: Data were obtained from 42 interviews (26 with SQNs and 16 with researchers) from 37 medical facilities across the United States. The authors found five themes pertaining to participant's attitudes regarding (1) automating data abstraction, (2) interpreting variable definitions, (3) the need for standardizing documentation, (4) factoring in human review of data collected automatically, and (5) SQNs' job security concerns. Conclusion: SQNs and VASQIP researchers expressed general interest and optimism about developing data science methods to automate data collection. However, participants considered human review a necessary part of data collection. More work is needed on how to automate data collection within existing surgical quality improvement programs. (Copyright © 2026 The Joint Commission. All rights reserved.) |
| Entry Date(s): | Date Created: 20260611 Date Completed: 20260729 Latest Revision: 20260729 |
| Update Code: | 20260730 |
| DOI: | 10.1016/j.jcjq.2026.04.012 |
| PMID: | 42276891 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1938-131X |
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| DOI: | 10.1016/j.jcjq.2026.04.012 |