Cognitive task analysis of clinicians' drug-drug interaction management during patient care and implications for alert design.

Autor:	Russ-Jara AL; Health Services Research and Development Service CIN 13-416, Center for Health Information and Communication, U.S. Department of Veterans Affairs (VA), Veterans Health Administration, Indianapolis, Indiana, USA alissajara@purdue.edu.; Department of Pharmacy Practice, College of Pharmacy, Purdue University, West Lafayette, Indiana, USA.; Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana, USA., Elkhadragy N; Department of Pharmacy Practice, College of Pharmacy, Purdue University, West Lafayette, Indiana, USA.; School of Pharmacy, University of Wyoming, Laramie, Wyoming, USA., Arthur KJ; Richard L. Roudebush VA Medical Center, U.S. Department of Veterans Affairs, Veterans Health Administration, Indianapolis, Indiana, USA., DiIulio JB; Applied Decision Science, LLC, Dayton, Ohio, USA., Militello LG; Applied Decision Science, LLC, Dayton, Ohio, USA., Ifeachor AP; Richard L. Roudebush VA Medical Center, U.S. Department of Veterans Affairs, Veterans Health Administration, Indianapolis, Indiana, USA., Glassman PA; Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.; Pharmacy Benefits Management Services, Department of Veterans Affairs (VA), Washington, DC, USA.; Department of Medicine, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA., Zillich AJ; Department of Pharmacy Practice, College of Pharmacy, Purdue University, West Lafayette, Indiana, USA., Weiner M; Health Services Research and Development Service CIN 13-416, Center for Health Information and Communication, U.S. Department of Veterans Affairs (VA), Veterans Health Administration, Indianapolis, Indiana, USA.; Richard L. Roudebush VA Medical Center, U.S. Department of Veterans Affairs, Veterans Health Administration, Indianapolis, Indiana, USA.; Center for Health Services Research, Regenstrief Institute, Inc, Indianapolis, Indiana, USA.; Department of Medicine, Indiana University, Indianapolis, Indiana, USA.
Jazyk:	angličtina
Zdroj:	BMJ open [BMJ Open] 2023 Dec 01; Vol. 13 (12), pp. e075512. Date of Electronic Publication: 2023 Dec 01.
DOI:	10.1136/bmjopen-2023-075512
Abstrakt:	Background: Drug-drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians' real-world DDI decision-making process to inform more effective alerts. Objective: Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts. Design: Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians' decision-making process. We then performed an inductive, qualitative analysis across incidents. Setting: Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre. Participants: Physicians, pharmacists and nurse practitioners. Outcomes: Themes to identify informational cues that clinicians used to manage DDIs. Results: We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians' decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians' decision-making efficiency, confidence and effectiveness. Conclusions: Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians' real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future. Competing Interests: Competing interests: LM is co-owner of Applied Decision Science, LLC, a company that studies decision-making in complex environments and utilises the critical decision method. She aided in the design of the cognitive task analysis approach used in this study and trained the interviewer. MW has held stock in Allscripts and Express Scripts Holding Company. (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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