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Appl Clin Inform 2019; 10(01): 001-009
DOI: 10.1055/s-0038-1676587
Research Article
Georg Thieme Verlag KG Stuttgart · New York

CDS in a Learning Health Care System: Identifying Physicians' Reasons for Rejection of Best-Practice Recommendations in Pneumonia through Computerized Clinical Decision Support

Barbara E. Jones
1   VA Salt Lake City IDEAS Center, VA Salt Lake City Healthcare System, Salt Lake City, Utah, United States
2   Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, Utah, United States
,
Dave S. Collingridge
3   Intermountain Healthcare, Murray, Utah, United States
,
Caroline G. Vines
3   Intermountain Healthcare, Murray, Utah, United States
,
Herman Post
4   Homer Warner Center for Informatics, Intermountain Healthcare, Murray, Utah, United States
,
John Holmen
4   Homer Warner Center for Informatics, Intermountain Healthcare, Murray, Utah, United States
,
Todd L. Allen
5   Department of Emergency Medicine, Intermountain Healthcare, Murray, Utah, United States
,
Peter Haug
4   Homer Warner Center for Informatics, Intermountain Healthcare, Murray, Utah, United States
,
Charlene R. Weir
6   Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States
,
Nathan C. Dean
7   Division of Pulmonary and Critical Care Medicine, Intermountain Healthcare and University of Utah, Murray, Utah, United States
› Author Affiliations Funding This work was supported by Intermountain Healthcare and the Intermountain Research and Medical Foundation. The Research Electronic Data Capture (REDCap) tool is funded by a grant from the National Institutes of Health (CTSA 3UL1RR025764–02). Dr. Jones is funded by a career development award from the Veterans Affairs Health Services Research & Development (# IK2HX001908).
Further Information

Publication History

30 August 2018

09 November 2018

Publication Date:
02 January 2019 (online)

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Abstract

Background Local implementation of guidelines for pneumonia care is strongly recommended, but the context of care that affects implementation is poorly understood. In a learning health care system, computerized clinical decision support (CDS) provides an opportunity to both improve and track practice, providing insights into the implementation process.

Objectives This article examines physician interactions with a CDS to identify reasons for rejection of guideline recommendations.

Methods We implemented a multicenter bedside CDS for the emergency department management of pneumonia that integrated patient data with guideline-based recommendations. We examined the frequency of adoption versus rejection of recommendations for site-of-care and antibiotic selection. We analyzed free-text responses provided by physicians explaining their clinical reasoning for rejection, using concept mapping and thematic analysis.

Results Among 1,722 patient episodes, physicians rejected recommendations to send a patient home in 24%, leaving text in 53%; reasons for rejection of the recommendations included additional or alternative diagnoses beyond pneumonia, and comorbidities or signs of physiologic derangement contributing to risk of outpatient failure that were not processed by the CDS. Physicians rejected broad-spectrum antibiotic recommendations in 10%, leaving text in 76%; differences in pathogen risk assessment, additional patient information, concern about antibiotic properties, and admitting physician preferences were given as reasons for rejection.

Conclusion While adoption of CDS recommendations for pneumonia was high, physicians rejecting recommendations frequently provided feedback, reporting alternative diagnoses, additional individual patient characteristics, and provider preferences as major reasons for rejection. CDS that collects user feedback is feasible and can contribute to a learning health system.

Keywords

pneumonia - implementation - clinical decision support - continuous quality improvement - health informatics - medical decision-making

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed and approved by the Intermountain Healthcare Institutional Review Board (IRB #1017598). Implied consent was obtained from all surveyed physicians by completion of the survey, and was approved by the IRB; waiver of consent was approved by the IRB for tool data collection.


Supplementary Material

 

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