Literature DB >> 30602195

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 Jones1,2, Dave S Collingridge3, Caroline G Vines3, Herman Post4, John Holmen4, Todd L Allen5, Peter Haug4, Charlene R Weir6, Nathan C Dean7.   

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. Georg Thieme Verlag KG Stuttgart · New York.

Entities:  

Year:  2019        PMID: 30602195      PMCID: PMC6327742          DOI: 10.1055/s-0038-1676587

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  42 in total

1.  CURB-65 pneumonia severity assessment adapted for electronic decision support.

Authors:  Barbara E Jones; Jason Jones; Thomas Bewick; Wei Shen Lim; Dominik Aronsky; Samuel M Brown; Wim G Boersma; Menno M van der Eerden; Nathan C Dean
Journal:  Chest       Date:  2010-12-16       Impact factor: 9.410

2.  Understanding physician adherence with a pneumonia practice guideline: effects of patient, system, and physician factors.

Authors:  E A Halm; S J Atlas; L H Borowsky; T I Benzer; J P Metlay; Y C Chang; D E Singer
Journal:  Arch Intern Med       Date:  2000-01-10

3.  Concept mapping: an introduction to structured conceptualization in health care.

Authors:  William Trochim; Mary Kane
Journal:  Int J Qual Health Care       Date:  2005-05-04       Impact factor: 2.038

4.  How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events.

Authors:  Timothy A D Graham; Andre W Kushniruk; Michael J Bullard; Brian R Holroyd; David P Meurer; Brian H Rowe
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

5.  A controlled trial of a critical pathway for treatment of community-acquired pneumonia. CAPITAL Study Investigators. Community-Acquired Pneumonia Intervention Trial Assessing Levofloxacin.

Authors:  T J Marrie; C Y Lau; S L Wheeler; C J Wong; M K Vandervoort; B G Feagan
Journal:  JAMA       Date:  2000-02-09       Impact factor: 56.272

6.  The Value of Monitoring Clinical Decision Support Interventions.

Authors:  Eileen Yoshida; Shirley Fei; Karen Bavuso; Charles Lagor; Saverio Maviglia
Journal:  Appl Clin Inform       Date:  2018-03-07       Impact factor: 2.342

7.  Variations in physician practice: the role of uncertainty.

Authors:  D M Eddy
Journal:  Health Aff (Millwood)       Date:  1984       Impact factor: 6.301

8.  Targets for antibiotic and healthcare resource stewardship in inpatient community-acquired pneumonia: a comparison of management practices with National Guideline Recommendations.

Authors:  T C Jenkins; S A Stella; L Cervantes; B C Knepper; A L Sabel; C S Price; L Shockley; M E Hanley; P S Mehler; W J Burman
Journal:  Infection       Date:  2012-11-17       Impact factor: 3.553

9.  Optimizing Clinical Decision Support in the Electronic Health Record. Clinical Characteristics Associated with the Use of a Decision Tool for Disposition of ED Patients with Pulmonary Embolism.

Authors:  Dustin W Ballard; Ridhima Vemula; Uli K Chettipally; Mamata V Kene; Dustin G Mark; Andrew K Elms; James S Lin; Mary E Reed; Jie Huang; Adina S Rauchwerger; David R Vinson
Journal:  Appl Clin Inform       Date:  2016-09-21       Impact factor: 2.342

10.  Mortality, morbidity, and disease severity of patients with aspiration pneumonia.

Authors:  Michael J Lanspa; Barbara E Jones; Samuel M Brown; Nathan C Dean
Journal:  J Hosp Med       Date:  2012-11-26       Impact factor: 2.960

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  6 in total

1.  Towards a Maturity Model for Clinical Decision Support Operations.

Authors:  Evan W Orenstein; Naveen Muthu; Asli O Weitkamp; Daria F Ferro; Mike D Zeidlhack; Jason Slagle; Eric Shelov; Marc C Tobias
Journal:  Appl Clin Inform       Date:  2019-10-30       Impact factor: 2.342

2.  Implementation of Real-Time Electronic Clinical Decision Support for Emergency Department Patients with Pneumonia Across a Healthcare System.

Authors:  Nathan C Dean; Caroline G Vines; Jenna Rubin; Dave S Collingridge; Mark Mankivsky; Raj Srivastava; Barbara E Jones; Kathryn G Kuttler; Missy Walker; Nathan Jenson; Brandon J Webb; Todd L Allen; Peter J Haug
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

3.  Physicians Voluntarily Using an EHR-Based CDS Tool Improved Patients' Guideline-Related Statin Prescription Rates: A Retrospective Cohort Study.

Authors:  Timothy S Chang; Ashwin Buchipudi; Gregg C Fonarow; Michael A Pfeffer; Jennifer S Singer; Eric M Cheng
Journal:  Appl Clin Inform       Date:  2019-06-19       Impact factor: 2.342

Review 4.  The Science of Learning Health Systems: Scoping Review of Empirical Research.

Authors:  Louise A Ellis; Mitchell Sarkies; Kate Churruca; Genevieve Dammery; Isabelle Meulenbroeks; Carolynn L Smith; Chiara Pomare; Zeyad Mahmoud; Yvonne Zurynski; Jeffrey Braithwaite
Journal:  JMIR Med Inform       Date:  2022-02-23

5.  The development and implementation of a guideline-based clinical decision support system to improve empirical antibiotic prescribing.

Authors:  H Akhloufi; H van der Sijs; D C Melles; C P van der Hoeven; M Vogel; J W Mouton; A Verbon
Journal:  BMC Med Inform Decis Mak       Date:  2022-05-10       Impact factor: 3.298

6.  Deploying an Electronic Clinical Decision Support Tool for Diagnosis and Treatment of Pneumonia Into Rural and Critical Access Hospitals: Utilization, Effect on Processes of Care, and Clinician Satisfaction.

Authors:  Jason R Carr; Barbara E Jones; Dave S Collingridge; Brandon J Webb; Caroline Vines; Blake Zobell; Todd L Allen; Rajendu Srivastava; Jenna Rubin; Nathan C Dean
Journal:  J Rural Health       Date:  2020-11-26       Impact factor: 4.333

  6 in total

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