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Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation

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Title: Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation
Authors: Kostopoulou, O
Porat, T
Corrigan, D
Mahmoud, S
Delaney, BC
Item Type: Journal Article
Abstract: Background Observational and experimental studies of the diagnostic task have demonstrated the importance of the first hypotheses that come to mind for accurate diagnosis. A prototype decision support system (DSS) designed to support GPs’ first impressions has been integrated with a commercial electronic health record (EHR) system. Aim To evaluate the prototype DSS in a high-fidelity simulation. Design and setting Within-participant design: 34 GPs consulted with six standardised patients (actors) using their usual EHR. On a different day, GPs used the EHR with the integrated DSS to consult with six other patients, matched for difficulty and counterbalanced. Method Entering the reason for encounter triggered the DSS, which provided a patient-specific list of potential diagnoses, and supported coding of symptoms during the consultation. At each consultation, GPs recorded their diagnosis and management. At the end, they completed a usability questionnaire. The actors completed a satisfaction questionnaire after each consultation. Results There was an 8–9% absolute improvement in diagnostic accuracy when the DSS was used. This improvement was significant (odds ratio [OR] 1.41, 95% confidence interval [CI] = 1.13 to 1.77, P<0.01). There was no associated increase of investigations ordered or consultation length. GPs coded significantly more data when using the DSS (mean 12.35 with the DSS versus 1.64 without), and were generally satisfied with its usability. Patient satisfaction ratings were the same for consultations with and without the DSS. Conclusion The DSS prototype was successfully employed in simulated consultations of high fidelity, with no measurable influences on patient satisfaction. The substantially increased data coding can operate as motivation for future DSS adoption.
Issue Date: 23-Feb-2017
Date of Acceptance: 11-Oct-2016
URI: http://hdl.handle.net/10044/1/43811
DOI: 10.3399/bjgp16X688417
ISSN: 1478-5242
Publisher: Royal College of General Practitioners
Start Page: e201
End Page: e208
Journal / Book Title: British Journal of General Practice
Volume: 67
Issue: 656
Copyright Statement: © British Journal of General Practice 2017 This is an OpenAccess article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: European Commission FP7
Keywords: Science & Technology
Life Sciences & Biomedicine
Primary Health Care
Medicine, General & Internal
General & Internal Medicine
decision support systems
diagnosis
diagnostic accuracy
diagnostic errors
electronic health record
first impressions
general practice
CARE
CONSULTATIONS
SATISFACTION
PHYSICIANS
decision support systems
diagnosis
diagnostic accuracy
diagnostic errors
electronic health record
first impressions
general practice
Adult
Aged
Computer Simulation
Decision Support Systems, Clinical
Diagnosis, Computer-Assisted
Diagnostic Errors
Early Diagnosis
Electronic Health Records
Female
General Practice
Humans
Male
Middle Aged
Quality Improvement
Referral and Consultation
Reproducibility of Results
United Kingdom
Young Adult
Humans
Diagnosis, Computer-Assisted
Diagnostic Errors
Early Diagnosis
Reproducibility of Results
Computer Simulation
Decision Support Systems, Clinical
Adult
Aged
Middle Aged
Referral and Consultation
Female
Male
Young Adult
Electronic Health Records
General Practice
Quality Improvement
United Kingdom
1117 Public Health and Health Services
Public Health
Publication Status: Published
Online Publication Date: 2017-02-23
Appears in Collections:Department of Surgery and Cancer
Faculty of Medicine
Dyson School of Design Engineering
Institute of Global Health Innovation
Faculty of Engineering