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Published on: August 27, 2021
Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis
Ashley N D Meyer1, Pamela J Thompson2, Arushi Khanna1
1Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center and Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
Objective:
Mobile applications for improving diagnostic decision making often lack clinical evaluation. We evaluated if a mobile application improves generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning.
Methods:
In an experimental, vignette study, physicians diagnosed 8 patient vignettes with normal prothrombin times (PT) and abnormal partial thromboplastin times (PTT). Physicians made test ordering and diagnosis decisions for 4 vignettes using each resource: a mobile app, PTT Advisor, developed by the Centers for Disease Control and Prevention (CDC)'s Clinical Laboratory Integration into Healthcare Collaborative (CLIHC); and usual clinical decision support. Then, physicians answered questions regarding their perceptions of the app's usefulness for diagnostic decision making and learning using a modified Kirkpatrick Training Evaluation Framework.
Results:
Data from 368 vignettes solved by 46 physicians at 7 US health care institutions show advantages for using PTT Advisor over usual clinical decision support on test ordering and diagnostic decision accuracy (82.6 vs 70.2% correct; P < .001), confidence in decisions (7.5 vs 6.3 out of 10; P < .001), and vignette completion time (3:02 vs 3:53 min.; P = .06). Physicians reported positive perceptions of the app's potential for improved clinical decision making, and recommended it be used to address broader diagnostic challenges.
Conclusions:
A mobile app, PTT Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes. Similar methods could be useful for evaluating apps aimed at improving testing and diagnosis for other conditions.
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