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Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management.

Authors :
Kerwagen, Fabian
Fuchs, Konrad F.
Ullrich, Melanie
Schulze, Andres
Straka, Samantha
Krop, Philipp
Latoschik, Marc E.
Gilbert, Fabian
Kunz, Andreas
Fette, Georg
Störk, Stefan
Ertl, Maximilian
Source :
Journal of Medical Systems; 2023, Vol. 47 Issue 1, p1-10, 10p, 2 Color Photographs, 4 Diagrams, 1 Chart, 1 Graph
Publication Year :
2023

Abstract

The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital Würzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile<superscript>1</superscript> that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital Würzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p <.001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p =.02) and effort expectancy (beta = 0.36, p =.04) were identified as predictors of acceptance, the full predictive model explained 65.4% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users' needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians' daily work. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01485598
Volume :
47
Issue :
1
Database :
Complementary Index
Journal :
Journal of Medical Systems
Publication Type :
Academic Journal
Accession number :
161820943
Full Text :
https://doi.org/10.1007/s10916-022-01896-y