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Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management
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(1) that uses speech recognition for the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9895017/ https://www.ncbi.nlm.nih.gov/pubmed/36729251 http://dx.doi.org/10.1007/s10916-022-01896-y |
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author | 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 |
author_facet | 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 |
author_sort | Kerwagen, Fabian |
collection | PubMed |
description | 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(1) 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-022-01896-y. |
format | Online Article Text |
id | pubmed-9895017 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-98950172023-02-04 Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management 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 J Med Syst Original Paper 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(1) 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-022-01896-y. Springer US 2023-02-02 2023 /pmc/articles/PMC9895017/ /pubmed/36729251 http://dx.doi.org/10.1007/s10916-022-01896-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper 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 Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title | Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title_full | Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title_fullStr | Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title_full_unstemmed | Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title_short | Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management |
title_sort | usability of a mhealth solution using speech recognition for point-of-care diagnostic management |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9895017/ https://www.ncbi.nlm.nih.gov/pubmed/36729251 http://dx.doi.org/10.1007/s10916-022-01896-y |
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