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Diagnostic concordance between mobile interfaces and conventional workstations for emergency imaging assessment
Instituto de Informática, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Universidade Federal da Fronteira Sul, Chapecó, Brazil. (Interaction Lab)ORCID iD: 0000-0001-6479-4856
Animati Computação Aplicada à Saúde, Santa Maria, Brazi.
Medvia Diagnóstico, Porto Alegre, Brazi.
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2018 (English)In: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 113, p. 1-8Article in journal (Refereed) Published
Abstract [en]

Introduction

Mobile devices and software are now available with sufficient computing power, speed and complexity to allow for real-time interpretation of radiology exams. In this paper, we perform a multivariable user study that investigates concordance of image-based diagnoses provided using mobile devices on the one hand and conventional workstations on the other hand.

Methods

We performed a between-subjects task-analysis using CT, MRI and radiography datasets. Moreover, we investigated the adequacy of the screen size, image quality, usability and the availability of the tools necessary for the analysis. Radiologists, members of several teams, participated in the experiment under real work conditions. A total of 64 studies with 93 main diagnoses were analyzed.

Results

Our results showed that 56 cases were classified with complete concordance (87.69%), 5 cases with almost complete concordance (7.69%) and 1 case (1.56%) with partial concordance. Only 2 studies presented discordance between the reports (3.07%). The main reason to explain the cause of those disagreements was the lack of multiplanar reconstruction tool in the mobile viewer. Screen size and image quality had no direct impact on the mobile diagnosis process.

Conclusion

We concluded that for images from emergency modalities, a mobile interface provides accurate interpretation and swift response, which could benefit patients' healthcare.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 113, p. 1-8
Keywords [en]
Mobile diagnosis, Radiology, Medical imaging
National Category
Medical and Health Sciences Health Care Service and Management, Health Policy and Services and Health Economy Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-14770DOI: 10.1016/j.ijmedinf.2018.01.019ISI: 000431199300001Scopus ID: 2-s2.0-85042208743OAI: oai:DiVA.org:his-14770DiVA, id: diva2:1185204
Available from: 2018-02-23 Created: 2018-02-23 Last updated: 2018-05-23Bibliographically approved

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Bevilacqua, Fernando

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