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Assessing the Usability of a Tumor Dashboard for Multidisciplinary Care Teams for First Time Users; First Exploration of a Comparative Participatory Cognitive Walkthrough to Show Mismatches in Cognitive Models.
Ter Beek, Emmanuelle; Kos, Milan; Streppel, Mirte; Dusseljee-Peute, Linda; van Oijen, Martijn.
  • Ter Beek E; Department Medical Informatics, University of Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • Kos M; Department Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • Streppel M; Department Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • Dusseljee-Peute L; Department Medical Informatics, University of Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • van Oijen M; Department Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands.
Stud Health Technol Inform ; 286: 99-106, 2021 Nov 08.
Article in English | MEDLINE | ID: covidwho-1512004
ABSTRACT
Due to the COVID-19 pandemic, multidisciplinary team (MDT) meetings have to switch from physical to digital meetings. However, the technology they currently use to facilitate these meetings can sometimes be lacking, therefore many software companies have developed new software to ease our new digital workspace. In this study, we propose a new method, a comparative participatory cognitive walkthrough, which can show mismatches in cognitive models. To test our method, we tested the compatibility of EPIC EMR (EPIC Care) and the NAVIFY Tumor Board for preparing MDT meetings. The identified mismatches are categorized in the HOT-fit model by Yusof et al, a common way to evaluate if a healthcare information system fits with the healthcare professionals and the organization. In total, 16 mismatches were identified. These mismatches were discussed in a feedback session with an implementation manager of the NAVIFY Tumor Board. The proposed method seems to be a fast and cheap method to gain useful insights in how well new software matches with the software currently in use, by comparing the cognitive models in place when performing tasks involved with specific scenarios. The identified aspects can be of use for the development and adaptation of the new software, as well as provide guidelines on which aspects to focus on when training healthcare professionals to use the new software to have a smooth transition of software.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Neoplasms Type of study: Experimental Studies Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210646

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Neoplasms Type of study: Experimental Studies Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210646