Journal article
Digital Methodology for Mobile Clinical Decision Support Development in Long-Term Care
Studies in health technology and informatics, Vol.290, pp.479-483
06/06/2022
DOI: 10.3233/SHTI220122
Abstract
The global COVID-19 pandemic has driven innovations in methods to sustain initiatives for the design, development, evaluation, and implementation of clinical support technology in long-term care settings while removing risk of infection for residents, family members, health care workers, researchers and technical professionals. We adapted traditional design and evaluation methodology for a mobile clinical decision support app – designated Mobile Application Information System for Integrated Evidence (“MAISIE”) – to a completely digital design methodology that removes in-person contacts between the research team, developer, and nursing home staff and residents. We have successfully maintained project continuity for MAISIE app development with only minor challenges while working remotely. This digital design methodology can be implemented in projects where software can be installed without in-person technical support and remote work is feasible. Team skills, experience, and relationships are key considerations for adapting to digital environments and maintaining project momentum.
Details
- Title: Subtitle
- Digital Methodology for Mobile Clinical Decision Support Development in Long-Term Care
- Creators
- Malaika R Gallimore - University of MissouriChelsea Howland - University of MissouriJo-Ana D ChaseAmy Grimsley - University of MissouriChuka Emezue - University of MissouriKatrina Boles - University of MissouriAllison B Anbari - University of MissouriLeeAnne B Sherwin - University of MissouriAmy Vogelsmeier - University of MissouriLori Popejoy - University of MissouriMarilyn J Rantz - University of MissouriBlaine Reeder - University of Missouri
- Resource Type
- Journal article
- Publication Details
- Studies in health technology and informatics, Vol.290, pp.479-483
- DOI
- 10.3233/SHTI220122
- ISSN
- 0926-9630
- eISSN
- 1879-8365
- Language
- English
- Date published
- 06/06/2022
- Academic Unit
- Nursing; Center for Social Science Innovation
- Record Identifier
- 9984696752702771
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