Paper Number
1943
Paper Type
Complete Research Paper
Abstract
In response to the challenges posed by demographic shifts and a shortage of professional caregivers, this study explores the design of Case Management Software (CMSW) to enhance the quality of care. Employing a design science approach in four iterative cycles, the research identifies critical issues, meta requirements, and design principles for CMSW in the care sector. Results reveal 12 issues with current CMSW and emphasize the importance of individualization, interface integration for external stakeholders, and alignment with case management specifics. This study's implications are significant, given the global shortage of healthcare professionals, particularly in aging societies. Recommendations include incorporating customization options, leveraging machine learning and artificial intelligence, and creating financial incentives for healthcare stakeholders. Clear communication about CMSW's relevance can promote its widespread adoption and long-term healthcare system improvement in industrial countries facing demographic changes and an aging population in need of care.
Recommended Citation
Kajüter Rodrigues, Patricia; Kus, Kevin; Arlinghaus, Tim; and Teuteberg, Frank, "Generating Design Knowledge for Case Management Software in the Care Sector" (2024). ECIS 2024 Proceedings. 12.
https://aisel.aisnet.org/ecis2024/track18_healthit/track18_healthit/12
Generating Design Knowledge for Case Management Software in the Care Sector
In response to the challenges posed by demographic shifts and a shortage of professional caregivers, this study explores the design of Case Management Software (CMSW) to enhance the quality of care. Employing a design science approach in four iterative cycles, the research identifies critical issues, meta requirements, and design principles for CMSW in the care sector. Results reveal 12 issues with current CMSW and emphasize the importance of individualization, interface integration for external stakeholders, and alignment with case management specifics. This study's implications are significant, given the global shortage of healthcare professionals, particularly in aging societies. Recommendations include incorporating customization options, leveraging machine learning and artificial intelligence, and creating financial incentives for healthcare stakeholders. Clear communication about CMSW's relevance can promote its widespread adoption and long-term healthcare system improvement in industrial countries facing demographic changes and an aging population in need of care.
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