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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Sociotechnical integration of decision support in the dementia domain
Helena Lindgren1, Sture Eriksson
1Department of Computing Science, Umeå University, Sweden. helena@cs.umu.se
Abstract:
The need for improving dementia care has driven the development of the clinical decision support system DMSS (Dementia Management and Support System). A sociotechnical approach to design and development has been applied, with an activity-centered methodology and user participation throughout the process. Prototypes have been developed based on the characteristics of clinical practice and domain knowledge, while clinical practice has been subjected to different efforts for development such as education and organizational change. This paper addresses the lessons learned and role and impact DMSS has had, and is expected to have on the clinical assessment of dementia in different clinics in Sweden, South Korea and Japan. Furthermore, it will be described in what way the development of DMSS and the development of dementia care in these three areas are interlinked. Results indicate that the most important contribution of DMSS at the point of care, is the educational support that DMSS provides, part from the tailored explanatory support related to a patient case. This effect was partly manifested in a change of routines in the encounter with patients.
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