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Updated: Jun 15, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Community detection and management of mild cognitive impairment in Shanghai: a mixed-methods study
Yuan Lu1, Dehua Yu2, Yvonne Wells3
1Department of Gerontology, Yangpu Hospital, Tongji University School of Medicine, 450 Tengyue Road,Tongji University Affiliated Yangpu Hospital, Shanghai 200090, China.
None:
Dementia has been regarded as a priority in public health for healthy ageing. Mild cognitive impairment (MCI) detection and management is one of the strategies to confront the challenge of increasing burden of dementia. However, MCI is not well recognized or managed in primary care. This study aimed to assess system barriers relating to MCI detection and management in the community. A mixed-methods study was undertaken over the period from October 2020 to October 2022. First, a focus group study (n = 124) in Shanghai explored the experiences of general practitioners (GPs), people with MCI and their informal caregivers, and community health managers using thematic analysis. This was followed by 2 rounds of national Delphi surveys among 22 eligible experts to solicit their consensus on the system conditions needed for community detection and management of MCI. A questionnaire survey based on the Delphi consultations was conducted with GPs (n = 1253) recruited from 56 community health centres (CHCs) in Shanghai to quantify their knowledge, attitudes, and practice (KAP) toward community detection and management of MCI and perceived system barriers. The results were mapped and triangulated in line with the chronic care model (CCM) and the health system building blocks articulated by the World Health Organization. Potential system barriers were identified from eight themes: (i) lack of self-management skills and enablement; (ii) lack of family support; (iii) lack of community support; (iv) unprepared healthcare system; (v) health service delivery deterrence; (vi) inadequate clinical decision support; (vii) lack of case management; and (viii) misaligned clinical information systems. The primary care system in Shanghai is not adequately equipped to handle the task of detecting and managing MCI. Both intrinsic and extrinsic obstacles impede the successful conversion of MCI knowledge into desired actions. A systems approach is needed to confront the challenge of MCI detection and management in China.
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