Applications of minimum data set in long-term care research

Liang Yu Chen, Ming Hsien Lin, Li Ning Peng, Liang Kung Chen*


研究成果: Review article同行評審


Population aging is a global phenomenon that poses special challenges to the health care systems. Advanced aging is often featured by the concurrent progressive declines in both physical and cognitive function, as well as more emotional problems, decreased social engagement, institutionalization and mortality. Although promoting aging in place is the main goal of elderly care, still a certain proportion of older adults need long-term care facilities (LTCFs) admissions. Providing effective management with continuing care services is of critical importance to the overall quality of care. In 1987, under the Omnibus Budget Reconciliation Act, Health Care Financing Administration of the United States started to provide and reimburse long-term care services for older people with complex care needs. To properly financing these services, Minimum Data Set (MDS) was constructed, which included resident assessment instrument, resident assessment protocols and guidelines utilization. MDS worked as a comprehensive, standardized evaluation tool on assessing and managing LTCF residents with different physical, psychological and social conditions. The systematic implementation of MDS substantially improved the quality of LTCF care by identifying the dynamic changes of each item, and understanding the complex intertwined network among each domains. Gradually, MDS became a powerful research resource in addition to its management of long-term care services. This review briefly introduced the development of MDS and related research using MDS, especially the Longitudinal Older VEterans (LOVE) study in Taiwan.

頁(從 - 到)118-125
期刊Journal of Clinical Gerontology and Geriatrics
出版狀態Published - 12月 2018


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