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A continuous time Markov model for the length of stay of elderly people in institutional long-term care

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The paper develops a Markov model in continuous time for the length of stay of elderly people moving within and between residential home care and nursing home care. A procedure to determine the structure of the model and to estimate parameters by maximum likelihood is presented. The modelling approach was applied to 4 years’ placement data from the social services department of a London borough. The results in this London borough suggest that, for residential home care, a single-exponential distribution with mean 923 days is adequate to provide a good description of the pattern of the length of stay, whereas, for nursing home care, a mixed exponential distribution with means 59 days (short stay) and 784 days (long stay) is required, and that 64% of admissions to nursing home care will become long-stay residents. The implications of these findings and the advantages of the proposed modelling approach in the general context of long-term care are discussed.

Keywords: Length-of-stay modelling; Long-term care; Markov model; Survival

Document Type: Research Article


Affiliations: University of Westminster, London, UK

Publication date: 2005-01-01

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