 A continuous time Markov model for the length of stay of elderly people in institutional long‐term careH. Xie, T. J. Chaussalet and P. H. Millard Journal of the Royal Statistical Society Series A, 2005, vol. 168, issue 1, 51-61 Abstract: Summary. 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. Date: 2005 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:168:y:2005:i:1:p:51-61 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC. |
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