A Continuous Time Markov Model for the Length of Stay of Elderly People in Institutional Long-Term Care
| Autor: | Thierry J. Chaussalet, Peter H. Millard, Haifeng Xie |
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| Rok vydání: | 2004 |
| Předmět: |
Statistics and Probability
Economics and Econometrics Exponential distribution Context (language use) Social Welfare Markov model medicine.disease Long-term care Short stay Borough Survival function medicine Medical emergency Statistics Probability and Uncertainty Psychology Social Sciences (miscellaneous) Demography |
| Zdroj: | Journal of the Royal Statistical Society Series A: Statistics in Society. 168:51-61 |
| ISSN: | 1467-985X 0964-1998 |
| DOI: | 10.1111/j.1467-985x.2004.00335.x |
| Popis: | SummaryThe 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. |
| Databáze: | OpenAIRE |
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