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WP-82-057.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/1965 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/1965 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/1965 archive 351 disk0/00/00/19/59 2016-01-15 01:51:25 2021-08-27 17:10:50 2016-01-15 01:51:25 monograph show 2 Yashin A.I. AL1394 pub iis_bio iis_pop prog_hss Medico-demographic models are used to describe the dynamic properties of a population's health status. In these models the human population is represented as a number of interacting social groups of individuals whose dynamic properties are birth, aging, death, and the transition of an individual from one state to another. The probability of these transitions plays a central role in the analysis of a population's health status. This paper concentrates on the expected number of transitions between states of selected groups of individuals and other variables from both discrete and continuous time models using the Markovian assumption. Correlation properties of the variables generated by the transition properties are also investigated. The derived formulas and properties may help the health care decision maker to estimate the expected frequency of hospitalization and the expected number of visits to physicians during a selected time interval. It also gives a reasonable basis for calculating health care resource demands within the limits of the assumptions used. Forecasting transition probabilities helps in detecting possible future problems that may arise in a health care system. 1982-06 published WP-82-057 WP-82-057 2535 public working_paper IIASA, Laxenburg, Austria 47 FALSE info:eu-repo/semantics/book