A Markov Chain Model for Analysing the Progression of Patient’s Health States

Robert Jonsson ()
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Robert Jonsson: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG

No 2011:6, Research Reports from University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law

Abstract: Markov chains (MCs) have been used to study how the health states of patients are progressing in time. With few exceptions the studies have been based on the questionable assumptions that the MC has order m=1 and is homogeneous in time. In this paper a three-state non-homogeneous MC model is introduced that allows m to vary. It is demonstrated how wrong assumptions about homogeneity and about the value of m can invalidate predictions of future health states. This can in turn seriously bias a cost-benefit analysis when costs are attached to the predicted outcomes. The present paper only considers problems connected with model construction and estimation. Problems of testing for a proper value of m and of homogeneity is treated in a subsequent paper. Data of work resumption among sick-listed women and men are used to illustrate the theory. A nonhomogeneous MC with m = 2 was well fitted to data for both sexes. The essential difference between the rehabilitation processes for the two sexes was that men had a higher chance to move from the intermediate health state to the state ‘healthy’, while women tended to remain in the intermediate state for a longer time.

Keywords: Rehabilitation; transition probability; prediction; Maximum Likelihood (search for similar items in EconPapers)
JEL-codes: C10 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2011-10-31
New Economics Papers: this item is included in nep-ecm, nep-for and nep-hea
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:gunsru:2011_006

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