A Markov Chain Model for Analysing the Progression of Patient’s Health States
AbstractMarkov 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg in its series Research Reports with number 2011:6.
Length: 32 pages
Date of creation: 31 Oct 2011
Date of revision:
Contact details of provider:
Postal: Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG
Web page: http://www.statistics.gu.se/
Rehabilitation; transition probability; prediction; Maximum Likelihood;
Find related papers by JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-07 (All new papers)
- NEP-ECM-2011-11-07 (Econometrics)
- NEP-FOR-2011-11-07 (Forecasting)
- NEP-HEA-2011-11-07 (Health Economics)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Linus Schiöler) The email address of this maintainer does not seem to be valid anymore. Please ask Linus Schiöler to update the entry or send us the correct address.
If references are entirely missing, you can add them using this form.