The Incorporation of Potential Confounding Variables in Markov Models
Mark J.C. Nuijten
Objective: To improve the quality of the methods used in Markov modelling studies by increasing the external validity by means of the incorporation of confounding variables. Study design: The concepts were illustrated using a hypothetical Markov model for Parkinson's disease. Methods: The methodology consisted of incorporation of an extra explanatory variable in the Markov health states by means of health state-specific relationships between this explanatory variable and costs as well as time-dependent values of the extra explanatory variable. In addition, we determined the relevance of the incorporation of an extra explanatory variable by means of various sensitivity analyses. Results: The results showed that the outcomes of a health economic model may be severely biased, when a confounding effect of an extra explanatory variable is not taken into account. Hence the external validity of Markov models may be limited, and consequently the results of the model are not an accurate reflection of reality. Conclusion: This study proves the need for the incorporation of all relevant explanatory variables in a health economic model.
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