DEVELOPMENT OF A MARKOV MODEL TO EVALUATE TREATMENTS OF ALCOHOL ABUSE

Purpose: A wide variety of psychosocial and pharmacological interventions are available for alcohol abuse, but there have been few cost-effectiveness analyses. We sought to develop a Markov model to describe health states related to alcohol consumption, with the goal of evaluating the effect on life expectancy of different alcohol abuse treatments.

Method: We developed a decision analytic model to project the lifetime clinical and economic consequences of alcohol use. The model consists of 2 sub-models: an alcohol consumption model and a mortality model. The alcohol sub-model simulates transitions between four drinking levels, dependent on gender and age. The drinking levels correspond to lifetime abstinent (0 grams of alcohol per day), former drinker (0 grams of alcohol per day), light or moderate drinker (up to 68 grams of alcohol per day), or heavy drinker (over 68 grams of alcohol per day). The probability of dying from each disease is related to alcohol consumption, age and gender. Both models are simulated in 1 year time steps for a life time horizon. The alcohol sub-model was calibrated and validated using the National Health and Nutrition Examination Survey Epidemiological Followup Study, the National Longitudinal Survey of Youth 1979 , and the Canadian Alcohol and Drug Use Monitoring Survey. The mortality sub-model was calibrated using Canadian datasets and a review by Rehm et al. (2010) that estimated increased mortality as a function of alcohol consumption for several diseases associated with alcohol use.

Result: Life expectancy for males and females 18 years of age is approximately 80.9 and 85.7 years of age, respectively. Our model estimated life expectancy of 74.0 and 78.4, respectively. Percentage of deaths due to different causes were also compared: 22.2% of males and 20.3% of females were expected to die due to heart disease compared with an estimated 36.7% and 20.8%. Death due to stroke was expected to make up 4.7% and 3.1% of deaths for males and females, respectively, but was estimated to be 11.3% and 1.3%.

Conclusion: Our model indicates that alcohol drinking patterns with probability of death associated with gender, age, and drinking pattern can adequately estimate life expectancy for the Canadian population. This Markov model can be used to further investigate the relative survival, quality of life, and cost characteristics of alcohol abuse treatments.