Evaluación de la costo-efectividad de un modelo integral de tratamiento ambulatorio en pacientes con síndrome coronario agudo: aplicación de un modelo de Markov probabilístico

OBJECTIVE: To evaluate the cost-effectiveness of an integral model of ambulatory treatment in patients who presented an acute coronary syndrome. METHODS: An economic evaluation was made from a quasi-experimental intervention study, which included 442 patients aged 30 to 70 years who presented an acute coronary syndrome. The intervention group (n = 165) received an integral model of ambulatory treatment based on managed care (disease management), while the control group (n = 277) received conventional cardiovascular rehabilitation. During one year of follow-up, the presentation of cardiovascular events and hospitalizations was evaluated. A probabilistic Markov model was developed. The study perspective was applied within the General System of Health Social Security in Colombia, including the direct health costs; the time horizon was 50 years with discounts of 3.42% for costs and effectiveness; and the measure of effectiveness was quality-adjusted life years (QALYs). A probabilistic and multivariate sensitivity analysis was performed using the Montecarlo simulation. RESULTS: During the year of follow-up, the direct costs related to the value paid were, on average, USD 2 577 for the control group and USD 2 245 for the intervention group. In the probabilistic sensitivity analysis, 91.3% of the simulations were located in the quadrant corresponding to incremental negative costs and positive incremental effectiveness (evaluated intervention at a lower cost, more effective). In the simulations, an average annual savings per patient of USD 1 215 per QALY was observed. CONCLUSIONS: The integral model of ambulatory treatment implemented in patients who suffered an acute coronary syndrome was found to be less expensive and more effective compared to conventional care. Considering it is a dominant alternative, it is recommended as a model of care in this population.