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Heart failure (HF) is a severe and costly clinical syndrome associated withincreased healthcare costs and a high burden of mortality and morbidity.Although drug therapy is the mainstay of treatment for heart failure,non-adherence to prescribed therapies is common and is associated with worsehealth outcomes and increased hospitalizations. In this study, we propose anovel approach using Latent Markov models to analyze drug adherence topolytherapy over time using a secondary database. Our methodology enables us toevaluate patients' drug utilization behaviour, identify complex behaviouralpatterns, and incorporate them into predictive models to improve clinicaloutcomes. The significance of adhering to prescribed therapies for patients'prognosis has been highlighted in this study. Our findings show that adherentpatients gained an additional ten months of life over a seven-year follow-upperiod compared to non-adherent patients. This underscores the importance ofsecondary prevention and continuous monitoring of heart failure patients. Theseprocedures are crucial for identifying areas of improvement and promotingbetter adherence to prescribed therapies.

Long-term adherence to polytherapy in heart failure patients: a novel approach emphasising the importance of secondary prevention