Abstract

REVIEW ON PHARMACOECONOMIC MODELLING METHODS IN INDIAN HEALTHCARE

Shivaani M. U.* and Abiya Varghese

ABSTRACT

Introduction: Pharmacoeconomic modelling is an advanced method to study the effective medical therapies. This article includes the presentation and outline of various models of pharmacoeconomic modelling like decision tree, how to develop a decision tree with a diagrammatic representation, ICER, markov model, cohort simulation, half cycle, discounting, how to develop markov model in excel, sensitivity analysis and microsimulation. Methods: We searched for all the literatures on various pharmacoeconomic models from the international database PubMed. We selected the articles that explained about various models and way to compute them. We had reviewed on the types of pharmacoeconomic models, how to develop/compute various models with their pros and cons also, the software packages available for free and subscription to compute these models. Results: Decision tree contains a structure that represents all the possible clinical pathways. A markov model is used to model chronic diseases and even relapse of the disease can be modelled. Markov model without a decision tree models only for the survival (terminal node). PSA measures the impact of combined uncertainty on the model outcomes. Microsimulation is used to model the cost effective analysis. Discussion: Pharmacoeconomic modelling plays an important role because the clinical trials are done only for a short period of time because it is a way too expensive, hence a pharmacoeconomic model is developed and the patients included in the study are followed until the end point say even death. But still these modelling methods are preferred for their accuracy, reliability and moreover they‟re inexpensive. Conclusion: Pharmacoeconomic models provide great evidence for the cost and effectiveness of an intervention along with their risks and benefits.

Keywords: Decision tree, Markov model, Markov in excel, ICER, Discounting, Cohort simulation, Probability sensitivity analysis, Microsimulation in R, Free software to compute models.