Selecting the Acceptance Criteria of Medicines in the Reimbursement List of Public Health Insurance of Iran, Using the "Borda" Method: a Pilot Study.

Decision-making for medicines to be accepted in Iran's public health insurance reimbursement list is a complex process and involves factors, which should be considered in applying a coverage for medicine costs. These processes and factors are not wholly assessed, while assessment of these factors is an essential need for getting a transparent and evidence-based approach toward medicine reimbursement in Iran. This paper aims to show an evidence-based approach toward medicine selection criteria to inform the medical reimbursement decision makers in Iranian health insurance organizations. To explore an adaptable decision-making framework while incorporating a method called "Borda" in medicine reimbursement assessment, we used the help of an expert group including decision makers and clinical researchers who are also policy makers to appraise the five chief criteria that have three sub criteria (Precision, Interpretability, and Cost). Also software "Math-lab"7, "SPSS" 17 and Excel 2007 were used in this study. "Borda" estimates the amount of perceived values from different criteria and creates a range from one to five while providing a comprehensive measurement of a large spectrum of criteria. Participants reported that the framework provided an efficient approach to systematic consideration in a pragmatic format consisting of many parts to guide decision-makings, including criteria and value (a model with the core of Borda) and evidences (medicine reimbursement based on criteria). The most important criterion for medicine acceptance in health insurance companies, in Iran, is the "life-threatening" factor and "evidence quality" is accounted as the fifth important factor. This pilot study showed the usefulness of incorporating Borda in medicine reimbursement decisions to support a transparent and systematic appraisal of health insurance companies' deeds. Further research is needed to advance Borda-based approaches that are effective on health insurance decision making.