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A model for priority setting of health technology assessment: the experience of AHP-TOPSIS combination approach
Mohammadreza Mobinizadeh1, Pouran Raeissi2, Amir Ashkan Nasiripour3
1Department of Health Services Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Background:
In recent times, the use of health technologies in the diagnosis and treatment of diseases experienced considerable and accelerated growth. The goal of the present study was to describe the designated pilot MCDM (Multiple Criteria Decision Making) model for priority setting of health technology assessment in Iran.
Methods:
Relevant articles were sought and retrieved from the most appropriate medical databases, including the Cochrane Library, PubMed and Scopus via three separate search strategies, using MESH and free text until March, 2015. Retrieved criteria were questioned from health technology assessment experts in two rounds and the relative weight for valid criteria was finally obtained from paired wise comparison method. After extraction of relative weights based on the aforementioned procedure, TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) priority setting model was designed. The stated model was applied for assessing three technologies (adenosine, tissue plasminogen activator and mechanical thrombectomy) which were available for projects call of Iranian health technology assessment department in order to determine applicability of the model for practical purpose.
Results:
Nine criteria, including efficiency/effectiveness, safety, population size, vulnerable population size, availability of alternative technologies, cost effectiveness in other countries, budget impact, financial protection, quality of evidence, were extracted by the Iranian health technology assessment experts. The relative weights of these criteria were as follows 0.12, 0.2, 0.06, 0.08, 0.08, 0.13, 0.08, 0.09, and 0.15, respectively. Finally TOPSIS pilot model was designed by three health technologies and nine criteria relative weights. Results showed that, the applicability of the stated model was suitable and as the pilot testing, tissue plasminogen activator was the first priority, adenosine was second and mechanical thrombectomy was third for performing health technology assessment by the Iranian ministry of health and medical education.
Conclusion:
According to the results of this study, this model with nine effective criteria and their relative weights and in combination with TOPSIS approach could be used with suitable applicability by health technology assessment department in deputy of curative affairs and food and drug organization for determination of research priorities in health technology assessment.
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