Developing a decision support system to link health technology assessment (HTA) reports to the health system policies in Iran
Bibliographic Data
| ID | 11491027 |
|---|---|
| Authors | Shahram Yazdani (0000-0002-9193-7557, Shahid Beheshti University of Medical Sciences), Mohammad-Pooyan Jadidfard (0000-0001-7438-8376, Shahid Beheshti University of Medical Sciences, corresponding author) |
| Year | 2016 |
| Volume | 32 |
| Issue | 4 |
| Pages | czw160 |
| Publication date | 2016-12-26 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Health Policy and Planning (JOURNAL) |
| Journal identifiers | ISSN: 0268-1080 • E-ISSN: 1460-2237 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/heapol/czw160 |
| PMID | 28025325 |
| OpenAlex | W2564926158 |
| Language | EN |
| References cited | 30 |
The recent increase of 'Health Technology Assessment' (HTA)-related activities in Iran has necessitated the clarification of policy-making process based on the HTA reports. This study aimed to develop a Decision Support System (DSS) in order to adopt evidence-informed policies regarding health technologies in Iran. The study can be classified as Health Policy and Systems Research. A core panel of seven experts conducted two separate reviews of relevant literature for: 1- Determining the potential technology-related policies. 2- Listing the criteria influencing those policy decisions. The policies and criteria were separately discussed and subsequently rated for appropriateness and necessity during two expert meetings in 2013. In the next step, The 'Discrete Choice Experiment' (DCE) method was employed to develop the DSS for the final technology-related policies. Accordingly, the core panel members independently rated the appropriateness of each policy for 30 virtual technologies based on the random values assigned to all the criteria for each technology. The obtained data for each policy were separately analysed using stepwise regression model, resulting in a minimal set of independent and statistically significant criteria contributing in the experts' judgments about the appropriateness of that policy. The obtained regression coefficients were used as the relative weights of the different levels of the final criteria of any policy statement, shaping the decision support scoring tool for each policy. The study has outlined 64 policy decisions under 7 macro policy areas concerning a health technology. Also, 34 criteria used for making those policy decisions have been organized within a portfolio. DCE, using stepwise regression, resulted in 64 scoring tools shaping the DSS for all HTA-related policies. Both the results and methodology of the study may serve as a guide for policy makers (researchers), particularly in low and middle income countries, in developing decision aids for their own context-specific HTA-related policies.
Actuarial science · Business · Clinical decision support system · Data mining · Decision support system · Economic growth · Economics · Health care · Health technology · Management science · Portfolio · Set (abstract data type) · Computer Science · Global Health Care Issues · Health Informatics · Health Systems, Economic Evaluations, Quality of Life · Healthcare Systems and Reforms · Health Policy
| Highly cited | No |
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