ArticleInternational journal of technology assessment in health care2025
Developing the Iranian health insurance benefit optimization model - the IR-HIBOM: a multicriteria decision analysis with decision rules for designing basic health insurance benefit packages.
Article in International journal of technology assessment in health care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesPrioritization of health technologies for insurance coverage is usually based on explicit and implicit criteria. This study presents the development of the multi-criteria decision analysis (MCDA) model, the Iranian Health Insurance Benefit Optimization Model (IR-HIBOM), to inform the design of basic health insurance benefit packages.
methodsAn initial set of twenty-nine potential allocation criteria was identified through a review of available evidence and other relevant literature. Review of this set by three specialized panels yielded a final set of thirteen criteria. A cross-sectional survey using the best-worst scaling method was then fielded to 163 health system experts to evaluate their preferences regarding the relative importance of the allocation criteria. The mixed logit method was employed to determine the weight of the relative importance of each criterion. Subsequently, a multilevel criteria scoring framework was defined based on a review of similar models and input from a panel of five expert members of the study team. Finally, model's appraisal was conducted.
resultsThirteen criteria, including relative safety, efficacy, disease severity, access to alternative health technologies, budget impacts, cost-effectiveness, quality of evidence, population size, age, job absenteeism, economic status, daily care needs, and ease-of-use/acceptance were selected. Cost-effectiveness and ease-of-use criteria had the highest and lowest relative importance weights, with 30.5 percent and 1 percent, respectively. Furthermore, scores were determined for the several levels of each criterion, and decision rules were defined for the cost-effectiveness and budget impact criteria. The final model's appraisal, based on weighted scores of thirteen selected technologies, indicated that it was valid and applicable.
conclusionsThe IR-HIBOM demonstrated its potential utility in the health resource allocation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.