Objectives: Develop the BDP through a technically sound and broadly consultative process. Methods: The process of developing the BDP was started with the drafting of a technical note discussing the rationale, contents and proposed approach for its development. This was followed by a broad consultation of stakeholders representing PhilHealth members, providers, the Department of Health, members from the academe and research community, and development partners. Results: There was consensus that the introduction of benefits under UHC will use criteria such as legal mandates, burden of disease, advances in technology, value for money and fund viability, among others. Appropriate decision rules will have to be developed to make use of these criteria in decision-making. In addition, the stakeholders agreed on a formal and explicit process in benefit development. Making the process explicit improves transparency in the benefit development process where interests of various stakeholders can be managed and operational considerations can be flagged. Both members and providers expressed strong preference to be involved in the benefit development process at its various stages. The role of the Health Technology Assessment Council (HTAC) also needs to be defined as new benefits can only be introduced if there is positive recommendation. Conclusions: PhilHealth is expected to complete its BDP soon. Other countries in similar stages of implementing UHC may want to study how an explicit benefit development process can be developed and implemented.
number of EU countries. The financial impact of the long-term sequelae has not yet been well studied. The large heterogeneity and the low number of data points found make it difficult to summarize the cost of meningococcal disease.
identified published economic evaluations of cancer treatments using a model, and single technology appraisals (STAs) submitted to the National Institute for Health and Care Excellence (NICE). Searches were performed in November 2018, capturing relevant publications and STAs published since 2013 up to the date of searching. Published literature was identified using Medline and EMBASE via Ovid. The review was supplemented with methods literature known to the authors discussing cancer modelling. Results: The review identified 100 NICE STAs and 124 published studies relevant to the topic. Published studies appeared to report a greater use of discretetime state transition-models (n=102, 82%) when compared to NICE submissions. Partitioned-survival analysis (n=54, 54%) and discrete-time state-transition structures (n=41, 41%) were the main structures submitted to NICE. Justification of model structures and consideration of structural uncertainty were very limited across both the publications and the NICE submissions. Conclusions: There appears to be a stronger dominance of the partitioned-survival analysis approach in submissions to NICE, however, we believe many of the published state transition models have been incorrectly labelled and are partitioned-survival analysis. Other structures, such as a decision tree or discrete-event simulation, have also been utilised in submissions and within the published literature but only in minority of cases. Justification for the model structure was very limited, despite a recognition in the literature that model structure can greatly influence cost-effectiveness results and the validity of the economic evaluation and studies would be improved with a thorough rationale for this choice.
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