Abstract
Historically, resource allocation in healthcare is mainly driven by demand (as opposed to actual need) and fails to incorporate a series of value judgements that are essential from a social welfare maximisation perspective. The objective of this study was to develop and apply a multiple societal value criteria approach in order to highlight the preferences regarding the priorities for resource allocation among disease categories within the context of a hypothetical (and anticipated) increase in the public healthcare budget of Greece. The approach broadly follows the principles of multiple criteria decision analysis. Initially, a list of relevant resource allocation criteria, under specific properties (completeness, non-redundancy, non-overlap, independence) was developed, following a detailed literature review. Societal value judgments were sourced via a multidisciplinary panel of experts. The panel, via compositional scoring elicitation, provided the scores for each alternative (sixteen disease categories, classified according to the Global Burden of Disease study) in each criterion. Finally, the weight for each criterion in the decision algorithm was determined and “total value” in terms of priority preference was estimated under an additive value function. The criteria that were deemed relevant to the decision-making process and their respective weights were: burden of disease of each disease category (0.245), capacity-to-benefit from further allocation of resources (0.190), direct cost and projected changes in the next 5years (0.160), indirect cost (0.132), intensity of unmet needs (0.109), incidence of catastrophic expenditure (0.091) and “option value” (0.073). Combining the performance scores of each disease category - against each criterion - and criteria weights, highest “total value” scores were recorded for neoplasms, circulatory diseases, injuries, neurological diseases and diseases of the musculoskeletal system (top-5 choices in descending order). Incorporation of societal value criteria in resource allocation decisions can highlight priorities and lead to different sets of planning decisions than solely demand-driven allocation.
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