title: Fixing the game: are between-silo differences in funding arrangements handicapping some interventions and giving others a head-start?
abstract: Given resource scarcity, not all potentially beneficial health services can be funded. Choices are made, if not explicitly, implicitly as some health services are funded and others are not. But what are the primary influences on those choices? We sought to test whether funding decisions are linked to cost effectiveness and to quantify the influence of funding arrangements and community values arguments. We tested this via empirical analysis of 245 Australian health-care interventions for which cost-effectiveness estimates had been published. The likelihood of government funding was modelled as a function of cost effectiveness, patient/target group characteristics, intervention characteristics and publication characteristics, using multiple regression analysis. We found that higher cost effectiveness ratios were a significant predictor of funding rejection, but that cost effectiveness was not related to the level of funding. Intervention characteristics linked to funding and delivery arrangements and community values arguments were significant predictors of funding outcomes. Our analysis supports the hypothesis that funding and delivery arrangements influence both whether an intervention is funded and funding level; even after controlling for community values and cost effectiveness. It suggests that adopting partial priority setting processes without regard to opportunity cost can have the perverse effect of compounding allocative inefficiencies.
authors.affiliation: Centre for Health Economics, Faculty of Business and Economics, Monash University, Victoria, Australia. leonie.segal@unisa.edu.au
authors.forename: Leonie
authors.initials: L
authors.lastname: Segal
authors.forename: Kim
authors.initials: K
authors.lastname: Dalziel
authors.forename: Duncan
authors.initials: D
authors.lastname: Mortimer
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001315:Australia; D002648:Child; D002675:Child, Preschool; D003362:Cost-Benefit Analysis; D003657:Decision Making; D005260:Female; D005380:Financing, Government; D006296:Health Services / Q000191:economics*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D055815:Young Adult