Variation in average costs among federally sponsored state-organized cancer detection programs: economies of scale?

Societal cost-effectiveness analysis and its variants help decision makers achieve an efficient allocation of resources across the set of all possible health interventions. Sometimes, however, decision makers are focused instead on the efficient allocation of resources within a particular intervention program that has already been implemented. This is especially true when the intervention is being delivered at several different sites. An analysis of average cost across program sites may help program officials to maximize the health benefits that can be achieved with limited resources. In this article, the authors present such an analysis, with special attention paid to the possible existence and implications of economies of scale.

Focusing on federally sponsored, state-organized cancer detection programs, the authors modeled 19 state programs as productive processes and examined their average costs over a 2- to 5-year period of operation. They considered 3 alternative definitions of output: women served, screens performed, and conditions detected. Average federal costs and average total costs were estimated for each grant period. Multivariate regression analysis was used to help explain the variation in average costs.

The average cost estimates were distributed in a skewed pattern with the majority of observations falling close to the median and substantially below the mean. For all measures considered, average cost decreased as output expanded. This inverse relationship between average cost and output level persisted even after controlling for the effects of other predictors, suggesting the possible existence of economies of scale.

The potential existence of economies of scale calls into question the assumption of a constant average cost frequently made in economic analyses of proposed public health programs. It also implies that a) differences in output level should be taken into account when comparing operating efficiency across program sites; b) conclusions from societal cost-effectiveness analyses may depend on the level of output at which the programs are evaluated; c) cost projections could be inaccurate if they do not take into account the decrease in average cost that occurs as output expands; and d) gains might be possible if similar programs with limited output potential are integrated, perhaps through cost sharing.