Choices about what to fund and what not to fund are necessary in health care because claims on resources always exceed those available. Moreover, the choices faced by decision-makers are often between or amongst a wide range of difficult to compare programs or interventions. It is no surprise, then, that processes that inform those choices are of considerable interest. Yet, we know that existing priority setting processes have found limited practical use and when used, are rarely used to their full potential. The objective of the current research was to produce new knowledge that would facilitate the use of formal priority setting processes in decision-making on resource allocation in health care.
Based on a detailed review of the literature, a decision was made to focus on one particular aspect of priority setting in health care that has long been recognized as a significant barrier to the successful implementation of priority setting processes: the identification of disinvestment options. Building on initial exploratory research, a proposed procedural change to the Program Budgeting and Marginal Analysis (PBMA) priority setting process was designed to address challenges in identifying disinvestment options. The proposed procedural change was then evaluated in a case study as part of a real-world priority setting exercise.
The key finding of this research project was that adding a step -- that focused on the determination and communication of acceptable service reductions, at the outset of process implementation -- to the standard PBMA process, has the potential to assist in ‘disarming’ organizational incentives that have been found to work against the identification of disinvestment options. This key finding is of critical importance because without practical disinvestment options, priority setting processes are likely to have limited impact on decision-making and therefore limited practical appeal. Further, without formal, structured priority setting processes that actually work in practice, resource allocation decisions will continue to follow historical patterns, leading to incremental growth without explicit consideration of return on investment. As such, this study makes a novel contribution to the literature in an area that is highly relevant to the everyday challenges faced by health care decision-makers.Medicine, Faculty ofPopulation and Public Health (SPPH), School ofGraduat