Using Best-Worst Scaling Choice Experiments to Measure Public Perceptions and Preferences for Healthcare Reform in Australia
Jordan Louviere and
Terry Flynn Additional contact information Jordan Louviere: Centre for the Study of Choice (CenSoC), University of Technology Sydney, Sydney, New South Wales, Australia
Terry Flynn: Centre for the Study of Choice (CenSoC), University of Technology Sydney, Sydney, New South Wales, Australia
Background: One of the greatest difficulties in evaluating healthcare system reform in any country is that governments often do not clearly articulate what it is they are attempting to do. In Australia, a recent inquiry set out 15 principles to guide the reform process, but it remains unclear how the Australian public values the principles, how such values vary across the country, and, more fundamentally, if Australians understand the principles. Objectives: To evaluate the Australian healthcare reform principles from the perspective of the Australian public, to test if such preferences are valued consistently across geographic and socioeconomic strata, and to test for the degree of understanding of the principles among the public. Methods: We employed best-worst scaling (BWS), a stated-preference method grounded in random utility theory, to elicit public preference for 15 healthcare reform principles. The BWS tasks were incorporated into an online survey that also gathered geographic and socioeconomic information and included questions relating to the understanding of the reform principles. Respondents were a geographically diverse set of Australians who were randomized to receive one of two versions of the survey, each containing a block of 15 choice tasks. Tasks in block one contained a subset of the choice tasks containing subsets of seven principles based on a balanced incomplete block design, while tasks in block two contained tasks with eight principles defined by the complement of the former. In each BWS task, respondents were simply asked to identify the most and least important principle. Analysis of preference was based on assigning the most valued principles a '1' and the least valued principles '-1', and with each item appearing eight times in each block, preferences were analyzed over a cardinal utility scale bounded by -8 and +8. Analysis was based on simple summary statistics and stratified by geographic and socioeconomic measures. Results: A sample of 204 respondents participated in the survey (a participation rate of 85%). Quality and safety was the most important principle and a culture of reflective improvement and innovation was the least important. Public voice and community engagement was the second least important principle and was also understood by barely half the respondents. Conclusions: This research demonstrates how random-utility-based methods can be used to provide estimates of the importance of reform principles that have known statistical properties. The BWS task used forced respondents to discriminate between the principles on offer, unlike rating scales. Researchers and practitioners in healthcare should consider using BWS tasks in preference to rating scales.