Does it matter who you are or what you gain? An experimental study of preferences for resource allocation.
Using an experimental conjoint-analysis like approach, preferences for resource allocation were studied. An interactive survey was developed which was published in the World Wide Web. A convenience sample of undergraduate students participated in the study. Subjects were confronted with nine pairwise scenarios describing hypothetical patient groups in need of life-saving treatments. The patient groups presented differed in terms of their health-related lifestyle, socioeconomic status, age, life expectancy, quality of life after treatment and whether they had received extensive medical care in the past. Participants were asked to allocate a finite budget to each patient group. All attributes used in this study significantly influenced respondents' preferences on how to allocate the budget between patient groups. The general importance of attributes used in the QALY approach is supported by this study with quality of life being a central criterion. The distributional patterns observed were, however, different from those expected when rigorously adhering to the QALY framework: In only a very small fraction of allocations subjects distributed the entire budget strictly on the patient group expecting the highest QALY gain. The vast majority of responders was willing to trade efficiency for a more equal distribution of resources. The approach described can be used to analyze the importance people place on different attributes in resource allocation decisions and to study preferences for the final distribution of resources.
Schwappach
David L B
DL
University Witten /Herdecke, Department of Health Policy and Management, Witten, Germany. dlb@healthecon.de
D000367:Age Factors; D001294:Attitude to Health; D002017:Budgets; D003258:Consumer Behavior / Q000191:economics / Q000706:statistics & numerical data*; D003657:Decision Making; D005858:Germany; D015276:Health Care Rationing / Q000191:economics / Q000706:statistics & numerical data*; D019538:Health Care Surveys / Q000379:methods*; D006292:Health Priorities / Q000145:classification / Q000191:economics; D006801:Humans; D008017:Life Expectancy; D008019:Life Style; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D040841:Resource Allocation / Q000191:economics; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires