Major efforts are underway to increase the information available to consumers in making health care choices. The premise of this research is that simply providing information is a necessary but not sufficient means of creating informed knowledgeable consumers: consumers need help interpreting and assimilating the growing amount of information. The general goal of this research is to determine how to help individuals process complex information about multi-attribute alternatives, specifically in the context of health plan choice. The specific objective of our research is to examine the effectiveness of alternative methods for computer-assisted interpretation and assimilation of health plan information. This research will examine the effectiveness of various forms of information restructuring strategies which are intended to assist decision makers with the judgement and integration of complex information. Two measures of decision making quality will be used to evalulate the strategies: a) a normative measure of decision accuracy (""""""""expected"""""""" versus """"""""actual"""""""" choice) and b) a self-report measure of post-decision satisfaction. The information restructuring processes will be integrated into a web-based computer research tool. This user- friendly system presents information in a hierarchial matrix format allowing subjects to perform alternative (information on all features of one alternative) and/or attribute (information on one selected feature for all alternatives) searches. The system will include six possible editing operations: rounding and re-scaling values; deleting, adding, and ordering attributes; and deleting alternatives. 475 subjects will be randomly assigned to 15 groups based on a factorial experimental design including control groups where subjects will be provided with health plan information on paper or computer, without any assistance. Subjects in the computer-assisted groups will be able to use one or more of the editing operations to assist with their interpretation and integration of a set of complex information about four health plans. Following their review and processing of the information, subjects will be asked to select a plan. Subjects will then be guided through a normative decision process to lead to a choice of plan based on a multi-attribute expected utility model. The perceived decision quality instrument will then be administered followed by the collection of a brief set of measures capturing the individual characteristics of these decision makers.
