PS 4-58
PREFERENCES FOR HEALTH ECONOMICS PRESENTATIONS AMONG VACCINE POLICY MAKERS AND RESEARCHERS
Method: We used qualitative and quantitative survey methods to understand the most valuable attributes of health economics presentations in decision making, preferences for the presentation of results and sensitivity analyses, the role of health economics studies in decision making, and strategies to improve guidelines for presenting health economics studies. The survey sample included current ACIP work group members, and current and previous ACIP voting members, liaison representatives, and ex-officio members dating back to 2007. From this sample, we used purposive sampling to select 13 individuals for key informant interviews (qualitative). In the quantitative survey, we used best-worst scaling to measure preferences of seven key attributes of health economics presentations: model overview and structural assumptions, description of cost and health valuation inputs, intermediate outcomes and disaggregated results, summary results, sensitivity analysis, discussion of limitations, and relationship of the results to other studies.
Result: The survey had a response rate of 51% (n=93). In the qualitative interviews, several common themes were identified. First, presentations of health valuations, sensitivity analyses, and model calibration were described as difficult to understand. Second, there was concern that it was difficult to assess the quality of inputs (health valuations, waning immunity assumptions) and results (projected costs, projected vaccine coverage, herd immunity). Third, additional guidance was desired regarding many aspects of the analyses, such as intermediate outcomes and disaggregated results. Results from the best-worst scaling exercise showed that summary results were the most important attribute for decision making (mean importance score: 0.69; potential range: 1,-1) and intermediate outcomes and disaggregated results were least important (mean importance score: -0.71). Among those with previous experience conducting a health economics study, sensitivity analysis had a mean importance score of 0.15 and relationship of the results to other studies had a score of -0.15. The inexperienced group had opposite preferences for these attributes, with sensitivity analysis having an aggregate score of -0.12 and relationship of the results to other studies having a score of 0.13.
Conclusion: Additional specificity in health economics presentations could allow for more efficient and effective presentation of evidence for vaccine decision making.