The Decision Uncertainty Toolkit: Risk Measures and Visual Outputs to Support Decision Making during Public Health Crisis
Speaker(s)
ABSTRACT WITHDRAWN
OBJECTIVES: To adapt and extend health economic methods for the visualization, measurement, and communication of uncertainty to ID modeling.
METHODS: In consultation with decision-makers and ID modelling experts, we develop the ‘Decision Uncertainty Toolkit’ with guidance on methods, risk visualization and measurement, as well as communication with decision-makers. We develop methods to integrate traditional ID approaches to uncertainty (which focus on calibration parameters) with probabilistic sensitivity analysis (which typically applies to a broader parameter set). Visualizations are developed to quantify risk probabilistically. Quantitative measures of downside risk for policy alternatives are specified to capture both the probability and magnitude of losses relative to policy targets. To better communicate with decision makers, we embed decision thresholds within visualizations, aligning outputs more directly with policy objectives.
RESULTS: We develop the toolkit visuals and risk measures through a series of workshops with ID modellers and decision-makers in early 2023. Adoption of the toolkit will support decision-making by quantifying outcome uncertainty and the risks associated with policy alternatives.
CONCLUSIONS: The toolkit is designed to improve decision-maker understanding of decision risk and could improve outcomes during future health shocks.
Code
EPH167
Topic
Health Technology Assessment, Methodological & Statistical Research, Organizational Practices
Topic Subcategory
Best Research Practices, Decision & Deliberative Processes
Disease
Vaccines