Fumie Yokota Griego
Dissertation Title: "Improving Value of Information Analysis in Health Risk Management"
Value of information (VOI) analysis is a decision analytic approach for evaluating the benefit of collecting additional information to reduce or eliminate uncertainty in a specific decision making context. Though experts have encouraged the use of a VOI approach in framing complex decision-making problems where uncertainties are large and stakes are high, formal VOI analysis do not yet play a major role in regulatory decision-making. Section 1 of the thesis explores the evolution of the VOI methods in health risk management through a comprehensive content analysis of VOI applications in the peer reviewed health literature. Chapter 1 shows the evolution of the methodology and advances in computing tools that allow analysis of problems with greater complexity. The analysis shows a lack of standardization of reporting methods and results, and little cross-fertilization across topic areas. Chapter 2 narrows the focus to applications in environmental health risk management (EHRM) and provides risk analysts and decision scientists with some guidance on how to structure and solve VOI problems related to EHRM decisions. Section 2 applies the VOI framework to a tiered toxicological testing program and explores the question: How much should uncertainty about risk be reduced before action is taken? Chapter 3 examines the optimal testing strategy from the perspective of a net benefits maximizing decision maker who is able to regulate chemical exposures based on predictions of carcinogenicity from lower tier tests. The analysis shows that both the level of expected human exposure and economic considerations such as control costs for reducing exposure are critical in the decision to pursue further testing, and that for a wide rage of exposures and costs, testing is not optimal. Furthermore, for a set of plausible exposure and control costs, it is optimal to regulate without further testing. Chapter 4 explores the optimal testing strategy of a constrained decision maker who, absent applicable human data, cannot regulate without bioassay data on a specific chemical. The analysis shows that delaying action until all tests results are available can lead to substantially lower societal net benefits for a large range of environmental exposures.