Decision-making for Risk Management Using Small Data Sets, Mathematical Models, and Heuristics

A critical skill of occupational hygienists (OHs) is making accurate exposure judgments to ensure that workers are properly protected and resources are efficiently utilized. Previous studies have documented that the accuracy of these judgments is low, suggesting that resources are inefficiently used and workers placed at unnecessary risk. We are proposing to develop and test and decision-making tool based on cognitive science principles, and incorporating simple heuristics, exposure models, and Bayesian statistics to help improve the accuracy of the exposure judgments. The proposal logically follows from several previous NIOSH-funded projects on improving specific components of the exposure decision-making process, is responsive to a need within the OH profession, and complements NIOSH’s initiative to update its Occupational Exposure Sampling Strategies Manual.