JOHN MULHAUSEN, PhD, CIH, CSP, FAIHA, retired in 2018 from 3M where he worked for 31 years in a variety of global health and safety risk management roles, most recently as director of corporate safety and industrial hygiene. Send feedback to The Synergist.

New Tools for Exposure Judgments
As I discussed in my November column, studies have shown that our qualitative and quantitative exposure judgments are often wrong and tend to underestimate exposure risks. The best way to improve our quantitative judgments is to use tools that provide statistical interpretation of our monitoring data. Research confirms the effectiveness of these tools; for example, a 2012 paper in the Journal of Occupational and Environmental Hygiene showed significant improvement in exposure judgments among OEHS professionals who were trained on the use of simple statistical rules of thumb.
For years, AIHA has offered free tools that use traditional statistics to interpret monitoring data on our website. While these tools are effective, they have some limitations that make them cumbersome for routine application to industrial hygiene datasets, which are typically characterized by a small number of samples and by “censored” data—that is, results that are reported as below the analytical laboratory’s limit of detection. Despite these constraints, the tools work well, and using them is certainly preferable to relying entirely on our unaided judgments. That said, these tools produce results that can be difficult to interpret and explain.
BAYESIAN TOOLS So I’m pleased to report that two powerful new tools have been added to our website. The new tools, Expostats and an AIHA version of IHDA (short for IHDataAnalyst), address the limitations of traditional statistical tools through the use of Bayesian statistics. They work well when we have as few as one sample on which to base our judgment. These tools elegantly handle censored data, including data that is severely or even completely censored. And, perhaps most importantly, their output is expressed in terms that are easy to interpret and explain.
The best way to improve our quantitative judgments is to use tools that provide statistical interpretation of our monitoring data.
AIHA has also prepared some free education to train members on how to use the new tools. An online course will soon be available via AIHA's website. People completing the free course will be awarded continuing education contact hours by AIHA University.
In addition, the free Exposure Decision Analysis Registry from AIHA Registry Programs LLC is perfectly suited for us to demonstrate our performance in using the new tools to make accurate exposure judgments. The registry distinguishes OEHS professionals who have acquired the skills and knowledge to effectively manage workplace exposure and monitoring data.
BETTER FEEDBACK Habitual use of the new Bayesian statistical tools will greatly improve our judgments when we have monitoring data and eliminate our bias toward underestimating exposure risk. But it will also benefit our qualitative judgments. As with our quantitative judgments, research shows that our qualitative judgment accuracy is also low, often no better than random chance, and biased toward underestimating worker risk. Using the statistical tools will provide feedback on correct exposure decisions for operations when we have data, and that feedback will inform our qualitative decisions when we do not. We should all be accelerating the effectiveness of that feedback loop by actively documenting our qualitative judgments regarding exposures before we collect our samples and then comparing our judgments to the results from our statistical analysis of the data.
Journal of Occupational and Environmental Hygiene: “Effect of Training on Exposure Judgment Accuracy of Industrial Hygienists” (April 2012).
The Synergist: “Faulty Judgment” (November 2021).
The Synergist: “How to Improve Exposure Judgments” (December 2021).