Course Description:
Recorded at AIHce EXP 2023

Is a group compliant with the OEL? Are individuals within a group likely to experience higher risk than the group average? Despite theoretical approaches being available to answer these questions, there has been a lack of practical applications to support decision making. IHSTAT is an available free IH statistics tool. It was first made available through the AIHA monograph "A Strategy for Assessing and Managing Occupational Exposures" published in 1998. Industrial hygiene statistics have recently evolved into a new stage thanks to Bayesian statistics. Bayesian statistics allow for more direct and easier to communicate answers such as that there is a 56% probability that a SEG is overexposed. Additional advantages include state of the art processing of non detects and the ability to merge exposure data with prior information. The University of Montreal group responsible for the www.expostats data interpretation toolset recently collaborated with Daniel Drolet to install a Bayesian calculation engine into IHSTAT and create a Bayesian version of this world renown application. The aim of this education session is to present the current theory underpinning the interpretation of exposure levels and to demonstrate how decision making can be conducted using the new IHSTAT_Bayes tool.

Learning Outcomes:
Upon completion of the session, the participant will be able to:

• Analyze the impact of airborne exposure variability on workplace risk assessment.
• Determine the most common metrics used to define overexposure.
• Use IHSTAT_Bayes to perform risk assessments.
• Present the results in the form of traditional point estimates and confidence limits.
• Write a probabilistic statement about probability that the group is overexposed.
• Detail a probabilistic statement about the relevant AIHA exposure control category.

Contact Hours:
1

Presentation Date:
05/23/2023

Presenter:
Jerome Lavoue