Course Description:
Recorded at AIHce EXP 2023
IHs anticipate, identify, evaluate and control, at times using assumptions in the initial steps cloaked as professional judgement. Exposure models (heuristics) can overcome weaknesses in our collective professional judgement based on obtainable data. Exposure predictor bands can estimate dust levels or vapor levels this way. If concentrations can be estimated with existing controls why are we anxious to sample first? When we do sample, why do we assume that everyone is equal in exposure by creating Similar Exposure Groups? An IH sample is defined as analyte trapped on a sorbent tube or filter to provide an average concentration. But at times the result offers minimal information to target intervention to reduce exposures. Real-time monitoring provides an average concentration and information on concentration variability throughout a monitoring period. We may collect many more samples to establish individualized exposure profiles eliminating any assumption of a common exposure. Real-time monitoring approaches do not give the same accuracy and precision as lab analyzed samples. But this is less significant than leveraging the utility of identifying within- and between-day exposure variability for interventions to reduce worker risks.
Learning Outcomes:
Upon completion of the session, the participant will be able to:
• Recognize exposure modeling as a means to prioritize air sample collections.
• Discuss redefining what an IH sample is, to better protect worker safety and health.
• Examine the limitations of collective exposure assessment (SEG).
• Leverage the collection of many data points to establish exposure profiles.
Contact Hours:
1
Presentation Date:
05/23/2023
Presenters:
Steven Jahn, CIH, MBA, FAIHA
Philip Smith, PhD, CIH, FAIHA
Michael Phibbs, CIH, ROH, MBA
