Accurate risk decisions are critical for effective and efficient safety programs. Recent research examining chemical exposure risk judgments identified opportunities for improving decision accuracy. This presentation explores actions that safety professionals can use to improve their risk decision accuracy and thus the effectiveness and efficiency of their safety management systems.

Background: Risk Decisions at the Heart of Safety Management

Hazard and risk assessments are at the heart of our safety and health management systems. They determine the types of training, mitigation, monitoring, and change management systems that must be implemented in our workplaces and have direct influence on the health and safety programs that we put in place. Accordingly, accurate risk decisions are critical for effective and efficient workplace safety and health management (Figure 1). Underestimate risk and our safety and health programs become ineffective as employees whose risk was underestimated continue to perform their duties with the risks unabated. Overestimate risk and our programs become inefficient as limited resources are wasted on risk controls where none were needed. The most effective and efficient safety and health programs begin with an emphasis on robust, accurate, and consistent risk assessment decisions.

Risk Decision Accuracy

Recent research examining worker chemical exposure risk judgments has identified opportunities for improving risk decision accuracy. Figure 2 is illustrative of the findings. Safety and health professionals were asked to rate the intensity of worker exposures to a chemical relative to its occupational exposure limit (OEL) using the exposure risk rating scale in Figure 3. Risk decisions were collected twice for each participant: once before receiving training on simple rules-of-thumb for interpreting data and once after the training. The accuracy of participant judgments increased after the simple rule-of-thumb training. In addition, a bias toward underestimation of risk was eliminated, possibly replaced by an overestimation bias.

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