Energy-based safety risk management : using hazard energy to predict injury severity Alexander, Dillon; Hallowell, Matthew; Gambatese, John
Worker injuries and fatalities have long been problematic in the construction industry. To address this ongoing concern, recent research has focused on risk-based approaches to proactive safety management. Although the quantity and quality of safety risk data has improved in recent years, available data do not link directly to natural principles and are, therefore, limited in their application and scientific extension. This study offers a new explanation of safety risk using the concept of energy where the underlying proposition is that all hazards are truly defined by the exposure to one or more of ten distinct forms of energy (e.g., gravity, motion, electrical). This concept of safety energy was introduced by William Haddon, was operationalized in a past Construction Industry Institute (CII) research team, and is currently being tested by an active CII research team. The present study aims to link energy transfer to safety risk for the first time. Inspired by natural disaster modeling, the concept of energy is translated to risk by defining the severity of a potential event as the ratio of the magnitude of the energy to the resiliency of the impacted human body part and the pressure exerted on impacted body part. Additionally, the likelihood component of risk is defined by the combination of human, social, technological, and other factors that contribute to the chance that there is an unwanted transfer of energy. To test this proposition, energy-based risk data were extracted from two sources: (1) a random sample of 40 injury reports taken from a larger database containing approximately 7,250 injury reports obtained from 281 private construction organizations and (2) a random sample of National Institute of Occupational Safety and Health Fatality Assessment and Control Evaluation (NIOSH FACE) reports. For each report, a combination of manual and automated content analyses was used to extract the following data: the chief energy source(s) contributing to the incident, the quantity of energy involved, the part of the body affected, and the severity of the outcome. Generalized linear models derived from initial results demonstrate that energy possesses legitimacy in predicting the severity of an injury that will result from a particular hazard, tentatively confirming the proposed theory. This research indicates that energy-based safety risk analysis is a promising line of scientific inquiry with predictive validity that has the potential to increase our understanding of the natural phenomena that contribute to injuries. This research corroborates previous hazard recognition research that introduced the energy principle of hazard classification but challenges the scientific merit of past safety risk data.
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