Application of disability-adjusted life years to predict the burden of injuries and fatalities due to public exposure to
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RESEARCH
Open Access
Application of disability-adjusted life years to predict the burden of injuries and fatalities due to public exposure to engineering technologies Arun Veeramany* and Srikanth Mangalam
Abstract Background: As a public safety regulator, the Technical Standards and Safety Authority (TSSA) of Ontario, Canada predicts and measures the burden of injuries and fatalities as its primary means of characterizing the state of public safety and for decision-making purposes through the use of a simulation model. The paper proposes a simulationbased predictive model and the use of disability-adjusted life years (DALYs) as a population health metric for the purposes of reporting, benchmarking, public safety decision-making, and organizational goal setting. The proposed approach could be viewed as advancement in the application of traditional population health metrics, used primarily for public health policy decisions, for the measurement and prediction of safety risks across a wide variety of engineering technologies to which the general public is exposed. Results: The proposed model is generic and applicable to a wide range of devices and technologies that are typically used by the general public. As an example, a measure of predicted risk that could result from the use of and exposure to elevating devices in the province of Ontario is presented in terms of the DALY metric. The predictions are further categorized in terms of the causal attribution of the risks for the purposes of identifying and focusing decision-making efforts. The results are also presented by taking into consideration factors such as near-misses or precursor events as termed in certain industries. Conclusions: The ability to predict potential health impacts has three significant advantages for a public safety regulator – external reporting, decision-making to ensure public safety, and organizational benchmarking. The application of the well-known Monte Carlo simulation has been proposed to predict the health impacts expressed in terms of DALYs. The practicality of the proposed ideas has been demonstrated through the application of the prediction model to characterizing and managing risks associated with elevating devices in the province of Ontario, Canada.
Background Information and data on incidents and near-misses are analogous to the visible tip of the iceberg that enables the regulator to be reactive to unfortunate occurrences. There may also be valuable data such as noncompliances obtained typically through regulatory inspection programs that identify underlying or nascent failures in the regulated systems that support proactive decision-making. Additionally, there could be unforeseen scenarios that are best anticipated through a thorough predictive risk assessment. Noncompliances, near-misses, and incidents form
* Correspondence: [email protected] Public Safety Risk Management, Technical Standards and Safety Authority, Ontario M8X 2X4, Canada
valuable predictive inputs to prevent fatalities and injuries. These represent a tri
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