Intervention Effectiveness Research: Understanding and Optimizing Industrial Safety Programs Using Leading Indicators
| Autor: | Parameshwaran S. Iyer, Enrique Castillo, Brian W. Tink, Joel M. Haight, Paul W. Hawkins |
|---|---|
| Rok vydání: | 2004 |
| Předmět: | |
| Zdroj: | Chemical Health & Safety. 11:9-19 |
| ISSN: | 1878-0504 1074-9098 |
| Popis: | A safety and health program is considered a suite of activities implemented at a worksite for preventing or reducing incidents. These include such activities as safety training, equipment and housekeeping inspections, safety meetings, safety observations, tailgate or tailboard meetings and the like. Optimizing safety and health intervention strategies to decrease rates of injury and property damage with less costly safety programs can contribute to improved productivity and economic vitality in all activities that involve such risks. This article details the results of research done to validate, improve, and extend a previously developed mathematical model that guides such optimization22. The results show that improved safety practices and improved profitability in industry is possible when one understands the mathematical cause and effect relationship between incidents (trailing indicators) and program interventions (inspections, training, safety meetings, and the like) designed to prevent them (leading indicators). At power company, Hydro One Network Services, Inc.’s, forestry services, researchers have shown over the study’s first phase (30 weeks) that a statistically significant relationship exists between incidents (injuries, fires, motor vehicle accidents, and the like) and the level of preventive intervention activity implemented (intervention application rate). Using this mathematical relationship and mathematical programming techniques, researchers developed an optimized “recipe”51 for the appropriate level of effort and mix of safety and health program interventions that minimize incidents while concurrently minimizing the amount of human resources required to implement the interventions. During the verification phase (22 weeks), achieving the model-suggested intervention program design proved to be difficult. Researchers were at least able to overlay actual performance input onto the model and found that consistent and accurate prediction of the incident rate was possible. Once a statistically significant mathematical relationship is identified, one can determine how, where and when to adjust specific safety and health program intervention activity. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|