摘要：Objectives. State environmental and health protection agencies have traditionally relied on a facility-by-facility inspection-enforcement paradigm to achieve compliance with government regulations. We evaluated the effectiveness of a new approach that uses a self-certification random sampling design. Methods. Comprehensive environmental and occupational health data from a 3-year statewide industry self-certification initiative were collected from representative automotive refinishing facilities located in Rhode Island. Statistical comparisons between baseline and postintervention data facilitated a quantitative evaluation of statewide performance. Results. The analysis of field data collected from 82 randomly selected automotive refinishing facilities showed statistically significant improvements ( P <.05, Fisher exact test) in 4 major performance categories: occupational health and safety, air pollution control, hazardous waste management, and wastewater discharge. Statistical significance was also shown when a modified Bonferroni adjustment for multiple comparisons was performed. Conclusions. Our findings suggest that the new self-certification approach to environmental and worker protection is effective and can be used as an adjunct to further enhance state and federal enforcement programs. Interest in the use of statistical measures to evaluate the effectiveness of environmental and human health protection programs has increased sharply in recent years. In 3 consecutive grant rounds (ending with the 2006 solicitation), for example, the US Environmental Protection Agency’s National Center for Environmental Innovation awarded competitive grants to 14 states for the development of pilot and large-scale performance measurement–based initiatives modeled after the Massachusetts Environmental Results Program (ERP). 1 , 2 This industry self-certification approach is viewed as a simple and efficient way to control chemical hazards and environmental releases. The program accommodates both multimedia pollution (air, water, and hazardous waste, for example) and occupational health issues and reaches a larger segment of the regulated community than traditional enforcement programs. The US Environmental Protection Agency describes the model in this way: The Environmental Results Program combines compliance assistance, self-audit/certification, and statistically based inspections and performance measurement in order to strengthen or replace an existing regulatory structure. . . . [R]egulators educate facilities about their environmental impacts and obligations, as well as voluntary best practices they can use to alleviate potential impacts. Facilities are then required to self-evaluate and certify compliance. By conducting “before and after” inspections and applying statistical analysis, regulators can leverage limited inspection and enforcement resources to verify compliance, measure performance, and institute lasting improvements. 3 The objectives of our study were to (1) evaluate the statistically based performance measurement component of the model, and (2) assess the overall effectiveness of the approach in a small-business industry sector that is characterized by a range of human health and environmental risks (the automotive refinishing industry). By using analytic techniques that follow accepted statistical theory and epidemiological practice, we show how state environmental health protection agencies can enhance accountability and inform programmatic decisionmaking through the collection and analysis of quantitative data on industry performance. In practice, the model proceeds in a sequential manner: (1) baseline inspections document industry conditions before the program launch, (2) industry sector-wide program implementation (i.e., self-certification and government-sponsored technical and compliance assistance), and (3) postintervention facility audits coupled with performance measurement over a defined time interval. Compliance performance continues to be tracked and data are analyzed longitudinally for trends. A key aspect of this approach is that, with proper program design and rigorous data evaluation, only a sample set of field inspections are needed to obtain statistically valid results for industry performance. This approach is currently being applied by state agencies to several US industry sectors, including confined animal feeding operations, lithographic and screen printing, dry cleaning, photo processing, automotive refinishing and repair, and gasoline service stations. State agency experience suggests that the model is broadly applicable and may be used to address other US and international public health issues such as the control of infectious diseases (e.g., health department food protection programs), biological waste treatment, and low-level radioactive waste storage operations.
