Measuring the effectiveness of performance-based training

摘要

This article describes a statistical analysis of small water systems’ turbidity data within thenframework of a logic model for the USEPA’s Performance-Based Training (PBT) program. The logicnmodel shows the theoretical linkages between optimization training for small system operators;noperator application of optimization techniques; improvements in plant filtration performance;nand public health protection. The analysis comprised two phases. For the first phase, the authorsnused Bayesian analysis of turbidity data to test the statistical significance of changes in finishednwater quality resulting from training for small water system operators. For the second phase,nthe authors estimated the potential health benefits resulting from measured improvements innfiltration performance. Considering only the improved removal of the pathogen Cryptosporidium,nthe expected annual health benefit of PBT is about ten fewer cases of infection per thousandnpersons served (within a 95% credible interval 0 to 18 fewer infections), though there may benbenefits associated with the removal of other pathogens. The article also describes factorsncontributing to uncertainty in the estimated potential health benefits. The proposed two-phasenapproach supports the USEPA’s development of drinking water program indicators which arenmeaningful, measurable, broadly applicable and change-sensitive.