OBJECTIVES: We describe a methodology for school-based sealant programs (SBSP) to estimate averted cavities, (i.e., difference in cavities without and with SBSP) over 9 years using a minimal data set. METHODS: A Markov model was used to estimate averted cavities. SBSP would input estimates of their annual attack rate (AR) and 1-year retention rate. The model estimated retention 2+ years after placement with a functional form obtained from the literature. Assuming a constant AR, SBSP can estimate their AR with child-level data collected prior to sealant placement on sealant presence, number of decayed/filled first molars, and age. We demonstrate the methodology with data from the Wisconsin SBSP. Finally, we examine how sensitive averted cavities obtained with this methodology is if an SBSP were to over or underestimate their AR or 1-year retention. RESULTS: Demonstrating the methodology with estimated AR (= 7 percent) and 1-year retention (= 92 percent) from the Wisconsin SBSP data, we found that placing 31,324 sealants averted 10,718 cavities. Sensitivity analysis indicated that for any AR, the magnitude of the error (percent) in estimating averted cavities was always less than the magnitude of the error in specifying the AR and equal to the error in specifying the 1-year retention rate. We also found that estimates of averted cavities were more robust to misspecifications of AR for higher- versus lower-risk children. CONCLUSIONS: With Excel (Microsoft Corporation, Redmond, WA, USA) spreadsheets available upon request, SBSP can use this methodology to generate reasonable estimates of their impact with a minimal data set.
OBJECTIVES: We describe a methodology for school-based sealant programs (SBSP) to estimate averted cavities, (i.e., difference in cavities without and with SBSP) over 9 years using a minimal data set. METHODS: A Markov model was used to estimate averted cavities. SBSP would input estimates of their annual attack rate (AR) and 1-year retention rate. The model estimated retention 2+ years after placement with a functional form obtained from the literature. Assuming a constant AR, SBSP can estimate their AR with child-level data collected prior to sealant placement on sealant presence, number of decayed/filled first molars, and age. We demonstrate the methodology with data from the Wisconsin SBSP. Finally, we examine how sensitive averted cavities obtained with this methodology is if an SBSP were to over or underestimate their AR or 1-year retention. RESULTS: Demonstrating the methodology with estimated AR (= 7 percent) and 1-year retention (= 92 percent) from the Wisconsin SBSP data, we found that placing 31,324 sealants averted 10,718 cavities. Sensitivity analysis indicated that for any AR, the magnitude of the error (percent) in estimating averted cavities was always less than the magnitude of the error in specifying the AR and equal to the error in specifying the 1-year retention rate. We also found that estimates of averted cavities were more robust to misspecifications of AR for higher- versus lower-risk children. CONCLUSIONS: With Excel (Microsoft Corporation, Redmond, WA, USA) spreadsheets available upon request, SBSP can use this methodology to generate reasonable estimates of their impact with a minimal data set.
Authors: Rocio B Quiñonez; Stephen M Downs; Dan Shugars; John Christensen; William F Vann Journal: J Public Health Dent Date: 2005 Impact factor: 1.821