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RESEARCH REPORT |
1 Centers for Disease Control and Prevention/Division of Oral Health/Surveillance, Investigations and Research Branch, 4770 Buford Highway, MSF10, Chamblee, GA 30341; and
2 School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205;
* corresponding author, sig1{at}cdc.gov
| ABSTRACT |
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KEY WORDS: dental sealants cost-effectiveness screening delivery of health care
| INTRODUCTION |
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One reason for the low prevalence of sealants is that this primary preventive service is perceived to cost more than treating caries among children with low caries rates. Caries is not uniformly distributed through the US school-aged population. Approximately 80% of all caries is concentrated in 25% of school-aged children (Brown et al., 1996). Thus, insurers may not cover sealants, since the cost of universal delivery is likely to be greater than the cost of treating decay that could be averted by sealants (Eklund, 1986). Even in community programs that generally target children at increased risk for caries and lack of access to care, most experts have recommended assessing individual risk (ASTDD, 1995; US Department of HHS, 2000), and a risk-based performance measure has been developed (Crall et al., 1999).
One study suggested that universal delivery of sealants is cost-saving compared with no delivery among low-income children with high caries prevalence (Weintraub et al., 1993). However, no economic analyses comparing universal delivery with risk-based delivery have been conducted. Our objective in this study was to analyze the relative cost effectiveness of 3 sealant delivery strategies: Seal none (SN); seal if the child is determined, through screening, to be at risk for future caries (TARGET); and seal all (SA). More detailed information on parameter estimates and results from the sensitivity analyses (referenced as Web-Table and Web-Fig.) may be accessed by the interested reader at an appendix on the Journal of Dental Research Web site (www.dentalresearch.org).
| MATERIALS & METHODS |
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In the analysis we made the following assumptions:
Clinical Data
Table 1
shows baseline parameter estimates and their sources. Obtaining valid estimates of 1st molar caries increments is difficult, because there have been no national longitudinal surveys on caries increment. A New York longitudinal study of 1st molar occlusal surface survival among schoolchildren, aged 10 to 13 yrs, reported an annual attack rate of 10.5% (Ripa et al., 1988). Because the nine-year cumulative caries increment estimated from this study was higher than prevalence estimates for children aged 12 to 19 yrs obtained from cross-sectional surveys, we estimated caries increment from the National Survey of Dental Caries in US School Children: 1986-1987, which reported caries prevalence by year of age ( Us Public Health Service, 1989). We deflated the estimated prevalence of permanent occlusal caries among 12-year-olds (1.58 surfaces) by the percentage decrease in occlusal caries prevalence among children, aged 5 to 17 yrs, between this study and the National Health and Nutrition Examination Survey III (20.9%) (Kaste et al., 1996). Assuming that permanent 1st molars erupt at age 6 and a constant annual caries increment, we estimated the annual occlusal caries increment per permanent 1st molar to be 0.062 surfaces,
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Costs
The costs of sealants and single-surface amalgams were obtained from the 1999 Survey of Dental Fees (ADA, 2000). Expected amalgam costs over 9 yrs were estimated from fee data and the imputed annual amalgam failure rate (Web-Table 4).
| RESULTS |
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One-way Sensitivity Analysis
Increased sealant delivery becomes less costly as the annual caries increment increases (Fig. 1
). For caries increments less than or equal to 0.05, SN is least costly. For caries increments greater than 0.05 and less than or equal to 0.95, TARGET is least costly, and for caries increments greater than 0.095, SA is the least costly strategy.
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If the sealant loss rate takes on its maximum value, 28% in year 1 and 4% thereafter (Web-Table 2), SN becomes the least costly strategy, SN = $35.84 < TARGET = $38.22 < SA = $47.60. Changing the baseline assumption of zero screening costs to a cost 0f $0.96 per child would result in SN being less costly than TARGET (Table 2
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Two-way Sensitivity Analysis
In Fig. 2
, we allow the ratio of restoration to sealant costs and annual caries increment to vary simultaneously. The break-even frontier shows all points at which the costs of the two comparison strategies are equal. Points above the frontier indicate that the strategy which delivers sealants to the most children is the least costly and thus the dominant strategy. For example, if the ratio of restoration to sealant costs were 12, TARGET would dominate SN if caries increment exceeded 0.007, SA would dominate SN if the caries increment exceeded 0.019, and SA would dominate TARGET if the caries increment exceeded 0.034.
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The SN-TARGET frontier shifts inward as screening sensitivity and specificity increase (Web-Fig. 2), because decreasing numbers of false-positives and false-negatives lower the cost of TARGET and thus lower the break-even ratio of restoration to sealant costs required for each caries increment. For example, if the caries increment equaled 0.02, increasing screening sensitivity and specificity from their baseline values to 0.9 lowers the break-even ratio of restoration to sealant costs from 5.0 to 2.8.
The vertical shift in the break-even frontier caused by increased screening sensitivity and specificity is greater for lower caries increment values. Thus, changes in sensitivity or specificity will be associated with smaller changes in the break-even ratio of restoration to sealant costs for higher caries increments.
| DISCUSSION |
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The ratio of restoration to sealant costs will vary by community, due to differential resource costs, dental market structures, and regulatory environments. Annual caries increment is also likely to vary by community. Thus, the sealant delivery strategy should be determined at the community level. The most important contribution of this research, the sensitivity analysis, allows decision-makers to determine if a dominant sealant delivery strategy exists. It is important to note that while points on or above the break-even frontier indicate that increased delivery of sealants is the dominant strategy, points below the frontier do not indicate that decreased delivery of sealants dominates. Although increased delivery is more costly, the associated increase in effectiveness may be well worth the investment. For example, spending $23 (SN to SA) to save one tooth surface from caries may be a very good investment, depending on such factors as an individuals valuation of oral health, his or her aversion to restorative dental care, and the value of competing alternatives.
Another caveat that should be mentioned when our results are interpreted is that we used dental fees as a proxy for the cost of resources to provide restorations and sealants in a clinical setting. If dental markets are competitive, or if demand for these two procedures is equally elastic, it is likely that the ratio of restoration to sealant costs will indeed measure relative resource costs. A national survey reported that providing single-surface restorations requires 2.5 times more effort than does providing sealants (RVU, 2000). This value is slightly higher than that which we obtained from dental fees, 2.33 ($63/$27). If we had used 2.5, SA would dominate SN for annual caries increments exceeding 0.075 surfaces.
Most of the assumptions used in this analysis are conservative and biased against accepting SA. Our assumptions (that all decay is treated with a single-surface amalgam instead of more costly treatment options, and that the cost of sealing additional teeth is the same as the cost of sealing the first tooth) inflate the costs of SA relative to TARGET and the costs of TARGET relative to SN. The assumption of zero screening costs would deflate the cost of TARGET relative to SA or SN. Finally, our assumption that the annual permanent 1st molar caries increment is constant or, equivalently, that the annual caries attack rate among sound surfaces is increasing deflates expected restoration costs and thus biases the results away from SA. (For example, assuming a constant caries increment equaling 0.105 per yr would imply attack rates of 0.105, 0.1173, and 0.135, respectively, in years 1, 2, and 3.) Almost no data exist on annual occlusal caries increment and its progression over time. We followed the example of two longitudinal studies that examined annual occlusal caries increment and found that it remained fairly constant over time in the first molars of schoolchildren ranging in age from 10-16 yrs and 6-13 yrs (Bohannan et al., 1984; Ripa et al., 1988). For our nine-year caries increment estimate, if we had assumed the attack rate among sound occlusal surfaces to be constant, then the caries increment in earlier years, which are weighted more heavily due to discounting, would be higher, and thus restoration costs would increase relative to sealant costs. [Pr (15-year-old has sound 1st molar occlusal surface) = 1 - 9*0.105 = 0.055; Pr (surface sound sound in previous period) = 0.0551/9 = 0.725; thus, Pr (surface decayed sound in previous period = 1 - 0.725 = 0.275.]
The costs of delivering sealants may also vary by setting. Estimates of sealing teeth in community programs, for example, are generally lower than those in clinical settings. Published estimates of the cost of sealing a tooth (1999 $US) range from $4.75 (Calderone and Mueller, 1983) to $6.50 (Klein et al., 1985), and thus the ratio of restoration to sealant costs would exceed 12. If we assume that the effectiveness of sealants does not vary by delivery site, in school-based/-linked sealant programs, SA could be less costly than SN for annual caries increments as low as 0.018 and less costly than TARGET for annual attack rates of 0.035 or higher. These findings suggest that, over a nine-year horizon, individualized risk assessment of children enrolled in most school-based programs may be unnecessary. School-based programs generally target low-income children who are less likely than higher-income populations to receive preventive services and to have a regular source of care (US Department of HHS, 2000).
| FOOTNOTES |
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Received December 6, 2001; Last revision April 17, 2002; Accepted June 17, 2002
| REFERENCES |
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