Sealant program
(updated on 2021-09-01 11:37:40)
SUMMARY
- Among all children who were screened, percent "Green" has increased: from 59% in 2017-2018 to 70% 2019-2020. On average across schools, it increased by 6% point each year.*
- However, the percent of all eligible children who participated in the program has remaind relatively low and decreased slightly: from 48% in 2017-2018 to 45% 2019-2020.
- Characteristics of children who participated in the program have been similar over time.
(*Based on further statistical analysis, adjusting for any school-specific characteristics. Results not presented)
0. Data prep
Summary
Number of schools participated in the sealant program
|
School year
|
Total
|
Title 1 schools
|
|
2017-2018
|
8
|
8
|
|
2018-2019
|
8
|
8
|
|
2019-2020
|
8
|
8
|
Child-level
See Annex for detailed note on the data.
1. Total number of children who are eligible for and received the program
1.1 Total number of sealants applied
1.2 Average number of sealants applied per child (among those who received sealants)
2. Gap analysis: consent rate
Note: only the consent rate among all eligible children is available. We do not have consent form return rate for sealant program. So, it is difficult to distinguish: response vs. participation. But, it may be similar to those in the screening program.
2.1 Further gap analysis: Do consent rates vary across school?
2.2 Further gap analysis: Where can we improve consent rate?
2.3 Further gap analysis: who are screened? Have their characteristics changed over time?
- Because of low consent rates, it is important to understand characteristics of "those who are screened" and, especially, if their characteristics change over time.
- For example, if the percent of children at-risk (based on socioeconomic background characteristics) decreases over time among those who are screened, overall outcomes may improve just because of the background characteristics of who are screened (positive selection, in this case).
- Below, we are looking at race and health insurance status as proxy, using the child-level data.
3. Screening outcome among those who were screened
3.1 Gap analysis: Where can we improve outcome?
4. Individual child-level analysis
What specific questions do we ask, considering that we have the detailed tables (i.e., table by background characteristics)?
Annex: Data note
- I did not edit any data in summary sealant data.