Objective: To investigate and determine periodontal treatment needs by the use of the Community Periodontal Index of Treatment Needs (CPITN) of a Medicaid expansion population in the state of Iowa (DWP) in comparison with patients insured by the traditional Medicaid State Plan, patients with private dental insurance, and self-pay patients, while evaluating for systemic health conditions and socio-behavioral factors.
Methods: A secondary data analysis of electronic health records (EHR) from the University of Iowa College of Dentistry was completed and analyzed. Univariate and bivariate analyses were conducted. Logistic regression models were used to analyze relationships between predictors and periodontal treatment need.
Results: Out of the study population, 54% were indicated for scaling and root planing (SRP). Predictors of indicating the need for SRP treatment were found to be: Age (p< .0001), gender (p< .0001), medical diagnosis of diabetes (p=.031), smoking status (p< .0001), and not receiving regular dental check-ups (p< .0001).
Discussion: Our findings are consistent with common periodontal disease predictors found in the literature. Interestingly, insurance status was not a significantly associated predictor of periodontal treatment needs. However, approximately 50% patients with all insurance types were indicated for SRP.
Implications: DWP patients must earn benefits by maintaining dental appointments. This earned benefits approach delays periodontal treatment as patients must earn this procedure, potentially leading to deteriorating periodontal health. Further assessment of periodontal burden in the DWP population should be conducted and potential program structure evaluated.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7131 |
| Date | 01 May 2017 |
| Creators | Sukalski, Jennifer Michelle Cecelia |
| Contributors | McKernan, Susan Christine |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2017 Jennifer Michelle Cecelia Sukalski |
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