MEDICAID FUNDING APPROVAL RATE VARIANCES FOR COMPREHENSIVE TREATMENT AMONG THE ORTHODONTIC CRITERIA INDEX AUTOMATIC QUALIFIERS AND THE SALZMANN EVALUATION INDEX
| Autor: | Golojuch, Nina Corinne |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Text |
| DOI: | 10.34944/dspace/10660 |
| Popis: | Introduction: Historically, in Pennsylvania, the Salzmann Evaluation Index (SEI) (Figure 2) was used to evaluate the medical necessity of orthodontic care and whether the government will cover costs for low-income patients. Approval discrepancies occur between doctor index scoring and insurance funding with the SEI, leading to questions about how indices determine funding. Each state and insurance administrator decides which, if any, medically necessary malocclusions to include that automatically qualify for treatment coverage. As of 2022, a major insurance administrator in the state of Pennsylvania added an additional qualifying criterion: the orthodontic criteria index (OCI), ten occlusal characteristics that lead to an automatic qualification (Figure 3). This leaves the possibility that a patient may qualify on one or both indices. This study is the first to evaluate the frequency of approvals between SEI and OCI in Pennsylvania. The secondary objectives for this investigation are to evaluate the OCI criteria insurance administrator approval rate compared to the doctors’ scoring and to evaluate if sex, age, race/ethnicity, and submission year impact insurance funding decisions and to evaluate the OCI criteria insurance administrator approval rate compared to the doctors’ scoring. The results of this study may promote standardization for the state of Pennsylvania to readily adopt a list of Automatic Qualifiers for all Medicaid insurance administrators. Materials and Methods: All subjects had no orthodontic treatment and underwent routine screening and record-taking through the Temple University Kornberg School of Dentistry Orthodontic Screening Clinic from November 1, 2022, to March 31, 2023 (n = 171). For all orthodontic providers, scoring SEI and OCI was calibrated in September 2022. Malocclusion characteristics of 171 subjects between the ages of 9-20 were characterized for treatment need with standardized SEI and OCI criteria. SEI gives a numeric score of treatment need by accessing intra-arch and inter-arch tooth position relationships. OCI is a binary list for the presence of specific severe malocclusion criteria, which leads to automatic qualification for treatment. Approval thresholds were at least one OCI AQ or a SEI≥25. Patient data, including age, date of initial submission, sex, race and ethnicity, date of submission, insurance response, and orthodontist scoring, was recorded. Insurance submission records were analyzed, and funding decisions based on the Salzmann Evaluation Index (SEI) and the Orthodontic Criteria Index (OCI) were recorded. Malocclusion severity evaluation had an inter-examiner reliability of 90%, using the Salzmann Evaluation Index, with a score of >25 determining treatment need or one of the ten automatic qualifiers from the Orthodontic Criteria Index form was perceived regardless of the Salzmann Evaluation Index score. Both indices scored, along with intraoral and extraoral photographs, a cephalogram, a panoramic radiograph, and an intraoral impression, were sent to Insurance Administrator A, a primary Medicaid company for patients at TUKSoD. An employee of the insurance administrator received the records submitted and made a funding decision. Results: Overall insurance approval was 38.6%. Doctor approval rates were 42.7% for OCI and 24.6% for SEI. The overall doctor versus approval discrepancy was 39.7% for both SEI and OCI combined. Patients who qualified for treatment with one or more OCI had an average SEI of 18. Only 24.6% of SEI scores ≥25 were approved. The greatest agreement between insurance and doctor approvals was for the OCI category: impacted of canines or incisors. There was no statistically significant difference in the approval rate between the OCI and SEI for gender, ethnicity, or submission year. Age groups have a statistically significant discrepancy (P Oral Biology M.S. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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