Publicly Funded Home and Community-Based Care for Children With Medical Complexity: Protocol for the Analysis of Medicaid Waiver Applications
Bibliographic record
Abstract
BACKGROUND: Children with medical complexity are a group of children with multiple chronic conditions and functional limitations that represent the highest health care utilization and often require a substantial number of home and community-based services (HCBS). In many states, HCBS are offered to target populations through 1915(c) Medicaid waivers. To date, no standard methods or approaches have been established to evaluate or compare 1915(c) waivers across states in the United States for children. OBJECTIVE: The purpose of this analysis was to develop a systematic and reproducible approach to evaluate 1915(c) Medicaid waivers for overall coverage of children with medical complexity. METHODS: Data elements were extracted from Medicaid 1915(c) approved waiver applications for all included waivers targeting any pediatric age range through October 31, 2018. Normalization criteria were established, and an aggregate overall coverage score was calculated for each waiver. RESULTS: Data extraction occurred in two phases: (1) waivers that were considered nonexpired through December 31, 2017, and (2) the final sample that included nonexpired waivers through October 31, 2018. A total of 142 waivers across 45 states in the United States were included in this analysis. We found that the existing adult HCBS taxonomy may not always be applicable for child and family-based service provision. Although there was uniformity in the Medicaid applications, there was high heterogeneity in how waiver eligibility, transition plans, and wait lists were defined. Study analysis was completed in January 2019, and after analyzing each individual waiver, results were aggregated at the level of the state and for each diagnostic subgroup. The published results are forthcoming. CONCLUSIONS: To our knowledge, this is the first study to systematically evaluate 1915(c) Medicaid waivers targeting children with medical complexity that can be replicated without the threat of missing data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/13062.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.077 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.062 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".