Linking Improvements in Health-Related Quality of Life to Reductions in Medicaid Costs Among Students Who Use School-Based Health Centers
Bibliographic record
Abstract
OBJECTIVES: We examined whether improvements in pediatric health-related quality of life (HRQOL) stemming from use of school-based health centers (SBHCs) resulted in lower Medicaid costs. METHODS: We analyzed data on 290 students from a 3-year, longitudinal SBHC evaluation conducted in Cincinnati, Ohio, in 2000 to 2003, including 71 with a mental health diagnosis and 31 with asthma, who had linked Ohio Medicaid records. HRQOL was measured using the Pediatric Quality of Life Inventory. Panel regression examined whether changes in parent-reported and student self-reported HRQOL predicted changes in Medicaid costs. RESULTS: After adjustment for gender, age, SBHC status, and Medicaid type, we found cost reductions for every 1-point increase of parent-reported total ($36.39; P<.01), physical ($35.36; P<.05), and psychosocial ($25.94; P<.01) HRQOL. Significant cost reductions were also associated with student-reported total ($8.94; P<.05) and psychosocial ($7.79; P<.05) HRQOL increases. These effects were significant among the asthma subgroup but not the mental health subgroup. Physical HRQOL ($6.12; P=.27) effects were not significant. CONCLUSIONS: Improvements in pediatric HRQOL translate into lower Medicaid costs, supporting the use of HRQOL as an outcome for evaluating SBHCs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".