Cost Saving and Quality of Care in a Pediatric Accountable Care Organization
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Accountable care organizations (ACOs) are responsible for costs and quality across a defined population. To succeed, the ACO must improve value by reducing costs while either maintaining or improving the quality of care. We examined changes from 2008 through 2013 in the cost and quality of care for Partners for Kids (PFK), a pediatric ACO serving an Ohio Medicaid population. METHODS: We measured the historical cost of care for PFK and gathered comparison statewide Ohio Medicaid fee-for-service (FFS) and managed care (MC) cost histories. Changes in quality of care measures were assessed by using 15 Agency for Healthcare Research and Quality Pediatric Quality Indicators and 4 indicators targeted by PFK. RESULTS: PFK per-member-per-month costs were lower in 2008 than either FFS or MC (P < .001) costs and grew at a rate of $2.40 per year compared with FFS increases of $16.15 per year (P < .001) and MC increases of $6.47 per year (P < .121) with ∼3.5 million member-months each year. The quality of care of children in PFK improved significantly (P < .05) in 2011-2013 versus 2008-2010 on 5 quality measures (including 2 composite measures) and declined significantly on 3 measures. Other measures did not change or were rare events with no measureable change. CONCLUSIONS: PFK reduced the growth in costs compared with FFS Medicaid and averages less than MC Medicaid. This slowing in cost growth was achieved without diminishing the overall quality or outcomes of care. PFK thus improved the value of care for Medicaid children.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".