Effects of forced disruption in Medicaid managed care on children with asthma
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of a forced disruption to Medicaid managed care plans and provider networks on health utilization and outcomes for children with persistent asthma. DATA SOURCES: Medicaid managed care administrative claims data from 2013 to 2016, obtained from a southeastern state. STUDY DESIGN: A difference-in-difference analysis compared patients' outpatient, inpatient, and emergency department (ED) utilization and receipt of recommended services before and after implementation of a statewide redistribution of patients among nine managed care plans. DATA COLLECTION/EXTRACTION METHODS: Enrollment data for children with asthma were linked to the administrative claims. Children were included if they had a diagnosis of persistent asthma in 2013 and if they were enrolled continuously throughout 2014-2016. PRINCIPAL FINDINGS: Among the 28 537 children with asthma, 26% were forced to switch their managed care plan after the redistribution. Of these, 67% also switched their primary care provider (PCP). Relative to those who remained in their plan, disruption was associated with an additional 2.1 percentage-point decrease in the number of children who had an outpatient visit per quarter [95%CI -2.8, -1.3], from 71% to 66% (compared to plan stayers: 74% to 71%). Among children experiencing a change to their plan, there was overall a decrease in the proportion of children receiving an asthma-specific visit per quarter, but there was less of a decrease in children that also changed their PCP [1.6 percentage points, 95%CI 0.7, 2.5], from 9.7% to 8.3% (compared to those who did not switch their PCP: 12% to 8.6%). Indicators of asthma care quality and emergent care utilization were not significantly different between the two periods. CONCLUSIONS: While there was a decrease in the number of outpatient visits associated with forced disruption of Medicaid managed care plans for children with persistent asthma, there were no consistent associations with worse asthma quality performance or higher emergent health care utilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".