The Impact of California's Full-Service Partnership Program on Mental Health-Related Emergency Department Visits
Bibliographic record
Abstract
OBJECTIVE: This study examined the effects of California's 2005 Mental Health Services Act (MHSA) on the use of mental health-related emergency department visits. It focused on one MHSA program, the full-service partnership program, and hypothesized that individuals with public insurance who participate in the higher-quality full-service partnership program would have fewer emergency department visits compared with clients with public insurance who receive usual care. METHODS: Data were obtained from the Short-Doyle/Medi-Cal (Medicaid) file, the Data Collection and Reporting system, and the Consumer and Service Information System, all maintained by the California Department of Mental Health. The analytic sample covered 931,218 observations (155,203 adults) ages 18 and older from January 2007 to June 2008. The data represented clients from seven counties, which made up 48.5% of the California population. Fixed-effects logistic regression was used and included a continuous measure of time, in quarters, in the full-service partnership program; separate quarter indicators; and quarter-county interaction terms. The model thus controlled for both time-invariant personal characteristics (including personality as well as psychiatric and medical history as of entry into the study) and all time-varying county-level characteristics. RESULTS: Relative to persons receiving usual care, the odds of full-service partnership participants visiting the emergency department were 54% less after four quarters of treatment and 68% less after six quarters. CONCLUSIONS: The full-service partnership program was highly effective in reducing emergency visits. A statewide cost-effectiveness study should be conducted to determine the economic viability of the program.
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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".