The Effectiveness of Recovery-Oriented ACT in Reducing Hospital Use: Do Effects Vary Over Time?
Bibliographic record
Abstract
OBJECTIVE: A previous study of recovery-oriented assertive community treatment (PACT) found large differences over three years in use of state psychiatric hospitals between PACT participants and consumers in a matched control group, especially for PACT participants with significant previous psychiatric hospitalization. This study extended these findings by examining the timing of PACT effects. METHODS: Generalized estimating equation models of monthly cost data for state, local, and crisis hospital use estimated the time-varying effects of participation in one of ten PACT teams in Washington State. Data from PACT participants (N=450) and propensity score-matched consumers (N=450) were included. Additional analyses determined whether effects differed by prior state hospital use. RESULTS: Differences in costs between PACT and control participants were largest immediately after PACT enrollment and tapered off. During the first quarter after enrollment, monthly per-person costs for state hospital use were $3,458 lower for PACT enrollees than for control participants. A composite measure of psychiatric hospital costs (state and local hospitals and local crisis stabilization units) declined by $3,539 monthly during the first quarter after PACT enrollment (p<.01). Differences were noted up to 27 months after enrollment, when the difference in the composite costs measure became insignificant compared with the prior quarter (months 25-27) (p>.05). Differences were larger for PACT enrollees with greater baseline state hospital use. CONCLUSIONS: The time-varying estimates may have implications for the length and intensity of ACT enrollment. However, the optimum time for receipt of ACT services needs to be considered in the context of outcomes other than hospitalization alone.
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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 | 0.022 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".