Outcomes of Flexible Assertive Community Treatment Versus Assertive Community Treatment or Intensive Case Management
Bibliographic record
Abstract
OBJECTIVE: In the context of increased uptake of flexible assertive community treatment (FACT)-despite a dearth of evidence on its outcomes-the authors aimed to compare the effectiveness of FACT with that of assertive community treatment (ACT) or intensive case management (ICM) for community-dwelling people experiencing serious mental illness. METHODS: This quasi-experimental study, using propensity score matching to minimize confounding factors, examined outcomes of acute psychiatric service use among individuals who received FACT (vs. ACT or ICM) at a large Canadian mental health hospital. Data from a period of transition to FACT and an implementation period were analyzed. RESULTS: The matched cohort consisted of 237 FACT and 237 ACT or ICM service users. During the transition period, no significant differences between the two groups were observed in emergency department (ED) visits, hospital admissions, or inpatient days. During the period of full FACT implementation, the FACT group had a significant increase in ED visits, compared with the group that received ACT or ICM (incidence rate ratio=1.65, 95% CI=1.02-2.67), but no significant differences were observed between the two groups in the rate of hospital admissions or inpatient days. CONCLUSIONS: To the authors' knowledge, this study is the first of its kind in Canada. Its findings suggest generally comparable outcomes of FACT (vs. ACT or ICM) in acute mental health services use. Although the rate of ED service use increased in the FACT group after implementation, inpatient service use did not increase. The higher rate of ED service use in the FACT group warrants further study.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".