Impact of switching to long-acting injectable antipsychotics on health services use in the treatment of schizophrenia.
Bibliographic record
Abstract
OBJECTIVE: To better understand the treatment patterns, persistence and compliance, resource use, and associated costs, of long-acting injectable antipsychotics (LAI-AP), using the Régie de l'assurance maladie du Québec database. METHOD: Patients with schizophrenia or schizoaffective disorder who were incident users of an LAI-AP prescribed between January 1, 2008, and March 31, 2012, were selected. Concomitant use of oral APs and treatment persistence and compliance with LAI-AP were analyzed. Patients were considered compliant if they had a medication possession ratio (MPR) of at least 0.80. Health care resource use (HCRU) and associated costs were analyzed during the year before and after LAI-AP initiation. RESULTS: A total of 1992 patients met the inclusion criteria. The average persistence with LAI-AP was 217.2 days (SD 144.2). The mean MPR with LAI-AP during the postinitiation year was 0.58 (SD 0.35), with 37.5% of patients being compliant. In the preinitiation year, 29.0% of patients were compliant with previous oral AP. In the pre- and postinitiation periods, 1484 and 958 patients had at least 1 hospitalization, and hospitalized days were reduced by one-half (P<0.001). Cost of HCRU, including medication, was significantly decreased from $24,382 (SD $27,234) to $13,090 (SD $16,987), respectively, in the pre- and postinitiation years (P<0.001). CONCLUSIONS: The initiation of an LAI-AP improved treatment compliance, compared with previous oral APs, resulted in significantly lower HCRU and costs. The primary drivers were the reduction in the occurrence and days of hospitalizations.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".