The Use of Long-Acting Injectable Antipsychotic Therapy for Schizophrenia
Bibliographic record
Abstract
IntroductionAntipsychotic medications form the cornerstone of schizophrenia treatment. However, only a minority of patients adhere to their initial antipsychotic regimen. It’s expected that Long-Acting Injectable (LAI) antipsychotics improves patient adherence to treatment, however previous research comparing the use of first generation LAI’s against oral antipsychotics reported results that were inconclusive. Objectives and ApproachExplore the effectiveness of the use of LAI’s in the delivery of mental health services in Alberta. Using linked data from AHS Analytics: Physician claims National Ambulatory Care Reporting System (NACRS), Discharge Abstract database (DAD) Pharmacy Information Network (PIN) Alberta Provincial Registry data Define a cohort of patients on antipsychotic medications. Explore and contrast outcomes related to the use of LAIs against other antipsychotic medication types. Specifically using linked data to define: Treatment Adherence Utilization of LAI vs. other medication Demographic differences Outcomes pre- and post-LAI treatment ResultsA patient cohort was established containing only cases from April 1, 2013 to March 31, 2015. Additional data was used to perform a two year washout and a one year follow-up. Case and medication definitions were determined by a team of psychiatric clinicians. Patient comorbidity information was extracted using previously validated methods. Overall, 6349 incident cases were identified. Preliminary analysis indicate: Overall patient cohort is older than expected Use of additional medication types is correlated with greater health services utilization after diagnosis Patients on only oral medications appear to have lower treatment adherence Males seem to have higher treatment adherence than females No significant differences were found between patients with rural vs. urban postal codes Conclusion/ImplicationsWe faced significant challenges when defining cases, medication use and outcomes. However, the linkage of a large number of data sources gives us powerful and multi-faceted insight into the use of antipsychotic medication use in Alberta. Future work will include work on definition validations and deeper analysis of outcomes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".