Appropriate prescribing in nursing homes demonstration project (APDP) study protocol: pragmatic, cluster-randomized trial and mixed methods process evaluation of an Ontario policy-maker initiative to improve appropriate prescribing of antipsychotics
Bibliographic record
Abstract
BACKGROUND: Antipsychotic medications are routinely prescribed in nursing homes to address the behavioral and psychological symptoms of dementia. Unfortunately, inappropriate prescribing of antipsychotic medications is common and associated with increased morbidity, adverse drug events, and hospitalizations. Multifaceted interventions can achieve a 12-20 % reduction in antipsychotic prescribing levels in nursing homes. Effective interventions have featured educational outreach and ongoing performance feedback. METHODS/DESIGN: This pragmatic, cluster-randomized control trial and embedded process evaluation seeks to determine the effect of adding academic detailing to audit and feedback on prescribing of antipsychotic medications in nursing homes, compared with audit and feedback alone. Nursing homes within pre-determined regions of Ontario, Canada, are eligible if they express an interest in the intervention. The academic detailing intervention will be delivered by registered health professionals following an intensive training program including relevant clinical issues and techniques to support health professional behavior change. Physicians in both groups will have the opportunity to access confidential reports summarizing their prescribing patterns for antipsychotics in comparison to the local and provincial average. Participating homes will be allocated to one of the two arms of the study (active/full intervention versus standard audit and feedback) in two waves, with a 2:1 allocation ratio. Homes will be randomized after stratifying for geography, baseline antipsychotic prescription rates, and size, to ensure a balance of characteristics. The primary outcome is antipsychotic dispensing in nursing homes, measured 6 months after allocation; secondary outcomes include clinical outcomes and healthcare utilization. DISCUSSION: Policy-makers and the public have taken note that antipsychotics are used in nursing homes in Ontario far more than other jurisdictions. Academic detailing can be an effective technique to address challenges in appropriate prescribing in nursing homes, but effect sizes vary widely. This opportunistic, policy-driven evaluation, embedded within a government-initiated demonstration project, was designed to ensure policy-makers receive the best evidence possible regarding whether and how to scale up the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NLM Identifier: NCT02604056 .
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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 | 0.032 | 0.027 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".