Strategic opportunities for effective optimal prescribing and medication management.
Bibliographic record
Abstract
BACKGROUND: Canadians receive over 422 million prescriptions and spend over $26 billion annually on drugs. Yet, we do not systematically capture information on whether the right drugs reach the right people with the intended benefits, while avoiding unintended harm. It is important to identify and understand the effectiveness of approaches used to improve prescribing and medication use. OBJECTIVE: To discuss the medication-use system, identify factors affecting prescribing, and assess effectiveness of interventions. METHODS: A literature review was conducted using electronic databases, federal agencies', provincial health departments', health service delivery organizations' and Canadian health research organizations' websites, the Internet, and some hand searching. Interventions identified were categorized according to the Effective Practice and Organization of Care Group (EPOC) classification, with effectiveness based on the literature. RESULTS: Factors affecting prescribing relate to the patient and society, medication, prescriber, practice environment and organization, available information and other external factors. Interventions reported as generally effective are multi-faceted interventions, academic detailing, and reminders. Interventions reported as sometimes effective are audit and feedback or physician profiling, local opinion leaders, drug utilization review, and local consensus guidelines. Passive dissemination of educational materials is deemed generally ineffective. CONCLUSIONS: No single approach is appropriate for every prescribing problem, health professional prescriber practice or health care setting. Interventions to improve prescribing in community and institutional settings have variable effect sizes. Effectiveness is related to content, delivery mechanisms, intensity, intervention's context, and implementation environment. Even an intervention with a small effect size (< 10%) may yield important changes in drug use when applied on a population basis. Further research and evaluation is needed to determine how or why the interventions work and identify barriers to effective implementation.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".