Proton pump inhibitors. Compliance with a mandated step-up program.
Bibliographic record
Abstract
OBJECTIVE: To assess compliance with a step-up approach to proton pump inhibitor (PPI) therapy before implementation of a new provincial policy to promote histamine-type 2 receptor antagonist (H2RA) use before PPI therapy. DESIGN: Population-based, retrospective, open cohort study using prescribing and medical procedure data from January 1, 1995, to April 30, 1999. SETTING: Health administration databases for the universal health care system in Ontario. PARTICIPANTS: Approximately 1.4 million residents of Ontario older than 65 years. MAIN OUTCOME MEASURES: Proportion of patients who received a trial of H2RA therapy or gastrointestinal diagnostic testing 12 months before starting PPI therapy in 1996. RESULTS: Among the 25,870 patients who met study criteria in 1996, about 63% had received H2RAs 12 months before starting PPI therapy and 73% had had a trial of H2RAs or gastrointestinal diagnostic testing. Repeat analysis for January through April 1999, following the new policy implementation, showed that about 72% of patients had had a trial of H2RAs within 12 months of starting PPI therapy. CONCLUSION: A modest gain (9%) in compliance with using H2RA therapy within 12 months before starting PPI therapy was seen following introduction of the step-up intervention. In future, costs and benefits of potential interventions should be carefully considered before implementing new policies.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".