Educational Intervention Improves Proton Pump Inhibitor Stewardship in Outpatient Gastroenterology Clinics
Bibliographic record
Abstract
BACKGROUND: Improper chronic proton pump inhibitor (PPI) use has risen significantly in the last few decades. In our gastroenterology trainees' clinics, we aimed to optimize PPI usage. METHODS: We collected baseline data on patients' PPI use for 8 weeks. Based on gastroenterology society guidelines, we determined conditions for appropriate PPI use. If the indication could not be determined, it was categorized as "unknown". Generated from the three most frequent causes for inappropriate PPI use, interventions were developed to correct each issue. Following a brief educational session, trainees implemented these interventions over a subsequent 8-week interval. RESULTS: During our pre-intervention period, trainees evaluated 263 patients who were prescribed a PPI. In 49% of the cases, the use of PPI was deemed inappropriate. The most common reasons were: gastroesophageal reflux disease (GERD) which was never titrated to the lowest effective dose, twice daily dosing for Barrett's esophagus (BE) chemoprevention and unknown indication. During our intervention period, trainees evaluated 145 patients prescribed a PPI for GERD with well-controlled symptoms in 101 cases. PPI had not been titrated to lowest effective dose in 37 cases prompting intervention which was successful in 23 cases. PPI indication was unknown in 17 cases prompting a message to the prescribing provider to review appropriateness. Two cases of BE chemoprevention with twice daily dosing were appropriately reduced to daily dosing. Ultimately, after intervention, PPI use was deemed appropriate after intervention in 172 (77%) cases. CONCLUSIONS: Improper chronic PPI use was significant. Focusing intervention efforts on PPI use for GERD, BE and unknown indications substantially increased appropriateness of PPI use.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".