Use of a Structured Panel Process to Define Quality Metrics for Antimicrobial Stewardship Programs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Antimicrobial stewardship programs are being implemented in health care to reduce inappropriate antimicrobial use, adverse events, Clostridium difficile infection, and antimicrobial resistance. There is no standardized approach to evaluate the impact of these programs. OBJECTIVE: To use a structured panel process to define quality improvement metrics for evaluating antimicrobial stewardship programs in hospital settings that also have the potential to be used as part of public reporting efforts. DESIGN: A multiphase modified Delphi technique. SETTING: Paper-based survey supplemented with a 1-day consensus meeting. PARTICIPANTS: A 10-member expert panel from Canada and the United States was assembled to evaluate indicators for relevance, effectiveness, and the potential to aid quality improvement efforts. RESULTS: There were a total of 5 final metrics selected by the panel: (1) days of therapy per 1000 patient-days; (2) number of patients with specific organisms that are drug resistant; (3) mortality related to antimicrobial-resistant organisms; (4) conservable days of therapy among patients with community-acquired pneumonia (CAP), skin and soft-tissue infections (SSTI), or sepsis and bloodstream infections (BSI); and (5) unplanned hospital readmission within 30 days after discharge from the hospital in which the most responsible diagnosis was one of CAP, SSTI, sepsis or BSI. The first and second indicators were also identified as useful for accountability purposes, such as public reporting. CONCLUSION: We have successfully identified 2 measures for public reporting purposes and 5 measures that can be used internally in healthcare settings as quality indicators. These indicators can be implemented across diverse healthcare systems to enable ongoing evaluation of antimicrobial stewardship programs and complement efforts for improved patient safety.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it