Use of a standardized order set in the management of an acute exacerbation of COPD
Bibliographic record
Abstract
INTRODUCTION: Acute exacerbations of COPD (AECOPD) are a common cause of hospitalization, morbidity and mortality. Despite the existence of management guidelines for AECOPD, there is variability in care amongst admitting services. Standardized admission orders have been demonstrated to result in consistent care and improved outcomes. OBJECTIVE: Our aim was to compare degree of variability in care among different admitting services at the University of Alberta Hospital (UAH). As a secondary outcome, we hypothesized that the use of a standardized order set (OS) based on current Canadian guidelines would reduce variability in management and improve patient outcomes. METHODS: We performed a retrospective chart review of 160 consecutive admissions for AECOPD to the UAH from September 1, 2012 to February 1, 2013. All patients were admitted to one of the Family Medicine (FM), Internal Medicine (IM) or Pulmonary Medicine (PM) wards. Comparisons in the medical management were made between admission services and in those using the OS versus current clinical practice. RESULTS: 29 patients were admitted to FM, 68 to IM and 63 to PM. Of the FM, IM and PM group, inhaler therapy was appropriate in 48%, 40%, 63.5% and discharge inhalers in 69%, 53% and 63.5% respectively. Outpatient rehabilitation referral was sent in 3%, 0% and 12.5% and smoking cessation counseled in 7%, 6% and 2% respectively. These values increased to 83%, 83%, 25% and 0% in the 12 patients that used the OS respectively. CONCLUSIONS: There is a significant variation in care among the admitting services. Patients in whom the OS had been used had a higher percent of appropriate therapy and therefore future work is directed at increasing OS uptake.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".