Development of a patient-centred, evidence-based and consensus-based discharge care bundle for patients with acute exacerbation of chronic obstructive pulmonary disease
Bibliographic record
Abstract
INTRODUCTION: Hospital and emergency department discharge for patients with chronic obstructive pulmonary disease (COPD) is often poorly organised. We developed a patient-centred, evidence-based and consensus-based discharge care bundle for patients with acute exacerbations of COPD. METHODS: A purposeful sample of clinicians and patients were invited to participate in a two-round Delphi study (July-November 2015). In round 1, participants rated on a seven-point Likert scale (1=not at all important; 7=extremely important) the importance of 29 unique COPD care actions. Round 2 comprised items selected from round 1 based on consensus (>80% endorsement for Likert values 5-7). A list of 18 care items from round 2 was discussed in a face-to-face nominal group meeting. RESULTS: Seven care items were included in the COPD discharge bundle based on clinician and patient input: (1) ensure adequate inhaler technique is demonstrated; (2) send discharge summary to family physician and arrange follow-up; (3) optimise and reconcile prescription of respiratory medications; (4) provide a written discharge management plan and assess patient's and caregiver's comprehension of discharge instructions; (5) refer to pulmonary rehabilitation; (6) screen for frailty and comorbidities; and (7) assess smoking status, provide counselling and refer to smoking cessation programme. CONCLUSION: We present a seven-item, patient-centred, evidence-based and consensus-based discharge bundle for patients with acute exacerbations of COPD. Alignment with clinical practice guidelines and feasibility of local adaptations of the bundle should be explored to facilitate wide applicability and evaluation of the effectiveness of the COPD discharge bundle.
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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 | 0.093 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".