Spreading improvements for advanced COPD care through a Canadian Collaborative
Bibliographic record
Abstract
BACKGROUND: A year-long pan-Canadian quality improvement collaborative (QIC) led by the Canadian Foundation for Healthcare Improvement (CFHI) supported the spread of the successful Halifax, Nova Scotia-based INSPIRED COPD Outreach Program™ to 19 teams in the 10 Canadian provinces. We describe QIC results, addressing two main questions: 1) Can the results of the Nova Scotia INSPIRED model be replicated elsewhere in Canada? 2) How did the teams implement and evaluate their versions of the INSPIRED program? METHODS: Collaborative faculty selected measures that were evidence-based, relatively simple to collect, and relevant to local context. Chosen process and outcome measures are related to four quality domains: 1) patient- and family-centeredness, 2) coordination, 3) efficiency, and 4) appropriateness. Evaluation of a complex intervention followed a mixed-methods approach. RESULTS: Most participants were nurse managers and/or COPD educators. Only 8% were physicians. Fifteen teams incorporated all core INSPIRED interventions. All teams carried out evaluation. Thirteen teams actively involved patients and families in customized, direct care planning, eg, asking them to complete evaluative surveys and/or conducting interviews. Patients consistently reported greater self-confidence in symptom management, a return to daily activities, and improvements to quality of life. Twelve teams collected data on care transitions using the validated three-item Care Transitions Measure (CTM-3). Twelve teams used the Lung Information Needs Questionnaire (LINQ). Admissions, emergency room visits, and patient-related costs fell substantially for two teams described in detail (combined enrollment 208 patients). Most teams reported gaining deeper knowledge around complexities of COPD care, optimizing patient care through action plans, self-management support, psychosocial support, advance care planning, and coordinating community partnerships. CONCLUSION: Quality-of-care gains are achievable in the short term among different teams across diverse geographical and social contexts. A well-designed, adequately funded public-private partnership can deliver widespread beneficial outcomes for the health care system and for those living with advanced COPD.
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".