Quantifying sustained health system benefits of primary care-based integrated disease management for COPD: a 6-year interrupted time series study
Bibliographic record
Abstract
BACKGROUND: Severe exacerbation of chronic obstructive pulmonary disease (COPD) is a trajectory-changing life event for patients and a major contributor to health system costs. This study evaluates the real-world impact of a primary care, integrated disease management (IDM) programme on acute health service utilisation (HSU) in the Canadian health system. METHODS: Interrupted time series analysis using retrospective health administrative data, comparing monthly HSU event rates 3 years prior to and 3 years following the implementation of COPD IDM. Primary outcomes were COPD-related hospitalisation and emergency department (ED) visits. Secondary outcomes included hospital bed days and all-cause HSU. RESULTS: There were 2451 participants. COPD-related and all-cause HSU rates increased in the 3 years prior to IDM implementation. With implementation, there was an immediate decrease (month 1) in COPD-related hospitalisation and ED visit rates of -4.6 (95% CI: -7.76 to -1.39) and -6.2 (95% CI: -11.88, -0.48) per 1000 participants per month, respectively, compared with the counterfactual control group. After 12 months, COPD-related hospitalisation rates decreased: -9.1 events per 1000 participants per month (95% CI: -12.72, -5.44) and ED visits -19.0 (95% CI: -25.50, -12.46). This difference nearly doubled by 36 months. All-cause HSU also demonstrated rate reductions at 12 months, hospitalisation was -10.2 events per 1000 participants per month (95% CI: -15.79, -4.44) and ED visits were -30.4 (95% CI: -41.95, -18.78). CONCLUSIONS: Implementation of COPD IDM in a primary care setting was associated with a changed trajectory of COPD-related and all-cause HSU from an increasing year-on-year trend to sustained long-term reductions. This highlights a substantial real-world opportunity that may improve health system performance and patient outcomes.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".