Determining the influence of the primary and specialist network of care on patient and system outcomes among patients with a new diagnosis of chronic obstructive pulmonary disease (COPD)
Bibliographic record
Abstract
INTRODUCTION: Care for patients with chronic obstructive pulmonary disease (COPD) is provided by both family physicians (FP) and specialists. Ideally, patients receive comprehensive and coordinated care from this provider team. The objectives for this study were: 1) to describe the family and specialist physician network of care for Ontario patients newly diagnosed with COPD and 2) to determine the associations between selected characteristics of the physician network and unplanned healthcare utilization. METHODS: We conducted a retrospective cohort study using Ontario health administrative data housed at ICES (formerly the Institute for Clinical Evaluative Sciences). Ontario patients, ≥ 35 years, newly diagnosed with COPD were identified between 2005 and 2013. The FP and specialist network of care characteristics were described, and the relationship between selected characteristics (i.e., continuity of care) with unplanned healthcare utilization during the first 5 years after COPD diagnosis were determined in multivariate models. RESULTS: Our cohort consisted of 450,837 patients, mean age 61.5 (SD 14.6) years. The FP was the predominant provider of care for 86.4% of the patients. Using the Bice-Boxerman's Continuity of Care Index (COCI), a measure reflecting care across different providers, 227,082 (50.4%) were categorized in a low COCI group based on a median cut-off. In adjusted analyses, patients in the low COCI group were more likely to have a hospital admission (OR = 2.27, 95% CI 2.20,2.22), 30-day readmission (OR = 2.44, 95% CI 2.39, 2.49) and ER visit (OR = 2.27, 95% CI 2.25, 2.29). CONCLUSION: Higher indices of continuity of care are associated with reduced unplanned hospital use for patients with COPD. Primary care-based practice models to enhance continuity through coordination and integration of both primary and specialist care have the potential to enhance the health experience for patients with COPD and should be a health service planning priority.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".