Exploring the Role of Primary Care Clinic Continuity for Patients with COPD or Heart Failure
Bibliographic record
Abstract
Context: Family physicians (FP) play a vital role in managing patients with chronic obstructive pulmonary disease (COPD) or heart failure (HF). Much emphasis has been placed on care pathways which involve community FPs caring for patients following hospitalization or treatment in the Emergency Department (ED). Given the trend in part-time practice, questions remain on the role of clinic continuity and its impact on health outcomes. Objective: Our objective is to understand the impact of varying level of primary care clinic continuity (i.e. group care) on patient health outcomes. Study Design and Analysis: We conducted a retrospective observational study of all FPs and COPD and HF patients in Alberta from 2015-18 to explore the association between patient health outcomes and three levels of community-based primary clinic continuity. FP claims data were linked to patients’ ED and inpatient encounters. Usual provider care index (UPC) was calculated for each provider and facility over 3 years. The proportion of a patient’s visits to a non-panel provider at their panel providers main facility was calculated and called the “Group Care Rate” (GCR). The GCR for each patient was calculated and categorized as low (0-10%), moderate (10-20%) and high (21+%). Patients with 100% UPC were removed from the analysis, since by definition their GCR=0, leading to collinearity in the modelling. Multivariable zero-inflated negative binomial models were fit, adjusting for age, sex, complexity and UPC. Dataset: De-identified FP claims were linked to ED and inpatient encounters from Alberta Health. Intervention or Instrument: None. Outcome Measures: ED visit or Hospital admission for COPD or HF. Result: Zero-inflated negative binomial regression models showed that high GCR (20%+) has a protective effect, for both COPD and HF patients, relative to low GCR (0-10%). Specifically, relative to low GCR, COPD patients with high GCR had an IRR of 0.75 (0.72, 0.80) in terms of hospital visits, and 0.90 (0.87, 0.93) in terms of ED visits. Similarly, relative to low GCR, HF patients with high GCR had an IRR of 0.77 (0.72, 0.81) in terms of hospital visits, and 0.90 (0.86, 0.95) in terms of ED visits. Conclusions: Patients with COPD or HF who seek care from community-based primary care clinics with high (relative to low) group care were associated with reduced rates of ED visits and hospitalizations.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".