The Impact of Primary Care Practice Models on Indicators of Unplanned Health Care Utilization for Ontario Adults Newly Diagnosed With Chronic Obstructive Pulmonary Disease: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a highly prevalent chronic disease. Most of the care for this population occurs within the primary care setting; however, the extent to which different primary care practice models influence the outcomes of patients with COPD remains unclear. OBJECTIVE: The study aimed to compare and analyze the influence of different primary care practice models on indicators of unplanned health care utilization among newly diagnosed COPD patients in Ontario. DESIGN: A retrospective cohort study was conducted using health administrative database within the Institute for Clinical Evaluative Sciences. The cohort included persons who were 35 years and older with physician-diagnosed COPD between January 1, 2014 and December 31, 2019. Patients were assigned into 3 practice models: team-based, traditional, and no enrolment. The primary outcomes examined was unplanned health care utilization, specifically emergency department (ED) visits and hospitalizations. To account for excessive zero values, the zero inflated negative binomial (ZINB) models were used to analyze the association between different practice models and unplanned health care utilization. RESULTS: Among 57,145 individuals who met the inclusion criteria, 55,994 were included in the regression analysis. Of the included participants, 62.8% of patients were in the traditional group, 30.3% were in the team-based group, and 6.9% were in the no enrolment group. Between 2014 and 2019, 70.7% of the cohort had at least 1 all-cause ED visit without hospitalization. The adjusted ZINB models showed no significant difference in risks of experiencing an unplanned health care utilization between the team-based and traditional groups. However, patients in the no enrolment group had a significantly higher risk of ED visit without hospitalization regardless of cause, ED visit with hospitalization regardless of cause, and 30-day readmissions regardless of cause. CONCLUSIONS: Primary care practice models are complex, influenced by remuneration and organizational structures, reinforcing the need for further research to enhance our understanding of primary care reforms. Furthermore, given the growing shortage of primary care providers, patients with COPD and other chronic conditions are particularly vulnerable.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".