The Primary-Specialty Care Interface in Chronic Diseases: Patient and Practice Characteristics Associated with Co-Management
Bibliographic record
Abstract
OBJECTIVE: Specialist physicians may act either as consultants or co-managers for patients with chronic diseases along with their primary healthcare (PHC) physician. We assessed factors associated with specialist involvement. METHODS: We used questionnaire and administrative data to measure co-management and patient and PHC practice characteristics in 702 primary care patients with common chronic diseases. Analysis included multilevel logistic regressions. RESULTS: In all, 27% of the participants were co-managed. Persons with more severe chronic diseases and lower health-related quality of life were more likely to be co-managed. Persons who were older, had a lower socioeconomic status, resided in rural regions and who were followed in a PHC practice with an advanced practice nurse were less likely to be co-managed. DISCUSSION: Co-management of patients with chronic diseases by a specialist is associated with higher clinical needs but demonstrates social inequalities. PHC practices more adapted to chronic care may help optimize specialist resources utilization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".