Patients' experience of chronic illness care in a network of teaching settings.
Bibliographic record
Abstract
OBJECTIVE: To evaluate chronic illness care delivery from the patient's perspective and to examine its main correlates. DESIGN: Cross-sectional, descriptive study using questionnaires and medical chart review. SETTING: Nine teaching family practices in Quebec. PARTICIPANTS: A total of 364 patients with diabetes, hypertension, or chronic obstructive pulmonary disease. MAIN OUTCOMES MEASURES: Score on the Patient Assessment of Chronic Illness Care (PACIC) questionnaire, which evaluates the patient's perspective on the care received based on the chronic care model (CCM); patients characteristics (sex, level of education, number of chronic illnesses); patient-physician relationship (relational continuity, interpersonal communication assessed from the patient's perspective); and interdisciplinary care and technical quality of care abstracted from patients' medical charts. RESULTS: The mean PACIC score obtained (2.8 out of 5) indicates that, on average, CCM-concordant care "generally did not occur" or occurred only "sometimes" in this network of teaching practices. However, with a mean technical quality-of-care score of nearly 80%, physicians in this network showed a high degree of adherence to clinical guidelines for the chronic illnesses under study. Patient education level lower than high school was negatively associated with PACIC scores, while positive associations were found with male sex, number of chronic illnesses, relational continuity, interpersonal communication, interdisciplinary care, and technical quality of care. CONCLUSION: Patients with less education reported receiving less CCM-concordant care. The patient-physician relationship was the strongest correlate of PACIC scores, while interdisciplinary care and technical quality of care had modest contributions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".