Predictors of relational continuity in primary care: patient, provider and practice factors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Continuity is a fundamental tenet of primary care, and highly valued by patients; it may also improve patient outcomes and lower cost of health care. It is thus important to investigate factors that predict higher continuity. However, to date, little is known about the factors that contribute to continuity. The purpose of this study was to analyse practice, provider and patient predictors of continuity of care in a large sample of primary care practices in Ontario, Canada. Another goal was to assess whether there was a difference in the continuity of care provided by different models of primary care. METHODS: This study is part of the larger a cross-sectional study of 137 primary care practices, their providers and patients. Several performance measures were evaluated; this paper focuses on relational continuity. Four items from the Primary Care Assessment Tool were used to assess relational continuity from the patient's perspective. RESULTS: Multilevel modeling revealed several patient factors that predicted continuity. Older patients and those with chronic disease reported higher continuity, while those who lived in rural areas, had higher education, poorer mental health status, no regular provider, and who were employed reported lower continuity. Providers with more years since graduation had higher patient-reported continuity. Several practice factors predicted lower continuity: number of MDs, nurses, opening on weekends, and having 24 hours a week or less on-call. Analyses that compared continuity across models showed that, in general, Health Service Organizations had better continuity than other models, even when adjusting for patient demographics. CONCLUSIONS: Some patients with greater health needs experience greater continuity of care. However, the lower continuity reported by those with mental health issues and those who live in rural areas is concerning. Furthermore, our finding that smaller practices have higher continuity suggests that physicians and policy makers need to consider the fact that 'bigger is not always necessarily better'.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it