Assessing the impact of general practitioner team service on perceived quality of care among patients with non-communicable diseases in China: a natural experimental study
Bibliographic record
Abstract
OBJECTIVE: China issued the national primary care policy of promoting general practitioner (GP) team service in 2011. We conducted this study to assess the impact of the GP team service on quality of primary care as perceived by patients with non-communicable diseases (NCDs). DESIGN: Natural experimental study. SETTING: This study was conducted in Shanghai, where the policy was effectively implemented, and Kunming, where the policy was not implemented. PARTICIPANTS: In both cities, NCD patients were interviewed with primary care assessment tool (PCAT) after their clinical consultations in their community health centers. INTERVENTION: The implementation of GP team service policy. MAIN OUTCOME MEASURES: Multiple linear regressions were employed to compare PCAT scores between the two rounds of the surveys in each city. Difference-in-difference (DID) analysis was used to identify the changes between two cities over time. RESULTS: A total of 663 and 587 patients in Shanghai, and 400 and 441 patients in Kunming were surveyed in 2011 and 2013, respectively. The DID analysis showed that the total primary care quality scores improved in Shanghai compared with Kunming between 2011 and 2013 (β = 1.30, 95% CI: 0.74, 1.87). In Shanghai, care quality in 2013 improved significantly for the total score and the six components when compared with those in 2011. No significant changes were observed in Kunming in the same period. CONCLUSION: Primary care policies that promote long-term provider-patient relationships, coordinated service with hospitals and capitation payment for the GP team may contribute to the improvement of care quality in Shanghai.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".