Public expectations of good primary health care in China: a national qualitative study
Bibliographic record
Abstract
BACKGROUND: China is currently making efforts to transform the current hospital-centric service delivery system to people-centred primary health care (PHC)-based delivery system, with service delivery organized around the health needs and expectations of people. To help direct China's PHC reform efforts, a profile of high-quality PHC from the public's perspective is required. OBJECTIVES: To profile high-quality PHC from the perspective of the Chinese public. METHODS: Semistructured interviews were conducted in 6 provinces (Henan, Shandong, Zhejiang, Shaanxi, Shanxi, and Heilongjiang) in China. In total, 58 interviewees completed the recorded interview. For transcription, trained research assistant listened to the recording of the interviews, summarizing each 30-s segment in English. Next, thematic analysis was performed on the narrative summaries to identify thematic families. RESULTS: Seven themes and 16 subthemes were generated from the analysis of our interview data. In order of their frequency, the interviewees expressed a high expectation for interpersonal communication and technical quality; followed by access, comprehensive care, cost, continuity, and coordination. CONCLUSIONS: Using qualitative data from 6 provinces in China, knowledge was generated to reveal the public's views and expectations for high-quality PHC. Our results confirm the urgent need for quality improvement efforts to improve patient experience and technical quality. The government also needs to further improve the delivery system and medical training programme to better meet public expectation in these areas, especially in establishing an innovative integrated primary care model, and strengthening interpersonal and clinical competency training for family doctors.
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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 | 0.003 | 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 | 0.001 |
| 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".