Improving the hepatitis cascade: assessing hepatitis testing and its management in primary health care in China
Bibliographic record
Abstract
Objective: The study aimed to decentralize hepatitis testing and management services to primary care in China. Methods: A nationwide representative provider survey amongst community health centres (CHCs) using randomized stratified sampling methods was conducted between September and December 2015. One hundred and eighty CHCs and frontline primary care practitioners from 20 cities across three administrative regions of Western, Central and Eastern China were invited to participate. Results: One hundred and forty-nine clinicians-in-charge (79%), 1734 doctors and 1846 nurses participated (86%). Majority of CHCs (80%, 95% CI: 74-87) offered hepatitis B testing, but just over half (55%, 95% CI: 46-65) offered hepatitis C testing. The majority of doctors (87%) and nurses (85%) felt that there were benefits for providing hepatitis testing at CHCs. The major barriers for not offering hepatitis testing were lack of training (54%) and financial support (23%). Multivariate analysis showed that the major determinants for CHCs to offer hepatitis B and C testing were the number of nurses (AOR 1.1) and written policies for hepatitis B diagnosis (AOR 12.7-27.1), and for hepatitis B the availability of reproductive health service. Conclusions: Primary care providers in China could play a pivotal role in screening, diagnosing and treating millions of people with chronic hepatitis B and C in China.
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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 | 0.003 |
| 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 | 0.001 |
| 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".