Antiviral drug Utilization and Annual Expenditures for Patients with Chronic HBV Infection in Guangzhou, China, in 2008–2015
Bibliographic record
Abstract
BACKGROUND: The aims of this study were to describe antiviral drug (AD) utilization and costs in patients with chronic HBV infection. METHODS: We conducted a retrospective study of patients in the hospital and calculated annual proportions of AD utilization and costs among patients. A two-part model was used to estimate adjusted odds ratio (OR) for antiviral therapy and cost ratios for antiviral costs associated with demographics. RESULTS: Of a total of 14,920 records, 143,658 records were involved in the analysis. The annual proportions of AD utilization were 56.99% (45.65%) for inpatients (outpatients) during 2008-2015 and increased annually. Entecavir (ETV), in particular, increased from 11.08% to 70.26% (11.05% to 49.35%) for inpatients (outpatients). The patients with medical insurance were more likely to use AD than patients without insurance, and the adjusted OR was 1.11 (95% CI: 1.03, 1.19) for inpatients and 1.66 (1.59, 1.73) for outpatients. With the disease progressing, the proportion of antiviral costs in total direct medical costs decreased from 13.91% to 4.07% (71.29% to 49.29%) for inpatients (outpatients). CONCLUSIONS: The use of AD for chronic HBV infection was less than expected based on established guidelines, and only half of patients received antiviral treatment. However, the AD utilization, especially ETV, increased annually. Reimbursement policy was the most important factor affecting antiviral treatment. Antiviral therapy was an important part of the direct medical costs, especially in the early stage of disease.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".