Prescriber Specialty Involvement in Medicare Patients With Chronic Hepatitis B
Bibliographic record
Abstract
Chronic hepatitis B (CHB) is a major cause of liver-related morbidity and mortality in the United States. Patients with CHB require long-term antiviral treatment and consistent follow-up, but often face numerous barriers to accessing care and medications. In this study, we used the Medicare Part D database and the Rural-Urban Continuum code to explore specialty and geographic characteristics of healthcare providers that manage Medicare patients with CHB. Between 2013 and 2021, more than 7000 prescribers prescribed over 2.4 million 30-day prescriptions of these CHB therapies, of which 2 million (85%) were in metropolitan counties. The number of 30-day prescriptions increased by 5.4% annually. The number of prescriptions by GI increased by 12.5% a year and prescriptions by APPs increased by 12.2% a year, while prescriptions by ID decreased by 14.0% annually. In non-metropolitan counties, APPs experienced -5% APC between 2013 and 2021, and PCPs experienced -12.5% APC between 2016 and 2021. In this study, we found that there has been a noticeable shift in the specialties prescribing medications for patients with hepatitis B. Gastroenterologists and APPs became significantly more involved as prescribers. The increase in APP management of patients with CHB is a welcoming development, especially in light of the physician workforce shortage. It is important to create solutions such as co-management to ensure that patients with CHB receive consistent care without further contributing to supply-demand mismatch in gastroenterology.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".