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Record W4396677586 · doi:10.1016/j.aohep.2024.101509

Spending on nucleos(t)ide analogues for hepatitis B in medicaid beneficiaries: 2012-2021

2024· article· en· W4396677586 on OpenAlexaff
Stephen E. Congly, Mayur Brahmania, Carla S. Coffin

Bibliographic record

VenueAnnals of Hepatology · 2024
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineMedicaidVirologyHepatitis BInternal medicineFamily medicineHealth care

Abstract

fetched live from OpenAlex

INTRODUCTION AND OBJECTIVES: Treatment of chronic hepatitis B (CHB) with nucelos(t)ide analogues (NA) can improve outcomes, but NA treatment is expensive for insurance plans. MATERIALS AND METHODS: The Centers for Medicare & Medicaid Services database was assessed from 2012 to 2021 to assess the use of NA for CHB in patients on Medicaid. Data extracted included the number of claims, units, and costs of each agent stratified by originator and generic. RESULTS: Over the study period, 1.9 billion USD was spent on NA, with spending peaking in 2016 at $289 million US, which has subsequently decreased. Lower expenditures since 2016 have been associated with increased use of generics. The use of generic tenofovir or entecavir led to savings of $669 million US over the study period. CONCLUSIONS: Increased generic use has significantly reduced expenditures for NA drugs; policy shifts towards generic drug use may help with sustainability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.386
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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