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Record W2511824391 · doi:10.18553/jmcp.2016.22.9.1064

Budget Impact of Adding Ivabradine to Standard of Care in Patients with Chronic Systolic Heart Failure in the United States

2016· article· en· W2511824391 on OpenAlexaff
Jeffrey Borer, Emily Dorman, Stanimira Krotneva, Ying Zheng, Harshali Patel, Luigi Tavazzi, Michel Komajda, Ian Ford, Michael Böhm, Adrian Kielhorn

Bibliographic record

VenueJournal of Managed Care & Specialty Pharmacy · 2016
Typearticle
Languageen
FieldMedicine
TopicHeart rate and cardiovascular health
Canadian institutionsEVRAZ (Canada)
FundersAmgen
KeywordsIvabradineMedicineHeart failureMedicare AdvantageFormularyEmergency medicineInternal medicineCardiologyHeart rateHealth carePharmacologyBlood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: Heart failure (HF) costs $21 billion annually in direct health care costs, 80% of which is directly attributable to hospitalizations. The SHIFT clinical study demonstrated that ivabradine plus standard of care (SoC) reduced HF-related and all-cause hospitalizations compared with SoC alone. OBJECTIVE: To estimate the budget impact of ivabradine from a U.S. commercial payer perspective. METHODS: A budget impact model estimated the per-member-per month (PMPM) impact of introducing ivabradine to existing formularies by comparing a reference scenario (SoC) and a new drug scenario (ivabradine + SoC) in hypothetical 1 million-member commercial and Medicare Advantage plans. In both scenarios, U.S. claims data were used for the reference cumulative annual rates of hospitalizations (HF, non-HF cardiovascular [CV], and non-CV), and hospitalization rates were adjusted using SHIFT data. The model controlled for mortality risk using SHIFT and U.S. life table data, and hospitalization costs were obtained from U.S. claims data: HF-related = $37,507; non-HF CV = $28,951; and non-CV = $17,904. The annualized wholesale acquisition cost of ivabradine was $4,500, with baseline use for this new drug at 2%, increasing 2% per year. RESULTS: Based on the approved U.S. indication, approximately 2,000 commercially insured patients from a 1 million-member commercial plan were eligible to receive ivabradine. Ivabradine resulted in a PMPM cost savings of $0.01 and $0.04 in years 1 and 3 of the core model, respectively. After including the acquisition price for ivabradine, the model showed a decrease in total costs in the commercial ($991,256 and $474,499, respectively) and Medicare populations ($13,849,262 and $4,280,291, respectively) in year 1. This decrease was driven by ivabradine's reduction in hospitalization rates. For the core model, the estimated pharmacy-only PMPM in year 1 was $0.01 for the commercial population and $0.24 for the Medicare Advantage population. CONCLUSIONS: Adding ivabradine to SoC led to lower average annual treatment costs. The negative PMPM budget impact indicates that ivabradine is an affordable option for U.S. payers. DISCLOSURES: This study was funded by Amgen. Patel is employed by Amgen; Kielhorn was employed by Amgen at the time of the study but is no longer affiliated with Amgen. Borer, Böhm, Ford, and Komajda have received scientific support, consultative fees, and/or speakers honoraria from Servier and Amgen in connection with SHIFT, the trial underlying this analysis. Borer also has received consultative fees from Celladon, Pfizer, ARMGO, Cardiorentis, Novartis, and Takeda USA. Kansal, Dorman, Krotneva, and Zheng are employees of Evidera, which was hired to assist with this study. Tavazzi has received research grants and consultation fees from Servier in connection with this study and has had advisory board memberships with Boston Scientific, Servier, Cardiorentis, Medtronic, St. Jude Medical, and CVie Therapeutics. Study concept and design were contributed by Dorman and Keilhorn, along with the other authors. Tavazzi, Komajda, Ford, BÖhm, and Borer oversaw collection of the data. Tavazzi, Komajda, Ford, BÖhm, and Borer (along with Karl Swedberg) formed the Executive Committee of SHIFT, the trial underlying this analysis. The manuscript was written by Kansal, along with the other authors, and revised by Borer and Patel, with assistance from the other authors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.009
GPT teacher head0.308
Teacher spread0.299 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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