Effect of Rivaroxaban Versus Warfarin on Health Care Costs Among Nonvalvular Atrial Fibrillation Patients: Observations from Rivaroxaban Users and Matched Warfarin Users
Bibliographic record
Abstract
INTRODUCTION: New target-specific oral anticoagulants may have benefits, such as shorter hospital length of stay, compared to warfarin in patients with nonvalvular atrial fibrillation (NVAF). This study aimed to assess, among patients with NVAF, the effect of rivaroxaban versus warfarin on health care costs in a cohort of rivaroxaban users and matched warfarin users. METHODS: Health care claims from the Humana database from 5/2011 to 12/2012 were analyzed. Adult patients newly initiated on rivaroxaban or warfarin with ≥2 atrial fibrillation (AF) diagnoses (The International Classification of Diseases, Ninth Revision, Clinical Modification: 427.31) and without valvular AF were identified. Based on propensity score methods, warfarin patients were matched 1:1 to rivaroxaban patients. Patients were observed up to end of data, end of insurance coverage, death, a switch to another anticoagulant, or treatment nonpersistence. Health care costs [hospitalization, emergency room (ER), outpatient, and pharmacy costs] were evaluated using Lin's method. RESULTS: Matches were found for all rivaroxaban patients, and characteristics of the matched groups (n = 2253 per group) were well balanced. Estimated mean all-cause and AF-related hospitalization costs were significantly lower for rivaroxaban versus warfarin patients (all-cause: $5411 vs. $7427, P = 0.047; AF-related: $2872 vs. $4147, P = 0.020). Corresponding estimated mean all-cause outpatient visit costs were also significantly lower, but estimated mean pharmacy costs were significantly higher for rivaroxaban patients ($5316 vs. $2620, P < 0.001). Although estimated mean costs of ER visits were higher for rivaroxaban users compared to those of warfarin users, differences were not statistically significant. Including anticoagulant costs, mean overall total all-cause costs were comparable for rivaroxaban versus warfarin users due to cost offset from a reduction in the number and length of hospitalizations and number of outpatient visits ($17,590 vs. $18,676, P = 0.542). CONCLUSION: Despite higher anticoagulant cost, mean overall total all-cause and AF-related cost remains comparable for patients with NVAF treated with rivaroxaban versus warfarin due to the cost offset from reduced health care resource utilization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".