Healthcare utilization and costs associated with dabigatran compared to warfarin treatment in newly diagnosed patients with non-valvular atrial fibrillation.



Real-world healthcare resource utilization and costs were compared among patients with non-valvular atrial fibrillation (NVAF) receiving either dabigatran or warfarin.


A retrospective cohort study was conducted using administrative claims data from the United States Department of Defense (DOD) Military Health System. Patients with newly diagnosed AF initiated on dabigatran or warfarin were identified using ICD-9 diagnosis, procedure and drug codes. Patients were observed for 3 months prior to treatment initiation to ascertain a diagnosis of valvular heart disease and 12 months for exclusion of those with a history of anticoagulation therapy. Propensity score matching was used to balance baseline characteristics between the two treatment cohorts. Medical and pharmacy utilization and costs were compared between the dabigatran and warfarin treatment groups for 3 and 12 months following treatment initiation.


A total of 1102 patients with newly diagnosed NVAF initiated on dabigatran were matched with corresponding warfarin-treated patients. In the 12 months following initiation of anticoagulation, the mean medical costs for patients initiated on dabigatran were significantly lower than for patients initiated on warfarin (-$6299, p < 0.001), largely due to fewer hospitalizations (-0.162, p = 0.009). While pharmacy costs were higher ($4369, p < 0.001) for dabigatran, overall healthcare costs were significantly lower compared with patients on warfarin (12 months: -$1940, p < 0.001). Mean hospital length of stay between these two groups were similar (6.033 days for dabigatran vs 6.318 days for warfarin, p = 0.139).


Despite higher pharmacy costs for NVAF patients initiated on dabigatran vs warfarin, this was more than offset by lower utilization of medical care resources.





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Publication Info

Francis, Kevin, Chen Yu, Hasmik Alvrtsyan, Stephen Sander, Sabyasachi Ghosh, Yajing Rao, Herman Sanchez, David Matchar, et al. (2015). Healthcare utilization and costs associated with dabigatran compared to warfarin treatment in newly diagnosed patients with non-valvular atrial fibrillation. Current medical research and opinion, 31(12). pp. 2189–2195. 10.1185/03007995.2015.1092124 Retrieved from

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David Bruce Matchar

Professor of Medicine

My research relates to clinical practice improvement - from the development of clinical policies to their implementation in real world clinical settings. Most recently my major content focus has been cerebrovascular disease. Other major clinical areas in which I work include the range of disabling neurological conditions, cardiovascular disease, and cancer prevention.
Notable features of my work are: (1) reliance on analytic strategies such as meta-analysis, simulation, decision analysis and cost-effectiveness analysis; (2) a balancing of methodological rigor the needs of medical professionals; and (3) dependence on interdisciplinary groups of experts.
This approach is best illustrated by the Stroke Prevention Patient Outcome Research Team (PORT), for which I served as principal investigator. Funded by the AHCPR, the PORT involved 35 investigators at 13 institutions. The Stroke PORT has been highly productive and has led to a stroke prevention project funded as a public/private partnership by the AHCPR and DuPont Pharma, the Managing Anticoagulation Services Trial (MAST). MAST is a practice improvement trial in 6 managed care organizations, focussing on optimizing anticoagulation for individuals with atrial fibrillation.
I serve as consultant in the general area of analytic strategies for clinical policy development, as well as for specific projects related to stroke (e.g., acute stroke treatment, management of atrial fibrillation, and use of carotid endarterectomy.) I have worked with AHCPR (now AHRQ), ACP, AHA, AAN, Robert Wood Johnson Foundation, NSA, WHO, and several pharmaceutical companies.
Key Words: clinical policy, disease management, stroke, decision analysis, clinical guidelines

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