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Using Phase-Based Costing of Real-World Data to Inform Decision–Analytic Models for Atrial Fibrillation

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Abstract

Background

Atrial fibrillation (AF) poses a significant economic burden. An increasing number of interventions for AF require cost-effectiveness analysis with decision–analytic modeling to demonstrate value. However, high-quality cost estimates of AF that can be used to inform decision–analytic models are lacking.

Objectives

The objectives of this study were to determine whether phase-based costing methods are feasible and practical for informing decision–analytic models outside of oncology.

Methods

Patients diagnosed with AF between 1 January 2003 and 30 June 2011 in Ontario, Canada were identified based on a hospital admission for AF using administrative data housed at the Institute for Clinical Evaluative Sciences. Patient observations were then divided into phases based on clinical events typically used for decision–analytic modeling (i.e., minor stroke/transient ischemic attack [TIA], moderate to severe ischemic stroke, myocardial infarction, extracranial hemorrhage [ECH], intracranial hemorrhage [ICH], multiple events, death from an event, or death from other causes). First 30-day and greater than 30-day costs of healthcare resources in each health state were estimated based on a validated methodology. All costs are reported in 2013 Canadian dollars (Can$) and from a healthcare payer perspective.

Results

Patients (n = 109,002) with AF who did not experience a clinical event incurred costs of Can$1566 per 30 days, on average. The average 30-day cost of experiencing a fatal clinical event was Can$42,871, but the cost of dying from all other causes was much smaller (Can$12,800). The clinical events associated with the highest short-term costs were ICH (Can$22,347) and moderate to severe ischemic stroke (Can$19,937). The lowest short-term costs were due to minor ischemic stroke/TIA (Can$12,515) and ECH (Can$12,261). Patients who had experienced a moderate to severe ischemic stroke incurred the highest long-term costs.

Conclusions

Real-world Canadian data and a phase-based costing approach were used to estimate short- and long-term costs associated with AF-related major clinical events. The results of this study can also inform decision–analytic models for AF.

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Author information

Authors and Affiliations

  1. Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, ON, M5S 3M2, Canada

    Amy Tawfik, Petros Pechlivanoglou, Jeffrey Hoch & Murray Krahn

  2. Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON, Canada

    Amy Tawfik, Petros Pechlivanoglou & Murray Krahn

  3. Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada

    Walter P. Wodchis

  4. Institute for Clinical Evaluative Sciences, Toronto Rehabilitation Institute, Toronto, ON, Canada

    Walter P. Wodchis

  5. Pharmacoeconomics Research Unit, Cancer Care Ontario, Toronto, ON, Canada

    Jeffrey Hoch

  6. Institute of Health Economics, Edmonton, AB, Canada

    Don Husereau

Authors
  1. Amy Tawfik
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  2. Walter P. Wodchis
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  3. Petros Pechlivanoglou
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  4. Jeffrey Hoch
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  6. Murray Krahn
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Corresponding author

Correspondence to Amy Tawfik.

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Funding sources

This work is funded by grants from the University of Toronto, the Toronto Health Economics and Technology Assessment Collaborative, and the Government of Ontario in the form of the Ontario Graduate Scholarship to assist in the completion of doctoral research. It was also funded in part by an unrestricted fellowship grant from Pfizer Canada.

Author contributions

AT led all aspects of this work including the design, analysis, interpretation, and drafting of the manuscript and is the guarantor of this work. WW helped collect and interpret data; PP helped analyze data; JH and MK oversaw the work; DH aided in the interpretation and drafting of the manuscript. All authors designed the study, helped to write the manuscript, and read and approved the final version of the manuscript.

Disclosures

Amy Tawfik, Walter Wodchis, Petros Pechlivanoglou, Jeffrey Hoch, Don Husereau, and Murray Krahn have signed conflict of interest forms and declare the following: current employment with Janssen Inc./J&J, a company which may have interest in this work (AT); no conflicts (WW, PP, JH); accepting consulting fees from drug/device companies and consultancies which may have an interest in this work (DH); and financial relationships with Pfizer Canada Inc. (through a fellowship grant; MK).

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Tawfik, A., Wodchis, W.P., Pechlivanoglou, P. et al. Using Phase-Based Costing of Real-World Data to Inform Decision–Analytic Models for Atrial Fibrillation. Appl Health Econ Health Policy 14, 313–322 (2016). https://doi.org/10.1007/s40258-016-0229-2

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  • DOI: https://doi.org/10.1007/s40258-016-0229-2

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