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Appl Health Econ Health Policy. 2016 Jun;14(3):313-22. doi: 10.1007/s40258-016-0229-2.

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

Author information

  • 1Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, ON, M5S 3M2, Canada. amytawfik1226@gmail.com.
  • 2Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON, Canada. amytawfik1226@gmail.com.
  • 3Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.
  • 4Institute for Clinical Evaluative Sciences, Toronto Rehabilitation Institute, Toronto, ON, Canada.
  • 5Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, ON, M5S 3M2, Canada.
  • 6Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON, Canada.
  • 7Pharmacoeconomics Research Unit, Cancer Care Ontario, Toronto, ON, Canada.
  • 8Institute of Health Economics, Edmonton, AB, Canada.

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.

PMID:
26924098
DOI:
10.1007/s40258-016-0229-2
[PubMed - in process]
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