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Real-world Resource Use and Costs of Haemophilia A-related Bleeding

Overview
Journal Haemophilia
Specialty Hematology
Date 2017 Jun 3
PMID 28574162
Citations 12
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Abstract

Introduction: Prophylaxis treatment is recommended for haemophilia patients, but associated real-world economic costs and potential cost-savings associated with improved disease management are not fully known. This study aimed to assess haemophilia A-related resource use and cost by treatment type (prophylaxis versus non-prophylaxis) and any associated cost-savings.

Methods: Truven MarketScan Commercial claims data (2004-2012) were used to identify haemophilia A-related healthcare utilization, healthcare costs and patterns of prophylaxis and non-prophylaxis treatment among 6- to 64-year-old males. We estimated bleeding-related resource utilization and costs in three age groups (6-18, 19-44, 45-64) by treatment types and assessed the extent to which early initiation of prophylactic treatment can mitigate them. T-tests and ordinary least squares regressions were used to compare unadjusted and demographics-adjusted cost estimates.

Results: Among children, overall haemophilia- and bleeding-related non-pharmacy costs were substantially lower for patients receiving prophylaxis (haemophilia-related: $15,864 vs. $53,408; P < 0.001; bleeding-related: $696 vs. $2013, respectively; P = 0.04). Among younger adults (19-44), haemophilia-related non-pharmacy costs were lower for patients receiving prophylaxis ($22,028 vs. $56,311, respectively; P = 0.001). Among children, these savings fully offset the incremental pharmacy cost due to prophylaxis. Among younger adults, the savings offset approximately 34% of the incremental pharmacy cost. No differences were found for older adults (45-64).

Conclusion: These results suggest that initiating prophylaxis earlier in life may reduce the healthcare costs of bleeding events and their long-term complications. Future studies should strive to collect more detailed information on disease severity and treatment protocols to improve estimates of disease burden.

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