Article Text

O-001 Lifetime quality of life and cost consequences of treatment delays in endovascular thrombectomy for stroke based on hermes data
1. W Kunz1,
2. M Almekhlafi2,
3. B Menon2,
4. J Saver3,
5. D Dippel4,
6. C Majoie5,
7. T Jovin6,
8. A Davalos7,
9. S Bracard8,
10. F Guillemin8,
11. B Campbell9,
12. P Mitchell9,
13. P White10,
14. K Muir11,
15. S Brown12,
16. A Demchuk2,
17. M Hill2,
18. M Goyal1
2. 2Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
3. 3Department of Neurology, University of California-Los Angeles, Los Angeles, CA
4. 4ERASMUS MC, Rotterdam, Netherlands
5. 5AMC Amsterdam, Amsterdam, Netherlands
6. 6University of Pittsburgh, Pittsburgh, PA
7. 7Hospital Universitari Germans Trias i Pujol, Barcelona, Spain
8. 8University Hospital of Nancy, Nancy, France
9. 9University of Melbourne, Melbourne, Australia
10. 10Newcastle University, Newcastle, UK
11. 11University of Glasgow, Glasgow, UK
12. 12Altair Biostatistics, St Louis, MN

## Abstract

Purpose The benefit that endovascular trombectomy (EVT) offers to stroke patients with large vessel occlusions is highly time-dependent. Our aim was to determine the lifetime quality of life and cost consequences of delaying EVT administration for patients, the healthcare system, and society.

Materials and methods A Markov model estimated lifetime quality-adjusted life years (QALYs) of EVT-treated patients and associated costs based on stroke onset to arterial puncture time. The analysis was performed from a United States perspective with two cost frameworks: 1) healthcare costs and 2) societal costs, which include productivity losses and costs of informal care given by family members. Input parameters were based on best evidence (table 1), including patient data from the 7-trial HERMES collaboration. In addition to diminished functional outcomes with later EVT, the model also projects that a proportion of patients become EVT-ineligible over time. The lead analysis was conducted for stroke onset at 65 years. Probabilistic sensitivity analysis was performed using Monte Carlo simulations.

Abstract O-001 Table 1

Model input parameters and references

Results Lifetime QALYs decreased for every hour of time delay until arterial puncture (figure 1A). Within the first 6 hours of onset, every hour of delay resulted in an average loss of 0.77 QALYs. The healthcare and societal costs of each QALY yielded by EVT increased for every hour of time delay (figure 1B). Within the first 6 hours of onset, every hour of delay increased the cost of QALYs yielded by EVT by $6,173/QALY in healthcare costs and by$7,597/QALY in societal costs. Within the first 3 hours of onset, a treatment delay of 2 hours -the amount typically associated with drip-and-ship compared to mothership care delivery- would result in an average loss of close to 2 QALYs per patient. In addition, this delay would result in an extra of about $11,000/QALY gained incurred by the healthcare system and$15,000/QALY gained incurred by society.

Abstract O-001 Figure 1

Conclusion Every hour of treatment delay reduces a patient‘s QALYs by three-quarters of a year, and substantially increases healthcare and societal costs per QALY. Investments in healthcare policies and procedures to improve efficiency of pre-hospital triage and in-hospital workflow are likely to be highly cost-saving.

Disclosures W. Kunz: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. M. Almekhlafi: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. B. Menon: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. J. Saver: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. D. Dippel: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. C. Majoie: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. T. Jovin: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. A. Davalos: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. S. Bracard: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. F. Guillemin: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. B. Campbell: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. P. Mitchell: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. P. White: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. K. Muir: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. S. Brown: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. A. Demchuk: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. M. Hill: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary. M. Goyal: 1; C; HERMES collaboration was supported by Medtronic through an unrestricted research grant to University of Calgary.

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