Modeling the cost-effectiveness of MRI-based treatment decisions for acute stroke patients with unknown stroke onset time
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Guest Speaker  Ankur Pandya, MPH, PhD
Assistant Professor
Department of Healthcare Policy and Research Health
Weill Cornell Medical College, NY Dr. Ankur Pandya is an Assistant Professor in the Department of Healthcare Policy and Research Health at Weill Cornell Medical College. He holds a secondary appointment as Assistant Professor of Public Health in Radiology in the Department of Radiology. He received his B.S. degree from Cornell University, his M.P.H Degree from the Yale School of Public Health, and his Ph.D. degree from Harvard University in Health Policy in 2012. His work focuses on the application of health decision science modeling techniques to assess the tradeoffs in health benefits, risks, and costs associated with competing clinical strategies. His current research projects aim to optimize the use of radiologic techniques and other risk assessment tools used in the treatment and prevention of chronic health conditions, such as cardiovascular disease. As a methodological area of interest, he is also working on the development and evaluation of various approaches used in disease model calibration. Abstract: Time since stroke onset is a key input in acute stroke treatment guidelines, but this information is unknown in 14-28% of ischemic stroke cases, often because the stroke occurred during sleep. Thrombolytic treatment (tissue-type plasminogen activator [tPA]) is recommended for acute stroke patients with stroke onset time <4.5 hours, but not in patients with stroke onset time >4.5 hours due to bleeding risks. Certain neuroimaging information, such as diffusion-weighted MRI (DWI) and fluid-attenuated inversion recovery (FLAIR) MRI mismatch, has been shown to estimate stroke onset time with considerable accuracy. We developed a micro-simulation model to evaluate the tradeoffs among health benefits, risks, and costs of MRI-based tPA decision-making compared to conventional decision rules for acute stroke patients with unknown stroke onset time. |
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Time Duration
Location
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Guest Speaker Ankur Pandya, MPH, PhD
Assistant Professor
Department of Healthcare Policy and Research Health
Weill Cornell Medical College, NY Dr. Ankur Pandya is an Assistant Professor in the Department of Healthcare Policy and Research Health at Weill Cornell Medical College. He holds a secondary appointment as Assistant Professor of Public Health in Radiology in the Department of Radiology. He received his B.S. degree from Cornell University, his M.P.H Degree from the Yale School of Public Health, and his Ph.D. degree from Harvard University in Health Policy in 2012. His work focuses on the application of health decision science modeling techniques to assess the tradeoffs in health benefits, risks, and costs associated with competing clinical strategies. His current research projects aim to optimize the use of radiologic techniques and other risk assessment tools used in the treatment and prevention of chronic health conditions, such as cardiovascular disease. As a methodological area of interest, he is also working on the development and evaluation of various approaches used in disease model calibration. Abstract: Time since stroke onset is a key input in acute stroke treatment guidelines, but this information is unknown in 14-28% of ischemic stroke cases, often because the stroke occurred during sleep. Thrombolytic treatment (tissue-type plasminogen activator [tPA]) is recommended for acute stroke patients with stroke onset time <4.5 hours, but not in patients with stroke onset time >4.5 hours due to bleeding risks. Certain neuroimaging information, such as diffusion-weighted MRI (DWI) and fluid-attenuated inversion recovery (FLAIR) MRI mismatch, has been shown to estimate stroke onset time with considerable accuracy. We developed a micro-simulation model to evaluate the tradeoffs among health benefits, risks, and costs of MRI-based tPA decision-making compared to conventional decision rules for acute stroke patients with unknown stroke onset time. |