Projects
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Simulation
Dr Stahl is a leading expert in the use of discrete-event simulation methods in healthcare. Discrete-event simulation (DES) is a computer modeling method for modeling systems. In these systems, entities may compete for resources, events can be interdependent and the flow of information and entities can evolve. Dr Stahl teaches DES widely and has published on models he has developed with it in areas ranging from organ allocation, stroke management to hospital and clinic organization.
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Specialized Program of Translational Research In Acute Stroke at the Partners (SPOTRIAS)
In 2006, the Partners Stroke Team at Massachusetts General Hospital and Brigham and Women’s Hospital received a 5-year SPOTRIAS award from the National Institute of Neurological Disorders and Stroke (NINDS) to perform three inter-related acute stroke research projects. Each of these projects originated in the MGH basic science research laboratories.
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The Development and Analysis of a Population simulation disease model of Gastroesophageal Reflux Disease (GERD), Barrett’s Esophagus (BE) and Esophageal Adencarcinoma (EAC)
Barrett’s esophagus - the construction and continued refinement of this disease model has allowed analyses that have attempted to determine the optimal management strategy for those patients with this pre-malignant condition which is a precursor to esophageal cancer. Specific analyses have addressed the cost-effectiveness of endoscopic surveillance, photodynamic therapy, as well aspirin for chemoprevention. Future areas of research include patient preferences in Barrett’s high grade dysplasia which is currently an area of much controversy.
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The Development of Prediction Rules to Improve Endoscopic Utilization for GERD/BE/EAC
Risk stratification to identify higher risk individuals will improve the effectiveness of endoscopic screening for BE/EAC. We are developing an endoscopic patient database to initially develop a logistic regression model in an attempt to develop prediction rules. These rules will be tested in our simulation disease model to assess their effectiveness and cost-effectiveness.
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The Effect of Self-referral on Cost and Utilization of Diagnostic Imaging Tests
Imaging represents one of the fastest growing components of healthcare spending. We will identify conditions for which the use of diagnostic imaging leads to improved health outcomes, decreased costs, or both, and quantify the benefits attributable to imaging.