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Saeid Shahraz, MD PhD
Meet Saeid Shahraz, MD PhD
Assistant Professor of Medicine, Tufts Medical Center Institute for Clinical Research and Health Policy Studies
Department + Services
Institute for Clinical Research and Health Policy Studies, Predictive Analytics and Comparative Effectiveness (PACE) Center
Clinical Focus Areas
Identification and validation of complex medical conditions in large observational data sets for predictive models in outcome research
Publications + National Presentations
1. Shaharz S, Lagu T, Ritter GA, Liu X, Tompkins C. Use of Systematic Methods to Improve Disease Identification in Administrative Data: The Case of Severe Sepsis.Med Care. 2014 Aug 13. [Epub ahead of print]
2. Shahraz S, Forouzanfar MH, Sepanlou SG, Dicker D, Naghavi P, Pourmalek F,Mokdad A, Lozano R, Vos T, Asadi-Lari M, Sayyari AA, Murray CJ, Naghavi M. Population health and burden of disease profile of Iran among 20 countries in the region: from Afghanistan to Qatar and Lebanon. Arch Iran Med. 2014 May;17(5):336-42
3. Murray CJ, et al. (Shahraz S on alphabetical author list). US Burden of Disease Collaborators. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013 Aug 14;310(6):591-608.
4. Shahraz S, Bhalla K, Lozano R, Bartels D, Murray CJ. Improving the quality of road injury statistics by using regression models to redistribute ill-defined events. Inj Prev. 2013 Feb;19(1):1-5. doi: 10.1136/injuryprev-2011-040178. Epub 2012 Apr 13.
5. Shahraz S, Barzanjeh A, Bahari A, Nadery Y, Farzadfar F, Beyranvand MR, Stason WB. The completeness of medical records to assess quality of hospital care: the case of acute myocardial infarction in a district-level general hospital in Iran. Arch Iran Med. 2012 Oct;15(10):592-5
6. Vos T, et al. (Shahraz S on alphabetical author list). Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15;380(9859):2163-96.
7. Murray CJ, et al. (Shahraz S on alphabetical author list). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15;380(9859):2197-223.
8. Salomon JA, et al. (Shahraz S on alphabetical author list. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. Lancet. 2012 Dec 15;380(9859):2129-43.
9. Bhalla K, Harrison JE, Shahraz S, Fingerhut LA; Global Burden of Disease Injury Expert Group. Availability and quality of cause-of-death data for estimating the global burden of injuries. Bull World Health Organ. 2010 Nov 1;88(11):831-838C. Epub 2010 Jun 22
10. Bhalla K, Shahraz S, Bartels D, Abraham J. Methods for developing country level estimates of the incidence of deaths and non-fatal injuries from road traffic crashes. Int J Inj Contr Saf Promot. 2009 Dec;16(4):239-48.
Saeid Shahraz, MD, PhD, is an Assistant Professor at the Tufts Medical Center Institute for Clinical Research and Health Policy Studies, Predictive Analytics and Comparative Effectiveness (PACE) Center. Dr. Shahraz has a long track record of using observational data of different types (e.g. national population surveys, and medical claims/hospital discharge data) and applying an ensemble of quantitative analytics to predict different medical and epidemiological outcomes. As a research fellow at Harvard School of Public Health, he used to serve as quantitative data analyst and researcher for the Global Burden of Disease Project. Part of his research is systematic assessment of coded medical information. Dr. Shahraz completed his PhD at Heller School of Social Policy at Brandeis University, and his dissertation focused on identification and validation of sepsis cases in hospital discharge data. Dr. Shahraz’s prospective research interest at PACE is to apply computational and predictive models to big data (claims data and electronic medical records) to evaluate the treatment outcomes for patients with multimorbid (complex) conditions.
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