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Comparative Effectiveness Research (CER)
The Need for CER
The American Recovery and Reinvestment Act of 2009 (ARRA) appropriated $1.1 billion for CER. The reasons for this investment are clear: Even with the large number of results of clinical trials and biomedical studies that are published every week, there is often insufficient evidence for doctors and patients to make informed judgments regarding the diagnosis and optimal treatment of a disease. In some cases, this happens because the right evidence to support personalized, patient-centered decisions is unavailable. In other cases, the rapid pace of drug discovery and the profusion of drugs, technologies, and tests marketed directly to patients make informed decisions harder. For drugs, clinical trials often compare a new drug to a placebo because this type of comparison is a low hurdle to pass. However, it would be better to conduct high-quality CER studies that directly compare clinically plausible choices and expedite the translation of best therapies into practice. Yet there is a definite lack of these studies. Therefore, improving the speed with which various diagnostic and treatment strategies can be evaluated and compared and training investigators to conduct such studies are important steps in improving the quality, effectiveness, and efficiency of health care.
CER at the University of Pittsburgh
The Institute for Clinical Research Education (ICRE) was created by the University of Pittsburgh to develop and manage clinical and translational research training for the six schools of the health sciences: the School of Medicine, School of Nursing, School of Dental Medicine, Graduate School of Public Health, School of Pharmacy, and School of Health and Rehabilitation Sciences. The ICRE is the home for all educational activities within the University of Pittsburgh Clinical and Translational Science Institute (CTSI). The Research Education and Career Development Core of the CTSI and ICRE currently supports extensive educational programs in the basic methods necessary to conduct high-quality CER, including clinical trial design, meta-analysis, decision and cost-effectiveness modeling, and large database analysis.