Clinical and public health research has generated tremendous knowledge on disease prevention, diagnosis, and treatment. However, there is a pressing need to not only generate but also synthesize evidence to inform us on what works best and how to get the intervention to the people who will benefit most.
Comparative effectiveness and outcomes research (CEOR) addresses these issues by identifying interventions most effective for specific patient groups. CEOR informs the practices of healthcare providers and policymakers to make evidence-based resource allocation decisions. It has been identified as a national priority by the federal government.
Despite the pressing need for highly trained professionals in this area, few programs for CEOR exist. Our new Certificate helps to fill this void by providing students with the essential skills needed to measure and compare the expected effectiveness, risks, and costs from both clinical and public health interventions—crucial skills at a time of rising costs and tighter budgets.
Graduates may go on to positions in academia, government, research organizations/think tanks as well as the bio-pharma sector—all of which seek professionals with this valued skill set.
Comparative Effectiveness and Outcomes Research is open to Columbia MPH students in:
Applicant to this certificate must score in the 75th percentile or higher on the Quantitative Reasoning Section of the GRE. Students who are interested in applying to this certificate after matriculation will submit a statement of interest describing how this certificate matches their professional and academic goals.
Visit the Certificates Database to learn more about core and credit requirements.
Analysis of Large Scale Data Sets
This is an applied, hands-on course designed to provide an introduction to several major health data sets and to guide students in processing and analyzing these data. It is designed to complement skills learned in other methods courses and prepare students to advance in the work force or perform independent research for a doctoral program. Students must have taken Biostatistics and have familiarity with Stata, but students comfortable with other software languages, such as SAS or SPSS, or students willing to take a NetCourse before the course begins may enroll.
Decision Analysis for Clinical and Public Health Practices
This course is designed to provide an introduction to the methods and growing range of applications of decision analysis and cost-effectiveness analysis in health care technology assessment, medical decision making, and health resource allocation.