Comparative Effectiveness Methods Series – Summer 2013

Comparative effective research (CER) is now a standard method of comparing tests and treatments. AHRQ, NIH and now PCORI are all major funders of CER, as well as the related concept of Patient-Centered Outcomes Research (PCOR). UNC has developed substantial expertise in both CER research and training. Historically, CER has involved comparisons of two active clinical treatments, often medications or procedures. Often these were comparisons of two medications in head-to-head trials or use of analytic procedures to simulate head-to-head comparisons. As an example, comparison of one antidepressant with another can be helpful in the decision-making of patients and providers. Over the past 15 years, advances in methods have substantially assisted CER research. These advances include work in areas such as meta-analysis, pragmatic randomized clinical trials, and ways to address selection bias such as new user designs, propensity scores, and use of instrumental variables.

Health services research (HSR) often examines methods of delivering services to patients. Increasingly, HSR studies involve interventions to alter the health care system with the goals of enhancing quality and access to care, while controlling the costs of care delivery. Implementation of the Affordable Care Act will accelerate this process. Interventions including care management, practice organization, workforce composition, and modifications of the payment system will need to be tested. Organizing care delivery so as to improve quality while avoiding major cost increases will be the major challenge of ACA implementation. How can CER methods be adapted to address these critical questions?

The Cecil G. Sheps Center will host a series of short work sessions to discuss these issues. For seminar dates and times go to our events page. We will post the Pubmed links to 1-2 articles prior to each session to get the discussion started. Each session will be facilitated by an experienced faculty member. Scheduled sessions will occur monthly, on Fridays from 9:00–10:00 am in the Rosenfeld Conference Room (3 rd floor of the Sheps Center – room 306), 725 Martin Luther King, Jr. Blvd.

Friday September 13, 2013

Alternatives to the Conventional RCT



Michael Kosorok, Ph.D., Professor & Chairman, Department of Biostatistics

Peter Thall, Ph.D., Professor, Biostatistics, The University of Texas MD Anderson Cancer Center

Zhao Y, Zeng D, Socinski MA, Kosorok MR. Reinforcement learning strategies for clinical trials in nonsmall cell lung cancer. Biometrics. 2011 Dec;67(4):1422-33. doi: 10.1111/j.1541-0420.2011.01572.x. Epub 2011 Mar 8.2.

Estey EH, Thall PF.New designs for phase 2 clinical trials. Blood. 2003 Jul 15;102(2):442-8. Epub 2003 Jan 30.

Thall PF, Wathen JK. Practical Bayesian adaptive randomisation in clinical trials.  Eur J Cancer. 2007 Mar;43(5):859-66. Epub 2007 Feb 16.

Thall PF, Wathen JK. Bayesian designs to account for patient heterogeneity in phase II clinical trials. Curr Opin Oncol. 2008 Jul;20(4):407-11. doi: 10.1097/CCO.0b013e328302163c.

Ren S, Davidian M, George SL, Goldberg RM, Wright FA, Tsiatis AA, Kosorok MR. Research Methods for Clinical Trials in Personalized Medicine: A Systematic Review. The University of North Carolina at Chapel Hill Department of Biostatistics Technical Report Series. Working Paper 25.

Friday August 23, 2013

Comparing Health Care Facilities

Faculty Expert: Alan Brookhart, PhD, Associate Professor, Epidemiology, Gillings Global School of Public Health

M. Alan Brookhart; Sebastian Schneeweiss; Jerry Avorn; et al. Comparative Mortality Risk of Anemia Management. JAMA. 2010;303(9):857-864 (doi:10.1001/jama.2010.206)

Sebastian Schneeweiss, M.D., Sc.D., John D. Seeger, Pharm.D., Dr.P.H., Joan Landon, M.P.H., and Alexander M. Walker, M.D., Dr.P.H. Aprotinin during Coronary-Artery Bypass Grafting and Risk of Death. N Engl J Med 2008; 358:771-783

M. Alan Brookhart, Sebastian Schneeweiss Preference-based instrumental variable methods for the estimation of treatment effects: assessing validity and interpreting results.  Int J Biostat. Author manuscript; available in PMC 2009 August 3. Published in final edited form as: Int J Biostat. 2007; 3(1): 14.

Philip S. Wang, M.D., Dr.P.H., Sebastian Schneeweiss, M.D., Jerry Avorn, M.D., Michael A. Fischer, M.D., Helen Mogun, M.S., Daniel H. Solomon, M.D., M.P.H., and M. Alan Brookhart, Ph.D. Risk of Death in Elderly Users of Conventional vs. Atypical Antipsychotic Medications.  N Engl J Med 2005; 353:2335-2341

Friday July 19, 2013

Some U(0,1) Thoughts on Measuring Systems and Facilities

Faculty Expert: Mark Holmes, PhD, Health Policy and Management, Gillings Global School of Public Health

Friday, June 14, 2013

Comparing Providers and Provider Teams

Faculty Expert: Darren DeWalt, MD, MPH, Associate Professor, Department of Medicine

Carter BL, Rogers M, Daly J, Zheng S, James PA. The potency of team-based care interventions for hypertension: A meta-analysis. Arch Int Med. 2009; 169(19):1748-1755.

Shah BR, Hux JE, Laupacis A, Zinman B, Zwarenstein M. Deficiencies in the quality of diabetes care: Comparing specialist with generalist care misses the point. J Gen Intern Med. 2007; 22(2): 275-9.

Friday, May 17, 2013

Comparing Epidodes of Care and Bundled Payment Approaches

Faculty Expert: Sally Stearns, PhD, Professor, Department of Health Policy & Management

Chambers JD, Weiner DE, Bliss SK, Neumann PJ. What can we learn from the U.S. expanded end-stage renal disease bundle? Health Policy. 2013;110(2-3):164-71.

Sood N, Huckfeldt PJ, Escarce JJ, Grabowski DC, Newhouse JP. Medicare’s bundled payment pilot for acute and postacute care: analysis and recommendations on where to begin. Health Aff (Millwood). 2011;30(9):1708-17.