Observational Studies in a Learning Health System Workshop Summary (2013) / Chapter Skim
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Appendix B: Workshop Agenda
Appendix B: Workshop Agenda
Pages 101-110
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From page 101... ...
in the generation of evidence to guide clinical and health policy decisions, with a focus on individual patient care, in a learning health system; 2. Consider concepts of OS design and analysis, emerging statistical methods, use of OSs to supplement evidence from experimental methods, identifying treatment heterogeneity, and providing effectiveness estimates tailored for individual patients; 3.
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9:45 am Engaging the issue of bias Moderator: Michael Lauer, National Heart, Lung, and Blood Institute Session format Ø o Introduction to issue Sebastian Schneeweiss, Harvard University
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o hat methods are best used to adjust for the changes W in treatment and clinical conditions among patients followed longitudinally? o hat are the implications of these promising W approaches for the use of observational study methods moving forward?
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12:30 pm Generalizing randomized controlled trial (RCT) results to broader populations Moderator: Harold Sox, Dartmouth College Session format Ø o Introduction to issue Robert Califf, Duke o Presentations: § eneralizing the right question G Miguel Hernán, Harvard University § sing observational studies to determine RCT U generalizability Eloise Kaizar, The Ohio State University o Respondents and panel discussion: § illiam Weintraub, Christiana Medical Center W § onstantine Frangakis, Johns Hopkins University C Q&A and open discussion Session questions: Ø o hat are the most cogent methodological and clinical W considerations in the use of observational study methods to test the external validity of findings from RCTs?
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2:15 pm Break 2:30 pm Detecting treatment effect heterogeneity Moderator: Richard Platt, Harvard Pilgrim Health Care Institute Session format Ø o Introduction to issue David Kent, Tufts University o Presentations: § omparative effectiveness of coronary artery bypass C grafting and percutaneous coronary intervention Mark Hlatky, Stanford University § dentification of effect heterogeneity using I instrumental variables Anirban Basu, University of Washington o Respondents and panel discussion: § ary Charlson, Cornell University M § ark Cullen, Stanford University M Q&A and open discussion
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o ow can longitudinal information on changes in H treatment categories and clinical condition be used to assess variations in treatment responses and individual patient decision making? § hat are the statistical methods for time-varying W changes in treatment (including cotherapies)
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o ow can we blend predictive models, which can H predict impact of treatment choices, and causal modeling, that compare predictions under different treatments? 10:45 am Break
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o hat are critical next steps in disseminating W information on new methods to increase their appropriate use? 12:15 pm Summary and next steps Comments from the Chairs Joe Selby, Patient-Centered Outcomes Research Institute Ralph Horwitz, GlaxoSmithKline Comments and thanks from the IOM Michael McGinnis, IOM 12:45 pm Adjourn
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Normand, Harvard University Richard Platt, Harvard Pilgrim Health Care Institute Burton H Singer, University of Florida Jean R
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