Discover New Methods, Answer Patient-Centered Questions
The kinds of health questions you ask and the analytic methods you use to answer them have dramatically changed. Questions are now often patient-centered and the answers require rigorous analysis using ‘causal’ modeling techniques. At CIMPOD 2016, you will learn from internationally recognized causal methods experts and prominent stakeholder representatives how to choose the methods needed to answer your PCOR questions. On Day 1, we will address ‘Principles and Conceptual Framework for Selecting CI Methods,’ and on Day 2, we will address ‘Matching the Methods to the Question’ using ‘real world’ case studies.
Conference attendees will leave CIMPOD equipped with the knowledge and tools needed to produce and interpret high-quality research. Research that takes into account the important analytical concerns related to using observational data such as confounding and bias.
We invite clinicians, patient advocates, epidemiologists, statisticians and other stakeholders that have an interest in designing and analyzing PCOR studies. Come participate in the exchange of ideas, network with participants from various disciplines and organizations, and gain practical skills and understanding from the interactive two-day conference.
This work is supported through a Patient-Centered Outcomes Research Institute (PCORI) Engagement Award (865-MTPPI) and is organized by the Medical Technology and Practice Patterns Institute (MTPPI).
Medical Technology and Practice Patterns Institute (MTPPI) is a nonprofit organization established in 1986 to conduct comparative research on new and emerging health care technologies. MTPPI's research is directed toward improving patient outcomes by identifying optimal clinical guidelines and health care policies. With extensive investigator experience in the public and private sectors, MTPPI's staff designs, implements, and conducts a full range of health services research activities. We specialize in using available national, state and local administrative, survey or patient registry data to conduct 'real time', 'real world' studies that are both affordable and useful for decision making.