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January 19, 2011

Implications of the Principle of Question Propagation for Comparative-Effectiveness and “Data Mining” Research

Author Affiliations

Author Affiliations: University of Florida, Gainesville (Ms Djulbegovic); and Center for Evidence-based Medicine and Health Outcomes Research; Department of Medicine, University of South Florida; and Departments of Hematology and Health Outcomes and Behavior, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida (Dr Djulbegovic).

JAMA. 2011;305(3):298-299. doi:10.1001/jama.2010.2013

Recent legislation incorporated comparative-effectiveness research (CER) as a scientific mechanism to help improve health care.1 The law expresses particular interest in discovering which treatments work “in a real world setting” and encourages conduct of observational studies using data mining techniques of standardized electronic records.1,2 Ideally, CER will identify effective interventions in the subgroup of patients, since traditional randomized trials typically provide efficacy data for an “average” patient only.1,2 It is likely that the amount of observational research will increase significantly, especially studies involving data mining of large administrative databases and electronic medical records. However, epistemological arguments suggest that data mining efforts cannot provide definitive answers to the questions asked by the CER program. Rather, CER should be considered hypothesis-generating research aiming to inform future prospective studies that will invariably require new (and better) data collection.