Abstract Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic.

As a direct benefit of the Health Care Reform Act (2010), concerted effort has been deployed to define and characterize the process by which the best available evidence for diagnosis or treatment intervention prognosis can be obtained. The science of research synthesis in health care has established the systematic research protocol by which randomized clinical trials and other clinical studies must be reviewed and compared for the level and quality of the evidence presented, as well as the consensus of the best available evidence synthesized and shared. This process of systematic review yields a reliable and valid approach in comparing different interventions and strategies to prevent, diagnose, treat and monitor health conditions in terms of efficacy, and or of effectiveness. The resulting bioinformation outcome of comparative effectiveness and efficacy research review of the available clinical data is expressed as a consensus of the best available evidence, which finds its way in evidence-based clinical practice guidelines, standards of care and eventually, in policies: hence, the acronym CEERAP (comparative effectiveness and efficacy review and policy). The methodological and the procedural criteria that determine and regulate the public reporting dissemination of this sort of bioinformation, and the extent of benefit to the patient's health literacy, which have remained a bit more elusive to this date, are investigated and discussed in this paper.

Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic.