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Recently, PCD published a longer, related article, “How Do You Know Which Health Care Effectiveness Research You Can Trust? A Guide for the Perplexed,” that was translational in nature. The article used simple graphs and easy-to-understand text—in five case studies—to illustrate how powerful biases, combined with weak study designs that cannot control for them, can yield untrustworthy research on several widespread interventions: influenza vaccination policy, health information technology, drug safety, prevention of childhood obesity and hospital safety (“mortality reduction”)\udprograms. Since this was not a formal methods paper, the target audiences were policy makers, journalists, trainees, and the public. The primary goal was to understand how weak or strong study designs are likely to fail or succeed in controlling for these pervasive biases. At the start of that article, we promised to add to these case examples of common biases and research designs to show why “caution is needed in understanding and accepting the results of research that may have profound and long-lasting effects on health policy and clinical practice.” In this sixth case study, the authors revisit one of the most common and virulent biases, threats of\udhistory. Studies can mislead policymakers and clinicians because they fail to control for history, which represents pre-existing or co-occurring changes in study outcomes that were happening with or without the intervention. The policy in this case, pay-for-performance (PfP, see below), is extremely sensitive to this powerful bias because medical practice is always changing as a result of factors unrelated to a\udpolicy, such as widespread media or national guidelines supporting a life-saving treatment, e.g., beta blockers for acute MI (1). Without investigating and visualizing outcomes over time before and after a policy or intervention, it is likely that the investigators will attribute such ongoing changes to “effects” of the quality improvement policy, resulting in millions of dollars of waste implementing ineffective PfP policies worldwide

History Bias, Study Design, and the Unfulfilled Promise of Pay-for-Performance Policies in Health Care