Meghan Dierks, MD, leads research activities in Clinical Systems Analysis, Risk Analysis, Decision Analysis, and Macroergonomics. This work is highly cross-disciplinary, applying analytical and theoretical principles from systems engineering, computer science, cognitive science, and decision theory to understand the relationships between clinical risk, performance, and finances in complex socio-technical clinical systems. This research uses modeling and simulation to explore the dynamic aspects of risk: how the probability of specific outcomes, both favorable and adverse, varies as a function of complex, time-dependent sequences of events and resource inter-dependencies. Research has been supported through NIH, AHRQ, and philanthropic foundation grants and contracts. She has researched value-based health care and clinical ‘system’ performance to incorporate allocative efficiency as an outcome – the optimal use of conventional and alternative health service resources to achieve specific changes in health states. The output of this research is new predictive (what will happen?) and prescriptive (what should be done?) models of risk based on the properties of the clinical and policy environments. She has expertise in regulatory issues relating to health information technology. She has developed a framework for conducting prospective risk assessments of healthcare IT based on design complexity and implementation of design controls and for conducting effective post-market surveillance on software-based healthcare technology. She has performed policy analysis, evaluating the potential impact of regulation on safety, compliance, interoperability, and innovation. She has worked with the FDA to develop policy and a research agenda to increase the knowledge base in this area. One major challenge is modulating the regulatory strategy to promote appropriate risk mitigation and management strategies for healthcare information technology but not impede innovation.