capacity and experience, and illustrating opportunities to improve care through capacity building. Emerging from these papers is the notion that although a number of diverse, innovative, and talented organizations are engaged in various aspects of this work, additional efforts are needed. Gains in efficiency are possible with improved coordination, prioritization, and attention to the range of methods that can be employed in CER.
Two papers provide a sense of the potential scope and scale of the necessary CER. Erin Holve and Patricia Pittman from AcademyHealth estimate that approximately 600 comparative effectiveness studies were ongoing in 2008, including head-to-head trials, pragmatic trials, observational studies, evidence syntheses, and modeling. Costs for these studies range broadly, but cluster according to study design. Challenges to develop the workforce needed for CER suggest the need for greater attention to infrastructure for training and funding researchers. Providing a sense of the overall need for comparative effectiveness studies, Douglas B. Kamerow from RTI International discusses the work of a stakeholder group to develop a prioritization process for CER topics and some possible criteria for prioritizing evidence needs. This process yielded 16 candidate research topics for a national inventory of priority CER questions. Possible pitfalls of such an evaluation and ranking process are discussed.
Three papers provide an overview of the work needed to support, develop, and synthesize research. Jesse A. Berlin and Paul E. Stang from Johnson & Johnson survey data resources for research, and discuss how appropriate use of data and creative uses of data collection mechanisms are crucial to help inform healthcare decision making. Given the described strengths and limitations of available data, current systems are primarily resources for the generation and strengthening of hypotheses. As the field transitions to electronic health records (EHRs) however, the value of these data could dramatically increase as targeted studies and data capture capabilities are built into existing medical care databases. Richard A. Justman, from the United Health Group, discusses the challenges of evidence synthesis and translation as highlighted in a recent Institute of Medicine (IOM) report (2008). Limitations of evidence synthesis and translation have led to gaps, duplications, and contradictions; and, key findings and recommendations from a recent IOM report provide guidance on infrastructure needs and options for systematic review and guideline development. Eugene H. Blackstone, Douglas B. Lenat, and Hemant Ishwaran from the Cleveland Clinic discuss five foundational methodologies that need to be refined or further developed to move from the current siloed, evidence-based medicine (EBM) to semantically integrated, information-based medicine and on to predictive personalized medicine—including reengineered randomized controlled trials (RCTs), approximate RCTs, semantically exploring disparate