This chapter addresses strategies for selecting variables for adjustment in nonexperimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network relating treatment to outcome. While selection approaches should be based on an understanding of the causal network representing the common cause pathways between treatment and outcome, the true causal netwo...

There is an increasing amount of clinical data in operational electronic health record (EHR) systems. Such data provide substantial opportunities for their re-use for many purposes, including comparative effectiveness research (CER). In a previous paper, we identified a number of caveats related to the use of such data, noting that they may be inaccurate, incomplete, transformed in ways that un...

Treatment effects, especially when comparing two or more therapeutic alternatives as in comparative effectiveness research, are likely to be heterogeneous across age, gender, co-morbidities and co-medications. Propensity scores (PSs), an alternative to multivariable outcome models to control for measured confounding, have specific advantages in the presence of heterogeneous treatment effects. I...

With the ongoing debate over health care reform in the United States, public health and policy makers have paid growing attention to the need for comparative effectiveness research (CER). Recent allocation of federal funds for CER represents a significant move toward increased evidence-based practice and better-informed allocation of constrained health care resources; however, there is also hea...

The United States is undertaking a major expansion of comparative effectiveness research, with the potential to achieve systemwide improvements in health care quality, outcomes, and resource allocation. However, to achieve these improvements in children's health and health care, comparative effectiveness research needs to be targeted, designed, conducted, and reported in ways that are responsiv...

Comparative effectiveness research (CER) using observational data requires informatics methods for the extraction, standardization, sharing, and integration of data derived from a variety of electronic sources. In the Oncoshare project, we have developed such methods as part of a collaborative multi-institutional CER study of patterns, predictors, and outcome of breast cancer care. In this pape...

BACKGROUND There is a need for more Comparative Effectiveness Research (CER) to strengthen the evidence base for clinical and policy decision-making. Effectiveness Guidance Documents (EGD) are targeted to clinical researchers. The aim of this EGD is to provide specific recommendations for the design of prospective acupuncture studies to support optimal use of resources for generating evidence t...

Comparative effectiveness research (CER) can make important contributions to the transformation of US health care by filling gaps left by tightly controlled clinical trials. However, without comprehensive and comparable data that reflect the diversity of the US health-care system, CER's value will be diminished. We document the limits of observational CER by examining the age at diagnosis, dise...

OBJECTIVES We analyzed the extent to which comparative effectiveness research (CER) organizations share terms for designs, analyzed coverage of CER designs in Medical Subject Headings (MeSH) and Emtree, and explored whether scientists use CER design terms. METHODS We developed local terminologies (LTs) and a CER design terminology by extracting terms in documents from five organizations. We d...

NC Med J May/June 2010, Volume 71, Number 3 developed, which involved strengthening the compressed bone through injection of cement. Case series studies that were restricted to a before-after comparison of patient outcomes demonstrated that they felt much better after the injection. Over 1,000 patients per year received this treatment in North Carolina. It was not until the summer of 2009 that ...