The high-dimensional propensity score (hdPS) algorithm was proposed for automation of confounding adjustment in problems involving large healthcare databases. It has been evaluated in comparative effectiveness research (CER) with point treatments to handle baseline confounding through matching or covariance adjustment on the hdPS. In observational studies with time-varying interventions, such h...

A PPROXIMATELY half of all medical care provided in the United States is based on insufficient scientific evidence and may even be of “uncertain or questionable value.” This realization has spurred interest and extensive government funding in comparative effectiveness research (CER) with the ultimate goal to improve the effectiveness, efficacy, and efficiency of health care. To date, few initia...

The need to focus healthcare expenditures on innovative and sustainable health systems that efficiently use existing effective therapies are the major drivers stimulating Comparative Effectiveness Research (CER) across the globe. Lack of adequate access and high cost of essential medicines and technologies in many countries increases morbidity and mortality and cost of care that forces people a...

Comparative effectiveness research (CER) is one of the Patient Protection and Affordable Care Act's significant initiatives that aims to improve treatment outcomes and lower health care costs. This article takes CER a step further and suggests a novel clinical application for it. The article proposes the development of a national framework to enable physicians to rapidly perform, through a comp...

Comparative effectiveness research (CER) is defined by the Institute of Medicine as "the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care." The goal of CER is to provide timely, useful evidence to healthcare decision makers including physicians, patien...

BACKGROUND A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising pat...

BACKGROUND Patient registry data serves an increasing role in drug safety and comparative effectiveness research, but registry databases often do not contain confounder information measured at the same time that treatments begin. This study evaluated a set of approaches for estimating confounder values at treatment initiation using actual data from a rheumatoid arthritis (RA) registry to examin...

OBJECTIVES Our objective was to gather perspectives from payers on how comparative effectiveness research (CER) in the United States and relative effectiveness (RE) research in Europe will impact evidentiary standards for access decisions of new drugs by 2020. METHODS We conducted semi-structured interviews with fourteen senior officials representing public and private payers, health technolo...

BACKGROUND There is a need for more Comparative Effectiveness Research (CER) on Chinese medicine (CM) to inform clinical and policy decision-making. This document aims to provide consensus advice for the design of CER trials on CM for researchers. It broadly aims to ensure more adequate design and optimal use of resources in generating evidence for CM to inform stakeholder decision-making. ME...

The widespread adoption of electronic medical records means there are now vast data resources available for comparative effectiveness research (CER). In concert with conventional randomized controlled trials, CER holds great promise for advancing our understanding of how different therapeutic treatments yield different health outcomes in different settings and with different populations. But in...