Abstract
Background/Aims The primary goal of comparative effectiveness research (CER) is to generate new evidence on the effectiveness, benefits, and harms of different treatments, diagnostics, and disease prevention methods under “real world” conditions. To accomplish this goal using data generated in the course of providing care, CER requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse care practices and data systems.
Methods To address the goals of CER, we built the CER Hub; a web-based platform for collaborative development and conduct of healthcare research studies using multi-institutional, comprehensive electronic medical record (EMR) data. The Hub provides informatics tools and methods for developing and applying study-specific processors of EMR data, enabling access to the entire clinical record (including text clinical notes) to answer study questions. These processors are developed on the Hub and then distributed out to participating study sites to enable efficient and accurate aggregation of study data, allowing pooling of standardized limited datasets for analysis of multi-institutional clinical data. As an Internet-based platform, the Hub provides support for collaborative design, development, and conduct of research studies that use electronic clinical data. The Hub provides investigator-initiated studies with capacity to address questions of interest to independent researchers and their organizations, while providing a mechanism for the knowledge gained to be built into subsequent, related research efforts.
Results To demonstrate the CER Hub, we established multiple research studies that involve six diverse health systems dispersed throughout the U.S. (including 3 HMORN sites), which utilize 3 distinct EMR systems. Each study developed, validated, and deployed a study-specific data processor to identify aspects of patient health and care services delivered to study patients, locally within their health system’s data processing environment. Aggregate data resulting from this process were then assembled at a central site for descriptive and outcomes analyses.
Conclusions The CER Hub provides a scalable method to generate evidence on fundamental questions in health and care delivery (including comparative effectiveness, epidemiology, health services, public health, quality and patient safety questions) with capacity to analyze large populations from multiple and diverse healthcare systems.
