This special focus issue on research data networks starts with a collection of articles describing a large initiative in the US that will use electronic health record data for patient-centered outcomes research in a privacy-preserving manner. This type of research will include observational and interventional studies. PCORnet, funded by the Patient-Centered Outcomes Research Institute (PCORI), leverages investments of several agencies such as the NIH, AHRQ, and FDA, as well as institutional support from healthcare systems to build a ‘network-of-networks’ aimed at helping researchers answer questions that matter most to patients and their caregivers.
An editorial by leaders of the NIH (See page 576) embodies the excitement that has permeated the biomedical science, health services research, and informatics communities around the big challenge of connecting highly diverse systems into a national network. Taken together, the 11 clinical data research networks (CDRNs) and the 18 patient-powered research networks (PPRNs) will have the potential to analyze de-identified data on over 100 million unique individuals located in all US states and territories.
The PCORnet program is introduced by the PCORI leadership and associated coordinating center members (See page 578), and each of the 11 CDRNs based on health systems is described in a brief communication (See pages 587, 591, 596, 602, 607, 612, 615, 621, 627, 633, 637). The participating health systems will contribute their infrastructure, expertise, and processes to run pragmatic trials and establish cohorts that can be followed over time for comparative effectiveness research.
PPRNs are another critical component of PCORnet. An article written by a consortium of PPRN and PCORI leaders (See page 583) summarizes the main characteristics of networks that originate from patient groups. The diversity of PPRNs is impressive: from networks that focus on rare diseases to ones that focus on several genetic disorders to those that focus on common conditions. These networks represent a bottom-up approach to organizing patient-reported outcomes, establishing a mechanism so that patients can actively participate in research, and posing questions that matter to patients. Several other articles address different aspects of data quality and organization (See pages 642, 692, 720, 758); health information networks (See pages 714, 650, 671, 730, 699); and personal health records, portals, and patient engagement activities (See pages 657, 664, 679, 687, 725, 737, 742, 751, 707). They help describe the context for the development and implementation of related initiatives.
Several informatics leaders are directly involved in PCORnet, and the whole informatics community can participate in this effort. The collective knowledge of informatics experts has the potential to put into action many of the best practices in data modeling, privacy technology, distributed computing, software and social engineering, and data sharing policies that JAMIA has been publishing for a long time. These best practices result from investments from many agencies that were able to recognize the value of big data well before the concept became a national priority.
Large initiatives such as PCORnet also pose some challenges: the ability to develop and combine different solutions that are suited for different health systems will be highly dependent on striking the right balance between flexibility and homogeneity. A one-size-fits-all approach is not likely to generalize beyond a few medical centers, and accommodation of every possible type of data model and technology would delay progress. The challenge is not just technological: many different data models, network software, analysis tools, and policies exist and every institutional prefers to keep using the ones already implemented. However, these models and tools do not cover some new types of data and new sharing models, and hence there are important gaps that need to be filled.
We are facing important challenges in achieving true interoperability and developing a path that accommodates institutional preferences without losing sight of the common goal of using data to develop knowledge that helps promote health. The informatics community can be an important partner to patients, clinicians, administrators, and researchers in health services, behavioral, and biomedical science. Due to HITECH, we now finally have EHRs implemented in most healthcare settings in the US. It is important to synergize efforts to avoid duplication and waste of resources as we develop new ways to use these data for research in a way that respects patient privacy.