Meeting the ACA Mandate to Build Data Capacity

The authorizing legislation1 for this work is in Section 937(f)--BUILDING DATA FOR RESEARCH.—

The Secretary shall provide for the coordination of relevant Federal health programs to build data capacity for comparative clinical effectiveness research, including the development and use of clinical registries and health outcomes research data networks, in order to develop and maintain a comprehensive, interoperable data network to collect, link, and analyze data on outcomes and effectiveness from multiple sources, including electronic health records.

Data capacity can be built via two approaches.

  1.  The first approach is the “development and use of clinical registries and health outcomes research data networks” as noted above. Examples of such  investments include the following:
    • Expanding Data Collection Infrastructure of the National Program of Cancer Registries for CER. The CDC received $20 million in ARRA funds in 2010 to support a multi-year project to enhance cancer registry infrastructure and to collect specific data to address CER questions. ARRA funding supported collection of detailed cancer treatment data — that cannot be obtained through claims or other existing electronic data sources — from cancer registries in 10 states that are part of the National Program of Cancer Registries. A combined set of these data from all 10 registries was made publicly available for analyses through the CDC’s National Center for Health Statistics Research Data Centers. $2.590 million of FY 2013 PCORTF funding was approved to build upon the ARRA-funded effort by: 1) augmenting a publicly available dataset for CER with additional longitudinal follow-up data on disease recurrence and vital status for colon, rectum, and breast cancer cases; and 2) enhancing software tools and methodology for managing and consolidating electronic data reported on a real-time basis from EHRs to registries to allow researchers to compare long-term outcomes from various treatments.
    • Strengthening and Expanding the Community Health Applied Research Network (CHARN). In 2010, HRSA received $10 million in ARRA CER funding to develop CHARN, a nationwide network of nineteen community health centers and five research organizations in ten states that built a CER infrastructure to benefit patients in underserved communities. CHARN is organized into four research nodes (RNs) and one data-coordinating center (DCC). Each RN consists of three or more health centers and one research university. CHARN’s infrastructure development activities included establishing data registries; training community-based providers in research methods and protocols; instituting research policies and study protocols; and conducting small pilot studies with data collected from the health centers. $2 million of FY 2013 PCORTF funding was awarded to HRSA to continue infrastructure development activities, including the RNs and DCC, a governance structure, and a web-based tool for research collaborations and additional data collection, and creation of a public-use patient data file for CER.
  2.  A second approach to building data capacity for CER is to enable interoperable data flows, linkage and analysis with the plethora of existing electronic clinical data resources.  This includes electronic health record systems in hospital and other care settings, in addition to Federal and private clinical data registries, claims data resources, and research data networks.  To do this, essential components (i.e., standards, services, policies, federal data access and governance structures) are needed to make these data more readily usable for research.   Examples of such investments include the following:
    • ONC’s Structured Data Capture (SDC) initiative facilitates CER by standardizing information collected for clinical purposes through an electronic health record (EHR) with information collected for research purposes. ONC is developing standards for the structure of common data elements that can be used to enable the incorporation of clinical data collected in an EHR system into electronic case report forms (eCRF) used in clinical research. With services utilizing the new standards, existing data from an EHR can “pre-populate” the eCRF. For example, a researcher trying to determine the effect of a new treatment on blood pressure would be able to obtain the patient’s recent blood pressure readings via a service that would automatically populate the eCRF from previously entered EHR data.
    • The Data Access Framework (DAF) is another PCORTF-funded ONC initiative that is creating the standards necessary to enable health providers and researchers with a specific question to easily access and extract information in EHRs, quickly and at a lower cost. Establishment and adoption of both the SDC and DAF national standards will facilitate data collection and data access for CER in a cost-effective and scalable manner.
    • CMS’ Chronic Condition Warehouse (CCW) and Virtual Research Data Center (VRDC). The CCW is a research database designed to make Medicare, Medicaid, and Part D Prescription Drug Event data more readily available to researchers to enable analyses to improve the quality of care and reduce costs and utilization. The VRDC allows researchers to access and analyze data stored on CMS’s servers, rather than physically receiving a copy of the data on portable media. This environment enables researcher access to federal data more quickly and cost effectively than before, while providing for greater security and protections. $3 million of FY2012 and FY2013 PCORTF funding supports researcher access to the VRDC and provides maintenance support for CMS’ Chronic Condition Warehouse.

1 The Patient Protection and Affordable Care Act (ACA) of 2010 amended the Public Health Service Act by adding Section 937: Dissemination and Building Capacity for Research; subsection (f) is the authorizing legislation.м