Health IT as a Driver for Advancing Health Research

Teresa Zayas Cabán, PhD | October 23, 2020

Successful health research hinges on the quality of the data used to advance discovery and needed health IT functionality. Electronic health data are increasingly available and can be a significant boon for the medical research community. Coupled with ubiquitous use of consumer and patient health technologies and increasing prevalence of application programming interfaces, or APIs, there is potential to expand existing data sources for research.

However, challenges remain to using electronic health data and health IT in research, including limited access to data, data quality issues, inconsistent data collection methods, and limited system functionality. To make data and health IT systems more useful to researchers, it is critical that electronic health data are captured and structured in such a way that they are findable, accessible, interoperable, and reusable.  And, as pointed out by Columbia University’s Dr. Suzanne Bakken in her recent JAMIA editorial, “scalable tools and [a] standards-based infrastructure” are needed to advance medical discovery and improve health outcomes.

Building Health IT for Research

There are several opportunities for stakeholders across the health IT ecosystem to better align electronic health data and health IT systems with modern research needs through changes to policy and technology. To realize these opportunities, progress could be made on establishing or strengthening five key capability areas:

  1. Data Quality and Accessibility: Health IT systems should ensure researchers are able to find, access, match, and utilize heath data as effortlessly as possible.
  2. Adaptability: Modular architectures and robust configuration tools are needed to address new data definitions, updated software versions, emerging standards, new tests and medical procedures, and varied medical and consumer data.
  3. Functionality: Research-specific functionality, such as operational dashboards that could identify opportunities to enroll patients in trials, needs to be fully incorporated into the IT architecture.
  4. Integration: Effective patient and caregiver engagement through health IT is needed to support research.
  5. Application: Not only can we use health IT to capture health data for research; we can use it to insert research and evidence directly into clinical practice to improve care through improved data visualization and knowledge sharing.

Several ambitious initiatives are creating large, population-based datasets for a million or more individuals, such as the Veterans Health Administration’s Million Veteran Program and the National Institutes of Health’s All of Us Research Program. However, improvements in the design of health IT and the data it produces are needed to fully leverage these datasets for research purposes and achieve these programs’ bold goals.

To this end, ONC recently led the development of National Health IT Priorities for Research: A Policy and Development Agenda, which outlines nine priorities, including concrete steps that stakeholders could take to better align health IT infrastructure to support both clinical and research ecosystems. These steps are vital to ensuring improved access to and use of data for research, greater engagement of patients in clinical trials and research activities, and improvements to data collection and fitness for use in research to produce new knowledge. ONC also recently released a background report that informed the development of the Policy and Development Agenda. The background report provides detailed information about health IT infrastructure needs and gaps that impede research.

If you would like to read more about how to better align electronic health data and health IT systems with research needs, leverage research results, and increase data access to support public health and treatment, please refer to my most recent article in JAMIA Open entitled, “Opportunities for the use of health information technology to support research.”