Health Affairs

There is a growing consensus that the regulatory system for research is in need of reform. Established 21 years ago by the Common Rule, it has functioned via a rigorous environment to assure that risk in research is dealt with and transparency maintained.

The trigger for these regulations is a definition of research as a “systematic investigation…designed to develop or contribute to “generalizable knowledge.” When this definition is satisfied, an intensive set of requirements ensues including review, approval, and continued oversight by an Institutional Review Board (IRB); reporting requirements;, the necessity for informed consent (often highly complex); and other administrative components. If projects are not “generalizable,” (e.g., local hospital programmatic or quality review), they fall strictly under healthcare system purview rather than under Common Rule regulatory oversight.

The current system has a strong moral imperative and has been critical to mitigating risk for research subjects and providing transparency. However, it is burdensome and fails to take into account the considerable progress made in both the research and clinical enterprises over the last few decades: in research, technological advances in generating data on routine care, and in healthcare, much more stringent oversight.

A goal of Twenty-First Century Healthcare is to establish and enhance the Learning Healthcare System (LHS). As discussed in numerous forums, journals, and social media, the LHS is viewed as critical to improving healthcare. Fundamentally, the LHS converts data about care and operations into knowledge that it translates into evidence-based clinical practice and health system change. In so doing, the LHS utilizes as vehicles health information technology, databases, the electronic healthcare record (EHR) and, importantly, a research infrastructure. The continuing narrow evidence base for clinical care combined with the need for substantial amounts of data to fill large evidentiary gaps, among other factors, have fostered the LHS concept.

To assure the utility and validity of data converted and then translated into improvements by the LHS, we need rigorous research approaches that are also efficient. Research is defined as “a systematic investigation…designed to develop or contribute to generalizable knowledge.” At present, evidentiary inputs to the LHS range from activities not generally considered research (e.g., programmatic and quality improvement evaluations) to various forms of research that are sufficiently rigorous, but for various reasons, can be difficult to employ and translate into the routine workings of the LHS.

For example, the randomized clinical trial (RCT) — considered the cornerstone, or “gold standard” methodology — provides the best data, but by its very nature, is separate from the workings of clinical care in a given healthcare system (HCS). Instead, the RCT functions in an alternate environment precisely controlled for the approach’s particulars. Further, the RCT is costly and time-consuming, and its rather narrow entry criteria may diminish its ability to be generalized to routine patients (e.g., those with comorbidities, or those outside of the entry criteria of age and severity).

This year marks the fiftieth anniversary of Watson and Crick (and Wilkins) being named Nobel Prize recipients for discovering DNA, the genetic code. In the half century since, there has been an exponential growth of knowledge and accomplishment based on their findings. More recently, a confluence of scientific and technical advances have made possible vast progress in our understanding of human disease, its diagnosis, and the most effective treatment(s). Among these advances are genetic testing, high performance computing platforms, and the electronic health record (EHR), which together offer the possibility of clinically rich databases that link genetic information to treatment outcomes.

These and other advances have made it clear that the genetic predispositions to adult diseases are in many cases extremely complex. In its early phases, human genetics focused on single genes for single diseases that generally occurred in childhood; e.g., Tay-Sachs disease. The genomics of adult diseases—such as coronary heart disease—are associated with complexity resulting from multigene interactions and strong environmental influences (e.g., lifestyle and exposures), that may in some cases result in organ-specific “epigenetic” changes that modify DNA.

A prominent example of how these various factors come together can be seen by looking at diabetes. Having a gene associated with diabetes may modestly increase one’s chances of developing this condition from—let us say—6 to 12 percent. But whether diabetes actually results is influenced by additional factors, such as the sequences of other genes, environmental influences (such as diet and exercise), and age.