There are challenges when translating research to practice

Despite convincing results for many health care interventions, translating evidence from research into clinical practice is often challenging. Implementation barriers are myriad and complex, but a number may arise from core design issues. While real-world environments are clearly vital to the success of any intervention, many traditional research efforts are structured to remove them from the proverbial equation.

In studying the impact of a new medication, for instance, a group might rigorously apply statistical methods to ensure that study results reflect the effect of the medication rather than of patient, study site, or other characteristics.

This makes sense for clinical studies in which the primary goal is to assess unbiased efficacy and understand how the medication fares regardless of patient and environmental influences. However, alternative approaches are needed for applied, “downstream” purposes, such as embedding medication use within a comprehensive wellness program or evaluating the best ways to promote adherence.

For example, the development of statins for treating dyslipidemia represents a major advance in modern medicine. Multiple studies have shown that, if used consistently by the right patients, statins can have significant, positive effects on cardiovascular risk.

Despite this knowledge, clinicians have not been able to realize the full potential of statins, in part because real-world adherence rates are much lower than those reported in traditional research settings. Research protocols do not reflect real life, where other environmental factors, such as motivation and medication access, are also at play. In turn, adherence to statins, which has been reported at less than 50%, represents an important translational issue.

Two related focus areas within health services research, health care implementation science and delivery science, have emerged out of this tension. If more traditional research focuses on what is ideally or theoretically possible, implementation and delivery science try to understand and improve its real-world feasibility.

In the case of statins, for example, academic clinicians collaborated with a large commercial insurer to conduct a real-world, pragmatic study in which patients who had suffered a myocardial infarction were randomized to either usual care (in which they paid their usual copayments for medications, including statins) or free care (in which no copayments were required for statins or other medications). Based on the finding that removing copayments led to increased medication adherence, the insurer subsequently enacted that policy for all other beneficiaries, an example of successful implementation.

More recently, other physician-investigators have utilized behavioral economics principles to test the real-world effects of financial incentives on statin adherence among patients with high cardiovascular risk. By revealing that shared incentives (those that link financial rewards for patients and physicians together) are more effective than individual or no incentives in controlling lipid levels and adherence, their randomized study raises the potential for using payment strategies as part of new implementation and delivery solutions.

Certainly, more work is needed in both cases, and results must be interpreted with certain caveats. Unanswered questions and challenges also remain for many other clinical situations.

However, amid national emphasis on improving the value of health care, as well as recognition that many poor health outcomes result from poor execution and care delivery rather than insufficient medical knowledge, the emergence of this kind of health services work is important and relevant for clinical practice.

These examples emphasize what all clinicians know implicitly through their work: Delivery mechanisms and implementation approaches can be as important for health outcomes as disease pathology and pharmacology.

As changes in medical evidence and policy create unforeseeable challenges in the future, such examples also remind policymakers, researchers, and clinicians alike of an enduring truth: that better health can only emerge from health care that is both scientifically and operationally sound.