Individual Treatment Effects: Implications for Research, Clinical Practice, and Policy
This research outlines a framework and policy considerations to help health care stakeholders understand when it is important take patients’ individual treatment responses into account when making treatment, coverage and policy decisions.
Increased funding for comparative effectiveness research (CER) has sharpened the interest in learning what works best, for whom, and under what specific clinical circumstances. The goal of CER is to provide patients, payers, clinicians and policymakers with information to assist them in making the best decisions about treatment options. Because not all patients respond in the same way, research findings, treatment decisions, clinical guidelines or coverage policies applied in a “one-size-fits-all” manner based upon the population “average” response may lead to less than ideal health outcomes.
According to the research, four factors were identified that indicate when it may be inappropriate to narrow treatment choices:
- Consequences of treatment choice are high: There are more significant consequences associated with delaying the optimal treatment choices for some conditions than others. For example, a person suffering from hay fever may try several successive treatments before finding the right one, with no long-term impact, while a person facing acute organ failure may not have the luxury of time or the disease may progress irreversibly while other alternatives are tried.
- Patient diversity exists: Patients with the same disease often vary in the symptoms they experience. For example, some patients with depression may have sadness, insomnia, or lack of interest in daily activities, whereas others also may have anxiety and agitation.
- Treatment response is independent of other treatments: The similarity between a patient’s likely responses to the available treatments for a condition (level of “treatment independence”) may vary. Some patients may be very likely to have consistent responses to other treatments, but in other conditions response may vary even when treatments belong to the same or different classes of medicines.
- Patient preferences vary: Dosing, tolerance of particular side effects, willingness to make necessary behavioral changes and other physical and lifestyle factors all can impact the suitability of a particular treatment regimen for an individual patient.
In addition to understanding when these differences are clinically important, the study also outlines policy recommendations that can help to ensure that the right treatment is delivered to the right patient:
- Researchers should conduct studies to better understand when, why and how much individual treatment differences matter. When patient response varies, researchers should directly compare treatment alternatives in the same patients. To understand when and why individual patients respond differently, researchers should pre-specify, collect and report individual patient characteristics and patient subgroups in their studies. Additional funding is needed for research to understand the impact of patient preferences on clinical and economic outcomes.
- Payers should consider flexible coverage and reimbursement policies when individuals differ in their treatment response. When treatment response varies across patients, more flexible and broader coverage and reimbursement is needed. In addition, patients who differ from the population “average” due to their biology or prior response to treatment alternatives should not be required to pay higher out-of-pocket copayments.
- Providers should ensure that clinical guidelines and patient care incorporate when, how and why individual patient treatment effects matter. Clinical guidelines and quality measures should take individual treatment effects into account. Funding is needed for research and tools to help providers identify which treatments work best for “similar” patients, and for training to enhance provider-patient communication about an individual patient’s preferences and potential for benefits and risks. Mobile health (mhealth) and other systems can increase the knowledge available to providers and allow them to determine when alternative treatments are needed.