Individual Treatment Effects
Within the health care system there has always been a struggle--among researchers, medical professionals, health insurance companies, and others--to meet the needs of millions of people and still recognize the unique needs each person has by getting the right treatment to the right person at the right time. As health care spending has risen over the years, the effort to both improve the quality of care and get spending under control has led to a growing public and private investment in comparative effectiveness research (CER), sometimes called “patient-centered outcomes research” (PCOR).
The goal of CER is to “assess the benefits and harms of preventive, diagnostic, therapeutic, palliative, or health delivery system interventions to inform decision making, highlighting comparisons and outcomes that matter to people.” At its most basic definition, CER involves comparing one treatment option against another treatment option. Examples include surgery vs. watchful waiting; using a device vs. exercising; or drug vs. drug--there are any number of treatments that can be compared.
While this information is helpful for the “average” patient or population, it might not be relevant for every patient. Each person is unique thanks to a multitude of factors, such as racial and ethnic backgrounds, age, genetics, chronic conditions, disease severity, gender, environment, and even personal preferences when it comes to health treatments. These and other factors make patients different and affect how they may respond to a certain treatment. For these reasons, while the “average patient” may respond best to a particular treatment, some patients may experience little to no benefit from it, so other treatment options may be best for them. These differences in how patients respond to treatments are known as “heterogeneity,” or “individual treatment effects.”
Heterogeneity matters because if a medical professional is providing a patient care based on how the “average” person fared on that treatment, then that patient might not be getting the most ideal treatment. It also matters because most insurance companies design their policies to meet the needs of the majority of people, so those who may respond differently may have a more difficult time getting other treatment options covered. Many groups that represent patients are concerned that CER could be used to block or restrict access to treatments that help some, but not “average,” people.
Health care stakeholders further explored this issue during a daylong conference on November 30, 2012, "The Myth of Average: Why Individual Patient Differences Matter."