The health care reform law is aimed at reshaping the health care landscape through the creation of many new regulations and regulatory entities including state health exchanges, rate reviews, the implementation of a federal medical loss ratio and rules concerning what benefits health plans must offer beneficiaries called “essential benefits,” just to name a few.
Included in this vast new landscape is the creation of the Patient-Centered Outcomes Research Institute (PCORI). And while PCORI is new, the issue it was created to address, comparative effectiveness research (CER), is not. In one form or another CER has been around for decades. What the new law does is give it a focus and level of funding never seen before in this country.
However, like much of the new law, it is not without controversy. CER conducted thoroughly and thoughtfully holds the promise of helping to inform health care providers about the best treatment for individual patients. Ill-advised and poorly conducted CER could actually lead to health care cost increases and worsen patient health outcomes.
The reason is fairly simple—specific drugs and treatments do not work for all people equally. Some respond to one treatment while others respond to another. Even within patient populations, individual patients will have varied preferences around what matters most to them. If CER is used to determine what works best on average, we may lose sight of what works best for individuals. This could lead to coverage and/or reimbursement decisions being made based on this information, then outcomes may not improve (they may decline) and costs may actually go up.
The reason for this is also simple—those patients who do not respond to the average treatment could end up costing more to treat if access is limited to other treatments that work better for them. Even if these patients are granted access to a second treatment, they likely will be forced to pay a higher copayment. For some patients, this could delay access to treatments that are deemed most effective for their condition.
We know of this risk due to two related studies funded by the National Pharmaceutical Council and published in the Journal of Health Economics and by the Manhattan Institute, which show “that product specific coverage policies may negatively impact health when they fail to account for patient-specific treatment effects.”*
In Manhattan Institute paper,** authors Dr. Tomas Philipson and Dr. Eric Sun write, CER “gives the patient, doctor, and payer hard information from thousands, or even millions of cases, saving them time and money that otherwise would be spent on a trial-and-error quest for the right treatment.”
However, the authors caution that "seeking the treatment that is most effective on average will not improve health or save money,” and explain that CER should be applied “as a tool for matching individual patients to the best treatments for those patients.”
They call out two reasons why CER as currently envisioned may not meet the hopes placed upon it to improve health and decrease costs:
- Differences: Individuals differ from one another and from population averages. The fact that a therapy is better on average for the whole patient population does not mean that it will be a better therapy for a large number of individual patients.
- Dependence: The likelihood that a patient who fails to respond to one therapy may not predict how he or she will respond to another. Dependence varies from illness to illness and from drug to drug but is often an important aspect of finding treatments that work. Reimbursement policies based upon the “average” patient or policies which refuse to reimburse for the “less” effective treatment are based on the assumption that failure with one treatment will predict failure with other treatments. A classic example of this fallacy is antipsychotics, where patients who fail to respond to one drug can often do well on another.
CER has significant potential for improving medical decision-making and, ultimately, overall health. However, CER must be conducted and implemented carefully and reflect information about patient-specific difference and treatment dependence effects if it is to be used by patients and providers to make the best possible clinical decisions. The current debate over health care and how to improve it has stressed a central point—higher quality care can lead to more efficient and precise medicine, leading to improved outcomes. CER can help the country down this path, but only if research is conducted appropriately and then put into practice, treating each patient as an individual, not an average.
* Basu, A; Jena, AB; Philipson, TJ. The impact of comparative effectiveness research on health and health care spending. Journal of Health Economics. June 1, 2011.
** Philipson, T; Sun, E. Blue pill or red pill: the limits of comparative effectiveness research. New York: Manhattan Institute. June 2011.