Think about the last time you visited a medical office. Even at a specialist’s office, chances are that each person waiting for his or her name to be called has a different health concern, different background and different genetic history. Considering each person’s unique health characteristics, it’s no wonder that two people who have the same medical condition may have very different reactions to a medication. We’ve recognized for years the existence of these individual patient reactions – a phenomenon known as heterogeneity.
The topic is gaining attention as state policymakers develop the marketplaces where uninsured and underinsured people will buy insurance under health care reform. Policymakers are preparing blueprints for these marketplaces, known as state health insurance exchanges, for submission to the Department of Health and Human Services by Nov. 16. Under one design option, the state health insurance exchanges would cover only one drug to treat a given condition. By pushing a standardized treatment for every patient, this model could lead to poor outcomes for the patients who see limited or no benefit from that particular drug. States are wrestling with this issue as they decide whether to cover a single drug, several, or the full range of medications for a health condition.
The state health insurance exchange discussion is illuminating some complexities involved in comparative effectiveness research (CER). By identifying the most effective treatment options, CER is intended to improve outcomes for patients and rein in soaring health care costs. That’s why the Patient-Centered Outcomes Research Institute (PCORI) is investing $400 million to $500 million a year to support CER studies.
Yet leveraging CER findings is not as simple as prescribing a proven treatment to every patient who has a disease. Due to biology, some patients will fare better if they are given a different treatment option. And it can be challenging to identify which people will benefit from alternative treatment options. Analyzing subgroups that respond differently to medications can provide some insights, but there are limitations to this type of research.
Patient preferences also play an important role in determining the best individual course of treatment. Whether it’s someone with cancer, heart disease, diabetes or depression, patients face choices not only among different drug therapies, but also among different modalities. Each patient may weigh medication, surgery, physical therapy or lifestyle changes through a different prism. Those individual preferences or concerns matter in the quest for achieving good clinical outcomes.
These issues demonstrate why it is so important to treat each patient as an individual and provide some important “guardrails” as those shaping up approaches to CER think about implications for patient access to individualized health care choices. Although it can be tempting to boil down CER findings into a recommendation for a single, standardized treatment option, we know that individual patient differences make that an impractical course of action.
The evidence has shown us that “one size fits all” approaches, like those being considered by some state insurance exchanges, can mean poor outcomes for key subgroups of patients. When individual patients respond poorly due to heterogeneity, the health care system in turn must devote more time and money to making them well. A CER study of antipsychotic drugs provides an example of how this dynamic plays out. Although the Clinical Antipsychotic Trials in Intervention Effectiveness (CATIE) found that first-generation antipsychotic drugs were as effective at treating schizophrenia as newer, more expensive medications, a follow-up study conducted by the Manhattan Institute for Policy Research and funded by NPC determined that a hypothetical policy denying Medicaid patients coverage for second-generation drugs would lead to higher overall health costs. For the 75 percent of patients who do not respond to first-generation antipsychotics, such a restrictive coverage policy would take a huge toll on their health. The study illustrates why failing to tailor care to individual patients’ needs can worsen the divide between those who have ready access to quality care and those who do not.
To effectively incorporate CER into the health care system, individual patient differences need to be taken into account in developing treatment recommendations, practice guidelines, and coverage and reimbursement policies. Stakeholders will discuss the role heterogeneity should play in setting these policies at a conference NPC, the National Health Council and WellPoint are holding Nov. 30 at the Omni Shoreham hotel in Washington, DC. "The Myth of Average: Why Individual Patient Differences Matter" will examine how patient differences affect clinical outcomes as well as policy.
We can only realize the goals of improving the health care system through CER if unique patient characteristics are part of the discussion. If we want to create a truly patient-centered health care system, maintaining access to alternative treatments that could benefit certain patients or subgroups will be an important part of the equation.