Looking at the Big Picture in Health Care

A more objective and complete way to determine health decisions is sorely needed

As the demand for health care increases, so does the need for smart, evidence-based decision making in health care. Yet a cost-effectiveness measure that has several shortcomings is the basis for a reimbursement decision-making model proposed by the Institute for Clinical and Economic Review (ICER).

While that method—called quality-adjusted life years (QALY)—is one useful tool for guiding health care decisions, it becomes problematic when we focus solely on this factor and generalize its applicability across disease states. If insurers and policymakers continue to make these missteps, patients will lose access to life-changing medicines.

Ariel Beresniak, founder and health economist at Data Mining International, believes quality-adjusted life years (QALYs) should not be the only measure used for health care decision-making.

Ariel Beresniak, founder and health economist at Data Mining International, believes the quality-adjusted life years (QALYs) should be abandoned for health care decision-making.

“Using QALYs for cost-effectiveness analyses of new medicines is problematic,” Ariel Beresniak, founder and health economist at Data Mining International, said. “This approach is quite unfair and discriminatory.”

Beresniak is not alone in this indictment. Health economists have been pointing out the drawbacks of QALYs ever since the formula was introduced in the 1980s. Over the years, QALYs have been shown to be too narrowly focused on patients’ physical health, ignoring benefits to their emotional and mental health, their careers and families and other societal benefits. QALYs also discriminate against the elderly, patients with chronic diseases and those who have limited treatment options. Finally, the approach is widely inconsistent when used to make health decisions.

The inconsistencies stem from how QALYs are calculated. The formula considers two factors: the length and quality of the extra life that a treatment offers. So if a treatment allowed a patient to live two years longer in perfect health, the benefit would be two QALYs. But if those two years were spent in a wheelchair, that might be reduced to only one QALY.

The formula is simple, maybe a little too simple, according to Beresniak. It’s based on the assumption that people generally agree about how they would prefer to live. But health economists have questioned whether two years in a wheelchair is actually equal to one year in perfect health in everyone’s eyes.

It’s impossible to get a consensus on patient preferences to justify using QALYs.”

To address this issue, Beresniak led a three-year, 1 million euro project funded by the European Union Commission. After interviewing 1,300 people in Belgium, France, Italy and the United Kingdom, the team found their preferences could not be simplified in the QALY approach.

“It’s impossible to get a consensus on patient preferences to justify using a QALY approach,” Beresniak said. “Countries who use this approach to make health care decisions are only delaying patients access to innovative medicines. It is anything but scientific.”

Beresniak likens the QALY approach to equating two 40-degree days with one 80-degree day. The relative enjoyment of the two days is a personal preference, not something we can come to a consensus about, he notes.

Looking at QALYs Is Not Enough

Beresniak believes that instead of relying on QALY assessments, insurers and policymakers should be more flexible with how they measure the value of new medicines by considering cases on an individual basis. As a result, health care decisions may better align with how patients and society actually value treatments for these specific conditions.

For instance, clinical trials have developed a variety of meaningful measures of outcomes and health-related quality of life for people with psoriasis and psoriatic arthritis, including the Psoriasis Severity Index and the American College Rheumatology Response Criteria. Yet many of these measures are not typically incorporated into cost-effectiveness analyses.

“We need to be more precise when making reimbursement decisions,” Beresniak said. “We should look at relevant clinical outcomes, and we should be disease-specific. We cannot only rely on QALYs to make health care decisions. It is time to use a number of alternative approaches which are much more robust to express the real value of innovative products.”