In this space, we spend a great deal of time talking about the methods some health economists use to measure health outcomes and the value of new treatments. For example, we’ve gone to some lengths to explain why analyses and valuations based on the quality adjusted life year (QALY) scale are not credible. We have also explained how QALY-based models are discriminatory, unethical, and fail to incorporate the needs and perspectives of real-life patients.
Despite its inherent flaws, many mainstream health economists have been using the QALY the value of new therapies for over three decades. And, in recent years, as U.S. public- and private-sector health insurers have looked far and wide for ways to bring down costs, they have started using those assessments – particularly those coming out of the Institute for Clinical and Economic Review (ICER) – to make pricing and coverage decisions for patients.
This is a problem. Fortunately, there are solutions.
A few weeks back, we highlighted the needs-based quality of life (N-QOL) scale, a new instrument developed to replace the QALY with a true quality-of-life measure. Unlike the QALY, the N-QOL follows the standards for normal scientific measurement. It is also a more accurate and useful approach to measuring how well a new drug or treatment meets the needs of patients.
The N-QOL is designed to fit the accepted framework for measuring the fulfillment of needs. The framework is based on two fundamental factors: difficulty and ability. In measuring health outcomes, a “difficulty” measure shows how hard it is to meet a particular patient need. At the same time, “ability” measures capture how likely it is that a patient will be able to meet that need.
Under this approach, when a patient’s ability to meet a particular need increases, there is a greater probability of a successful response to a new drug or therapy. That probability goes down as the inherent difficulty of meeting the need increases.
In other words, a treatment that either increases patient’s ability OR reduces the level of difficulty is more likely fulfill a patient’s needs and be judged a success.
In contrast, QALY-based valuations rely on instruments that virtually ignore these factors. For example, one of the more widely used quality-of-life instruments is the EQ-5D-3L, which generates simple profiles in the health status among patients. It has five symptoms with one question for each: mobility, self-care, usual activity, pain/discomfort, and anxiety/depression. Each attribute has three response levels: no problems, some problems, major problems.
As we have discussed many times, one major problem with this method is that it produces ordinal scores. That means they can tell us whether a patient improved in one of the five measured areas, but it cannot tell us by how much. For example, after undergoing a specified treatment, a patient could report mobility improvements of one percent or 100 percent – the score on the EQ-5D-3L would be the same.
But let’s set those glaring mathematic and scientific problems aside for a moment.
Another problem is that the factors measured by the EQ-5D-3L are entirely clinical. The scale measures nominal improvements from the perspective of healthcare providers, but any non-clinical factors that can affect patients’ quality of life do not factor into scores.
Given that QALY proponents claim it is a tool for measuring quality of life, the fact that it essentially ignores patients’ perspectives is a problem.
The N-QOL uses a different approach. Rather than a universal measure of clinical factors, it relies on disease-specific questionnaires that reflect the needs of patients and caregivers and determines whether and by how much a new treatment helps in the fulfillment of those needs.
After all, that is how patients are most likely to measure their own quality of life. That is also how patients will ultimately judge how valuable a new drug or therapy is for them. Any quality-of-life instrument that focuses on something else is going to produce comparably less meaningful results.