BioCentury reports that NICE is seeking input on proposed changes to its health technology assessment methodology that the agency said would more explicitly take into account the burden of a person's illness and the wider impact of a disease on people's ability to be part of society. NICE is proposing to measure burden of illness as the proportional shortfall in quality-adjusted life years (QALYs) for those with a disease compared with the expected QALYs for those of the same age and gender without the disease. NICE said evaluating burden of illness as a proportional difference "recognizes the position of those patients who stand to lose the greatest proportion of their remaining health expectancy." The agency noted that the measure "is not particularly sensitive to the age at which people are diagnosed."
What NICE calls "societal impact" would be measured as the absolute difference between the expected QALY in a patient with a disease and the expected QALY in people of the same age and gender without the disease. The agency noted that for an absolute shortfall, "the larger the shortfall, the larger the effect" on society. Comments on the proposed methodology changes are due June 20, with NICE planning to introduce the changes this fall.
In 2010, the U.K. government proposed to establish a system under which NICE would have assessed the value of a new drug and assigned a value-based price. But the 2014 Pharmaceutical Price Regulation Scheme (PPRS) agreement essentially marked the end of value-based pricing as it was originally proposed, with NICE instead shifting toward a "value-based" assessment process.
It’s important to consider VBID in the broader conversation of clinical effectiveness and more specifically HTA modeling a la QALY – because that brings you into the direct path of VSLY – the value of a statistical life year. According to Dr. Frank Lichtenberg of Columbia University, for a healthcare technology assessment scheme (such as the NICE model) to yield valid decisions in practice, it is necessary to have reliable estimates of:
ΔCOST
ΔQALY
and VSLY (Value of a Statistical Life Year)
and his main point is that the devil is in the details.
Lichtenberg believes that incorrect estimates of some or all of these key inputs are often used:
ΔCOST is frequently overestimated
ΔQALY and VSLY are frequently underestimated
And due to these estimation biases, health technologies that are truly cost-effective may often be rejected as cost-ineffective.
Per the recent debate over the utility of new cancer treatments, he makes a very interesting point -- that even though, over the past 30 years, the U.S. Mortality Age-Adjusted Rates for cancer have remained relatively constant -- (leading to such mainstream media headlines as Fortune Magazine's "Why have we made so little progress in the War on Cancer?” and NEJM articles like "The effect of new treatments for cancer on mortality has been largely disappointing” -- the often ignored reality is that 5-year relative survival rates, for all cancer sites, have increased from 50.1% in 1975 to 65.9% in 2000.
Lichtenberg cites two crucial studies, pointing out how health care economists must seriously reconsider the outdated estimates of a QALY:
Viscusi and Aldy: The value of a statistical life for prime-aged workers has a median value of about $7 million in the United States
Viscusi, W. Kip and Joseph E. Aldy, “The Value of a Statistical Life: A Critical Review of Market Estimates Throughout the World,” The Journal of Risk and Uncertainty, 27:1; 5–76, 2003.
and
Murphy and Topel: The value of a life year is $373,000.
Murphy, Kevin M., and Robert H. Topel, “The value of health and longevity,” Journal of Political Economy, 2006.
If the devil is in the details (and it is) -- it's time for a deep dive beyond simplistic and self-serving "comparative effectiveness."
