Despite receiving another $14 million from the Laura and John Arnold Foundation, ICER is turning into the walking dead.
The recent spate of ICER reports all come to the same premature and prejudged conclusion: that every new medicine that does not cure is not worth paying for at almost any price. Overextended and overexposed, ICER is slowly being destroyed by its ideological rigidity and analytic obsolescence. At a time when the use of data to match people to the right treatments over time and pay for performance at the patient level, ICER has doubled down on one size fits all reports that focus on saving insurers money by cutting drug prices. It roams the health care policy terrain in search of new targets to devour, guided by the same research methods and beliefs that shaped the eugenics movement. Like that movement, ICER is finding itself ridiculed and rejected by the same stakeholders that feared it just a year ago.
Of course, the unspoken but clear assumption behind ICER reports -- the same assumptions informing those who wanted to use eugenics to save society -- is another reason that Steve Pearson and company have jumped the shark: ICER assumes the use of new drugs siphons money from healthy people, wage increases, roads, potholes, etc. and that we need to put a limit on how much we pay and how much we spend for new medicines for people, most of whom, are not receiving many benefits from existing treatments.
These assumptions are laughable, and everyone knows it. Better medicines reduce the cost of treatment and staying healthy longer. Longer and better lives generate happiness and wealth, which in turn makes spending on everything -- including health care -- sustainable. ICER, now includes, but does not calculate, those goods, services, and actions we enjoy and product because we live longer and healthier. By listing those virtues but not measuring them, ICER has exposed how superficial and irrelevant it is.
Beyond that, ICER is unable to close the gap between a new generation of personalized medicines and finding a way to pay for them in order to "enhance health, prevent disease, track its development, intervene early, and manage disease most effectively if it occurs." Such treatments are based on a deep understanding of what causes disease as well as the individual differences in disease risk and response to medicine. As result, illnesses such as cancer, heart disease, and multiple sclerosis are being treated with greater effectiveness, while many rare or fatal diseases - such as cystic fibrosis, Hepatitis C, and HIV --now have treatments where none existed.
Simply put, personalized medicine is a powerful tool for extending life and making the delivery of great health, simple, convenient and more affordable. Yet ICER, captive of it paymasters and increasingly outdated approach, can't produce information to let consumers and everyone else determine which treatments work best for them to live healthier, longer. Rather, as the ability to deliver personalized medicine grows, ICER only proposes ways to reduce prices for PBMs and limit access. Meanwhile, PBMs are expanding step therapy, prior authorization and increasing cost sharing as more personalized or precision medicines become available. That means they are keeping people sick when they should be healthy and forcing them to spend more time and money on substandard care.
The rebate driven approach to drug benefits is under siege and intelligent stakeholders are seeking other ways to provide patient-centered coverage. That does not include ICER.
In addition to its need to carry out the societal rationing agenda of the Arnold Foundation, ICER lacks the bandwidth to help promote personalized medicine. The digitalization of medical data and the rapid increase in computing power now permits identifying what treatments work and measuring outcomes and analyzing such evidence to determine the links between the use of medicines and outcomes. Traditional analytical approaches employ manual, time-consuming, single hypothesis algorithms. As a result, ICER is limited in its ability to integrate multiple data types and are often limited to population averaged approaches.
For example, ICER makes all sorts of assumptions about the condition of patients and treatment patterns based on models it develops from clinical trial data. Such assumptions - including the selection of the treatment it uses to compare new medicines - are based on correlations that lack any basis in the reality of the life of every patient.
ICER will become increasingly irrelevant. Other stakeholders could accelerate that process by ignoring ICER's request for 'input' and invest the millions of dollars into creating models that capture personalized treatment response.
Such models would be based on the probabilistic and causal relationships between disease progression and treatment response (unbiased by methodological and data choices that characterize much of ICER's work) for each patient. They are less expensive to produce because the machine learning supporting it is automated. They are quicker to produce and more useful.
Indeed, personalized medicine models can be used to demonstrate and qualify an approach for using real-world evidence. The Food and Drug Administration is required to create a guidance and/or pathway for integrating real-world evidence into their approval processes. If the FDA encourages the use of real-world evidence to measure and predict clinical benefit at the individual level, it will force payors to rely more on such analyses and less on those developed by ICER and other groups. Speedily in our time.