Comparative Effectiveness Research - Threat or Opportunity

The Obama administration is promising major health care reform, and this time … unlike all the times before since the creation of Medicare more than 40 years ago … the promises seem likely to be kept. We’ll see. What is most interesting to me is that of all the reform elements that have been proposed – broadened insurance coverage, mandatory electronic health records, a public insurance option to compete with private insurers, radiology benefits management, a defined approval path for biosimilars, a deepened commitment to so-called “personalized medicine”, etc. - the one causing the most anxiety to life science companies seems to be “comparative effectiveness research”.

The commitment to comparative effectiveness research (lets call it CER) has already been made. The February economic stimulus package contained $1.1 billion for CER. The 15 person council to set priorities and coordinate the commitment of that money was appointed March 18. And it is hard to argue that better knowledge about the relative merits of different medical therapies isn’t a good thing. So why is it that the formal CER policy statements of the key trade associations are so guardedly supportive, and the private communications of many industry heavies are clearly negative?

It is not as if we don’t already compare one therapy to another in clinical research all the time. Every controlled clinical trial involves such a comparison, and FDA increasingly wants to see active controls – best available therapy – rather than placebo controls. Insurers, too, in their coverage decisions, ask to see therapeutic outcomes as they compare to alternatives already covered. In the established processes for securing market entry and initial utilization, CER is already the coin of the realm.

The perceived threat is that the new CER initiative … which focuses on comparative outcomes in clinical practice (as opposed to clinical trials) … will extend the utilization of clinical research results in at least two ways:

1. To withdraw insurance coverage of an approved therapy when research indicates the relative superiority of another; and
2. To inject structural consideration of relative cost into the coverage process.

Both of these extensions envision more or less “global” CER findings: one therapy revealed to be superior to another as a general rule. Both would rightly be considered substantial threats by industry, and both would be strenuously opposed using well-defined and frankly shopworn arguments about the proper relative roles of physicians and payers (clinical choices ought to be the exclusive realm of the physician, medicine is an art not a science), and the proper utilization of cost-effectiveness data (none - you can’t put a price on human life).

But the fact is that worry about administrative restrictions on therapy choice by insurers and the injection of cost considerations into coverage decisions, and any momentum that either of those initiatives might in fact have (a lot for insurer restrictions on therapy choices, very little so far for cost as a critical element in limiting coverage) long predates the current vogue for CER. Those dynamics continue independent of the level of CER spending, or any formal commitment to a CER initiative.

The real import of the CER initiative is more subtle and far reaching than is reflected in industry’s conventional response – CER can be a critical enabler of the realization of the promise of personalized medicine: the right treatment for the right patient at the right time. I look to Clayton Christenson’s formulation in his challenging recent book The Innovator’s Prescription: A Disruptive Solution for Health Care (McGraw-Hill, 2009). Christenson charts the ongoing evolution of medicine from intuitive (decisions based upon the experience, special skills and intuition of highly-trained physicians) through empirical (decisions based upon validated statistical probabilities) toward precision (evidence-based determinations that are 100% accurate). The advent of precision medicine is largely enabled by genomics, proteomics and molecular diagnostics – variables and tools that are providing great insight into why some medicines work for some people and not others and how we can identify which medicine will work for a particular patient.

CER moves therapy selection – even absent genetic determinants - toward the precision medicine model. It isn’t the blunt instrument industry seems to imagine – obliterating established markets with large-scale studies. It is ultimately a highly refined tool, providing insight as to the circumstances under which one therapy is preferable to another: What are the characteristics of the patients helped by Option A? What were the circumstances under which they did best? And when and for whom was Option B better? It is, viewed this way, a piece of Christenson’s disruptive solution. Paired with reliable patient evaluation tools and diagnostics, CER can provide the knowledge to enable lesser-trained professionals to achieve better clinical outcomes at lower cost. Just what the doctor ordered … and an enormous opportunity for industry. I'll address the nature of that opportunity in a subsequent post.