I believe your impressions of Baychol winning the DoD and other business are correct.

Comparative effectiveness is a subtlely different concept than comparative efficacy. Efficacy values the measure (for example LDL reduction) whereas effectiveness measures the outcome (for example, reduced heart attacks and CV disease/disability). Focusing on comparative effectiveness changes the emphasis from cost-efficacy comparisions (where Baychol could win business - despite unknown, but not unsuspected risks) to which product(s) provide different/improved health outcomes.

It is a fairly easy thing to convince people that paying for improved lab values, possibly at the risk of higher costs for worse outcomes down the line is not the best allocation of limited resources.

This does create situations where the low cost agent is excluded from consideration. This can also result in actual increases in medication costs, which are then offset by reductions in other costs. However, the data supporting the effectiveness value needs to be there.

Atlex, you are correct also about the need to include procedures along with the medications. There are lots of good examples of where procedures have been shown not produce benefits greater than medical treatments. For that matter there are also ‘non-medical’ treatments which are more effective than medications for a variety of conditions. Medications are a little easier to compare, because there are already a number of comparative studies (and outcome studies) out there. There aren’t nearly as many as would be helpful, but it is a starting point.

As for the $300 million, you are correct, it is not likely enough to be highly productive. However, finding savings without bad health outcomes trade-offs is not difficult - if you know where to look. The programs I’ve worked with have “saved” or avoided costs well over $75 million in the past three years, This was with a methodical, careful approach to comparative effectiveness, and looking at medications only. Remember too, this is on a base of less than 750,000 covered lives initially (Part D brought it down to around 650,000).

At least as I understand the story, Baycol got the Medicare and DOD gigs essentially because of low-balling price. Then there is the history of underplaying risks of higher doses and gemfib interactions and false promos of relative efficacy (compared with Lipitor).

Will such an organization be able to tease out the truth, in the face of such blue light specials? And will that truth trump cost-saving as whatever it finds is translated into tx guidelines?

You sound like a Pharma Sales Rep from TAP pharmaceuticals!!!!!!!!!!!!!!!!!!!

You are correct. For evidence look at any number of good NIH studies of comparative effectiveness which showed us new information, but resulted in minimal if any change in treatments. The best example is the CATIE study.

However, the primary users of this information are likely to be the decision-makers who determine the allocation of our limited healthcare resources. In other words, public, private and self-insured health plans. This is already taking place, though the comparative effectiveness information can sometimes be challenging to find.

Nothing changes physician behavior like insurer coverage policies. The challenge is always to ensure that the determinations of what is covered are the most appropriate and best supported treatments. This is an evaluation which is independent of costs (or manufacturer rebates) - the historic focus of PBMs. Another critical component is to anticipate and avoid unintended consequences which do not lead to desirable health outcomes.

In my experience, focusing on comparative effectiveness evidence can result in significant improvements for health plans. These include substantial cost savings, increases in evidence-based uses of medications, diminished “off-label” or inappropriate/unproven uses of medications. These benefits can be accomplished without increasing costs or utilization of other healthcare services. Improvements in management of chronic diseases can also result.

Health plans have been historically reluctant to say “no” to just about any use of any medication. This has put the hurt on payers to the benefit of PhRMA, BIO and device makers. Increasingly there is awareness that the high costs of medications (or large cost disparities between treatments for a single condition) may not be providing additional value for the patient or the health plan.

Again, based on my experience over three years with two plans currently covering around 650,000 covered lives, finding $300 million from the plans who benefit from the knowledge will be no problem at all.

Clearly, the devil is in details re: representation and decision-making.

In the meantime, not hard to anticipate the pro/con debating points. In this case, cost-lowering is explicitly the goal.