Can the Centers for Medicare & Medicaid Services fix reimbursement for cancer care without having the changes metastatize into other specialties?
That's the question oncologists are asking. They want CMS to acknowledge how badly Medicare underpays for their practice expenses, especially if CMS is determined to slash payments for the drugs they dispense (see article 12). But given CMS' requirement for budget neutrality, any boost to the Relative Value Units (RVUs) for oncologists would have to come out of any other specialty.
Oncologists would prefer that Congress implement a legislative solution to the problem of overpriced drugs and undervalued services, according to the American Society of Clinical Oncology. Taking the money out of someone else's RVU isn't a solution that ASCO would support, officials add.
But they note that CMS appears determined to address the drug reimbursement issue administratively if Congress doesn't act, and Administrator Tom Scully has said it wouldn't be fair to cut drugs without paying fairly for other expenses.
"Our goal is to pay properly for the drugs and pay properly for the administration of the drugs," CMS officials tell PBI. "If we were to change the practice expense, then we would have to look at the issue of what that does to the fee schedule." They add that CMS is looking at options and hasn't yet come to a decision.
But ASCO officials hope a study they performed last year with the help of the Gallup Organization will sway CMS. The Gallup/ASCO survey provided data that the Falls Church, VA-based Lewin Group analyzed on behalf of CMS. The Lewin analysis, released last fall, showed oncology practice expenses averaged 89 percent more than Medicare payments.
The Lewin Group concluded the Gallup data met all existing criteria for validity, notes ASCO. But CMS said in its comments along with the 2003 Fee Schedule that it was concerned about some high variables in the clinical salary data.
ASCO has since met with CMS officials and explained those values. CMS includes outliers in its overall analysis of data, but if you remove those outliers, then the numbers come down to more reasonable levels.