Next-Generation Oncology APMs Need More Planning to Succeed

SAP Partners | <b>OneOncology</b>

Originally set to expire on June 30, 2021, the Oncology Care Model was extended for an additional year in light of the COVID-19 pandemic.

The Oncology Care Model (OCM) from CMS’ Center for Medicare & Medicaid Innovation (CMMI) was originally supposed to expire on June 30, 2021, to be replaced by Oncology Care First (OCF). However, in light of the COVID-19 pandemic, that date was pushed back by 1 year—and this may be a good thing.

With value-based care at its core due to ever-increasing cancer care costs, in the 5 years since OCM was originally implemented on July 1, 2016, results have been mixed, with experts pointing out the model’s complexity, that it may not be all about the patient, and potential outlier costs.

“Medicare did not go into this to improve the quality of cancer care,” stated Michael Kolodziej, MD, FACP, vice president and chief innovation officer at ADVI Health, a health care and life sciences consulting company. “They went into this to save money.”

He adds that performance measures are “so confusing that many practices do not fully understand how they have managed to generate savings, which deprives them of the confidence that they can continue to succeed in the model.”

A Viewpoint published online today in JAMA Oncology adds to the discussion by highlighting challenges the OCM has encountered over the past 5 years but also proposing solutions to enable next-generation alternative payment models (APMs) to succeed in the precision medicine era.

“After accounting for monthly and performance-based payments, the OCM actually led to a $155 million net loss to Medicare,” the authors wrote. “Administrative burdens also resulted in eroded participation: Of the 192 original practices in 2016, 138 (71.9%) remained as of January 2020.”

They proposed 3 main reasons that the OCM has not met expectations:

  1. Administrative claims data did not account for disease specifics, such as cancer diagnosis, histology, and molecular characteristics. Yet, these data were used to define episodes of care and measure cost savings in the OCM.
  2. Payment adjustments under the OCM that accounted for newer, more expensive therapies introduced after the model began were applied at the practice level, with the authors noting this should have been at a disease-specific level.
  3. Performance-based risk measures did not account for oncologists’ lack of control over therapeutic drug use, as most of the regional variation in spending is linked with acute hospital care rather than drug prescribing. The necessity of OCM payments may also differ based on the level of care coordination needed for low-risk vs high-risk cancer episodes. In particular, the authors point out, under the OCM, monthly spending for low-risk cancers rose while simultaneously dropping for high-risk cancers.

Next steps to improve upon this first-generation APM involve drilling down to specifics. For this, the authors proposed 2 solutions:

  1. Utilize more granular data, instead of relying only on claims data, when defining episodes of care. Also, put in place patient protections for these data, “given ethical challenges in sharing individual genetic and molecular data with payers,” the authors note.
  2. Be judicious when designating accountability for oncologists regarding low-value decisions that have alternative choices (eg, administering intravenous fluids in the emergency department instead of on an outpatient basis) and high-value decisions that do not (eg, standard-of-care targeted therapies)

“Being thoughtful about key design features around episode creation and physician accountability,” the authors concluded, “will ensure the success of the next generation of APMs in oncology in the precision medicine era.”

Reference

Mullangi S, Schleicher SM, Parikh RB. The Oncology Care Model at 5 years—value-based payment in the precision medicine era. JAMA Oncol. Published online July 1, 2021. doi:10.1001/jamaoncol.2021.1512