The Oncology Care Model (OCM)
A Risk Arbitrage Analysis
September 7, 2015
The OCM – What is it?
The OCM is a CMS (CMMI) value based care payment program of nationwide scope, targeted at 100 practices and 1,500 Medical Oncologists. The program pays medical oncologists a $160 per beneficiary per month management fee, plus up to 16% of total patient medical cost savings (for all care of any type), after the 4% savings that will be retained by CMS. The program was promulgated on February 12, 2015, and final applications were submitted by qualifying medical oncology practices on June 30, 2015. Program participants are to be selected prior to year end, and the program is slated to go live in the spring of 2016. The program channels all financial benefits through the medical oncologists, and has a set of 6 minimum qualifying conditions and 32 quality metrics which must be met to receive payment under the shared savings program. (Please see the article about the OCM and the OCM for hospitals for details and references). The estimated total market for savings under the program is $27.4 billion, with around 90+% of savings expected from services outside of those billed by the medical oncologist.
Risk Analysis in the OCM
The OCM takes a little analysis to really understand the sharing of risks and rewards. One of my favorite ways to approach the problem is to consider the OCM in a risk Arbitrage model, using synthetic options to capture the purchase, sale and value of risk.
Risk arbitrage is fairly simple – for academics, it is the simultaneous purchase and sale of an asset in two different markets, and capturing the price difference as a “locked-in profit”. In the real world, there is always risk, and the arbitrage normally captures and prices the risk – sounds a lot like health insurance. For an arbitrage to take place one of three conditions must always exist:
- The same asset does not trade at the same price on all markets (“the law of one price“).
- Two assets with identical cash flows do not trade at the same price.
- An asset with a known price in the future does not today trade at its future price discounted at the risk-free interest rate.
If you think of the asset in this model being the delivery of healthcare, and the risk being both the price of the asset and the amount purchased, then the arbitrage model starts to make a lot of sense.
Arbitrage – Real World Examples
One of my favorite examples of arbitrage, involves the Battle of Waterloo, and the famous financier, Nathan Mayer Rothschild. The Battle of Waterloo was the apogee of the second coming of Napoleon Bonaparte, and all of Europe (non-Francophone) was in terror of a French victory. The prices of securities had plummeted on exchanges all over Europe, but the biggest and most liquid exchange – London – had suffered more than most. The battle was a close call, but ultimately the allied forces, led by the Duke of Wellington were victorious.
This was in the era before modern communication, and legend has it that Nathan Mayer Rothschild had a man dispatched to London, who arrived several hours before the official representative of the Duke of Wellington. The representative went straight to the bond exchange, and shorted bonds called consols heavily, whispering that Waterloo had been lost, engineering a short-term panic, and further depressing the price of consols. When the price of the consols was sufficiently depressed, he bought to cover his short position, and then delivered the good news that Napoleon was defeated and Wellington was victorious – thereby boosting the price of the consols and making a fortune – and arbitrage was born.
Wellington at Waterloo – Napoleon is defeated and arbitrage is born
Arbitrage Model in Healthcare
In the simplest terms, in health insurance, the Insurer buys risk from a Patient by receiving premiums. This can be thought of as the Insurer writing a put in which the Insurer buys the healthcare risk of the Patient for a fixed premium. The Patient then has the right to put his claims for medical care back to the Insurer. The insurer makes money when the aggregate claims are less than the risk premiums – effectively the medical loss ratio (MLR).
Again in a simplified model, the Insurer buys care from providers in the following ways that the Patient cannot:
- Discounted rates negotiated for bulk purchases,
- Limitations for access to the “risk pool” through medical utilization review,
- Requirements for adherence to specific formularies and pathways to limit access to expensive therapeutics and diagnostics.
In arbitrage terms, health insurance is a statistical arbitrage, in which the arbitration relies on statistical pricing differentials (actuarially determined) rather than strictly on distinct markets. Historically, one of the most effective methods of limiting risk has been to limit the population of insured parties to lower risk Patients. Additional risk mitigation has been accomplished by capping payout, reinsurance, limiting specific disease states covered by the insurance, shortening the period of coverage and limiting renewals.
While co-insurance and deductibles also tend to limit consumption, they function by influencing consumer behavior rather than by actually addressing the underlying risk associated with the arbitrage.
A Simple Healthcare Risk Arbitrage Model
The OCM Arbitrage Model
The arbitrage model associated with the OCM is considerably more complicated, both adding new players into the payment model, and fundamentally changing the alignment of the participants. In the OCM, the role of the Medical Oncologist is conflated in many ways with the Payer. Providing very substantial economic rewards (up to 100% of avoided costs) to the Medical Oncologist for the elimination of unnecessary medical care is the most noteworthy, but the perhaps more importantly for the other players in the oncology care ecosystem, the Medical Oncologist will have the ability to form durable care delivery networks under prior agreement regarding pricing and best practice. In the OCM, the Medical Oncologist is unique among providers, directing both medical care and economic arbitrage. The tools of risk management available to the Medical Oncologist as provider and arbitrageur are vastly more powerful than the tools available to the Payer in the prior model.
The OCM Arbitrage Model
The complexity of the new arbitrage model includes new agency as well as contracting relationships and responsibilities for the Medical Oncologist. To a very large degree, the arbitrage relationships afforded by the OCM vastly exceed the prior opportunities afforded the Payer – almost entirely through the shared savings payment mechanism. To put the amount available under the shared savings into perspective, it exceeds the minimum MLR (15%) allowed under the ACA.
The arbitrage model is a powerful tool for analyzing the OCM. Arbitrage and options can be utilized to understand both the activities and economic incentives brought by the OCM. The OCM will place a new level of complexity and managerial skills on medical oncology groups looking to be successful in the OCM.