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The American Journal of Managed Care August 2013
Cost of Care for Malignant and Benign Renal Masses
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Geoffrey D. Barnes, MD; Alexander Katz, MD; Jeffrey S. Desmond, MD; Steven L. Kronick, MD, MS; Jamie Beach, RN; Stanley J. Chetcuti, MD; Eric R. Bates, MD; and Hitinder S. Gurm, MD
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Option Pricing: A Flexible Tool to Disseminate Shared Savings Contracts
Mark W. Friedberg, MD, MPP; Anthony M. Buendia, BA; Katharine E. Lauderdale, BA; and Peter S. Hussey, PhD
A Natural Experiment in Mass Media Modulated Pharmacokinetics After a Change in Tablet Formulation
Natan R. Kahan, PhD, RPh, MHA; Daniel A. Vardy, MD, MSc; Dan-Andrei Waitman, MD, MPH; and Gherta Brill, MD

Option Pricing: A Flexible Tool to Disseminate Shared Savings Contracts

Mark W. Friedberg, MD, MPP; Anthony M. Buendia, BA; Katharine E. Lauderdale, BA; and Peter S. Hussey, PhD
By pricing options that protect providers from downside risk,health plans can more clearly evaluate different shared savings contracts and expand them to smaller providers.
Objectives: Due to volatility in healthcare costs, shared savings contracts can create systematic financial losses for payers, especially when contracting with smaller providers. To improve the business case for shared savings, we calculated the prices of financial options that payers can “sell” to providers to offset these losses.

Study Design and Methods: Using 2009 to 2010 member-level total cost of care data from a large commercial health plan, we calculated option prices by applying a bootstrap simulation procedure. We repeated these simulations for providers of sizes ranging from 500 to 60,000 patients and for shared savings contracts with and without key design features (minimum savings thresholds,bonus caps, cost outlier truncation, and downside risk) and under assumptions of zero, 1%, and 2% real cost reductions due to the shared savings contracts.

Results: Assuming no real cost reduction and a 50% shared savings rate, per patient option prices ranged from $225 (3.1% of overall costs) for 500-patient providers to $23 (0.3%) for 60,000-patient providers. Introducing minimum savings thresholds, bonus caps, cost outlier truncation, and downside risk reduced these option prices. Option prices were highly sensitive to the magnitude of real cost reductions. If shared savings contracts cause 2% reductions in total costs, option prices fall to zero for all but the smallest providers.

Conclusions: Calculating the prices of financial options that protect payers and providers from downside risk can inject flexibility into shared savings contracts, extend such contracts to smaller providers, and clarify the tradeoffs between different contract designs, potentially speeding the dissemination of shared savings.

Am J Manag Care. 2013;19(8):e285-e292
Volatile healthcare costs and asymmetric shared savings contracts can create systematic financial losses for payers.
  • Calculating the fair prices of “options” that payers can sell to providers to offset these losses can improve the business case for shared savings and clarify tradeoffs between contract designs.

  • In a large sample of commercial health plan members, simulated option prices reached 3.1% of overall healthcare costs for providers with just 500 members. Prices were considerably lower for larger providers and more balanced contract designs.

  • If shared savings contracts create 2% real savings, selling options may be unnecessary for most providers.
Shared savings contracts between payers and providers are important features of many innovative healthcare payment and delivery models, including Accountable Care Organizations (ACOs) and medical homes.1-4 These contracts incentivize cost  containment by allowing providers to share in any savings they create, usually by paying them a percentage of the difference between observed and expected costs for their patient panels. However, providers generally do not pay an equivalent penalty if observed costs exceed expectations. This asymmetric risk distinguishes shared savings contracts from pure capitation or “global payment” arrangements in which providers stand to absorb gains and losses in equal measure.5

The Problem: Paying for Volatility

For a given patient, costs of care from year to year exhibit volatility, or unpredictable variation due to chance alone. Patients who are relatively healthy with low health expenditures in one year may become sick with high health expenditures in the next, and vice versa. Due to this random variation, observed costs for a provider’s patient panel can vary widely from expected costs, producing apparent savings in one year and cost overruns in the next. Therefore a substantial proportion of shared savings bonuses may be paid due to chance alone (“paying for volatility”), even if providers do nothing to contain costs. While random variation also can produce cost overruns, the resulting penalties will not counterbalance random rewards when shared savings contracts are asymmetric.

Faced with the prospect of paying for volatility, payers justifiably may avoid shared savings contracts: unless payers are confident  that shared savings contracts will result in highly effective cost-containment efforts, random cost variation can undermine payers’ business case for such arrangements.4 Whether due to lack of confidence in cost-containment ability or aversion to financial risk, providers have resisted contracts that include penalties for cost overruns.6 Therefore to enable widespread adoption of shared savings contracts, we need tools to bridge the gap between providers who want protection against downside risk and payers who need a winning (or at least neutral) business proposition.

Current Solutions

Tools to improve payers’ business case for shared savings contracts work in 2 general ways: reduce the amount of random variation (ie, volatility) in costs, and make the contract more symmetric. To reduce random variation in costs, payers frequently require patient populations larger than a specified minimum threshold.4 For example, Medicare ACO demonstrations require 5000 or more patients (for the Shared Savings Program) and 15,000 for non-rural Pioneer ACOs (Appendix A).7,8 Due to the “law of large numbers,” larger patient populations have less random variation as a percentage of overall costs, thereby reducing payers’ risk of losses.9

Truncating cost outliers (patients with extremely high costs) also can reduce random variation in shared savings contracts. The Medicare Shared Savings Program truncates costs at the 99th percentile: for the purposes of calculating savings, the most expensive 1% of patients are considered to have costs equal to the patient at the 99th percentile.7 Both expected and observed costs are truncated, so while this method reduces the threat that cost outliers pose to providers, it also produces lower expected costs (ie, a tougher target for providers to beat).

To make shared savings more symmetric and improve the likelihood that bonuses are paid for real savings rather than volatility, some contracts include provisions that reduce the shared percentage of observed savings. For example, Medicare Pioneer ACO and Shared Savings Program contracts include both minimum savings rates that must be achieved before providers receive bonuses (ranging from 1 to 3.9%, depending on ACO size) and maximum caps on the amount of bonus any provider can receive (ranging from 10 to 15% of expected costs in the Medicare ACO programs).7,8

Penalizing providers for cost overruns also makes shared savings contracts more symmetric. However, even in programs with downside risk for providers, some asymmetry generally persists. For example, when quality criteria are met the Medicare Pioneer ACO and Track 2 of the Medicare Shared Savings Program penalize providers 40% of the amount of cost overruns—less than the 60 to 70% bonuses triggered by savings.7,8

Limitations of Current Solutions

By limiting shared savings contracts to large providers, payers may miss opportunities to engage ambitious smaller ones (like primary care practices transforming into medical homes) in cost containment. In addition, the relative strengths and weaknesses of current solutions can be unclear. For example, how does excluding outliers compare with requiring a minimum savings rate before sharing begins? Is the answer the same for small primary care practices and large ACOs? What about combinations of these features? We believe a new tool can help evaluate a wide variety of shared savings arrangements and enable such contracts with small providers.

A New Solution: Selling Options

To allow a broad range of providers to enter asymmetric shared savings contracts without systematically disadvantaging payers, we propose to borrow a commonly used financial tool: the “call option.”10 When an investor wants to profit if a stock price climbs but not incur a loss if the price falls, he or she can purchase a call option that protects against downside risk. These options are not cost-free to the investor; instead, investors must pay for them.

Shared savings contracts present an analogous situation, and they might spread more rapidly if payers offer to sell “call options” to providers as a condition of entering such contracts. These options can be priced to counterbalance exactly payers’ expected losses due to random variation in healthcare costs, under any shared savings arrangement, with providers large and small. Once calculated, these option prices can clarify the business cases for both payers and providers, enabling construction of customized shared savings contracts when both parties are willing to negotiate.



Using total cost data from a large sample of members in a commercial health plan, we simulated differences between observed and expected costs due to chance, calculated the resulting shared savings bonus payments (ie, payments for volatility), estimated the average financial loss to payers causedby these bonus payments, and priced a call option to offset these expected losses. We then extended the simulation to scenarios where shared savings contracts caused “real savings” (ie, reductions in costs due to providers changing their care).

Data on Healthcare Costs

We obtained data on total healthcare spending in 2009 and 2010 for each continuously enrolled member of a large commercial health plan who was attributable to a pilot or control practice in a current medical home demonstration. By selecting patients attributable to primary care providers based on office visits, our patient sample consisted of those who might be included in shared savings contracts (and not those who would be impossible to attribute to a specific provider).7 To ensure that our simulations were not affected by the medical home demonstration, we excluded all patients attributed to pilot practices.

These spending data represented the total allowed amounts for all medical and prescription drug claims, including both the plan’s expenditures and any deductibles or coinsurance amounts paid by patients. Because we wanted to compare the financial impact of shared savings arrangements with fee-for-service payment, we excluded members of health plan products that featured other types of payment (eg, capitation). After exclusions, our study population comprised 77,364 patients.

Calculating Expected Costs

To simulate shared savings contracts, we first calculated the expected costs for each patient in 2010 based on his or her 2009 costs. To do this, we assumed perfect prediction of general medical inflation for the entire patient population. Our assumption of a population-level cost prediction model that cannot be improved allowed us to focus cleanly on how volatility in patient-level costs affected shared savings contracts.

Of the Medicare ACO programs, our method for calculated expected costs is most similar to the Pioneer demonstration, which also performs risk adjustment using same-patient historical expenditures.8 However, because commercially insured populations tend to be younger and healthier than Medicare beneficiaries (among other differences between these populations), we did not attempt to replicate exactly any Medicare ACO contracts.

Shared Savings Contracts

We simulated a variety of shared saving contracts, each defined by 5 key dimensions (Table 1): percentage of savings shared; minimum savings rate, with and without first-dollar sharing; shared savings bonus cap; cost outlier truncation; and provider penalties for cost overruns. The main analyses varied these dimensions 1 at a time, but in supplementary analyses we explored their combinations. Although shared savings contracts can be limited to just 1 kind of spending (eg, just outpatient care),4 our scenarios included comprehensive costs of care across all providers and types of services.

Simulating Shared Savings and Calculating Option Prices

To estimate the financial impact of shared savings contracts, we performed a bootstrap simulation by randomly drawing samples of patients from the study population. We simulated providers of many sizes by drawing samples ranging in size from 500 to 60,000 patients, with each sample representing a provider’s patient panel (or a “simulated provider,” for short).11 We included panel sizes smaller than 2000 (a size that might be expected for a solo primary care provider) because in general, a single health plan rarely will enroll a provider’s entire patient panel. For example, a shared savings contract between a solo practitioner and a plan enrolling 25% of his or her overall panel might include only 500 patients. Within each size category, we repeated this process 10,000 times, effectively generating 10,000 simulated providers.

For each simulated provider, we calculated total costs per patient in 2009 and 2010. Within each provider size category, we used the average ratio of 2009 to 2010 actual costs per patient (across all 10,000 simulated providers) to calculate an expected 2010 total cost for each simulated provider. We then calculated, for each simulated provider, the difference between actual and expected 2010 costs. If negative, this difference was “savings;” if positive, it was a “cost overrun.”

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