Why Benchmarks Change
Market data is an efficient and cost effective way to structure a physician contracting compliance program, and is used by hundreds of hospitals across the country. Among the perks of using market data are consistency, accessibility, and flexibility.
As long as the database used to calculate payment benchmarks is both large and diverse, benchmarks typically remain stable from year to year. However, there are several factors that may change benchmarks from year to year, like a significant increase in the sample size or changes in the market. It is always important to document FMV compliance, even if benchmarks shift.
By understanding why benchmarks may change from year to year, you can prepare for these changes within your compliance plan. Having a process in place to deal with potentially challenging conversations will help facilitate the process.
Why Benchmarks Can Change:
Benchmarks can change from year to year, significant shifts are uncommon.
Overall, we have found that the average change for any benchmark, whether that be compensation or hours worked, at the 50th or 75th percentile is 5%. This 5% change in contracts can often be accounted for by:
- General salary inflation and cost of living increases.
- Shift in responsibilities for a physician role, whether that be increased or decreased responsibilities.
- Change in hospital characteristics. For example, if a hospital adds more beds or moves from a level 3 trauma center to a level 2 trauma center, the burden of call is going to be more significant and likely will require a higher payment.
- New counterparty in a contract.
It is also important to take into account that most contracts have 2-3 year terms. This means that contract values do not increase or decrease in a linear fashion, the contract value changes in steps up or down.
In some cases, adding one contract can change the benchmarks.
Even in large sample sizes, when contract values are clustered at multiple different values, sometimes adding one new contract can shift the benchmarks considerably. This is best illustrated by an example. If we have five contracts with values of $150, $150, $150, $1,000, and $2,000, the 75th percentile is calculated as $787.50, as seen below. MD Ranger would round this benchmark to $790. If we are evaluating a contract with the value of $650, it would fall below the 75th percentile in this case.
If we add a fourth contract with the value $150, then the 75th percentile drops to $575. Now, that same $650 contract is above the 75th percentile and could be considered risky.
Even in a large sample size, if the contract values are clustered, one new contract can shift the benchmarks.
A data set which has a larger, diverse sample size will be less volatile than a data set with a small sample size. Sometimes data sets can appear larger and more diverse than they actually are. For example, if the data are collected from physicians, it is important to look not only at the number of physicians included but how many medical groups are represented. Medical groups often negotiate a single payment rate with a hospital, thus making the data set less diverse than it seems.
If the data is collected from hospitals, make sure that there are data from at least five health systems and/or independent facilities included. Typically, dozens of individual physician contracts are included in a sample from this many hospitals. Since physicians from the same medical group may get paid the same rate, or a health system may have a policy to pay physicians the same amount for call coverage or medical direction, it's important to ensure a good sample of hospital corporations or systems in the data. The larger the data set, the more safeguards you have for ensuring high quality data.
Dealing with Changing Benchmarks:
If the contract was within fair market value when signed, and documentation exists, payment rates can remain as is until the contract expires.
This is when documentation becomes crucial. If you document the benchmark data and that the value of a contract was fair market value when the contract was signed, it is compliant until the contract expires. At this time, if the contract is still below the 75th or the 90th percentile, the payment rate may still be compliant. If the rate is now too high and you cannot negotiate it lower, consider documenting the value of the contract to the organization, general inflation rates, and the changes in the benchmark data.
Be strategic while setting payment rates.
Perhaps your organization has determined that rates at or below the 75th percentile is considered compliant. That doesn't mean that every contract signed should be at the 75th percentile. Allow some wiggle room by negotiating a rate between the 50th and 75th percentile. If rates fluctuate over time, you have some cushion before the rate becomes problematic. This is especially true if the service in question comes from a smaller data set, given that these rates are more likely to fluctuate.
Document why the situation is unique.
A high rate can be justified when the situation is unique. Maybe there are a limited number of physicians in a particular specialty in the area, there is a high burden for taking call, or the payer mix is unfavorable. These can all be legitimate reasons for high rates; after all, someone has to be at the 90th percentile in all benchmarks. However, all payment rates above the 90th percentile need thorough documentation.
Demonstrate the effort to negotiate the lowest possible rate.
Documenting conversations and efforts made to set a payment rate that is fair market value is essential. If you are unable to successfully lower the rate to an amount you are comfortable calling fair market value, take special care to document conversations. Note who met with whom, and explain the attempts made to negotiate lower rates.