Benchmarks That Mirror the Market

FAIR Health employs recognized statistical methodologies to create our FH® Benchmarks. In addition to our in-house staff of mathematicians and statistical and clinical experts, we consult with independent healthcare economists and statisticians-all leaders in their fields-to gain an external perspective on our methodologies. In fulfillment of our mission of transparency, we make our methodologies available to the public.

Creating Benchmark Products

To create the FH Benchmarks, we organize the claims data we receive by procedure code and geographic area. We group our data into 493 geozips—geographic areas typically based on the first three digits of a zip code or group of zip codes. FAIR Health employs a statistical outlier methodology to exclude any extremely low and extremely high values that might otherwise distort the distribution of data. All of our benchmarks are based on a recent 12-month window of claims and arerefreshed every6 months.

FH Benchmarks Methodology

FAIR Health uses two methodologiesto create FH Benchmarks:

• Actual methodology. When there is a sufficient number of values for a procedure in a geozip, actual values reported on claims for procedure code/geozip combinations are arrayed from lowest to highest to determine percentiles. A percentile is a position in a distribution of values below which a specified percentage of the values fall. For example, in a distribution of 100 values, 70 percent of the values are equal to or below the value in the 70th position—the 70th percentile.
• Derived methodology. When data do not meet frequency and validation thresholds, percentiles may be derived mathematically.

Learn more about the methodologies FAIR Health uses to create benchmarks.