Table 2 Attributes used in the analysis
From: Discovering healthcare provider behavior patterns through the lens of Medicare excess charge
Attribute | Example/Definition |
|---|---|
Healthcare Provider | |
 Type (Specialty) | Cardiology, Family Practice, … |
 Gender | Male/Female |
 Credential | M.D.; D.O.; CRNP,… |
 Entity Code | Individual/Organization |
Medical Procedure | |
 Place of Service | Office/Facility |
 Service Volume | Number of services performed |
 Number of Unique Beneficiaries | Number of distinct Medicare beneficiaries receiving the service |
 Number of Visits | Number of distinct Medicare beneficiary/per day services |
 Number of Services Per Unique Beneficiarya | Number of Services per unique beneficiary |
 Number of Service Per Visita | Number of services per visit |
 Medicare Allowed Amount | Average of the Medicare allowed amount for the service |
 Submitted Charge Amount | Average of the charges that the provider submitted for the service |
 Medicare Payment Amount | Average amount that Medicare paid |
 Excess Charge Ratioa | Average Submitted Charge Amount/ Average Medicare Allowed Amount |
Medical Practice | |
 Total Number of Unique Procedures | Total number of unique services provided by the provider |
 Total Service Volume | Total services performed by the provider across all procedures |
 Total Number of Unique Beneficiaries | Total number of distinct Medicare beneficiaries serviced by the provider |
 Total Medicare Allowed Amount | Total Medicare allowed amount for all services |
 Total Submitted Charge Amount | Total charge the provider submitted for all services |
 Total Medicare Payment Amount | Total amount that Medicare paid to the provider |
 Overall Excess Charge Ratioa | Total Submitted Charge amount/ Total Medicare Allowed amount |
Demographic and Socioeconomic | |
 Location | Urban/Rural/Very Rural |
 Beneficiary Average Age | % of the provider’s beneficiaries qualifying for both Medicare and Medicaid |
 Beneficiary Male %a | % of male beneficiaries |
 Beneficiary Female %a | % of female beneficiaries |
 Beneficiary White %a | % of beneficiaries who identify themselves as non-Hispanic white |
 Beneficiary Average Risk Score | Average age of the beneficiaries serviced by the provider |
 Beneficiary Dual Percentagea | Average risk score of beneficiaries serviced by the provider |