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Table 1 Description of features chosen from the Medicare datasets

From: The effects of class rarity on the evaluation of supervised healthcare fraud detection models

Datasets Feature Description Type
Combined Part B npi* Unique provider identification number Categorical
provider_type Medical provider’s specialty (or practice) Categorical
nppes_provider_gender Provider’s gender Categorical
line_srvc_cnt Number of procedures/services the provider performed Numerical
bene_unique_cnt Number of distinct Medicare beneficiaries receiving the service Numerical
bene_day_srvc_cnt Number of distinct Medicare beneficiary / per day services performed Numerical
average_submitted_chrg_amt Average of the charges that the provider submitted for the service Numerical
average_medicare_payment_amt Average payment made to a provider per claim for the service performed Numerical
Part D npi* Unique provider identification number Categorical
specialty_description Medical provider’s specialty (or practice) Categorical
bene_count Number of distinct Medicare beneficiaries receiving the drug Numerical
total_claim_count Number of drug the provider administered Numerical
total_30_day_fill_count Number of standardized 30-day fills Numerical
total_day_supply Number of day’s supply Numerical
total_drug_cost Cost paid for all associated claims Numerical
DMEPOS referring_npi* Unique provider identification number Categorical
referring_provider_type Medical provider’s specialty (or practice) Categorical
referring_provider_gender** Provider’s gender Categorical
number_of_suppliers Number of suppliers used by provider Numerical
number_of_supplier_beneficiaries Number of beneficiaries associated by the supplier Numerical
number_of_supplier_claims Number of claims submitted by a supplier due to an order by a referring order Numerical
number_of_supplier_services Number of services/products rendered by a supplier Numerical
avg_supplier_submitted_charge Average payment submitted by a supplier Numerical
avg_supplier_medicare_pmt_amt Average payment awarded to suppliers Numerical
All Exclusion Fraud labels from the LEIE database Categorical
  1. * Not used in building models
  2. ** Not used in the combined dataset