BuyRxData - Prescription Buyer Insights

This Prescription Discount Card Claims Data package offers a comprehensive view into consumer behavior and pharmacy activity related to prescription and over-the-counter medications in the U.S. The dataset captures detailed claim-level transactions, reflecting real-world medication access patterns outside of traditional insurance channels. It includes demographic breakdowns of members, granular pricing data tied to specific National Drug Codes (NDCs), and geographic distribution of claim volumes across pharmacy locations. With insights into both the demand and cost dimensions of drug utilization, this dataset supports robust analysis for healthcare, pharmaceutical, and market research applications. All data is fully de-identified and HIPAA compliant. Data Fields:

id: Unique identifier for the claim

member_gender: Gender of the member ( M, F)

member_state: State of residence of the member (e.g., CA, NV, NY)

member_age_group: Age group bucket for the member (e.g., 0-24 Y, 25-34 Y, 35-44 Y, 45-54 Y, 55-64 Y, 65+ Y)

master_member_date_submitted: Date the member first submitted a claim through us.

master_repeat_usage: Indicates if the member has used us before (e.g., New, Repeat)

unique_member: Indicates if the member information added is unique and entered properly (Boolean )

date_filled: Date the prescription was filled

date_submitted: Date the claim was submitted

weekday: Day of the week the claim was submitted

date_submitted_month: Month the claim was submitted as date, always first day of the month (e.g., 2023-01-12 = 2023-01-01)

created_date: Date the record was created in the system

changed_date: Date the record was last modified in the system

rxclaim_actual_status: Final status of the claim (e.g., Paid, Reversed)

refill_number: Refill sequence number of the prescription

refill_maximum: Total number of refills allowed

pharmacy_id: Internal identifier for the pharmacy

pharmacy_name: Name of the dispensing pharmacy

pharmacy_ncpdp_id: NCPDP (National Council for Prescription Drug Programs) ID

pharmacy_npi: National Provider Identifier for the pharmacy

pharmacy_address_1: Primary street address of the pharmacy

pharmacy_address_2: Additional address info (suite, etc.)

pharmacy_city: City where the pharmacy is located

pharmacy_state: State where the pharmacy is located

pharmacy_zip: ZIP code of the pharmacy

drug_id: Internal identifier for the drug

drug_name: Brand or generic name of the drug

drug_ndc: National Drug Code identifier

drug_gpi: Generic Product Identifier

drug_group_description_gpi_02: Drug class or group based on GPI-02 level

drug_therapeutic_class_name: Therapeutic class the drug belongs to

drug_strength: Strength or dosage of the drug (e.g., 10mg)

drug_form: Physical form of the drug (e.g., tablet, capsule)

drug_name_and_strength: Combined name and strength for display

drug_dea_code: DEA classification code (e.g., controlled substance)

drug_maintenance_code: Indicates maintenance vs acute medication

mony: Multi-Source Indicator code

brand_generic_code: Indicates if the drug is brand or generic

daw_code: Dispense As Written code (provider instruction)

speciality_non_speciality_code: Indicates if the drug is specialty or non-specialty

total_quantity: Total quantity dispensed in the claim

total_days_supply: Total number of days supplied

avg_quantity_day: Average quantity per day(total_quantity/total_days_supply)

net_rxs: Net claims after adjustments

total_rxs: Total number of prescriptions associated with the claim

gross_rxs: Paid Claim's Total Rxs when not reversed on the same day.

uc_rxs: Usual and Customary prescription count

total_drug_cost: Total drug cost billed

total_awp_cost: Total cost based on Average Wholesale Price

total_ingredient_cost: Total cost of the drug ingredients

total_dispensing_fee: Total pharmacy dispensing fee

total_sales_tax: Sales tax charged on the prescription

total_incentive_fee: Incentive fee paid to the pharmacy (if applicable)

total_plan_paid: Amount paid by the health plan

total_deductible: Deductible portion paid by the member

total_member_paid: Total paid out-of-pocket by the member

total_copay: Copayment amount

uc_amount: Usual and Customary amount

member_savings: Total savings for the member

member_savings_percent: Member savings as a percentage

awp_unit_cost: Unit cost based on AWP

wac: Wholesale Acquisition Cost

retail_30_90_days_supply: Indicates if supply is 30 or 90 days supply

transaction_provider_id: Internal identifier for the provider

transaction_bin_id: Internal identifier for the Bank Identification Number(BIN)

transaction_client_id: Internal identifier for the client

transaction_owner_id: Internal identifier for the owner

transaction_group_id: Internal identifier for the group

reversal_date_submitted: Date the paid claim was reversed (if applicable)

reversed: Boolean flag indicating if the claim was reversed

days_to_reverse: Number of days between paid and reversal date of a paid claim

paid_tx_id: ID of the original paid transaction (used in reversal linking)

created_master_member: Boolean flag indicating this claim created a new member in the database

Potential Use Cases:

In-depth insights into prescription and over-the-counter drug usage among uninsured and underinsured patients in the U.S., with demographic details such as member gender, state, and age group.

Comprehensive drug pricing data by National Drug Code (NDC), including metrics like Average Wholesale Price, Wholesale Acquisition Cost, Usual and Customary Price, and Total Member Paid.

Claim volume by pharmacy location, including total prescriptions filled and full address details—enabling regional performance analysis and targeting of high-traffic sites.

Sample SQL Query(Top 10 Drugs for uninsured and underinsured California Residents. Grouped by Member Age Group and Gender):

WITH RankedDrugs AS (
  SELECT
    MEMBER_AGE_GROUP,
    MEMBER_GENDER,
    DRUG_NAME,
    SUM(TOTAL_RXS) AS TOTAL_RXS_SUM,
    ROW_NUMBER() OVER (
      PARTITION BY MEMBER_AGE_GROUP, MEMBER_GENDER
      ORDER BY SUM(TOTAL_RXS) DESC
    ) AS rn
  FROM
    MARKETPLACE_LISTING_DATA_TRANSACTION_CLAIMS.PUBLIC.TRANSACTIONS_CLAIMS
  WHERE
    DATE_SUBMITTED BETWEEN '2023-01-16' AND '2023-01-22'
    AND PHARMACY_STATE = 'CA'
    AND RXCLAIM_ACTUAL_STATUS = 'Paid'
    AND MEMBER_GENDER IN ('M', 'F')
  GROUP BY
    MEMBER_AGE_GROUP,
    MEMBER_GENDER,
    DRUG_NAME
)
SELECT
  MEMBER_AGE_GROUP,
  MEMBER_GENDER,
  DRUG_NAME,
  TOTAL_RXS_SUM
FROM
  RankedDrugs
WHERE
  rn <= 10
ORDER BY
  MEMBER_AGE_GROUP,
  MEMBER_GENDER,
  TOTAL_RXS_SUM DESC;