Synthetic Pharmacy Prescription Orders

This dataset provides comprehensive, anonymized records of pharmacy prescription orders and medication fulfillment events, including patient, prescriber, medication, and pharmacy details. It enables robust analysis of medication adherence patterns and pharmacy workflow efficiency, supporting research, quality improvement, and operational analytics in healthcare settings.

  • last updated 22 Jul 2025
  • by GoMask
The brief that made it

Medication adherence analysis for population health management

Sample rows

preview · 8 of 200 rows · all 27 columns
prescription_idstringinsurance_typestringcopay_amountfloatadherence_flagbooleanpharmacy_statestringpatient_idstringprescriber_idstringpharmacy_idstringmedication_idstringmedication_namestringmedication_strengthstringmedication_formstringquantity_prescribedintegerdays_supplyintegerrefills_allowedintegerrefills_remainingintegerprescription_written_datedateprescription_expiration_datedatefulfillment_idstringfulfillment_datedatequantity_dispensedintegerpharmacist_idstringpickup_datedatepharmacy_street_addressstringpharmacy_citystringpharmacy_postal_codestringpharmacy_countrystring
RX000101private10trueILPAT0101DR101PHARMA021MED201Atorvastatin20mgtablet3030552023-01-102024-01-10FILL21012023-01-1130PHARM1012023-01-12100 Main StChicago60614USA
RX000102private15trueOHPAT0102DR102PHARMA022MED202Lisinopril10mgtablet909011112023-01-022024-01-02FILL21022023-01-0390PHARM1022023-01-0323 Oak AvenueCincinnati45219USA
RX000103government0trueMAPAT0103DR103PHARMA023MED203Metformin500mgtablet6060332023-01-142024-01-14FILL21032023-01-1560PHARM1032023-01-1645 Maple DrBoston02115USA
RX000104private7.5trueILPAT0104DR104PHARMA021MED204Levothyroxine75mcgtablet3030222023-02-142024-02-14FILL21042023-02-1530PHARM1042023-02-16100 Main StChicago60614USA
RX000105government0trueMOPAT0105DR105PHARMA024MED205Azithromycin250mgtablet66002023-02-202023-03-20FILL21052023-02-206PHARM1052023-02-20200 Elm StSpringfield65806USA
RX000106self-pay75falseOHPAT0106DR106PHARMA025MED206Amphetamine XR20mgextended-release tablet3030222023-02-252023-08-25FILL21062023-02-2630PHARM106blank309 King AveColumbus43201USA
RX000107private17trueMAPAT0107DR107PHARMA026MED207Albuterol90mcginhaler130112023-03-012024-03-01FILL21072023-03-021PHARM1072023-03-0419 Market StBoston02118USA
RX000108self-pay40falseCAPAT0108DR108PHARMA027MED208Omeprazole20mgcapsule2828112023-03-032024-03-03FILL21082023-03-0528PHARM108blank788 BroadwayLos Angeles90012USA

What the 200 rows show

from the 200-row sample

Self-pay (insurance type) stands out: mean copay_amount is 45.3, against 10.2 for the rest.

  • 81%adherence_flag = true
  • 13.0median copay_amount
  • 2pharmacy countries
  • 10medication forms
  • 45medication strengths
  • 55pharmacy cities
Mean copay_amount by insurance_type200 rows
0408014.0private121 rows0.0governme…26 rows45.3self-pay25 rows3.4other28 rows
copay_amount200 rows, in bands of 20
09018017115103001080140copay_amount →

Median 13.0, from 0.0 to 125.0.

pharmacy_state200 rows · top 10 of 28 values
  1. OH30
  2. ON21
  3. IL16
  4. MA14
  5. CA13
  6. TX12
  7. NY11
  8. MO8
  9. PA7
  10. CO7
27 columns by typefrom the column list below
  • string 16
  • integer 5
  • float 1
  • date 4
  • boolean 1

Columns

27 columns in four groups
blueprint · 27 columns
columntypedescriptionexample
Text 16 columns
prescription_idstringUnique identifier for each prescription orderuniqueRX000101
patient_idstringAnonymized unique identifier for each patientPAT0101
prescriber_idstringAnonymized unique identifier for the healthcare provider who prescribed the medicationDR101
pharmacy_idstringUnique identifier for the pharmacy fulfilling the prescriptionPHARMA021
medication_idstringUnique identifier for the prescribed medicationMED201
medication_namestringGeneric or brand name of the medicationAtorvastatin
medication_strengthstringStrength of the medication (e.g., 500mg, 10mg/mL)20mg
medication_formstringForm of the medication (e.g., tablet, capsule, liquid)10 formstablet
fulfillment_idstringUnique identifier for each fulfillment event (including original and refills)uniqueFILL2101
pharmacist_idstringAnonymized unique identifier for the pharmacist who processed the fulfillmentPHARM101
insurance_typestringType of insurance used for the prescription (e.g., private, government, self-pay)private · government · self-pay · other · optionalprivate
pharmacy_street_addressstringStreet address of the pharmacyoptional100 Main St
pharmacy_citystringCity where the pharmacy is locatedoptionalChicago
pharmacy_statestringState where the pharmacy is locatedoptionalIL
pharmacy_postal_codestringPostal code of the pharmacy locationoptional60614
pharmacy_countrystringCountry where the pharmacy is located2 countries · optionalUSA
Numbers 6 columns
quantity_prescribedintegerNumber of units prescribed1 or more30
days_supplyintegerNumber of days the prescription is intended to last1 or more30
refills_allowedintegerNumber of refills authorized by the prescriber0 or more5
refills_remainingintegerNumber of refills remaining at the time of fulfillment0 or more5
quantity_dispensedintegerNumber of medication units dispensed in this fulfillment1 or more30
copay_amountfloatAmount paid by the patient for the prescription0 or more · optional10
Dates and times 4 columns
prescription_written_datedateDate the prescription was written by the prescriber2023-01-10
prescription_expiration_datedateDate after which the prescription is no longer valid2024-01-10
fulfillment_datedateDate the prescription was filled at the pharmacy2023-01-11
pickup_datedateDate the patient picked up the medication (if applicable)optional2023-01-12
True or false 1 column
adherence_flagbooleanIndicates if the patient picked up the medication within the recommended window (true/false)optionaltrue

Use it for

  • adherence flag81%162 of 200 rowsmean copay amount by …14.0priv…0.0gove…45.3self…3.4other

    A healthcare dashboard

    The adherence_flag rate, copay_amount by insurance_type and a breakdown of pharmacy_state. Excel, Power BI or Tableau.

  • Why do the 25 self-pay rows have a mean copay_amount of 45.3?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable prescriptions with patient_id, prescriber_id and pharmacy_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

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This dataset200 rows27 columns
Yours1,000 rows27 columnspharmacy_street_address: UK only

blueprint · synthetic-pharmacy-prescription-orders

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 27 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Medication type impacts refill frequency
  • Prescriber specialty influences order patterns
  • Insurance coverage status included
  • Pick-up vs mail order tracked
  • Drug interaction warnings generated
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
synthetic-pharmacy-prescription-orders

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