Prescription Adherence Monitoring

This dataset provides detailed tracking of patient prescription refills, medication details, and adherence assessments, enabling healthcare providers to identify and intervene with at-risk patients. It includes patient demographics, prescription and refill information, adherence scoring, and provider/pharmacy details, supporting comprehensive analysis of medication adherence patterns and outcomes.

  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Identifying patients at risk of poor medication adherence for targeted intervention

Sample rows

preview · 8 of 80 rows · all 21 columns
adherence_idstringadherence_statusstringadherence_scorefloatintervention_flagbooleanmedication_dosestringpatient_idstringpatient_birth_datedatepatient_genderstringprescription_idstringmedication_namestringmedication_frequencystringprescription_start_datedateprescription_end_datedateprescribing_provider_idstringpharmacy_idstringrefill_numberintegerrefill_datedatedays_supplyintegerexpected_next_refill_datedateactual_next_refill_datedatenotesstring
ADH-001on-time1false500mgPAT-10011963-07-14femaleRX-4001Metformintwice daily2023-10-012024-10-01PRV-2001PHM-300102023-10-01302023-10-312023-10-31Initial fill, patient instructed on adherence
ADH-002late0.78true10mgPAT-10021980-01-22maleRX-4002Lisinoprilonce daily2023-09-152024-09-15PRV-2002PHM-300202023-09-15302023-10-152023-10-17Patient notified about late refill
ADH-003early0.95false20mgPAT-10031956-11-02femaleRX-4003Atorvastatinonce nightly2023-06-102024-06-10PRV-2003PHM-300312023-07-10302023-08-092023-08-07Refilled two days early
ADH-004late0.75true75mcgPAT-10041972-03-30maleRX-4004Levothyroxineonce daily2023-03-012024-03-01PRV-2004PHM-300422023-05-01902023-07-302023-08-10Late refill, flagged for follow-up
ADH-005on-time0.98false500mgPAT-10011963-07-14femaleRX-4001Metformintwice daily2023-10-012024-10-01PRV-2001PHM-300512023-10-31302023-11-302023-11-30Good adherence, no issues
ADH-006late0.79true5mgPAT-10051990-05-12maleRX-4005Amlodipineonce daily2023-12-012024-12-01PRV-2005PHM-300102023-12-01302023-12-312024-01-011 day late; patient reported travel
ADH-007on-time0.99false50mgPAT-10062002-08-19femaleRX-4006Sertralineonce daily2023-11-102024-11-10PRV-2006PHM-300202023-11-10302023-12-102023-12-09Consistent with therapy
ADH-008late0.74true20mgPAT-10071975-02-14maleRX-4007Simvastatinonce daily2023-04-102024-04-10PRV-2007PHM-300312023-05-10302023-06-092023-06-17Late refill; discussed with patient

What the 80 rows show

from the 80-row sample

Missed (adherence status) stands out: mean adherence_score is 0.34, against 0.88 for the rest.

  • 51%intervention_flag = true
  • 0.81median adherence_score
  • 4patient genders
  • 6medication frequencies
  • 30median days_supply
Mean adherence_score by adherence_status80 rows
00.510.97on-time31 rows0.77late29 rows0.95early8 rows0.34missed12 rows
adherence_score80 rows, in bands of 0.1
02040500005323539intervention_flag below 0.900.50.9adherence_score →

Every row with adherence_score under 0.9 has intervention_flag = true. None above it.

medication_dose80 rows · top 10 of 27 values
  1. 10mg11
  2. 20mg10
  3. 5mg6
  4. 50mg6
  5. 25mg6
  6. 500mg5
  7. 100mg5
  8. 40mg4
  9. 2mg3
  10. 75mg3
21 columns by typefrom the column list below
  • string 11
  • integer 2
  • float 1
  • date 6
  • boolean 1

Columns

21 columns in four groups
blueprint · 21 columns
columntypedescriptionexample
Text 11 columns
adherence_idstringUnique identifier for each prescription adherence recorduniqueADH-001
patient_idstringUnique identifier for the patientPAT-1001
patient_genderstringPatient's gendermale · female · other · unknownfemale
prescription_idstringUnique identifier for the prescriptionRX-4001
medication_namestringName of the prescribed medicationMetformin
medication_dosestringDosage of the medication as prescribed (e.g., 10mg, 1 tablet)500mg
medication_frequencystringFrequency of medication intake (e.g., once daily, twice daily)6 frequenciestwice daily
prescribing_provider_idstringUnique identifier for the prescribing healthcare providerPRV-2001
pharmacy_idstringUnique identifier for the pharmacy where the prescription is filledPHM-3001
adherence_statusstringAssessment of adherence for this refill (on-time, late, early, missed)on-time · late · early · missedon-time
notesstringAdditional notes or comments from provider or pharmacistoptionalRefilled two days early
Numbers 3 columns
refill_numberintegerThe sequential number of the refill (0 for initial fill, 1 for first refill, etc.)0 or more0
days_supplyintegerNumber of days the refill is expected to last1 or more30
adherence_scorefloatQuantitative adherence score (e.g., proportion of days covered, between 0 and 1)0 to 1 · optional1
Dates and times 6 columns
patient_birth_datedatePatient's date of birth1963-07-14
prescription_start_datedateDate when the prescription was first issued2023-10-01
prescription_end_datedateDate when the prescription is scheduled to endoptional2024-10-01
refill_datedateDate when the prescription was refilled2023-10-01
expected_next_refill_datedateCalculated date when the next refill is due based on days_supply2023-10-31
actual_next_refill_datedateActual date when the next refill was obtained (if available)optional2023-10-31
True or false 1 column
intervention_flagbooleanIndicates if provider intervention is recommended for this patient/prescriptionfalse

Use it for

  • intervention f…51%41 of 80 rowsmean adherence score …0.97on-t…0.77late0.95early0.34miss…

    A healthcare dashboard

    The intervention_flag rate, adherence_score by adherence_status and a breakdown of medication_dose. Excel, Power BI or Tableau.

  • Why do the 12 missed rows have a mean adherence_score of 0.34?

    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 adherences with patient_id, patient_birth_date and patient_gender to fill a screen in front of a buyer.

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This dataset80 rows21 columns
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blueprint · prescription-adherence-monitoring

Behind this dataset

Same schema. As many rows as you need.

These 80 rows came out of a blueprint — 21 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
  • Record refill date and scheduled refill date
  • Mark refills delayed by over 7 days as non-adherent
  • Capture medication type and dosage
  • Link patient demographics to refill history
  • Flag non-adherence for clinician follow-up
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
prescription-adherence-monitoring

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