EHR Patient Demographics and Registration

This dataset provides comprehensive patient demographic and registration data for healthcare organizations, including unique identifiers, contact details, emergency contacts, insurance information, and race/ethnicity. Designed for master patient indexing, it supports accurate patient identification, care coordination, and regulatory reporting, making it invaluable for clinical workflows and analytics.

  • last updated 2 Nov 2025
  • by GoMask
The brief that made it

Master patient index creation and maintenance

Sample rows

preview · 8 of 100 rows · all 27 columns
patient_idstringgenderstringemergency_contact_relationshipstringfirst_namestringmiddle_namestringlast_namestringdate_of_birthdateaddress_streetstringaddress_citystringaddress_statestringaddress_postal_codestringaddress_countrystringphone_primarystringphone_secondarystringemailstringemergency_contact_namestringemergency_contact_phonestringinsurance_providerstringinsurance_policy_numberstringinsurance_group_numberstringpreferred_languagestringracestringethnicitystringssnstringmedical_record_numberstringregistration_datedatetimeactive_statusboolean
PAT-10001femaleSpouseLindaAnneSimmons1980-05-17321 Oak StSeattleWA98101USA+1-206-555-1482+1-206-555-2482linda.simmons80@gmail.comPaul Simmons+1-206-555-6482UnitedHealthcareUHC5748392AGRP-99824EnglishWhiteNon-Hispanic537-24-1948MRN-32001012023-11-18T13:22:15true
PAT-10002maleMotherMiguelblankHernandez1992-08-02401 Pine AveSan DiegoCA92103USA+1-619-555-0034blankmiguel.hernandez92@outlook.comMaria Hernandez+1-619-555-1034Blue Cross Blue ShieldBCBS838273BCBS-10029SpanishWhiteHispanic637-56-9932MRN-32001022024-02-07T10:09:45true
PAT-10003femaleBrotherAishaFatimaAli1975-03-221123 Maple DrHoustonTX77005USA+1-713-555-0291+1-713-555-1291aisha.ali75@icloud.comImran Ali+1-713-555-2291AetnaAET-750223AETN-12209EnglishAsianNon-Hispanic451-71-2047MRN-32001032024-03-19T15:20:36true
PAT-10004maleWifeDavidMichaelJones1962-11-1389 Elm StDenverCO80203USA+1-303-555-4902blankdavidmjones62@gmail.comSusan Jones+1-303-555-5902blankblankblankEnglishWhiteNon-Hispanic101-65-3928MRN-32001042024-04-10T09:11:12true
PAT-10005femaleFatherGraceElizabethKim1988-06-291870 Willow RdPortlandOR97210USA+1-503-555-0192+1-503-555-1192gracekim88@ymail.comDaniel Kim+1-503-555-2192Kaiser PermanenteKP-2201384KP-80132KoreanAsianNon-Hispanic352-44-1087MRN-32001052024-04-05T17:25:15true
PAT-10006maleblankBrandonblankNguyen2002-01-19530 Birch AveSacramentoCA95814USA+1-916-555-3982blankbrandon.nguyen02@protonmail.comblankblankCignaCGN-4209921CGN-30492VietnameseAsianNon-Hispanic642-23-2911MRN-32001062024-02-15T11:43:22true
PAT-10007maleDaughterSamuelLeePeterson1955-04-08212 Cherry LnMinneapolisMN55401USA+1-612-555-8820blanksam.peterson1955@gmail.comKaren Peterson+1-612-555-9820MedicareMED-8820321MED-20032EnglishWhiteNon-Hispanic278-90-1045MRN-32001072023-12-03T16:44:11true
PAT-10008femaleMotherEmilyRoseClark1999-09-10822 Aspen RdBostonMA02110USA+1-617-555-2108+1-617-555-3108emilyrclark99@icloud.comSarah Clark+1-617-555-4108Harvard PilgrimHP-1092341HP-80210EnglishWhiteNon-Hispanic202-44-7890MRN-32001082023-11-01T14:10:22true

What the 100 rows show

from the 100-row sample
  • 4races
  • 4ethnicities
  • 7preferred languages
gender100 rows by value
0255049male49%50female50%1other1%
emergency_contact_relationship99 rows with a value · 1 left blank
  1. Mother40
  2. Wife20
  3. Father19
  4. Spouse5
  5. Brother5
  6. Husband5
  7. Daughter2
  8. Sister2
  9. Sibling1
27 columns by typefrom the column list below
  • string 24
  • date 1
  • datetime 1
  • boolean 1

Columns

27 columns in three groups
blueprint · 27 columns
columntypedescriptionexample
Text 24 columns
patient_idstringMaster patient index unique identifier for each patientuniquePAT-10001
first_namestringPatient's legal first nameLinda
middle_namestringPatient's middle nameoptionalAnne
last_namestringPatient's legal last nameSimmons
genderstringPatient's gender identitymale · female · other · unknownfemale
address_streetstringPatient's residential street address321 Oak St
address_citystringPatient's residential citySeattle
address_statestringPatient's residential state or provinceWA
address_postal_codestringPatient's residential postal or ZIP code98101
address_countrystringPatient's country of residenceUSA
phone_primarystringPatient's primary contact phone number+1-206-555-1482
phone_secondarystringPatient's secondary contact phone numberoptional+1-206-555-2482
emailstringPatient's email addressoptionalaisha.ali75@icloud.com
emergency_contact_namestringFull name of patient's emergency contactoptionalPaul Simmons
emergency_contact_relationshipstringRelationship of emergency contact to patient9 relationships · optionalSpouse
emergency_contact_phonestringPhone number of emergency contactoptional+1-206-555-6482
insurance_providerstringName of patient's primary insurance provideroptionalUnitedHealthcare
insurance_policy_numberstringPatient's insurance policy numberoptionalUHC5748392A
insurance_group_numberstringPatient's insurance group numberoptionalGRP-99824
preferred_languagestringPatient's preferred language for communication7 languages · optionalEnglish
racestringPatient's self-identified race4 races · optionalWhite
ethnicitystringPatient's self-identified ethnicity4 ethnicities · optionalNon-Hispanic
ssnstringPatient's Social Security Number (if applicable)unique · optional537-24-1948
medical_record_numberstringPatient's medical record number (MRN)unique · optionalMRN-3200101
Dates and times 2 columns
date_of_birthdatePatient's date of birth1980-05-17
registration_datedatetimeDate and time when patient was registered2023-11-18T13:22:15
True or false 1 column
active_statusbooleanIndicates if the patient is currently active in the systemtrue

Use it for

  • rows10027 columnsrows by gender49male50female1other

    A healthcare dashboard

    A breakdown of emergency_contact_relationship. Excel, Power BI or Tableau.

  • What pattern can you find in 100 rows?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 100 rows.

  • A software demo

    Believable patients with first_name, middle_name and last_name to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 27 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset100 rows27 columns
Yours1,000 rows27 columnsaddress_street: UK only

blueprint · ehr-patient-demographics-and-registration

Behind this dataset

Same schema. As many rows as you need.

These 100 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
  • Medical Record Number (MRN) unique per facility or health system
  • Patient name: legal first, middle, last, suffix
  • Date of birth required for age calculation
  • Social Security Number (SSN) optional, used for identity verification
  • Gender: male, female, other, unknown, decline to state
  • Race and ethnicity per OMB categories for meaningful use
  • Preferred language for interpreter services
  • Primary insurance and secondary insurance details
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
ehr-patient-demographics-and-registration

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