Patient Chronic Illness Progression

This dataset provides detailed, longitudinal records of patients with chronic illnesses, capturing demographic information, diagnoses, visit-level observations, treatments, laboratory results, and outcomes. Designed for healthcare research and predictive analytics, it enables tracking of disease progression, treatment efficacy, and patient outcomes over time.

  • last updated 21 Jul 2025
  • by GoMask
The brief that made it

Predictive modeling of chronic disease progression and patient outcomes

Sample rows

preview · 8 of 216 rows · all 28 columns
patient_idstringoutcome_statusstringsymptom_severity_scorefloathospitalizationbooleanrace_ethnicitystringfirst_namestringlast_namestringdate_of_birthdatesexstringdiagnosis_codestringdiagnosis_datedatevisit_idstringvisit_datedateprovider_idstringprovider_specialtystringmedication_namestringmedication_dosagestringlab_test_namestringlab_test_resultfloatlab_test_unitstringhospitalization_reasonstringaddress_streetstringaddress_citystringaddress_statestringaddress_postal_codestringaddress_countrystringdiagnosis_descriptionstringclinical_notesstring
P0001worsened8.3trueHispanic/LatinoCarlosMendez1955-02-11maleI50.92016-03-21V0001A2023-04-15D1023CardiologyFurosemide40mg once dailyBNP520pg/mLAcute decompensated heart failure episode32 Calle de la PazMadridMadrid28013SpainHeart failure, unspecified type, chronicPatient reports increased shortness of breath and some swelling in his ankles. Symptoms have gradually worsened over the last month.
P0002stable6.7falseSouth AsianAyeshaChopra1987-09-25femaleE11.92018-05-19V0002A2022-12-02D2456EndocrinologyMetformin1000mg twice dailyHbA1c7.2%blank10 Shanti GardensMumbaiMaharashtra400001IndiaType 2 diabetes mellitus without complicationsBlood glucose slightly elevated. Patient is adhering to prescribed medication and diet. Encouraged continued lifestyle changes.
P0003stable5falseWhiteJamesO'Connor1973-06-30maleJ45.402009-10-12V0003A2023-01-23D3098PulmonologyFluticasone110mcg twice dailyFEV12.8Lblank412 Maple AvenueBostonMA02118USAModerate persistent asthma without complicationPatient experienced mild wheezing and cough during the winter. Inhaler use has increased but no ER visits.
P0004improved4.1falseArabFatimaAl-Farsi2008-11-14femaleE10.92017-08-30V0004A2022-09-03D1120Pediatric EndocrinologyInsulin glargine12U at bedtimeHbA1c6.8%blank99 Al Sahil RoadMuscatMuscat113OmanType 1 diabetes mellitus without complicationsGlucose control is improving with recent insulin regimen adjustments. No recent hypoglycemic events.
P0005improved5.9falseVietnameseLindaNguyen1999-03-15femaleF32.12020-01-10V0005A2023-02-12D2872PsychiatrySertraline50mg once dailyblankblankblankblank77 Le Loi StreetHo Chi Minh CityHo Chi Minh700000VietnamMajor depressive disorder, moderate episodeThe patient reports improved mood and energy. Sleep and appetite are normalizing. Continue current treatment.
P0006worsened7.8falseWest AfricanMusaDiallo1964-07-18maleN18.42015-09-07V0006A2022-10-26D1835NephrologyLisinopril20mg once dailyCreatinine3.2mg/dLblank12 Avenue de la PaixDakarDakar10200SenegalChronic kidney disease, stage 4Renal function deteriorating. Discussed dialysis options and dietary restrictions.
P0007worsened9.1trueRussianElenaVolkova1951-01-05femaleG30.92017-11-18V0007A2023-03-20D1201GeriatricsDonepezil10mg once dailyblankblankblankProgressive cognitive decline requiring observation23 Prospekt MiraMoscowMoscow101000RussiaAlzheimer’s disease, unspecifiedPatient shows further memory loss and needs assistance with daily activities. Family advised on care strategies.
P0008stable7.2falseMiddle EasternZainKhalil1977-10-21maleJ44.92018-04-26V0008A2023-02-11D1999PulmonologyTiotropium18mcg once dailyO2 Sat95%blank7 Al Hamra StreetBeirutBeirut2020LebanonChronic obstructive pulmonary disease, unspecifiedPatient reports frequent cough and mild chest tightness. Oxygen saturation stable at rest.

What the 216 rows show

from the 216-row sample

Worsened (outcome status) stands out: 37 of its 48 rows have hospitalization = true, against 12 of 167 for the rest.

  • 23%hospitalization = true
  • 6.0median symptom_severity_score
  • 3sexes
  • 15lab test units
  • 17provider specialties
  • 31lab test names
Hospitalization rate by outcome_statushospitalization = true
0%50%100%8%stable6 of 780%improved0 of 8377%worsened37 of 48100%deceased6 of 6

Worsened (outcome status)'s mean symptom_severity_score is 8.4, against 6.2 for stable, 4.5 for improved and 9.4 for deceased.

symptom_severity_score215 rows, in bands of 1
02550316172841312933171610symptom_severity_score →

Median 6.0, from 1.6 to 9.8.

race_ethnicity215 rows with a value · 1 left blank
  1. White78
  2. Arab21
  3. Black17
  4. Latino7
  5. Vietnamese6
  6. East Asian6
  7. Hispanic6
  8. Asian6
  9. Latina6
  10. South Asian5
28 columns by typefrom the column list below
  • string 22
  • float 2
  • date 3
  • boolean 1

Columns

28 columns in four groups
blueprint · 28 columns
columntypedescriptionexample
Text 22 columns
patient_idstringUnique identifier for each patient in the datasetuniqueP0001
first_namestringPatient's first nameCarlos
last_namestringPatient's last nameMendez
sexstringPatient's biological sexmale · female · other · unknownmale
race_ethnicitystringPatient's self-identified race or ethnicityoptionalHispanic/Latino
diagnosis_codestringStandardized code for the chronic illness (e.g., ICD-10)I50.9
diagnosis_descriptionstringText description of the diagnosed chronic illnessObesity, unspecified
visit_idstringUnique identifier for each patient visit or observationuniqueV0001A
provider_idstringIdentifier for the healthcare provider responsible for the visitoptionalD1023
provider_specialtystringSpecialty of the healthcare provideroptionalCardiology
clinical_notesstringFree-text notes from the clinician regarding the patient's condition and progressionoptionalPatient reports increased…
medication_namestringName of medication prescribed or administered at the visitoptionalFurosemide
medication_dosagestringDosage and frequency of the medication (e.g., '10mg once daily')optional40mg once daily
lab_test_namestringName of laboratory test performed at the visitoptionalBNP
lab_test_unitstringMeasurement unit for the lab test resultoptionalpg/mL
hospitalization_reasonstringReason for hospitalization, if applicableoptionalCOPD exacerbation
outcome_statusstringCurrent status of the patient at the time of the visit (e.g., stable, improved, worsened, deceased)stable · improved · worsened · deceased · unknown · optionalworsened
address_streetstringPatient's street addressoptional32 Calle de la Paz
address_citystringPatient's city of residenceoptionalMadrid
address_statestringPatient's state or province of residenceoptionalMadrid
address_postal_codestringPatient's postal or ZIP codeoptional28013
address_countrystringPatient's country of residenceoptionalSpain
Numbers 2 columns
symptom_severity_scorefloatNumerical score representing severity of symptoms at the visit (e.g., 0-10)0 to 10 · optional8.3
lab_test_resultfloatResult value of the laboratory testoptional520
Dates and times 3 columns
date_of_birthdatePatient's date of birth1955-02-11
diagnosis_datedateDate when the chronic illness was diagnosed2016-03-21
visit_datedateDate of the patient visit or observation2023-04-15
True or false 1 column
hospitalizationbooleanIndicates if the patient was hospitalized during this visitoptionaltrue

Use it for

  • hospitalization23%49 of 215 rowsmean symptom severity…6.2stab…4.5impr…8.4wors…9.4dece…

    A healthcare dashboard

    The hospitalization rate, symptom_severity_score by outcome_status and a breakdown of race_ethnicity. Excel, Power BI or Tableau.

  • Why do 49 of 215 rows have hospitalization = true?

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

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This dataset216 rows28 columns
Yours1,000 rows28 columnsaddress_street: UK only

blueprint · patient-chronic-illness-progression

Behind this dataset

Same schema. As many rows as you need.

These 216 rows came out of a blueprint — 28 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
  • Multiple timepoints per patient ID.
  • Diagnosis, treatment, and outcome fields included.
  • Missing visits imputed or flagged.
  • Basic demographics provided.
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
patient-chronic-illness-progression

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