Healthcare
17 columns
200 rows
8 formats

Patient Symptom Progression Records

This dataset provides detailed, time-stamped records of patient-reported symptoms, including severity, duration, medication usage, and demographic information. It enables comprehensive tracking of disease progression and supports advanced analytics and AI-based diagnostic research in healthcare. The structure is optimized for longitudinal studies and integration with clinical systems.

last updated 22 Jul 2025
by GoMask

The brief that made it

Tracking disease progression and patient outcomes over time

Sample rows

preview · 8 of 200 rows · all 17 columns

record_idstring	reporting_methodstring	ageinteger	medication_takenboolean	diagnosis_codestring	patient_idstring	report_datedate	symptom_namestring	symptom_severityinteger	symptom_duration_daysinteger	symptom_onset_datedate	symptom_notesstring	medication_namestring	medication_dosagestring	follow_up_requiredboolean	genderstring	ethnicitystring
REC00001	mobile_app	24	true	blank	PAT10001	2023-03-06	headache	5	2	2023-03-04	Mild throbbing, worse in afternoon.	acetaminophen	500mg, 1 tablet	false	male	Asian
REC00002	web_portal	42	true	R53.83	PAT10002	2023-06-14	fatigue	8	102	2023-03-04	Ongoing since spring, affects work.	vitamin B12 supplement	1000mcg daily	true	female	White
REC00003	in_person	58	true	M25.50	PAT10003	2023-06-19	joint pain	7	32	2023-05-18	Pain in knees and wrists.	ibuprofen	400mg twice daily	true	male	Black/African American
REC00004	web_portal	29	false	blank	PAT10004	2023-08-25	none	0	0	blank	blank	blank	blank	false	female	Hispanic/Latino
REC00005	mobile_app	24	false	blank	PAT10001	2023-04-01	nausea	4	1	2023-03-31	blank	blank	blank	false	male	Asian
REC00006	in_person	61	true	H53.8	PAT10005	2023-07-10	blurred vision	9	20	2023-06-20	Episodes worse at night.	lutein supplement	10mg daily	true	female	White
REC00007	mobile_app	21	false	blank	PAT10006	2023-05-13	muscle cramps	6	4	2023-05-09	Calf cramps after exercise.	blank	blank	false	female	Pacific Islander
REC00008	phone_call	38	true	G47.00	PAT10007	2023-09-02	insomnia	7	60	2023-07-04	Difficulty falling asleep.	melatonin extended release	5mg at bedtime	true	female	White
REC00009	web_portal	19	false	blank	PAT10008	2023-09-14	rash	2	2	2023-09-12	Small red patches on arm.	blank	blank	false	male	Native American
REC00010	phone_call	75	false	R41.0	PAT10009	2023-02-12	confusion	9	1	2023-02-11	Sudden onset, resolved after rest.	blank	blank	true	male	White
REC00011	in_person	82	true	H54.41	PAT10010	2023-10-01	vision loss	10	3	2023-09-28	Central vision loss in right eye.	ranibizumab injection	0.5mg monthly	true	female	Black/African American
REC00012	web_portal	47	false	M25.50	PAT10011	2023-08-09	joint pain	6	15	2023-07-25	blank	blank	blank	true	female	Hispanic/Latino
REC00013	mobile_app	32	false	blank	PAT10012	2023-12-17	fatigue	5	3	2023-12-14	Slept poorly for a few days.	blank	blank	false	male	Pacific Islander
REC00014	web_portal	39	true	blank	PAT10013	2023-11-22	nausea	6	5	2023-11-17	Nausea mostly in mornings.	ondansetron	4mg as needed	false	female	Asian
REC00015	mobile_app	18	false	blank	PAT10014	2023-10-18	muscle cramps	3	1	2023-10-17	blank	blank	blank	false	male	Native American
REC00016	mobile_app	17	false	blank	PAT10015	2023-09-15	headache	2	0	2023-09-15	Lasted only a few hours.	blank	blank	false	female	Asian
REC00017	web_portal	54	false	R53.83	PAT10016	2023-12-02	fatigue	7	19	2023-11-13	Energy level fluctuates.	blank	blank	true	male	Hispanic/Latino
REC00018	in_person	66	true	M25.50	PAT10017	2023-07-19	joint pain	8	120	2023-03-21	Both elbows sore, worse in mornings.	naproxen sodium	220mg twice daily	true	male	White
REC00019	web_portal	22	false	blank	PAT10018	2023-02-03	rash	3	2	2023-02-01	blank	blank	blank	false	female	Pacific Islander
REC00020	phone_call	45	true	G47.00	PAT10019	2023-09-29	insomnia	8	41	2023-08-19	Trouble staying asleep.	zolpidem tartrate	10mg nightly	true	female	Black/African American

What the 200 rows show

from the 200-row sample

In_person (reporting method) stands out: mean age is 67.2, against 35.5 for the rest.

51%medication_taken = true
41.5median age
2genders
6ethnicities
12symptom names
6median symptom_severity

Mean age by reporting_method200 rows

age200 rows, in bands of 10

Median 41.5, from 16 to 83.

diagnosis_code82 rows with a value · 118 left blank

M25.5013
R53.839
H53.88
M25.56
G47.004
R41.04
H54.414
G47.04
H54.04
E61.13

17 columns by typefrom the column list below

string 10
integer 3
date 2
boolean 2

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 10 columns
`record_id`	string	Unique identifier for each symptom progression record entryunique	REC00001
`patient_id`	string	Unique identifier for the patient	PAT10001
`symptom_name`	string	Name of the reported symptom (e.g., fever, cough, fatigue)12 names	headache
`symptom_notes`	string	Additional notes or descriptions provided by the patient regarding the symptomoptional	Episodes worse at night.
`medication_name`	string	Name of the medication taken for the symptom, if anyoptional	acetaminophen
`medication_dosage`	string	Dosage of the medication taken (e.g., 500mg, 1 tablet)optional	500mg, 1 tablet
`diagnosis_code`	string	Standardized diagnosis code (e.g., ICD-10) if the symptom is associated with a known diagnosisoptional	R53.83
`reporting_method`	string	Method used to report the symptom (e.g., mobile app, web portal, phone call)mobile_app · web_portal · phone_call · in_person · other · optional	mobile_app
`gender`	string	Gender of the patientmale · female · other · prefer_not_to_say · optional	male
`ethnicity`	string	Ethnicity of the patient, if provided6 ethnicities · optional	Asian
Numbers 3 columns
`symptom_severity`	integer	Severity of the symptom on a standardized scale (e.g., 0-10, where 0 is none and 10 is most severe)0 to 10	5
`symptom_duration_days`	integer	Number of days the symptom has persisted at the time of reporting0 or more · optional	2
`age`	integer	Age of the patient at the time of report0 or more · optional	24
Dates and times 2 columns
`report_date`	date	Date when the symptom report was submitted by the patient	2023-03-06
`symptom_onset_date`	date	Date when the symptom first appearedoptional	2023-03-04
True or false 2 columns
`medication_taken`	boolean	Indicates if the patient took any medication for this symptomoptional	true
`follow_up_required`	boolean	Indicates if clinical follow-up is recommended based on this reportoptional	false

Use it for

A healthcare dashboard
The medication_taken rate, age by reporting_method and a breakdown of diagnosis_code. Excel, Power BI or Tableau.
Why do the 43 in_person rows have a mean age of 67.2?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records200
REC0000124mobile_a…
REC0000242web_port…
REC0000429web_port…
A software demo
Believable records with patient_id, report_date and symptom_name to fill a screen in front of a buyer.

This dataset200 rows17 columns

Yours1,000 rows17 columns

blueprint · patient-symptom-progression-records

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 17 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

Each patient has multiple symptom records over time.
Severity and duration scored.
Linked to diagnosis and demographic data.
Symptom onset and outcome dates included.

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: patient-symptom-progression-records

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A healthcare dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?