Healthcare
20 columns
200 rows
8 formats

Clinical Trial Enrollment Dataset

This dataset provides detailed records of clinical trial enrollments, including participant demographics, recruitment sources, eligibility criteria, and enrollment status. It enables comprehensive analysis of recruitment flows, diversity metrics, and participant retention, supporting optimization of trial recruitment strategies and regulatory reporting.

last updated 20 Aug 2025
by GoMask

The brief that made it

Analyze recruitment and enrollment flows for clinical trials

Sample rows

preview · 8 of 200 rows · all 20 columns

enrollment_idstring	enrollment_statusstring	ageinteger	exclusion_criteria_metboolean	trial_idstring	participant_idstring	enrollment_datedate	genderstring	ethnicitystring	racestring	countrystring	statestring	citystring	zip_codestring	recruitment_sourcestring	withdrawal_reasonstring	inclusion_criteria_metboolean	consent_signed_datedate	visit_countinteger	adverse_event_reportedboolean
E0001	completed	28	false	T101	P1001	2024-03-22	female	Not Hispanic or Latino	White	US	CA	Los Angeles	90001	online ad	blank	true	2024-03-19	8	false
E0002	completed	66	false	T102	P1002	2023-08-16	male	Not Hispanic or Latino	Asian	JP	13	Tokyo	1000001	physician referral	blank	true	2023-08-13	7	false
E0003	enrolled	34	false	T103	P1003	2024-01-30	male	Hispanic or Latino	White	US	TX	Houston	77001	online ad	blank	true	2024-01-28	6	false
E0004	screened	2	true	T104	P1004	2024-05-07	female	Not Hispanic or Latino	Black or African American	IN	DL	Delhi	110001	community event	blank	false	blank	0	blank
E0005	eligible	58	true	T102	P1005	2023-07-20	female	Not Hispanic or Latino	Asian	CN	BJ	Beijing	100000	physician referral	blank	false	blank	0	false
E0006	enrolled	24	false	T101	P1006	2024-04-10	male	Hispanic or Latino	White	US	NY	New York	10001	online ad	blank	true	2024-04-08	5	false
E0007	enrolled	39	false	T103	P1007	2024-02-15	female	Not Hispanic or Latino	White	US	FL	Miami	33101	online ad	blank	true	2024-02-12	4	false
E0008	withdrawn	120	true	T104	P1008	2024-03-09	prefer_not_to_say	Prefer not to say	Prefer not to say	US	AK	Anchorage	99501	community event	Adverse event	false	2024-03-07	1	true
E0009	completed	31	false	T101	P1009	2023-11-18	female	Not Hispanic or Latino	White	US	IL	Chicago	60601	online ad	blank	true	2023-11-16	9	true
E0010	enrolled	44	false	T102	P1010	2023-05-02	male	Not Hispanic or Latino	Asian	KR	11	Seoul	04524	physician referral	blank	true	2023-04-30	5	false
E0011	eligible	60	true	T103	P1011	2023-12-20	other	Not Hispanic or Latino	Black or African American	US	GA	Atlanta	30301	community event	blank	false	blank	0	false
E0012	screened	4	true	T104	P1012	2024-06-03	male	Hispanic or Latino	Native American	MX	CMX	Mexico City	01000	community event	blank	false	blank	0	blank
E0013	enrolled	18	false	T101	P1013	2024-02-06	female	Not Hispanic or Latino	Asian	US	WA	Seattle	98101	online ad	blank	true	2024-02-03	4	false
E0014	enrolled	72	false	T102	P1014	2023-09-25	male	Not Hispanic or Latino	White	DE	BE	Berlin	10117	physician referral	blank	true	2023-09-23	3	false
E0015	completed	29	false	T103	P1015	2024-04-27	female	Not Hispanic or Latino	White	US	CO	Denver	80201	online ad	blank	true	2024-04-24	9	false
E0016	eligible	80	true	T104	P1016	2023-10-14	female	Not Hispanic or Latino	Asian	US	PA	Philadelphia	19101	physician referral	blank	false	blank	0	false
E0017	disqualified	119	true	T101	P1017	2023-12-06	other	Prefer not to say	Prefer not to say	US	HI	Honolulu	96801	community event	blank	false	blank	0	blank
E0018	enrolled	42	false	T102	P1018	2024-05-21	male	Hispanic or Latino	Asian	US	NV	Las Vegas	89101	online ad	blank	true	2024-05-18	3	false
E0019	completed	35	false	T103	P1019	2024-02-27	female	Not Hispanic or Latino	White	US	OH	Columbus	43085	online ad	blank	true	2024-02-25	7	false
E0020	eligible	63	true	T104	P1020	2023-04-09	female	Not Hispanic or Latino	Asian	FR	blank	Paris	75001	physician referral	blank	false	blank	0	false

What the 200 rows show

from the 200-row sample

Eligible (enrollment status) stands out: 22 of its 22 rows have exclusion_criteria_met = true, against 33 of 178 for the rest.

28%exclusion_criteria_met = true
39median age
3ethnicities
3recruitment sources
4genders
7races

Exclusion criteria met rate by enrollment_statusexclusion_criteria_met = true

age200 rows, in bands of 20

Median 39, from 0 to 120.

trial_id200 rows · top 10 of 17 values

T10133
T10231
T10430
T10328
T1057
T1067
T1077
T1087
T0417
T0426

20 columns by typefrom the column list below

string 13
integer 2
date 2
boolean 3

Columns

20 columns in four groups

blueprint · 20 columns
column	type	description	example
Text 13 columns
`enrollment_id`	string	Unique identifier for each enrollment recordunique	E0001
`trial_id`	string	Unique identifier for the clinical trial	T101
`participant_id`	string	Unique identifier for the participant	P1001
`gender`	string	Gender of the participantmale · female · other · prefer_not_to_say	female
`ethnicity`	string	Ethnicity of the participant3 ethnicities · optional	Not Hispanic or Latino
`race`	string	Race of the participant7 races · optional	White
`country`	string	Country of residence of the participant11 countries	US
`state`	string	State or region of residence of the participantoptional	CA
`city`	string	City of residence of the participantoptional	Los Angeles
`zip_code`	string	Postal code of the participant's residenceoptional	90001
`recruitment_source`	string	Source through which the participant was recruited (e.g., online ad, physician referral, community event)3 sources · optional	online ad
`enrollment_status`	string	Current status of the participant's enrollment6 values	completed
`withdrawal_reason`	string	Reason for participant withdrawal, if applicable5 reasons · optional	Adverse event
Numbers 2 columns
`age`	integer	Age of the participant at enrollment0 to 120	28
`visit_count`	integer	Number of study visits completed by the participant0 or more · optional	8
Dates and times 2 columns
`enrollment_date`	date	Date the participant enrolled in the trial	2024-03-22
`consent_signed_date`	date	Date participant signed informed consentoptional	2024-03-19
True or false 3 columns
`inclusion_criteria_met`	boolean	Indicates if participant met all inclusion criteria	true
`exclusion_criteria_met`	boolean	Indicates if participant met any exclusion criteria	false
`adverse_event_reported`	boolean	Indicates whether the participant reported any adverse eventsoptional	false

Use it for

A healthcare dashboard
The exclusion_criteria_met rate, age by enrollment_status and a breakdown of trial_id. Excel, Power BI or Tableau.
Why do 55 of 200 rows have exclusion_criteria_met = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Enrollments200
E000128completed
E00042screened
E000558eligible
A software demo
Believable enrollments with trial_id, participant_id and enrollment_date to fill a screen in front of a buyer.

This dataset200 rows20 columns

Yours1,000 rows20 columnscountry: UK only

blueprint · clinical-trial-enrollment-dataset

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 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

Eligibility criteria strictly applied
Dropout events logged
Trial phase clearly marked
Participant demographics captured

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: clinical-trial-enrollment-dataset

What should your data show?

No signup. No card.

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?