Healthcare
22 columns
200 rows
8 formats

Healthcare Clinical Trial Enrollment

This dataset provides detailed, participant-level records for multiple healthcare clinical trials, including screening, randomization, and enrollment outcomes, along with demographic and site information. It enables comprehensive analysis of trial recruitment, participant flow, and site performance, supporting operational optimization and regulatory reporting in clinical research.

last updated 29 Jul 2025
by GoMask

The brief that made it

Analyze participant recruitment and enrollment rates across multiple clinical trials and sites

Sample rows

preview · 8 of 200 rows · all 22 columns

participant_idstring	screening_statusstring	ageinteger	randomizedboolean	statestring	trial_idstring	trial_namestring	site_idstring	site_namestring	screening_datedate	screening_failure_reasonstring	randomization_datedate	randomization_groupstring	enrollment_datedate	enrolledboolean	enrollment_statusstring	enrollment_failure_reasonstring	sexstring	race_ethnicitystring	countrystring	citystring	postal_codestring
P0001	eligible	12	true	CA	T2019-001	Pediatric Epilepsy Drug Study	S1	Children's Hospital Los Angeles	2019-05-12	blank	2019-05-14	treatment	2019-05-16	true	enrolled	blank	female	Hispanic or Latino	USA	Los Angeles	90027
P0002	eligible	71	true	ON	T2020-002	Geriatric Osteoporosis Registry	S2	Toronto General Hospital	2020-11-17	blank	2020-11-20	control	2020-11-23	true	enrolled	blank	male	White	Canada	Toronto	M5G 2C4
P0003	eligible	15	true	blank	T2021-003	Adolescent Migraine Prevention Study	S3	Great Ormond Street Hospital	2021-09-10	blank	2021-09-13	placebo	2021-09-16	true	enrolled	blank	female	Black	UK	London	WC1N 3JH
P0004	ineligible	23	false	blank	T2022-004	Global Adult Depression Program	S4	São Paulo Clinical Center	2022-03-05	Did not meet DSM-5 criteria	blank	blank	blank	false	not_enrolled	Failed screening criteria	male	Pardo	Brazil	São Paulo	01310-100
P0005	eligible	72	true	VIC	T2018-005	Rare Disease Registry Australia	S5	Royal Melbourne Hospital	2018-08-21	blank	2018-08-23	treatment	2018-08-27	true	enrolled	blank	female	White	Australia	Melbourne	3004
P0006	eligible	34	true	blank	T2023-006	Adult COVID-19 Vaccine Safety	S6	Seoul National University Hospital	2023-01-12	blank	2023-01-14	treatment	2023-01-16	true	enrolled	blank	other	Korean	Korea	Seoul	03080
P0007	ineligible	41	false	NY	T2022-004	Global Adult Depression Program	S7	New York Presbyterian Hospital	2022-04-15	History of bipolar disorder	blank	blank	blank	false	not_enrolled	Clinical exclusion criteria	male	Asian	USA	New York	10032
P0008	eligible	14	true	MA	T2021-007	Pediatric Migraine Real-World Study	S8	Boston Children's Hospital	2021-02-19	blank	2021-02-21	control	2021-02-25	true	enrolled	blank	female	White	USA	Boston	02115
P0009	pending	46	false	blank	T2022-008	Adult Type 2 Diabetes Outcomes	S9	Charité – Universitätsmedizin Berlin	2022-07-10	blank	blank	blank	blank	false	not_enrolled	Screening pending	male	White	Germany	Berlin	10117
P0010	eligible	8	true	PA	T2024-009	Childhood Asthma Prevention	S10	Children's Hospital of Philadelphia	2024-03-08	blank	2024-03-10	treatment	2024-03-14	true	enrolled	blank	other	Black	USA	Philadelphia	19104
P0011	eligible	55	true	blank	T2023-010	Oncology Immunotherapy Japan	S11	Osaka University Hospital	2023-06-18	blank	2023-06-21	placebo	2023-06-25	true	enrolled	blank	female	Japanese	Japan	Osaka	565-0871
P0012	eligible	84	true	BC	T2020-002	Geriatric Osteoporosis Registry	S12	Vancouver General Hospital	2020-09-11	blank	2020-09-13	treatment	2020-09-17	true	enrolled	blank	male	South Asian	Canada	Vancouver	V5Z 1M9
P0013	eligible	10	true	ON	T2021-011	Juvenile Rheumatoid Arthritis Study	S13	The Hospital for Sick Children	2021-12-30	blank	2022-01-02	control	2022-01-04	true	enrolled	blank	female	Chinese	Canada	Toronto	M5G 1X8
P0014	ineligible	78	false	blank	T2022-012	European Rare Disease Cohort	S14	Hôpital Necker-Enfants Malades	2022-08-09	Age outside protocol limits	blank	blank	blank	false	not_enrolled	Protocol exclusion	unknown	White	France	Paris	75015
P0015	pending	7	false	CA	T2019-001	Pediatric Epilepsy Drug Study	S15	Rady Children's Hospital	2019-08-15	blank	blank	blank	blank	false	not_enrolled	Screening pending	male	Native American	USA	San Diego	92123
P0016	eligible	91	false	VIC	T2022-013	Geriatric Memory Loss Registry	S16	Austin Health	2022-02-19	blank	2022-02-20	blank	2022-02-25	true	enrolled	blank	female	White	Australia	Heidelberg	3084
P0017	eligible	67	true	blank	T2022-008	Adult Type 2 Diabetes Outcomes	S17	Hospital das Clínicas	2022-10-02	blank	2022-10-03	treatment	2022-10-06	true	enrolled	blank	male	Pardo	Brazil	São Paulo	05403-000
P0018	eligible	22	true	MD	T2023-014	Young Adult Depression Study	S18	Johns Hopkins Hospital	2023-07-25	blank	2023-07-27	control	2023-07-31	true	enrolled	blank	female	Black	USA	Baltimore	21287
P0019	eligible	11	true	blank	T2021-015	Global Pediatric Rare Disease	S19	National University Hospital	2021-11-28	blank	2021-12-01	treatment	2021-12-05	true	enrolled	blank	other	Malay	Singapore	Singapore	119074
P0020	pending	39	false	blank	T2023-016	Adult Migraine Real-World Evidence	S20	Auckland City Hospital	2023-02-17	blank	blank	blank	blank	false	not_enrolled	Screening pending	female	Maori	New Zealand	Auckland	1010

What the 200 rows show

from the 200-row sample

Eligible (screening status) stands out: 120 of its 135 rows have randomized = true, against 0 of 65 for the rest.

60%randomized = true
29median age
2enrollment statuses
3randomization groups
4sexes
25countries

Randomized rate by screening_statusrandomized = true

age200 rows, in bands of 10

Median 29, from 3 to 93.

state104 rows with a value · 96 left blank

ON8
VIC8
MA8
Ontario6
QLD5
Queensland4
Texas4
Maryland4
Quebec4
NSW3

22 columns by typefrom the column list below

string 16
integer 1
date 3
boolean 2

Columns

22 columns in four groups

blueprint · 22 columns
column	type	description	example
Text 16 columns
`participant_id`	string	Unique identifier for each participant across all trialsunique	P0001
`trial_id`	string	Unique identifier for the clinical trial	T2019-001
`trial_name`	string	Official name or title of the clinical trial	Pediatric Asthma Cohort
`site_id`	string	Unique identifier for the clinical trial siteoptional	S1
`site_name`	string	Name of the clinical trial site or locationoptional	Toronto General Hospital
`screening_status`	string	Outcome of the screening processeligible · ineligible · pending	eligible
`screening_failure_reason`	string	Reason for screening failure if participant was ineligibleoptional	COVID test negative
`randomization_group`	string	Assigned group after randomization (e.g., treatment, control, placebo)3 groups · optional	treatment
`enrollment_status`	string	Final enrollment outcome for the participantenrolled · withdrawn · lost_to_followup · not_enrolled	enrolled
`enrollment_failure_reason`	string	Reason for not enrolling or withdrawal if applicableoptional	Screening pending
`sex`	string	Sex of the participantmale · female · other · unknown	female
`race_ethnicity`	string	Self-reported race or ethnicity of the participantoptional	Hispanic or Latino
`country`	string	Country where the participant was enrolled	USA
`city`	string	City of the trial siteoptional	Los Angeles
`state`	string	State or province of the trial siteoptional	CA
`postal_code`	string	Postal code of the trial siteoptional	90027
Numbers 1 column
`age`	integer	Age of the participant at screening0 to 120	12
Dates and times 3 columns
`screening_date`	date	Date when the participant was screened for the trial	2019-05-12
`randomization_date`	date	Date when the participant was randomized in the trialoptional	2019-05-14
`enrollment_date`	date	Date when the participant was officially enrolled in the trialoptional	2019-05-16
True or false 2 columns
`randomized`	boolean	Indicates if the participant was randomized (true/false)	true
`enrolled`	boolean	Indicates if the participant was enrolled in the trial	true

Use it for

A healthcare dashboard
The randomized rate, age by screening_status and a breakdown of state. Excel, Power BI or Tableau.
Why do 120 of 200 rows have randomized = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Participants200
P000112eligible
P000271eligible
P000423ineligib…
A software demo
Believable participants with trial_id, trial_name and site_id to fill a screen in front of a buyer.

This dataset200 rows22 columns

Yours1,000 rows22 columnssite_id: UK only

blueprint · healthcare-clinical-trial-enrollment

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 22 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

Log trial ID and inclusion criteria met
Track demographics and study arm
Flag early withdrawals
No real patient identifiers

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: healthcare-clinical-trial-enrollment

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?