Healthcare
23 columns
200 rows
8 formats

Patient Readmission Risk Factors

This dataset provides detailed records of hospital admissions, patient demographics, diagnoses, clinical risk factors, and readmission outcomes. It enables healthcare organizations to analyze the drivers of patient readmissions, optimize care plans, and reduce unnecessary costs through targeted interventions and predictive modeling.

last updated 20 Aug 2025
by GoMask

The brief that made it

Predicting patient readmission risk for targeted care interventions

Sample rows

preview · 8 of 200 rows · all 23 columns

patient_idstring	discharge_dispositionstring	risk_scorefloat	readmittedboolean	address_statestring	admission_idstring	admission_datedate	discharge_datedate	readmission_datedate	ageinteger	genderstring	racestring	secondary_diagnosisstring	comorbiditiesstring	length_of_stayinteger	insurance_typestring	address_streetstring	address_citystring	address_postal_codestring	address_countrystring	care_plan_adherenceboolean	follow_up_visitsinteger	primary_diagnosisstring
PAT0001	home	0.12	false	TX	ADM00001	2023-01-07	2023-01-12	blank	33	female	White	blank	blank	5	private	4342 Forest Lane	Dallas	75243	USA	true	2	S06.0X0A - Concussion without loss of consciousness, initial encounter
PAT0002	home	0.18	false	FL	ADM00002	2023-01-10	2023-01-11	blank	8	male	Hispanic	blank	asthma	1	Medicaid	178 Maple Drive	Miami	33145	USA	true	1	J21.0 - Acute bronchiolitis due to RSV
PAT0003	skilled_nursing_facility	0.64	false	PA	ADM00003	2023-02-04	2023-02-08	blank	70	female	Black	E11.9 - Type 2 diabetes mellitus without complications	diabetes, hypertension	4	Medicare	12 Elm Street	Philadelphia	19104	USA	false	0	I10 - Essential (primary) hypertension
PAT0004	home	0.09	false	CA	ADM00004	2023-01-18	2023-01-19	blank	21	male	Asian	blank	blank	1	private	150 Hillcrest Ave	San Jose	95120	USA	true	1	S52.501A - Unspecified fracture of the shaft of radius, initial encounter
PAT0005	skilled_nursing_facility	0.87	true	IL	ADM00005	2023-02-12	2023-02-22	2023-03-09	79	female	White	I50.9 - Heart failure, unspecified	COPD, heart failure, hypertension	10	Medicare	918 Willow Way	Chicago	60657	USA	false	0	J44.1 - Chronic obstructive pulmonary disease with acute exacerbation
PAT0006	home	0.36	false	NM	ADM00006	2023-03-03	2023-03-09	blank	56	male	Native American	blank	depression	6	Medicaid	355 Cedar Street	Albuquerque	87110	USA	true	2	F32.9 - Major depressive disorder, single episode, unspecified
PAT0007	home	0.2	false	TX	ADM00007	2023-03-15	2023-03-20	blank	38	female	Middle Eastern	blank	blank	5	private	208 Pine Ave	Houston	77005	USA	true	2	K35.80 - Acute appendicitis
PAT0008	rehab	0.59	false	GA	ADM00008	2023-03-11	2023-03-15	blank	68	male	Black	blank	heart failure, hypertension	4	Medicare	4820 Oak Lane	Atlanta	30318	USA	true	1	I50.9 - Heart failure, unspecified
PAT0009	rehab	0.76	true	WA	ADM00009	2023-02-17	2023-02-25	2023-03-22	82	female	Asian	E78.5 - Hyperlipidemia, unspecified	stroke, hyperlipidemia	8	Medicare	1200 Summit St	Seattle	98101	USA	false	0	I63.9 - Cerebral infarction, unspecified
PAT0010	home	0.14	false	NY	ADM00010	2023-02-26	2023-03-07	blank	29	male	White	blank	blank	9	private	1578 Broadway	New York	10019	USA	true	2	S93.401A - Sprain of right ankle, initial encounter
PAT0011	home	0.28	false	OR	ADM00011	2023-01-23	2023-01-32	blank	50	female	Indian	blank	diabetes	9	private	1945 Lakeview Blvd	Portland	97201	USA	true	1	E11.9 - Type 2 diabetes mellitus without complications
PAT0012	deceased	0.93	false	CA	ADM00012	2023-03-21	2023-03-22	blank	90	male	White	blank	hypertension	1	Medicare	3905 Redwood Dr	Sacramento	95816	USA	blank	blank	I10 - Essential (primary) hypertension
PAT0013	home	0.26	false	CA	ADM00013	2023-03-13	2023-03-17	blank	46	female	Black	blank	anxiety	4	private	1000 Sunset Blvd	Los Angeles	90046	USA	true	2	F41.9 - Anxiety disorder, unspecified
PAT0014	home	0.22	false	CO	ADM00014	2023-03-28	2023-03-32	blank	4	female	Asian	blank	blank	4	Medicaid	2012 Willowbrook Dr	Denver	80203	USA	true	2	P07.32 - Preterm newborn, gestational age < 28 completed weeks
PAT0015	rehab	0.8	true	NC	ADM00015	2023-04-03	2023-04-08	2023-04-27	67	male	White	blank	COPD, hypertension	5	Medicare	320 Southside Ave	Charlotte	28209	USA	false	0	J44.1 - Chronic obstructive pulmonary disease with acute exacerbation
PAT0016	rehab	0.53	false	HI	ADM00016	2023-04-16	2023-04-20	blank	44	female	Pacific Islander	blank	substance abuse	4	Medicaid	1522 Pacific Ave	Honolulu	96815	USA	false	1	F19.20 - Substance use disorder, moderate, unspecified substance
PAT0017	home	0.17	false	MI	ADM00017	2023-04-21	2023-04-23	blank	14	male	Black	blank	blank	2	Medicaid	934 Green St	Detroit	48202	USA	true	1	S06.5X0A - Traumatic subdural hemorrhage, initial encounter
PAT0018	home	0.37	false	AZ	ADM00018	2023-04-24	2023-04-30	blank	59	male	White	E78.0 - Pure hypercholesterolemia	heart disease, hypercholesterolemia	6	private	1302 Oakmont Dr	Phoenix	85014	USA	true	2	I25.10 - Atherosclerotic heart disease of native coronary artery
PAT0019	home	0.2	false	TX	ADM00019	2023-05-02	2023-05-07	blank	41	other	Hispanic	blank	anxiety	5	private	990 Walnut St	San Antonio	78212	USA	true	1	F41.1 - Generalized anxiety disorder
PAT0020	skilled_nursing_facility	0.67	true	OH	ADM00020	2023-05-09	2023-05-11	2023-05-18	75	female	White	J44.1 - COPD with acute exacerbation	hypertension, COPD	2	Medicare	4321 Cherry St	Cleveland	44114	USA	false	0	I10 - Essential (primary) hypertension

What the 200 rows show

from the 200-row sample

Home (discharge disposition) stands out: mean risk_score is 0.19, against 0.78 for the rest.

13%readmitted = true
0.21median risk_score
4genders
4insurance types
9races
44median age

Mean risk_score by discharge_disposition200 rows

risk_score200 rows, in bands of 0.1

Median 0.21, from 0.05 to 0.96.

address_state200 rows · top 10 of 37 values

CA25
TX18
OH14
CO10
MO8
NC7
MN7
FL6
PA6
WA6

23 columns by typefrom the column list below

string 14
integer 3
float 1
date 3
boolean 2

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 14 columns
`patient_id`	string	Unique identifier for the patientunique	PAT0001
`admission_id`	string	Unique identifier for each hospital admission eventunique	ADM00001
`gender`	string	Gender of the patientmale · female · other · unknown	female
`race`	string	Race or ethnicity of the patient9 races · optional	White
`primary_diagnosis`	string	Primary diagnosis code or description for the admission	S06.0 - Concussion
`secondary_diagnosis`	string	Secondary diagnosis code or description, if anyoptional	E78.5 - Hyperlipidemia
`comorbidities`	string	Comma-separated list of comorbid conditions (e.g., diabetes, hypertension)optional	asthma
`discharge_disposition`	string	Disposition at discharge (e.g., home, skilled nursing facility, deceased)home · skilled_nursing_facility · rehab · deceased · other	home
`insurance_type`	string	Type of insurance coverage (e.g., Medicare, Medicaid, private, uninsured)4 types · optional	private
`address_street`	string	Street address of the patientoptional	4342 Forest Lane
`address_city`	string	City of the patient's addressoptional	Dallas
`address_state`	string	State of the patient's addressoptional	TX
`address_postal_code`	string	Postal code of the patient's addressoptional	75243
`address_country`	string	Country of the patient's addressoptional	USA
Numbers 4 columns
`age`	integer	Age of the patient at the time of admission0 to 120	33
`length_of_stay`	integer	Number of days the patient stayed in the hospital during the admission1 or more	5
`risk_score`	float	Calculated risk score for readmission based on patient factors0 to 1 · optional	0.12
`follow_up_visits`	integer	Number of follow-up visits completed within 30 days post-discharge0 or more · optional	2
Dates and times 3 columns
`admission_date`	date	Date when the patient was admitted to the hospital	2023-01-07
`discharge_date`	date	Date when the patient was discharged from the hospital	2023-01-12
`readmission_date`	date	Date of readmission if applicable; null if not readmittedoptional	2023-03-09
True or false 2 columns
`readmitted`	boolean	Indicates if the patient was readmitted within 30 days after discharge	false
`care_plan_adherence`	boolean	Indicates whether the patient adhered to the prescribed care plan post-dischargeoptional	true

Use it for

A healthcare dashboard
The readmitted rate, risk_score by discharge_disposition and a breakdown of address_state. Excel, Power BI or Tableau.
Why do the 154 home rows have a mean risk_score of 0.19?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Patients200
PAT00010.12home
PAT00050.87skilled_…
PAT00090.76rehab
A software demo
Believable patients with admission_id, admission_date and discharge_date to fill a screen in front of a buyer.

This dataset200 rows23 columns

Yours1,000 rows23 columnsaddress_street: UK only

blueprint · patient-readmission-risk-factors

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 23 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

Include only discharged adult patients
Exclude elective procedures
Link clinical and demographic attributes
Flag patients readmitted within 30 days
Integrate length of stay data

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

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: patient-readmission-risk-factors

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?