Healthcare
22 columns
200 rows
8 formats

Healthcare Procedure Cost Dataset

This dataset contains detailed synthetic records of healthcare procedure costs, including patient demographics, provider information, procedure details, and comprehensive financial breakdowns. Designed for cost modeling and pricing analytics, it enables in-depth analysis of healthcare expenses, demographic trends, and provider performance across various medical procedures.

opened 6 times
last updated 20 Aug 2025
by GoMask

The brief that made it

Healthcare cost modeling and price benchmarking

Sample rows

preview · 8 of 200 rows · all 22 columns

record_idstring	insurance_typestring	patient_ageinteger	provider_citystring	patient_idstring	patient_genderstring	patient_race_ethnicitystring	patient_zip_codestring	procedure_codestring	procedure_descriptionstring	procedure_datedate	provider_idstring	provider_namestring	provider_statestring	provider_postal_codestring	provider_countrystring	cost_billedfloat	cost_paidfloat	cost_patient_responsibilityfloat	cost_insurance_coveredfloat	payment_datedate	procedure_outcomestring
REC-01A23B45D	medicaid	7	San Francisco	PAT-0001ABCD	female	hispanic	94107	CPT-99213	Office/outpatient visit	2024-03-14	PRV-10XJ8WQK5	UCSF Pediatrics	CA	94107	USA	250	200	10	190	2024-03-21	successful
REC-02B34C56E	private	29	New York	PAT-0002EFGH	male	asian	10001	CPT-93000	Electrocardiogram	2024-04-07	PRV-11YH9KLM2	NYU Cardiology	NY	10001	USA	320	250	30	220	2024-04-13	successful
REC-03C45D67F	medicare	68	Chicago	PAT-0003IJKL	male	white	60611	CPT-27130	Hip replacement	2024-02-19	PRV-12ZH6WXR7	Northwestern Hospital	IL	60611	USA	38500	28500	900	27600	2024-02-27	complications
REC-04D56E78G	medicare	86	Houston	PAT-0004MNOP	female	black	77030	CPT-99291	Critical care evaluation	2024-01-22	PRV-13QK4FDV8	Houston Medical Center	TX	77030	USA	7700	6000	700	5300	2024-01-27	readmission
REC-05E67F89H	medicaid	2	Phoenix	PAT-0005QRST	female	native-american	85016	CPT-59410	Vaginal delivery	2024-05-05	PRV-14DL6PWO2	Phoenix Children's Hosp	AZ	85016	USA	4200	3800	40	3760	2024-05-12	successful
REC-06F78G90I	private	34	Los Angeles	PAT-0006UVWX	female	asian	90001	CPT-45378	Colonoscopy	2024-04-15	PRV-15RM2GTE5	Cedars Sinai	CA	90001	USA	2800	2100	120	1980	2024-04-18	successful
REC-07G89H01J	private	45	Chicago	PAT-0007YZAB	male	white	60616	CPT-70450	CT head/brain	2024-03-02	PRV-16EG3VBN9	Rush University Med	IL	60616	USA	1100	950	130	820	2024-03-09	successful
REC-08H90I12K	medicare	71	Atlanta	PAT-0008CDEF	female	asian	30303	CPT-33533	Coronary artery bypass	2024-02-09	PRV-17DS6EWM3	Emory University Hosp	GA	30303	USA	42000	30000	1500	28500	2024-02-19	complications
REC-09I01J23L	uninsured	19	Detroit	PAT-0009GHIJ	other	other	48201	CPT-81001	Urinalysis automated	2024-06-04	PRV-18UJ7QWL4	Detroit Medical Center	MI	48201	USA	120	120	120	0	2024-06-04	successful
REC-10J12K34M	private	57	Atlanta	PAT-0010KLMN	male	black	30308	CPT-43235	Upper GI endoscopy	2024-05-19	PRV-19QK9RWE8	Atlanta GI Clinic	GA	30308	USA	800	650	85	565	2024-05-25	successful
REC-11K23L45N	medicaid	3	Miami	PAT-0011OPQR	male	hispanic	33101	CPT-99392	Preventive medicine, infant	2024-06-08	PRV-20VD3KQP1	Miami Children's Hosp	FL	33101	USA	180	160	10	150	2024-06-16	successful
REC-12L34M56O	private	50	Dallas	PAT-0012STUV	female	white	75201	CPT-29827	Shoulder arthroscopy	2024-04-21	PRV-21TG3NWM7	Baylor Ortho Center	TX	75201	USA	6200	5100	450	4650	2024-04-27	successful
REC-13M45N67P	medicare	68	Chicago	PAT-0003IJKL	male	white	60611	ICD10-I63.9	Cerebral infarction unspecified	2024-03-02	PRV-12ZH6WXR7	Northwestern Hospital	IL	60611	USA	8300	7000	850	6150	2024-03-06	readmission
REC-14N56O78Q	uninsured	35	San Francisco	PAT-0013WXYZ	other	other	94110	CPT-99214	Office visit, established patient	2024-05-30	PRV-22RT2JQK6	Mission Health SF	CA	94110	USA	180	180	180	0	2024-05-30	successful
REC-15O67P89R	private	23	New York	PAT-0014ABCD	female	asian	10003	CPT-71020	Chest x-ray	2024-04-25	PRV-23YD4JKP3	NYC Imaging	NY	10003	USA	220	180	20	160	2024-04-28	successful
REC-16P78Q90S	medicaid	12	Detroit	PAT-0015EFGH	male	black	48226	CPT-12001	Simple wound repair	2024-02-20	PRV-24ZM7ELM8	Detroit Children's Hosp	MI	48226	USA	370	310	15	295	2024-02-24	successful
REC-17Q89R01T	medicare	67	Miami	PAT-0016IJKL	female	white	33132	CPT-99223	Hospital discharge day	2024-03-23	PRV-25ET6KZW4	Jackson Memorial Hosp	FL	33132	USA	2100	1900	100	1800	2024-03-28	successful
REC-18R90S12U	private	39	New York	PAT-0017MNOP	male	asian	10016	CPT-72148	MRI lumbar spine	2024-06-13	PRV-26RP5KWE9	NYC Radiology	NY	10016	USA	1700	1400	110	1290	2024-06-18	successful
REC-19S01T23V	private	25	San Francisco	PAT-0018QRST	female	white	94115	CPT-81002	Urinalysis, non-auto	2024-05-12	PRV-10XJ8WQK5	UCSF General Clinic	CA	94115	USA	60	50	10	40	2024-05-14	successful
REC-20T12U34W	other	120	Houston	PAT-0019UVWX	unknown	unknown	blank	ICD10-E11.9	Type 2 diabetes mellitus	2024-04-10	PRV-27VT8JWP1	blank	TX	77098	USA	300	180	60	120	2024-04-10	ongoing

What the 200 rows show

from the 200-row sample

Medicare (insurance type) stands out: mean patient_age is 76.7, against 32.6 for the rest.

41median patient_age
4patient genders
4procedure outcomes
8patient race ethnicities
14provider states
370.0median cost_billed

Mean patient_age by insurance_type200 rows

patient_age200 rows, in bands of 20

Median 41, from 0 to 120.

provider_city200 rows · top 10 of 19 values

Chicago37
San Francisco27
Miami22
Atlanta21
Los Angeles20
Houston13
Phoenix13
New York12
Detroit10
Seattle7

22 columns by typefrom the column list below

string 15
integer 1
float 4
date 2

Columns

22 columns in three groups

blueprint · 22 columns
column	type	description	example
Text 15 columns
`record_id`	string	Unique identifier for each procedure cost recordunique	REC-01A23B45D
`patient_id`	string	Unique identifier for the patient	PAT-0001ABCD
`patient_gender`	string	Gender of the patientmale · female · other · unknown	female
`patient_race_ethnicity`	string	Race or ethnicity of the patient8 values · optional	hispanic
`patient_zip_code`	string	ZIP or postal code of patient's residenceoptional	94107
`insurance_type`	string	Type of insurance coverage for the procedureprivate · medicare · medicaid · uninsured · other · optional	medicaid
`procedure_code`	string	Standardized code for the medical procedure (e.g., CPT, ICD-10)	CPT-99213
`procedure_description`	string	Short description of the medical procedure	Office/outpatient visit
`provider_id`	string	Unique identifier for the healthcare provider or facility	PRV-10XJ8WQK5
`provider_name`	string	Name of the healthcare provider or facilityoptional	UCSF Pediatrics
`provider_city`	string	City where the procedure was performedoptional	San Francisco
`provider_state`	string	State where the procedure was performedoptional	CA
`provider_postal_code`	string	Postal code of the provider's locationoptional	94107
`provider_country`	string	Country of the provider's locationoptional	USA
`procedure_outcome`	string	Outcome of the procedure (e.g., successful, complications, readmission)successful · complications · readmission · ongoing · unknown · optional	successful
Numbers 5 columns
`patient_age`	integer	Age of the patient at the time of procedure0 to 120	7
`cost_billed`	float	Total amount billed for the procedure0 or more	250
`cost_paid`	float	Actual amount paid for the procedure (after insurance adjustments)0 or more	200
`cost_patient_responsibility`	float	Amount the patient is responsible for paying (copay, deductible, etc.)0 or more · optional	10
`cost_insurance_covered`	float	Amount covered by insurance0 or more · optional	190
Dates and times 2 columns
`procedure_date`	date	Date when the procedure was performed	2024-03-14
`payment_date`	date	Date when payment was madeoptional	2024-03-21

Use it for

A healthcare dashboard
Patient_age by insurance_type and a breakdown of provider_city. Excel, Power BI or Tableau.
Why do the 52 medicare rows have a mean patient_age of 76.7?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records200
REC-01A23B45D7medicaid
REC-02B34C56E29private
REC-03C45D67F68medicare
A software demo
Believable records with patient_id, patient_age and patient_gender to fill a screen in front of a buyer.

This dataset200 rows22 columns

Yours1,000 rows22 columnspatient_zip_code: UK only

blueprint · healthcare-procedure-cost-dataset

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

Procedure type and code tracked
Cost standardized per region
Patient insurance status included
Discounts and adjustments logged

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-procedure-cost-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?