Healthcare
18 columns
100 rows
8 formats

Claim Edits and Scrubbing Results

This dataset provides a detailed record of automated claim edits and scrubbing results, capturing errors, inconsistencies, medical necessity issues, coding problems, and compliance violations prior to insurance claim submission. It enables healthcare organizations to track, resolve, and analyze claim issues, improving billing accuracy and compliance while reducing denials and delays.

last updated 2 Nov 2025
by GoMask

The brief that made it

Automated claim error tracking and resolution workflow

Sample rows

preview · 8 of 100 rows · all 18 columns

claim_idstring	edit_severitystring	claim_amountfloat	resolvedboolean	procedure_codestring	patient_idstring	provider_idstring	edit_idstring	edit_typestring	edit_codestring	edit_detected_datetimedatetime	resolution_datetimedatetime	resolution_notesstring	claim_submission_datetimedatetime	payer_idstring	service_datedate	diagnosis_codestring	edit_descriptionstring
CLM10001	critical	125	true	99213	PAT20232	PRV5091	EDT30001	error	HIPAA-001	2024-04-10T09:13:25	2024-04-10T10:14:05	Patient address updated.	2024-04-10T10:15:30	PYR2001	2024-04-09	J45.909	Missing required field: patient address.
CLM10002	warning	98.5	true	93000	PAT20212	PRV5096	EDT30002	coding_problem	CPT-5912	2024-03-28T14:25:36	2024-03-28T14:45:22	Codes bundled as per payer guidelines.	2024-03-28T15:01:10	PYR2002	2024-03-27	I10	Unbundling of CPT codes detected.
CLM10003	critical	308.75	false	70450	PAT20219	PRV5095	EDT30003	medical_necessity	PAYER-PA-321	2024-03-30T11:08:57	blank	blank	blank	PYR2003	2024-03-29	R51	Procedure requires prior authorization.
CLM10004	critical	55.25	true	85025	PAT20207	PRV5097	EDT30004	inconsistency	HIPAA-002	2024-03-20T08:55:13	2024-03-20T09:05:42	Corrected patient birth date.	2024-03-20T09:06:11	PYR2001	2024-03-19	E11.9	Service date precedes patient birth date.
CLM10005	warning	76	true	96372	PAT20225	PRV5092	EDT30005	compliance_violation	ICD-10-ERR	2024-04-01T16:42:18	2024-04-01T17:01:22	Diagnosis code updated.	2024-04-01T17:05:18	PYR2004	2024-03-31	M54.5	ICD-10 code not valid for date of service.
CLM10006	critical	142.6	false	99214	PAT20217	PRV5094	EDT30006	error	PAYER-DUP-01	2024-04-02T12:13:14	blank	blank	blank	PYR2002	2024-04-01	J06.9	Duplicate claim detected for same service date.
CLM10007	warning	89.15	true	71020	PAT20214	PRV5091	EDT30007	error	HIPAA-NPI-01	2024-04-05T15:03:39	2024-04-05T15:22:19	NPI entered.	2024-04-05T15:30:01	PYR2003	2024-04-04	R07.9	Missing referring provider NPI.
CLM10008	informational	110	true	93010	PAT20216	PRV5097	EDT30008	coding_problem	CPT-MOD-22	2024-03-25T10:45:10	2024-03-25T10:47:58	Modifier corrected.	2024-03-25T11:01:00	PYR2001	2024-03-24	R42	Incorrect modifier on CPT code.
CLM10009	warning	320	false	45378	PAT20229	PRV5096	EDT30009	medical_necessity	PAYER-FREQ-01	2024-04-07T09:58:21	blank	blank	blank	PYR2002	2024-04-06	K52.9	Frequency of service exceeds policy limits.
CLM10010	critical	125	true	96360	PAT20211	PRV5095	EDT30010	compliance_violation	PAYER-NC-05	2024-03-22T13:30:16	2024-03-22T14:11:52	Claim withdrawn.	2024-03-22T14:15:30	PYR2004	2024-03-21	F41.9	Service not covered under payer policy.
CLM10011	informational	62.3	true	80053	PAT20223	PRV5092	EDT30011	error	HIPAA-GEN-02	2024-03-31T17:14:29	2024-03-31T17:16:57	Gender added.	2024-03-31T17:17:33	PYR2003	2024-03-30	E78.5	Patient gender missing.
CLM10012	warning	85	false	99212	PAT20215	PRV5091	EDT30012	inconsistency	HIPAA-ID-03	2024-04-08T08:12:00	blank	blank	blank	PYR2001	2024-04-07	R51	Mismatch in patient ID across documents.
CLM10013	critical	44	true	82947	PAT20221	PRV5096	EDT30013	medical_necessity	PAYER-DOC-12	2024-03-26T16:22:43	2024-03-26T16:45:10	Additional documentation submitted.	2024-03-26T17:02:48	PYR2002	2024-03-25	E11.9	Documentation does not support diagnosis.
CLM10014	critical	76.45	true	92002	PAT20228	PRV5095	EDT30014	coding_problem	CPT-ICD-03	2024-04-03T13:02:07	2024-04-03T13:22:10	Diagnosis code updated.	2024-04-03T13:30:00	PYR2003	2024-04-02	H52.4	ICD code incompatible with CPT code.
CLM10015	warning	165	false	99396	PAT20210	PRV5092	EDT30015	compliance_violation	PAYER-GEO-08	2024-03-29T07:41:21	blank	blank	blank	PYR2004	2024-03-28	Z00.00	Service performed outside covered region.
CLM10016	critical	90	true	71045	PAT20227	PRV5094	EDT30016	error	PAYER-POL-11	2024-03-24T18:25:52	2024-03-24T18:47:00	Policy number corrected.	2024-03-24T18:55:30	PYR2001	2024-03-23	R05	Patient insurance policy number invalid.
CLM10017	informational	22	true	36415	PAT20213	PRV5097	EDT30017	inconsistency	CPT-DOC-09	2024-03-23T11:15:17	2024-03-23T11:35:20	Documentation updated.	2024-03-23T11:40:30	PYR2002	2024-03-22	D64.9	Mismatch in procedure code documentation.
CLM10018	critical	210	false	99215	PAT20226	PRV5091	EDT30018	medical_necessity	PAYER-NEC-02	2024-04-09T10:33:11	blank	blank	blank	PYR2003	2024-04-08	R53.83	Procedure not supported by presenting symptoms.
CLM10019	warning	45	true	99211	PAT20218	PRV5095	EDT30019	coding_problem	CPT-OBS-14	2024-03-27T15:44:59	2024-03-27T16:01:07	Code replaced with current version.	2024-03-27T16:10:30	PYR2002	2024-03-26	R10.9	Obsolete CPT code used.
CLM10020	critical	47.6	true	80048	PAT20224	PRV5096	EDT30020	compliance_violation	PAYER-CON-06	2024-04-06T08:23:00	2024-04-06T08:55:15	Consent uploaded.	2024-04-06T09:01:00	PYR2004	2024-04-05	E11.65	Failure to include required consent documentation.

What the 100 rows show

from the 100-row sample

63%resolved = true
98.5median claim_amount
5edit types
12payers

edit_severity100 rows by value

claim_amount100 rows, in bands of 100

Median 98.5, from 16.4 to 512.0.

procedure_code100 rows · top 10 of 38 values

992137
963727
992147
930006
800536
993965
992124
364154
992034
993954

18 columns by typefrom the column list below

string 12
float 1
date 1
datetime 3
boolean 1

Columns

18 columns in four groups

blueprint · 18 columns
column	type	description	example
Text 12 columns
`claim_id`	string	Unique identifier for the insurance claim being edited and scrubbedunique	CLM10001
`patient_id`	string	Unique identifier for the patient associated with the claim	PAT20232
`provider_id`	string	Unique identifier for the healthcare provider submitting the claim	PRV5091
`edit_id`	string	Unique identifier for the specific edit or scrub performed on the claimunique	EDT30001
`edit_type`	string	Type of edit detected (e.g., error, inconsistency, medical necessity, coding problem, compliance violation)5 values	error
`edit_description`	string	Detailed description of the issue identified during claim scrubbing	Patient gender missing.
`edit_severity`	string	Severity level of the edit (e.g., critical, warning, informational)critical · warning · informational	critical
`edit_code`	string	Standardized code representing the type of edit or error (e.g., HIPAA, CPT, ICD-10, payer-specific codes)optional	HIPAA-001
`resolution_notes`	string	Notes or comments regarding how the issue was resolvedoptional	Patient address updated.
`payer_id`	string	Unique identifier for the insurance payer to whom the claim is submitted12 payers	PYR2001
`procedure_code`	string	Procedure code (e.g., CPT, HCPCS) for the medical service billed in the claim	99213
`diagnosis_code`	string	Diagnosis code (e.g., ICD-10) associated with the claim	J45.909
Numbers 1 column
`claim_amount`	float	Total dollar amount billed in the claim0 or more	125
Dates and times 4 columns
`edit_detected_datetime`	datetime	Timestamp when the edit or issue was detected	2024-04-10T09:13:25
`resolution_datetime`	datetime	Timestamp when the issue was resolved (if applicable)optional	2024-04-10T10:14:05
`claim_submission_datetime`	datetime	Timestamp when the claim was submitted after scrubbingoptional	2024-04-10T10:15:30
`service_date`	date	Date of the medical service associated with the claim	2024-04-09
True or false 1 column
`resolved`	boolean	Indicates whether the identified issue has been resolved prior to claim submission	true

Use it for

A healthcare dashboard
The resolved rate, claim_amount by edit_severity and a breakdown of procedure_code. Excel, Power BI or Tableau.
Why do 63 of 100 rows have resolved = true?
A class exercise
Hand out the rows and one question. Everyone works from the same 100 rows.
Claims100
CLM10001125critical
CLM1000298.5warning
CLM10003308.75critical
A software demo
Believable claims with patient_id, provider_id and edit_id to fill a screen in front of a buyer.

This dataset100 rows18 columns

Yours10,000 rows18 columns

blueprint · claim-edits-and-scrubbing-results

Behind this dataset

Same schema. As many rows as you need.

These 100 rows came out of a blueprint — 18 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

Edit ID unique per claim edit
Edit type: error (must fix), warning (review), info
Coding edits: unbundling, mutually exclusive codes, gender/age mismatch
Medical necessity: diagnosis does not support procedure
NCCI (National Correct Coding Initiative) edits
LCD/NCD (Local/National Coverage Determination) checks
Duplicate claim detection
Missing or invalid data elements

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: claim-edits-and-scrubbing-results

What should your data show?

No signup. No card.

Sample rows

What the 100 rows show

Columns

Use it for

A healthcare dashboard

A class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?