Healthcare Diagnostic Error Analysis

This dataset provides detailed records of diagnostic errors in clinical settings, including patient demographics, clinician roles, error types, severity, outcomes, and organizational context. It enables healthcare organizations to analyze diagnostic accuracy, identify patterns in errors, and support targeted quality improvement and compliance initiatives. The comprehensive structure facilitates benchmarking, risk analysis, and regulatory reporting.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Diagnostic error rate analysis and benchmarking

Sample rows

preview · 8 of 200 rows · all 24 columns
diagnostic_error_idintegeroutcome_impactstringpatient_ageintegercompliance_flagbooleanorganization_statestringpatient_idstringpatient_genderstringdiagnosis_datedateclinical_settingstringdiagnosis_codestringdiagnosis_descriptionstringerror_typestringerror_detected_datedateerror_severitystringclinician_idstringclinician_rolestringorganization_idstringorganization_namestringorganization_citystringorganization_postal_codestringorganization_countrystringfollow_up_requiredbooleanerror_descriptionstringquality_improvement_actionstring
1minor7falseCAPAT1001female2024-03-14emergencyJ20.9Acute bronchitis, unspecifiedmissed2024-03-17moderateCLIN2001residentORG1001Central Valley Medical CenterFresno93722USAtrueInitial symptoms attributed to allergy, bronchitis diagnosis not made until follow-up.blank
2none62falseAZPAT1002male2024-04-11outpatientI10Essential (primary) hypertensionincorrect2024-04-14lowCLIN2002physicianORG1002Westside Family HealthPhoenix85021USAfalseHypertension incorrectly coded as secondary, corrected after pharmacy review.blank
3fatal88trueMAPAT1003male2023-11-25inpatientN18.6End stage renal diseasedelayed2023-12-07criticalCLIN2003physicianORG1003Metro Regional HospitalBoston02118USAtrueRenal failure progression not recognized, dialysis initiation delayed by 12 days.Renal consult protocol revised for early assessment.
4moderate34trueTXPAT1004female2024-05-08outpatientE11.9Type 2 diabetes mellitus without complicationsincorrect2024-05-09moderateCLIN2004nurseORG1004Greenway Primary CareAustin78701USAtruePatient incorrectly diagnosed with Type 1 diabetes, corrected after lab results.Lab result review process updated for accuracy.
5severe14trueGAPAT1005other2024-01-22emergencyS06.0X0AConcussion without loss of consciousnessmissed2024-01-25highCLIN2005residentORG1005Eastside Children's HospitalAtlanta30342USAtrueConcussion symptoms not recognized, patient discharged with headache diagnosis.Head injury checklist implemented in ER.
6severe77trueCAPAT1006female2024-02-03inpatientJ44.9Chronic obstructive pulmonary disease, unspecifieddelayed2024-02-08highCLIN2006physicianORG1006St. Mary's Medical CenterSan Jose95128USAtrueCOPD exacerbation not identified, delayed treatment for 5 days.COPD alert system added to EHR.
7none24falseFLPAT1007male2024-06-10outpatientJ45.909Unspecified asthma, uncomplicatedincorrect2024-06-11lowCLIN2007residentORG1007Sunrise Health ClinicMiami33130USAfalseAsthma incorrectly coded as chronic bronchitis.blank
8fatal92trueOHPAT1008female2024-03-23inpatientF03.90Unspecified dementia without behavioral disturbancedelayed2024-04-02criticalCLIN2008physicianORG1008Riverbend Elder Care CenterColumbus43215USAtrueDementia diagnosis delayed due to incomplete cognitive assessment.Cognitive assessment form added to intake.

What the 200 rows show

from the 200-row sample

Fatal (outcome impact) stands out: mean patient_age is 83.0, against 37.2 for the rest.

  • 67%compliance_flag = true
  • 40median patient_age
  • 4patient genders
  • 4clinical settings
  • 4error types
  • 4error severities
Mean patient_age by outcome_impact200 rows
05010031.8none50 rows37.4minor65 rows23.2modera…33 rows64.0severe27 rows83.0fatal25 rows
patient_age200 rows, in bands of 20
0306053474132252060120patient_age →

Median 40, from 3 to 101.

organization_state200 rows · top 10 of 39 values
  1. CA22
  2. TX15
  3. FL14
  4. OH10
  5. NC10
  6. MO9
  7. TN8
  8. IL7
  9. WA6
  10. CO6
24 columns by typefrom the column list below
  • string 18
  • integer 2
  • date 2
  • boolean 2

Columns

24 columns in four groups
blueprint · 24 columns
columntypedescriptionexample
Text 18 columns
patient_idstringUnique identifier for the patient involved in the diagnostic eventPAT1001
patient_genderstringGender of the patientmale · female · other · unknownfemale
clinical_settingstringType of clinical setting where the diagnosis occurred (e.g., ER, outpatient, inpatient)emergency · outpatient · inpatient · otheremergency
diagnosis_codestringStandardized code for the diagnosed condition (e.g., ICD-10)J20.9
diagnosis_descriptionstringDescription of the diagnosed conditionEnd stage renal disease
error_typestringType of diagnostic error (e.g., missed, delayed, incorrect)missed · delayed · incorrect · othermissed
error_descriptionstringDetailed description of the diagnostic errorInitial symptoms attribut…
error_severitystringSeverity level of the diagnostic errorlow · moderate · high · criticalmoderate
clinician_idstringUnique identifier for the clinician responsible for the diagnosisCLIN2001
clinician_rolestringRole of the clinician (e.g., physician, nurse, resident)physician · nurse · resident · otherresident
organization_idstringUnique identifier for the healthcare organizationORG1001
organization_namestringName of the healthcare organizationWestside Family Health
organization_citystringCity where the healthcare organization is locatedFresno
organization_statestringState where the healthcare organization is locatedCA
organization_postal_codestringPostal code of the healthcare organization93722
organization_countrystringCountry where the healthcare organization is locatedUSA
quality_improvement_actionstringDescription of actions taken for quality improvement following the erroroptionalRenal consult protocol re…
outcome_impactstringImpact of the error on patient outcomenone · minor · moderate · severe · fatalminor
Numbers 2 columns
diagnostic_error_idintegerUnique identifier for each diagnostic error recordunique1
patient_ageintegerAge of the patient at the time of diagnosis0 to 1207
Dates and times 2 columns
diagnosis_datedateDate when the diagnosis was made2024-03-14
error_detected_datedateDate when the diagnostic error was identified2024-03-17
True or false 2 columns
compliance_flagbooleanIndicates if the error was reported for compliance purposesfalse
follow_up_requiredbooleanIndicates if follow-up was required due to the errortrue

Use it for

  • compliance flag67%133 of 200 rowsmean patient age by o…31.8none37.4minor23.2mode…64.0seve…

    A healthcare dashboard

    The compliance_flag rate, patient_age by outcome_impact and a breakdown of organization_state. Excel, Power BI or Tableau.

  • Why do the 25 fatal rows have a mean patient_age of 83.0?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable rows with patient_id, patient_age and patient_gender to fill a screen in front of a buyer.

Not quite right?

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This dataset200 rows24 columns
Yours1,000 rows24 columnsorganization_city: UK only

blueprint · healthcare-diagnostic-error-analysis

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 24 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
  • Compare initial and final diagnoses
  • Track error types by department
  • Include patient outcome metrics
  • Segment data by provider role
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
healthcare-diagnostic-error-analysis

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