1. Computer Assisted Evaluation of Clinical Data Quality Nordic Casemix Conference 4.6.2010 Olafr Steinum, Sequelae AB Seppo Ranta, Datawell Oy

2. 2 Introduction  Reported health care information is widely used by authorities For health care planning For quality analyses For reimbursement For science and research  It is of paramount importance that the reported health data are correct and valid  Quality assurance is needed Coding audits Automatized controls

3. 3 Datawell DRG QA for data quality assurance  DRG QA is a Datawell product  Uses three different logics for data quality evaluation 1. Rules and reference databases (e.g. diagnosis codes) used for NordDRG grouping 2. Evaluation of the order of diagnoses (which one is the primary diagnosis, which are secondary diagnoses) inferrred from large statistical database (Normalization) 3. Clinical Validation Rulebase (CVRB) created and maintained by Sequelae AB  The software can be used as part of encoder system for immediate feedback of coding quality standalone system for evaluation of organization data quality benchmarking system comparing several peer organizations

4. 4 Datawell DRG QA  DRG QA is a Datawell product ****  Uses three different logics for data quality evaluation 1. Rules and reference databases (e.g. diagnosis codes) used for NordDRG grouping 2. Evaluation of the order of diagnoses (which one is the primary diagnosis, which are secondary diagnoses) inferrred from large statistical database (Normalization) 3. Clinical Validation Rulebase (CVRB) created and maintained by Sequelae AB  The software can be used as part of encoder system for immediate feedback of coding quality standalone system for evaluation of organization data quality benchmarking system comparing several peer organizations Sequelae AB Is a joint colloboration between Emendor Consulting AB, (Staffan Bryngelsson) and Olafr Steinum (diaQualos AB) Gunnar Henriksson (DRG Henriksson AB) Sequelae AB Is a joint colloboration between Emendor Consulting AB, (Staffan Bryngelsson) and Olafr Steinum (diaQualos AB) Gunnar Henriksson (DRG Henriksson AB)

5. 5 Datawell DRG QA  DRG QA is a Datawell product  Uses three different logics for data quality evaluation 1. Rules and reference databases (e.g. diagnosis codes) used for NordDRG grouping 2. Evaluation of the order of diagnoses (which one is the primary diagnosis, which are secondary diagnoses) inferrred from large statistical database (Normalization) 3. Clinical Validation Rulebase (CVRB) created and maintained by Sequelae AB  The software can be used as part of encoder system for immediate feedback of coding quality standalone system for evaluation of organization data quality benchmarking system comparing several peer organizations

6. 6 PatIdDg-aDg-dPrLOSAgeDischgSex 132133134HOMEM 43242H10.1J80WX101154HOMEN 43242 F0289 E756 GD1BD63HOSPN 64243V02.0241HOMEN 34212O75.7MAF00434HOMEM DRG QA – An Example of Indicator Calculation Logic Age not within acceptable limits External cause code as principal diagnosis Input data set Erroneous ICD-10 code Missing principal diagnosis PatIdDg-aDg-dPrLOSAgeDischgSex 132133134HOMEM 43242H10.1J80WX101154HOMEN 43242 F0289 E756 GD1BD63HOSPN 64243V02.0241HOMEN 34212O75.7MAF00434HOMEM Local procedure code Mismatch of diagnosis and gender Validations

7. 7 PatIdDg-aDg-dPrLOSAgeDischgSexFDGFPRSEXDGFAGE 132133134HOMEM11002 43242H10.1J80WX101154HOMEN10011000 43242 F0289 E756 GD1BD63HOSPN100 00 64243V02.0241HOMEN12000 34212O75.7MAF00434HOMEM100 30 DRG QA – An Example of Indicators in DRG QA Database Errors in Diagnosis coding Errors in Procedure coding Mismatch of diagnosis and gender Errors in Age coding

8. 8 DRG QA Pilot Benchmark Database  Seven Hospital Districts in Finland DRG QA Database contains patient cases from the Ecomed KPP databases from 2008 Data source: Ecomed KPP used in the 7 hospitals  Three County Councils in Sweden DRG QA Database contains all patient visits and stays from 2008 Data source: Patient Administrative Systems in corresponding county councils  Number of patient cases Finland n = 4.928.113 Sweden n = 4.332.206

9. 9 Hospital Districts’ Ecomed KPP databases (FI), or similar data retrieval from Patient Administrative Systems (SE) etc. County Council C DRG QA Database Formation Process Datawell DRG QA ETL Ecomed DRG QA Database Ecomed Analyzer Analysis of Data Quality Reporting County Council B County Council A District C District B District A Datawell DRG QA Indicator Calculation Data format transformations: hospital code  common code mappings Calculation of DRG grouping indicators DRG normalization Calculation of CVRB matching Includes refence population data (1-year intervals) for standardization

10. 10 Data Analysis for the Current Presentation  For this presentation purporses we produced a sample of the benchmarking database  Rules for formation of the present sample Included hospital stays (coded as ward stays in the source data) Length of stay (LOS) over zero days Excludes psychiatry  After applying above mentioned filters the analysis sample consists of 493 689 ward stays in seven Finnish Hospital Distrcits’ hospitals, and 444 255 ward stays in three Swedish County Councils’ hospitals

11. 11 Background Information: Number of Hospital Stays Finnish University Hospitals Non-university (Fi) Swedish County Councils n = 493 674 (FI); n = 444 255 (SE)

12. 12 Background Information: Number of Stays in Different Age Groups n = 493 674 (FI); n = 444 255 (SE)

13. 13 Background information: Average Length of Hospital Stays Finnish University Hospitals Non-university (Fi) Swedish County Councils n = 493 689 (FI); n = 444 255 (SE)

14. 14 Background information: Average Number of Diagnosis Codes per Stay Finnish University Hospitals Non-university (Fi)Swedish County Councils n = 493 689 (FI); n = 444 255 (SE)

15. 15 Background information: Average Number of Procedure Codes per Stay Finnish University Hospitals Non-university (Fi) Swedish County Councils n = 493 689 (FI); n = 444 255 (SE)

16. 16 Background information: Average DRG Weight per Stay Finnish University HospitalsNon-university (Fi) Swedish County Councils n = 493 689 (FI); n = 444 255 (SE)

17. 17 DRG CC Cases Finnish University Hospitals Non-university (Fi) Swedish County Councils n = 120 060 (FI); n = 147 740 (SE)

18. 18 Diabetes as Principal or Secondary Diagnosis Finnish University Hospitals Non-university (Fi) Swedish County Councils n = 20 713 (FI); n = 40 085 (SE)

19. 19 Number of Surgical Procedure Codes (OR property in NordDRG) Finnish University Hospitals Non-university (Fi)Swedish County Councils n = 493 689 (FI); n = 444 255 (SE)

20. 20 Surgical Procedure Codes after Stays in Operative Wards n = 283 633 (FI); n = 203 684 (SE)

21. 21 The classification of diagnosis (ICD-10)  A complex system for collecting data for statistics Many axes Many rules Explicit rules Rules expressed in the Tabular volume in connection to code categories Rules assumed, but not explicitely expressed  Clinical validation rule base - CVRB A collection of identified rules

22. 22 Rate of Z51.1 Chemotherapy session as Principal or Secondary diagnosis. Swedish county councils 2008 Data from Swedish National Patient Registry Principal dx Secondary dx

23. 23 1 Not to be used 2 Ought not to be used 3 Not to be used for children < 15 years 4 Ought not to be used for children < 15 yrs 5 Not to be used in inpatient care 6 Ought not to be used in inpatient care 7 Not to be combined with code2 8 Ought not to be combined with code2 9 Not to be used as principal dx 10 Ought not to be used as principal dx 11 Not to be used as secondary dx 12 Ought not to be used as secondary dx 13 Not to be used as principal dx in combination with code2 14 Ought not to be used as principal dx in combination with code2 15 Not to be used as secondary dx in combination with principal dx code2 16 Ought not to be used as secondary dx In combination with principal dx code2 17 Not to be used as single code 18 Ought not to be used as single code 19 Not to be used in combination with other dagger code than code2 20 Ought not to be used in combination with other dagger code than code2 21 Must be combined with code2 22 Ought to be combined with code2 23 Must be combined with an external cause code (chapter XX) for toxic agent 24 Ought to be combined with external cause code (chapter XX) for toxic agent 25 Must be used as secondary dx only in combination with principal dx = code2 26 Ought to be used as secondary dx only in combination with principal dx = code2 27 Must be secondary dx when combined with code2 28 Ought to be secondary dx when in combination with code2 29 Must be principal dx in combination with code2 30 Ought to be principal dx in combination with code2 31 Rare code 32 Rare code inpatient care 33 Rare code outpatient care © Sequelae AB CVRB Rules 2009

24. 24 Frequency of CVRB violation in a test database from 10 provinces n = 493 689 (FI); n = 444 255 (SE)

25. 25 CVRB Violation Profile in Finland and Sweden, Ward Stays, LOS > 0 days n = 493 689 (FI); n = 444 255 (SE)

26. 26 Distribution of CVRB violation in test database (10 provinces) CVRB violation rule

27. 27 CVRB Violation rules Not to be used Ought not to be used Not to be used in inpatient care Not to be combined with code2 Ought not to be combined with code2 Not to be used as principal dx Ought not to be used as principal dx Not to be used as secondary dx Not to be used as principal dx in combination with code2 Ought not to be used as secondary dx in combination with principal dx code2 Ought not to be used as single code Not to be used in combination with other dagger code than code2 Must be combined with code2 Ought to be combined with code2 Ought to be combined with external cause code (chapter XX) for toxic agent Ought to be used as secondary dx only in combination with code2 Must be secondary dx when in combination with code2 Rare code Rare code inpatient care

28. 28 CVRB11 Not to be used as secondary dx 273 codes from Ch 21 (Z-codes) only to be used as Reason for admission CVRB10 Ought not to be used as principal dx 16 code categories, mainly unspecified codes and codes marking sequelae Example of CVRB Violation rules result in percent of inpatient stays FinlandSweden CVRB10 CVRB11 1 2 3 4 5 6 7 8 9 10

29. 29 Information Process and the Identified Sources of Quality Failure Human-Computer interface Feeding of structured information into the PAS Processing rules and logics of the information systems Usability and maintenance of national code systems (ICD, NCSP, DRG etc.) Current transversal study of the information process Entry of data Processing of data Utilization of data and information Code systems

30. 30 Information Process and Benefits of Datawell DRG QA Immediate feedback of coding results to coding personnel Information on organization data quality for focusing education and other corrective actions. Benchmarking data quality with peer organizations. Entry of data Processing of data Utilization of data and information Code systems Reports of data quality incorporated with other reporting

31. 31 Data which nobody is using has a quality that nobody wants Thank you!