Health Roundtable Performance Indicators for Coding Quality Example Analysis

1. Health RoundtablePerformance Indicators for Coding Quality Example Analysis Period: January 2011 to March 2011 Joe Berry, Operations and Program Manager Jack Aisbett, PICQTM Data Manager Paul O’Connor, Principal David Dean, The Health Roundtable March 2012

2. Table of Contents • Background • PICQTM Concepts • Input Dataset Attributes • Benchmarking Results • PICQTM Indicator Degrees • Performance Measurement Results • Targeting Education and Training • ‘Special Request’ Benchmark Analysis • Take Outs

3. Background • Goal: Compare Coding Quality Levels Amongst Member Hospitals • Pavilion Health’s Performance Indicators for Coding Quality (PICQ™) software tool • Three Month Data Sample provided by The Health Roundtable (January 2011 through March 2011)

4. PICQTMA Coding Quality Tool Performance Indicators for Coding Quality • an auditing tool to identify records that may be incorrectly coded • measures coding accuracy by using a set of indicators • used for benchmarking across health services, hospitals and clinical coders • used for internal performance management to support: • the continuous review of coding quality, and • review of amended coded data quality

5. Why is Coding Quality Important?‘Good Clinical Documentation Guide’ • Good documentation supports quality patient care • Quality clinical documentation also ensures the information is reliable for many other purposes • Quality documentation quantifies hospital activity

6. Health Roundtable Sample Data Set • 1,123,242 medical record episodes of care • 180,743 medical records were excluded • 140,596 dialysis records were outside this exercise • 23,536 records were deleted where DOB was ‘null’ • 12,108 records were deleted where sex was ‘null’ • 2,600 records were deleted where calculated age was less than 0 • 1,590 records were deleted where the primary diagnosis was ‘null’ • Several other smaller deletions • Result: 942,499 records were processed through PICQTM

7. What does a PICQTM Indicator do? • When an indicator examines a record, it analyses diagnosis and procedure codes: • in combination with other codes • in combination with National Health Data Dictionary (NHDD) data items • in a sequence • for their presence or absence • for their specificity • PICQ™ can be applied at any stage of data collection • PAS extract • Data warehouse extract • PICQTM indicators are expressed in a standard format allowing comparison of outcomes: • over time • between facilities • between coders

8. PICQTM ReportingNumerator, Denominator and Ratio • Numerator records are the cases the indicator is seeking to identify (problem records); these records are selected from the denominator records • Denominator records are the cases in the data set under analysis in which the numerator records (problem records) could occur • When the PICQ™ program processes indicators against a data set the results are expressed as a ratio of numerator to denominator

9. Hospital BenchmarkPICQTM quality ratio results

10. PICQTM Indicator Degree • F, Fatal Indicator – any record found by such an indicator has been coded incorrectly by definition • W1, Warning Indicator, 1% threshold – records found by a warning indicator indicates that individual codes or combinations of codes or data items are likely to be incorrect • W2, Warning Indicator, other – records found by a warning indicator indicates that individual codes or combinations of codes or data items are likely to be incorrect (although the record is possibly correct) • R, Relative Indicator – records found by such an indicator are counted and expressed as a ratio of a larger (usually) group of episodes. These indicators would generally be used to assess the overall quality of coded data rather than identify individual problem records. Focus

11. Hospital Performance Measure - NSWFatal and Warning 1% PICQTM Indicators 1%

12. Hospital Performance Measure - QLDFatal and Warning 1% PICQTM Indicators 1%

13. Hospital Performance Measure - VICFatal and Warning 1% PICQTM Indicators 1%

14. Hospital Performance Measure - OtherFatal and Warning 1% PICQTM Indicators 1%

15. Performance Measures for NZ MembersMarkedly Different Effect of different ICD10 version?

16. Relative Specificity Indicator AnalysisICD Chapters 20, 19, 10, 11 and 4 education opportunities Target Use of ‘un-specified’ diagnoses codes will limit research capabilities Target Use of ‘other’ and ‘un-specified’ diagnoses codes can reduce the quality of the information used support patient care and correctly assign a DRG

17. Top 10 PICQTM Indicators by DegreeFailure to understand... first principles education theme

18. Top 10 PICQTM Indicators by DegreeFailure to understand... first principles education theme

19. Special Request Benchmark AnalysisICD Chapter 10 Respiratory specificity

20. Special Request Benchmark AnalysisPrincipal diagnosis I64, Stroke “Unspecified”

21. Take Outs • Clinical coding quality tools play a role in a quality management system • Data integrity • Consistent benchmarking • Performance measurement that supports policy • Targeting education and training • Quality clinical coding supports: • patient care and continuity of care, • research, and • the accurate description of activities provided to the patient • You can investigate and learn from each other • Overall clinical coding quality performance • Reduction of triggered Fatal, Warning 1% and Warning Other PICQTM indicators • Understanding the root causes of specificity and agreeing the benefit of their reduction