Review of the AR-DRG Classification Case Complexity Process: Final Report 1
Glossary of Abbreviations 4
Executive Summary 8
Overview 9
Aims of the Review of the Case Complexity Process 10
1Review the current Patient Clinical Complexity (PCCL) process and identify improvements and modifications. 10
2Determine the codes considered significant (currently the Complication and Comorbidity (CC) codes) in measuring case complexity. 10
3Determine whether there is a need for separate CC codes and/or matrix for paediatric and geriatric age splits. 10
4Determine whether more levels of complexity for significant diagnoses are required (currently for medical DRGs there are three Complication and Comorbidity Level (CCL) values and for surgical DRGs there are four CCL values). 10
5Examine whether more levels of complexity for the overall episode PCCL score are required (currently there is a maximum value of four). 10
6Determine whether the condition onset flag (COF) data should impact the case complexity score when the COF value indicates that the condition arose during the current episode of care. 10
7Validate codes that are to be significant to the DRG classification and the clinical reasonableness of the final case complexity results through clinical consultation. 10
Important terminology 11
Methodology 12
Key Findings and Recommendations 13
Implications 16
Stability of the Episode Clinical Complexity Model 17
Episode Clinical Complexity Model implementation 18
Changes to episode grouping 19
Private Hospitals 20
Education about the Episode Clinical Complexity Model and its implications 21
Next steps 22
8Introduction 23
9Determine the codes considered significant (currently the Complication and Comorbidity (CC) codes) in measuring case complexity. 25
10Determine whether there is a need for separate CC codes and/or matrix for paediatric and geriatric age splits. 25
11Determine whether more levels of complexity for significant diagnoses are required (currently for medical DRGs there are three Complication and Comorbidity Level (CCL) values and for surgical DRGs there are four CCL values). 25
12Examine whether more levels of complexity for the overall episode PCCL score are required (currently there is a maximum value of four). 25
13Determine whether the condition onset flag (COF) data should impact the case complexity score when the COF value indicates that the condition arose during the current episode of care. 25
14Validate codes that are to be significant to the DRG classification and the clinical reasonableness of the final case complexity results through clinical consultation. 25
14.1Background 26
14.2Brief history and development of DRGs in Australia 27
14.3Use of costing data in DRG Refinement 28
14.4Current case complexity definitions 30
14.5Case complexity processing within the current AR-DRG classification 31
14.6Approaches to DRG development taken internationally to account for complications and comorbidities 32
14.6.1The United States 33
14.6.2Germany 34
14.6.3France 35
14.6.4Canada 36
14.6.5England 37
14.6.6Other 38
14.6.7In summary 39
14.7Episode Clinical Complexity Model terminology 40
14.8Governance and consultation process 41
14.9Project Overview 44
15Data preparation 45
15.1Source data 46
15.2ICD-10-AM mapping 47
15.3Data exclusions 48
16Using Adjacent DRG and diagnosis cost profiles to evaluate AR-DRG Version 7.0 Complications and Comorbidities Levels 49
16.1ADRG cost profiles 50
16.2Diagnosis cost profiles 52
16.3Evaluation of AR-DRG V7.0 CCLs using diagnosis cost profiles 54
17The Episode Clinical Complexity Model 57
17.1Summary of the development of the Episode Clinical Complexity Model 58
17.1.1Measuring relative changes in cost associated with diagnosis cost profiles 59
17.1.2Standardising the diagnosis relative costs within each ADRG 62
17.1.3Combined diagnosis relative cost associations at the episode level 63
17.2Formal development of the Episode Clinical Complexity Model 64
17.2.1Diagnosis exclusions 65
17.2.2Modelling of ADRG costs 66
17.2.3Estimation of relative costs associated with diagnoses within the context of ADRGs 75
17.2.4Derivation of the Diagnosis Complexity Level 77
17.2.5Combining Diagnosis Complexity Levels across episodes and derivation of the Episode Clinical Complexity Score 89
17.2.6ECCS formula 91
18Treatment of the Principal diagnosis in classification design 96
18.1The DRG Classification Process 97
18.2Did the diagnoses include acute quadriplegia or paraplegia? The role of the Principal diagnosis in AR-DRG development 100
18.3Principal diagnosis impact on cost 102
19Guiding principles for Diagnosis Complexity Level assignment 107
19.1Diagnosis Complexity Level Assignment 108
19.2DCL scope guiding principle 1 109
19.2.1Group 1: Chapter 18 Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified (R00-R99) 110
19.2.2Group 2: Chapter 21 Factors influencing health status and contact with health services (Z00-Z99) 111
19.2.3Group 3: Unacceptable principal diagnoses 112
19.2.4Group 4: Special case exclusions 113
Codes that add descriptive information to an already assigned ICD-10-AM code 113
Sequelae (late effect) codes not appearing in Group 3. 113
Full-time dagger (aetiology) codes. 113
Conditional Exclusions (CEs) 113
19.3DCL scope guiding principle 2 115
19.3.1Codes identified as ‘in scope’ for DCL assignment from Groups 1– 3 above 116
20The use of condition onset flag in classification design 118
20.1Background 119
20.2Is there a potential role for COF in classification development? 121
20.3Other Considerations 123
20.3.1Retaining the integrity of the COF information 124
20.3.2Treating at risk patients 125
20.4In summary 126
21Evaluation of performance of the ECC Model 127
21.1Comparison of the 5-category ECCS models against the PCCL model 131
21.2Comparison of the 5-category ECCS models against the AR-DRG classification 133
21.3Comparison of performance across all models 136
21.4Comparative performance on paediatric episodes 141
21.5Comparative performance on geriatric episodes 144
22Continued refinement of ECC Model 148
22.1Ongoing evaluation and refinement of methodological and technical components of the ECC Model 149
22.1.1Enhancing DCL precision 150
22.2Ongoing evaluation and refinement of empirically derived components of the ECC Model 151
22.2.1Sample variation and DCL stability 152
23Conclusion 156
24References 159
25Appendices 162
26List of Figures 163
27List of Tables 164