Comparing co-morbidities in total joint arthroplasty patients using the RxRisk-V, Elixhauser, and Charlson Measures: a cross-sectional evaluation

Background

Joint arthroplasty patients have a high prevalence of co-morbidities and this impacts their surgical outcomes. There are different ways to ascertain co-morbidities and appropriate measurement is necessary. The purpose of this study was to: (1) describe the prevalence of co-morbidities in a cohort of total hip arthroplasty (THA) and knee arthroplasty (TKA) patients using two diagnoses-based measures (Charlson and Elixhauser) and one prescription-based measure (RxRisk-V); (2) compare the agreement of co-morbidities amongst the measures.

Methods

A cross-sectional study of Australian veterans undergoing THAs (n = 11,848) and TKAs (n = 18,972) between 2001 and 2012 was conducted. Seventeen co-morbidities were identified using the Charlson, 30 using the Elixhauser, and 42 using the RxRisk-V measure. Agreement between co-morbidities was calculated using Kappa (κ) statistics.

Results

Combining measures, 64 conditions were identified, of these 28 were only identified using the RxRisk-V, 11 using the Elixhauser, and 2 using the Charlson. The most prevalent conditions was pain treated with anti-inflammatories (58.7 % THAs, 55.9 % TKAs), pain treated with narcotics (55.0 % THAs, 50.9 % TKAs), hypertension (56.0 % THAs and TKAs), and anticoagulation disorders (53.0 % THAs, 48.6 % TKAs). Diabetes was the only condition with substantial agreement (all κ > 0.6) amongst all measures. When comparing the diagnoses based algorithms, agreement was high for overlapping conditions (all κ > 0.71).

Conclusions

Different measures identified different co-morbidities, provided different estimates for the same co-morbidity, and had different levels of agreement for common co-morbidities. This highlights the importance of understanding co-morbidity measures and using them appropriately in studies and case-mix adjustments analyses.