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The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Menendez, Mariano E. Neuhaus, Valentin Van Dijk, C. Niek Ring, David
Spatial Coverage	United States
Description	Author Affiliation: Menendez ME ( Orthopaedic Hand and Upper Extremity Service, Massachusetts General Hospital, Yawkey Center, Suite 2100, 55 Fruit Street, Boston, MA, 02114, USA, marianofurrer@gmail.com.)
Abstract	BACKGROUND: Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are well-known risk adjustment models, yet the optimal score for orthopaedic patients remains unclear. QUESTIONS/PURPOSES: We determined whether there was a difference in the accuracy of the Charlson and Elixhauser comorbidity-based measures in predicting (1) in-hospital mortality after major orthopaedic surgery, (2) in-hospital adverse events, and (3) nonroutine discharge. METHODS: Among an estimated 14,007,813 patients undergoing orthopaedic surgery identified in the National Hospital Discharge Survey (1990-2007), 0.80% died in the hospital. The association of each Charlson comorbidity measure and Elixhauser comorbidity measure with mortality was assessed in bivariate analysis. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and one of the two comorbidity-based measures (and age, sex, and year of surgery) as independent variables. A base model that included only age, sex, and year of surgery also was evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC). The AUC quantifies the ability of our models to assign a high probability of mortality to patients who die. Values range from 0.50 to 1.0, with 0.50 indicating no ability to discriminate and 1.0 indicating perfect discrimination. RESULTS: Elixhauser comorbidity adjustment provided a better prediction of in-hospital case mortality (AUC, 0.86; 95% CI, 0.86-0.86) compared with the Charlson model (AUC, 0.83; 95% CI, 0.83-0.84) and to the base model with no comorbidities (AUC, 0.81; 95% CI, 0.81-0.81). In terms of relative improvement in predictive performance, the Elixhauser measure performed 60% better than the Charlson score in predicting mortality. The Elixhauser model discriminated inpatient morbidity better than the Charlson measure, but the discriminative ability of the model was poor and the difference in the absolute improvement in predictive power between the two models (AUC, 0.01) is of dubious clinical importance. Both comorbidity models exhibited the same degree of discrimination for estimating nonroutine discharge (AUC, 0.81; 95% CI, 0.81-0.82 for both models). CONCLUSIONS: Provider-specific outcomes, particularly inpatient mortality, may be evaluated differently depending on the comorbidity risk adjustment model selected. Future research assessing and comparing the performance of the Charlson and Elixhauser measures in predicting long-term outcomes would be of value. LEVEL OF EVIDENCE: Level II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.
File Format	HTM / HTML
ISSN	0009921X
e-ISSN	15281132
DOI	10.1007/s11999-014-3686-7
Journal	Clinical Orthopaedics and Related Researchtextregistered
Issue Number	9
Volume Number	472
Language	English
Publisher	Springer
Publisher Date	2014-09-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Orthopaedics Bone Diseases Epidemiology Hospital Mortality Inpatients Statistics & Numerical Data Orthopedic Procedures Mortality Risk Assessment Surgery Comorbidity Patient Discharge Prognosis Roc Curve Retrospective Studies Multicenter Study
Content Type	Text
Resource Type	Article
Subject	Orthopedics and Sports Medicine Surgery Sports Science

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