Abstract
BackgroundThe Charlson and Elixhauser comorbidity indices are mortality predictors often used in clinical, administrative, and research applications. The Intermountain Mortality Risk Scores (IMRS) are validated mortality predictors that use all factors from the complete blood count and basic metabolic profile. How IMRS, Charlson, and Elixhauser relate to each other is unknown.MethodsAll inpatient admissions except obstetric patients at Intermountain Healthcare’s 21 adult care hospitals from 2010–2014 (N = 197,680) were examined in a observational cohort study. The most recent admission was a patient’s index encounter. Follow-up to 2018 used hospital death records, Utah death certificates, and the Social Security death master file. Three Charlson versions, 8 Elixhauser versions, and 3 IMRS formulations were evaluated in Cox regression and the one of each that was most predictive was used in dual risk score mortality analyses (in-hospital, 30-day, 1-year, and 5-year mortality).ResultsIndices with the strongest mortality associations and selected for dual score study were the age-adjusted Charlson, the van Walraven version of the acute Elixhauser, and the 1-year IMRS. For in-hospital mortality, Charlson (c = 0.719; HR = 4.75, 95% CI = 4.45, 5.07), Elixhauser (c = 0.783; HR = 5.79, CI = 5.41, 6.19), and IMRS (c = 0.821; HR = 17.95, CI = 15.90, 20.26) were significant predictors (p<0.001) in univariate analyses. Dual score analysis of Charlson (HR = 1.79, CI = 1.66, 1.92) with IMRS (HR = 13.10, CI = 11.53, 14.87) and of Elixhauser (HR = 3.00, CI = 2.80, 3.21) with IMRS (HR = 11.42, CI = 10.09, 12.92) found significance for both scores in each model. Results were similar for 30-day, 1-year, and 5-year mortality.ConclusionsIMRS provided the strongest ability to predict mortality, adding to and attenuating the predictive ability of the Charlson and Elixhauser indices whose mortality associations remained statistically significant. IMRS uses common, standardized, objective laboratory data and should be further evaluated for integration into mortality risk evaluations.
Highlights
Charlson et al [1] and Elixhauser et al [2] previously proposed comorbidity measures to predict mortality using diagnoses of chronic diseases and health conditions
Three Charlson versions, 8 Elixhauser versions, and 3 Intermountain Mortality Risk Scores (IMRS) formulations were evaluated in Cox regression and the one of each that was most predictive was used in dual risk score mortality analyses
Both scores rely on International Statistical Classification of Diseases and Related Health Problems (ICD) coding to define the various comorbidities, summarizing conditions the patient has currently or was diagnosed with in the past even if they are in remission. These comorbidity indices provide a useful and practical summary of risk information that is clinically attractive because they summarize overall patient status through a common-sense approach. They use data elements that are readily available to clinicians in the electronic health record (EHR), or at the conclusion of the history and physical exam
Summary
Charlson et al [1] and Elixhauser et al [2] previously proposed comorbidity measures to predict mortality using diagnoses of chronic diseases and health conditions. Both scores rely on International Statistical Classification of Diseases and Related Health Problems (ICD) coding to define the various comorbidities, summarizing conditions the patient has currently or was diagnosed with in the past even if they are in remission These comorbidity indices provide a useful and practical summary of risk information that is clinically attractive because they summarize overall patient status through a common-sense approach. They use data elements that are readily available to clinicians in the electronic health record (EHR), or at the conclusion of the history and physical exam. How IMRS, Charlson, and Elixhauser relate to each other is unknown
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