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Updated: Dec 20, 2025
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Comparative evaluation of the clinical laboratory-based Intermountain risk score with the Charlson and Elixhauser
Gregory L Snow1, Joseph R Bledsoe2,3, Allison Butler1
1Office of Research, Intermountain Healthcare, Salt Lake City, Utah, United States of America.
Insights
The Intermountain Mortality Risk Scores (IMRS) significantly improve mortality prediction compared to Charlson and Elixhauser indices. IMRS, using common lab data, offers superior accuracy for patient risk assessment.
Area of Science:
- Clinical Informatics
- Health Services Research
- Biostatistics
Background:
- Charlson and Elixhauser comorbidity indices are established mortality predictors.
- Intermountain Mortality Risk Scores (IMRS) are validated mortality predictors utilizing complete blood count and basic metabolic profile data.
- The relationship between IMRS, Charlson, and Elixhauser indices in mortality prediction was previously unknown.
Purpose of the Study:
- To compare the predictive performance of IMRS against Charlson and Elixhauser indices for patient mortality.
- To investigate the combined predictive power of IMRS with Charlson and Elixhauser indices.
- To determine the optimal formulation of each index for mortality risk assessment.
Main Methods:
- An observational cohort study analyzed 197,680 inpatient admissions from 2010-2014.
- Cox regression evaluated multiple versions of Charlson, Elixhauser, and IMRS.
- Dual risk score analyses were performed for in-hospital, 30-day, 1-year, and 5-year mortality.
Main Results:
- The age-adjusted Charlson, van Walraven Elixhauser, and 1-year IMRS were selected for dual analysis.
- IMRS demonstrated the strongest individual mortality prediction (c=0.821) compared to Charlson (c=0.719) and Elixhauser (c=0.783).
- Dual models combining IMRS with either Charlson or Elixhauser showed significant predictive value for both indices across all mortality time points.
Conclusions:
- IMRS offers superior mortality prediction compared to Charlson and Elixhauser indices.
- IMRS enhances and modulates the predictive ability of existing comorbidity indices.
- IMRS, leveraging standardized laboratory data, warrants further evaluation for integration into clinical mortality risk assessments.
Background:
The 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.
Methods:
All 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).
Results:
Indices 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.
Conclusions:
IMRS 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.
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