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OBJECTIVE: To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a 1-year lookback period improved prognostic adjustment by these scores individually, and combined, for 30-day mortality. STUDY DESIGN AND SETTING: We analyzed inpatient admissions from January 1, 2007 to May 18, 2018 in Oxfordshire, UK. Comorbidity scores were calculated using secondary diagnostic codes in the diagnostic-dominant episode, and primary and secondary codes from the year before. Associations between scores and 30-day mortality were investigated using Cox models with natural cubic splines for nonlinearity, assessing fit using Akaike Information Criteria. RESULTS: The 1-year lookback improved model fit for Charlson and Elixhauser scores vs. using diagnostic-dominant methods. Including both, and allowing nonlinearity, improved model fit further. The diagnosis-dominant Charlson score and Elixhauser score using a 1-year lookback, and their interaction, provided the best comorbidity adjustment (reduction in AIC: 761 from best single score model). CONCLUSION: The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from the current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (1-year lookback) scores, incorporating nonlinearity and interactions for optimal confounding control.

Original publication




Journal article


J Clin Epidemiol

Publication Date





32 - 41


Charlson, Comorbidity, Confounding, Electronic health records, Elixhauser, ICD-10, Adult, Aged, Comorbidity, Data Analysis, Female, Forecasting, Hospital Mortality, Humans, Inpatients, Logistic Models, Male, Middle Aged, Prognosis, Proportional Hazards Models, Retrospective Studies, Risk Assessment, United Kingdom