Development of an electronic frailty index for hospitalized geriatric patients in Sweden

Background: Frailty assessment in the Swedish health system relies on the Clinical Frailty Scale (CFS), but it requires training, in-person evaluation, and is often missing in medical records. We aimed to develop an electronic frailty index (eFI) from routinely collected electronic health records (EHRs) and assess its predictive ability for adverse outcomes in geriatric patients. Methods: EHRs were extracted for 18,225 geriatric patients with unplanned admissions between 1/3/2020 and 17/6/2021 from nine geriatric clinics in Stockholm, Sweden. A 48-item eFI was constructed using diagnostic codes, functioning and other health indicators, and laboratory data. The CFS, Hospital Frailty Risk Score, and Charlson Comorbidity Index were used for comparative assessment of the eFI. We modelled in-hospital mortality and 30-day readmission using logistic regression; 30-day and 6-month mortality using Cox regression; and length of stay using linear regression. Results: 13,188 patients were included in analyses (mean age 83.1 years). A 10% increment in the eFI was associated with higher risks of in-hospital (odds ratio: 5.34; 95% confidence interval: 4.20-6.82), 30-day (hazard ratio [HR]: 3.28; 2.91-3.69), and 6-month mortality (HR: 2.70; 2.52-2.90) adjusted for age and sex. Of the frailty and comorbidity measures, the eFI had the best predictive accuracy for in-hospital mortality, yielding an area under receiver operating characteristic curve of 0.813. Higher eFI also predicted a longer length of stay, but had a rather poor discrimination for 30-day readmission. Conclusions: An EHR-based eFI has good predictive accuracy for adverse outcomes, suggesting that it can be used in risk stratification in geriatric patients.