An automated model using electronic medical record data identifies patients with cirrhosis at high risk for...

Patients with cirrhosis have 1-month rates of readmission as high as 35%. Early identification of high-risk patients could permit interventions to reduce readmission. The aim of our study was to construct an automated 30-day readmission risk model for cirrhotic patients using electronic medical record (EMR) data available early during hospitalization.

We identified patients with cirrhosis admitted to a large safety-net hospital from January 2008 through December 2009. A multiple logistic regression model for 30-day rehospitalization was developed using medical and socioeconomic factors available within 48 hours of admission and tested on a validation cohort. Discrimination was assessed using receiver operator characteristic curve analysis.

We identified 836 cirrhotic patients with 1291 unique admission encounters. Rehospitalization occurred within 30 days for 27% of patients. Significant predictors of 30-day readmission included the number of address changes in the prior year (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.05-1.21), number of admissions in the prior year (OR, 1.14; 95% CI, 1.05-1.24), Medicaid insurance (OR, 1.53; 95% CI, 1.10-2.13), thrombocytopenia (OR, 0.50; 95% CI, 0.35-0.72), low level of alanine aminotransferase (OR, 2.56; 95% CI, 1.09-6.00), anemia (OR, 1.63; 95% CI, 1.17-2.27), hyponatremia (OR, 1.78; 95% CI, 1.14-2.80), and Model for End-stage Liver Disease score (OR, 1.04; 95% CI, 1.01-1.06). The risk model predicted 30-day readmission, with c-statistics of 0.68 (95% CI, 0.64-0.72) and 0.66 (95% CI, 0.59-0.73) in the derivation and validation cohorts, respectively.

Clinical and social factors available early during admission and extractable from an EMR predicted 30-day readmission in cirrhotic patients with moderate accuracy. Decision support tools that use EMR-automated data are useful for risk stratification of patients with cirrhosis early during hospitalization.