UC Irvine

Background: Hospital readmissions are burdensome to patients and costly to the healthcare system. Readmissions may be the result of poor transitional care and targeted interventions may help prevent unnecessary hospitalizations. Identifying patients that are at high risk for hospital readmission could help hospitals focus their resources towards preventing these events.

Methods: In a retrospective study at the University of California, Irvine Medical Center, multiple patient-level variables, including the LACE index and HOSPITAL score, were collected on patient admissions from February 1, 2017 to April 30, 2017 to determine which variables were significant predictors of 30-day hospital readmission.

Results: The analysis included data for 827 discharges within the study period. The prediction model using the LACE index demonstrated a C-statistic of 0.83 (95% CI, 0.81-0.86). The C-statistic for the model using the HOSPITAL score was 0.77 (95% CI, 0.74-0.80). A prediction model that utilized the LACE index, plus two other significant variables (number of hospital admissions within the previous 12 months and presence of an abnormal vital sign within 24 hours of discharge), demonstrated a C-statistic of 0.91 (95% CI, 0.89-0.93). The Hosmer-Lemeshow goodness of fit test for the LACE “plus” model had a chi-squared value of 1.63 with a p-value of 0.99. The HOSPITAL score, plus three additional significant variables (the Charlson Comorbidity Index, discharge by the Hospitalist service, and an abnormal vital sign within 24 hours of discharge), showed a C-statistic of 0.88 (95% CI, 0.85-0.90). The Hosmer-Lemeshow goodness of fit test for the HOSPITAL “plus” model had a chi-squared value of 10.99 with a p-value of 0.20.

Interpretation: Both the LACE index and HOSPITAL score performed well in predicting hospital readmissions in this retrospective study. The addition of other significant variables to these scores improved the discrimination of the prediction models, suggesting that the addition of other variables may improve the ability of these scores to predict 30-day hospital readmissions.