A derived logistic regression model predicted 30-day readmissions with a c-statistic of 0.650, compared to 0.628 for the LACE index, in a cohort with a 9.8% readmission rate.
Observational (n=5,862)
Does a derived logistic regression model improve the prediction of 30-day readmissions compared to the LACE index in general medicine patients?
A derived logistic regression model demonstrated fair discriminative ability and slightly outperformed the LACE index for predicting 30-day readmissions in a general medicine population.
The LACE index (length of stay, acuity of admission, Charlson comorbidity index, CCI, and number of emergency department visits in preceding 6 months) derived in Canada is simple and may have clinical utility in Singapore to predict readmission risk. We compared the performance of the LACE index with a derived model in identifying 30-day readmissions from a population of general medicine patients in Singapore. Additional variables include patient demographics, comorbidities, clinical and laboratory variables during the index admission, and prior healthcare utilization in the preceding year. 5,862 patients were analysed and 572 patients (9.8%) were readmitted in the 30 days following discharge. Age, CCI, count of surgical procedures during index admission, white cell count, serum albumin, and number of emergency department visits in previous 6 months were significantly associated with 30-day readmission risk. The final logistic regression model had fair discriminative ability c-statistic of 0.650 while the LACE index achieved c-statistic of 0.628 in predicting 30-day readmissions. Our derived model has the advantage of being available early in the admission to identify patients at high risk of readmission for interventions. Additional factors predicting readmission risk and machine learning techniques should be considered to improve model performance.
Low et al. (Thu,) conducted a observational in 30-day hospital readmission (n=5,862). Derived logistic regression model vs. LACE index was evaluated on 30-day readmission. A derived logistic regression model predicted 30-day readmissions with a c-statistic of 0.650, compared to 0.628 for the LACE index, in a cohort with a 9.8% readmission rate.