Evaluation of Patients at Risk of Hospital Readmission (PARR) and LACE Risk Score for New Zealand Context
Baig, M.; Zhang, E.; Robinson, R.; Ullah, E.; Whitakker, R.
Studies in Health Technology and Informatics 252: 21-26
2018
ISSN/ISBN: 1879-8365 PMID: 30040677 Document Number: 697072
Identification and prediction of patients who are at risk of hospital readmission is a critical step towards the reduction of the potential avoidable costs for healthcare organisations. This research was focused on the evaluation of LACE Index for Readmission - Length of stay (days), Acute (emergent) admission, Charlson Comorbidity Index and number of ED visits within six months (LACE) and Patients At Risk of Hospital Readmission (PARR) using New Zealand hospital admissions. This research estimates the risk for all readmissions rather than only those in a subset of referenced conditions. In total, 213,440 admissions between 1 Jan 2015 and 31 Dec 2016 were selected after appropriate ethics approvals and permissions from the three hospitals. The evaluation method used is the Receiver Operating Characteristics (ROC) analysis to evaluate the accuracy of both the LACE and PARR models. As a result, The LACE index achieved an Area Under the Curve (AUC) score of 0.658 in predicting 30-day readmissions. The optimal cut-off for the LACE index is a score of 7 or more with sensitivity of 0.752 and specificity of 0.564. Whereas, the PARR algorithm achieved an AUC score of 0.628 in predicting 30-day readmissions. The optimal cut-off for the PARR index is a score of 0.34 or more with sensitivity of 0.714 and specificity of 0.542.