Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore
Joint Authors
Low, Lian Leng
Lee, Kheng Hock
Wang, Sijia
Tan, Shu Yun
Thumboo, Julian
Liu, Nan
Ong, Marcus Eng Hock
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-23
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Low, Lian Leng& Lee, Kheng Hock& Ong, Marcus Eng Hock& Wang, Sijia& Tan, Shu Yun& Thumboo, Julian…[et al.]. 2015. Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore. BioMed Research International،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1054474
Modern Language Association (MLA)
Low, Lian Leng…[et al.]. Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore. BioMed Research International No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1054474
American Medical Association (AMA)
Low, Lian Leng& Lee, Kheng Hock& Ong, Marcus Eng Hock& Wang, Sijia& Tan, Shu Yun& Thumboo, Julian…[et al.]. Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1054474
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1054474