Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

Mei-Chin Su, Yi-Jen Wang, Tzeng-Ji Chen, Shiao-Hui Chiu, Hsiao-Ting Chang, Mei-Shu Huang, Li-Hui Hu, Chu-Chuan Li, Su-Ju Yang, Jau-Ching Wu and Yu-Chun Chen
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Mei-Chin Su: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Yi-Jen Wang: Department of Family Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Tzeng-Ji Chen: Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei 11221, Taiwan
Shiao-Hui Chiu: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Hsiao-Ting Chang: Department of Family Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Mei-Shu Huang: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Li-Hui Hu: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Chu-Chuan Li: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Su-Ju Yang: Department of Nursing, Taipei Veterans General Hospital, Taipei 11217, Taiwan
Jau-Ching Wu: School of Medicine, National Yang-Ming University, Taipei 11221, Taiwan
Yu-Chun Chen: Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei 11221, Taiwan

IJERPH, 2020, vol. 17, issue 3, 1-17

Abstract: The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488–0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582–0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068–0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician’s model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients.

Keywords: home care patient; readmission; prediction model; simulation; risk management (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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