LACE Score-Based Risk Management Tool for Long-Term Home Care Patients: A Proof-of-Concept Study in Taiwan

Mei-Chin Su, Yu-Chun Chen, Mei-Shu Huang, Yen-Hsi Lin, Li-Hwa Lin, Hsiao-Ting Chang and Tzeng-Ji Chen
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Mei-Chin Su: Department of Nursing, Taipei Veterans General Hospital, Taipei 112, Taiwan
Yu-Chun Chen: Institute of Hospital and Health Care Administration, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
Mei-Shu Huang: Department of Nursing, Taipei Veterans General Hospital, Taipei 112, Taiwan
Yen-Hsi Lin: Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
Li-Hwa Lin: Department of Nursing, Taipei Veterans General Hospital, Taipei 112, Taiwan
Hsiao-Ting Chang: Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
Tzeng-Ji Chen: Institute of Hospital and Health Care Administration, National Yang Ming Chiao Tung University, Taipei 112, Taiwan

IJERPH, 2021, vol. 18, issue 3, 1-13

Abstract: Background: Effectively predicting and reducing readmission in long-term home care (LTHC) is challenging. We proposed, validated, and evaluated a risk management tool that stratifies LTHC patients by LACE predictive score for readmission risk, which can further help home care providers intervene with individualized preventive plans. Method: A before-and-after study was conducted by a LTHC unit in Taiwan. Patients with acute hospitalization within 30 days after discharge in the unit were enrolled as two cohorts (Pre-Implement cohort in 2017 and Post-Implement cohort in 2019). LACE score performance was evaluated by calibration and discrimination (AUC, area under receiver operator characteristic (ROC) curve). The clinical utility was evaluated by negative predictive value (NPV). Results: There were 48 patients with 87 acute hospitalizations in Pre-Implement cohort, and 132 patients with 179 hospitalizations in Post-Implement cohort. These LTHC patients were of older age, mostly intubated, and had more comorbidities. There was a significant reduction in readmission rate by 44.7% (readmission rate 25.3% vs. 14.0% in both cohorts). Although LACE score predictive model still has room for improvement (AUC = 0.598), it showed the potential as a useful screening tool (NPV, 87.9%; 95% C.I., 74.2–94.8). The reduction effect is more pronounced in infection-related readmission. Conclusion: As real-world evidence, LACE score-based risk management tool significantly reduced readmission by 44.7% in this LTHC unit. Larger scale studies involving multiple homecare units are needed to assess the generalizability of this study.

Keywords: long-term care (LTC); long-term home care (LTHC); readmission; LACE score; predictive model; readmission risk management (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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