A prospective cohort study of two predictor models for 30-day emergency readmission in older patients

Michael N. Armitage*, Vivek Srivastava, Benjamin K. Allison, Marcus V. Williams, Michelle Brandt-Sarif, Geraldine Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Aim: To undertake a prospective study of the accuracy of two models (LACE and BOOST) in predicting unplanned hospital readmission in older patients (>75 years). Methods: Data were collected from a single centre prospectively on 110 patients over 75 years old admitted to the acute medical unit. Follow-up was conducted at 30 days. The primary outcome was the c-statistic for both models. Results: The readmission rate was 32.7% and median age 82 years, and both BOOST and LACE scores were significantly higher in those readmitted compared with those who were not. C-statistics were calculated for both tools with BOOST score 0.667 (95% CI 0.559-0.775, P =.005) and LACE index 0.685 (95% CI 0.579-0.792, P =.002). Conclusion: In this prospective study, both the BOOST and LACE scores were found to be significant yet poor, predictive models of hospital readmission. Recent hospitalisation (within the previous 6 months) was found to be the most significant contributing factor.

Original languageEnglish
Article numbere14478
JournalInternational Journal of Clinical Practice
Volume75
Issue number9
Early online date25 Jun 2021
DOIs
Publication statusPublished - Sept 2021

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