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Can we predict Acute Medical readmissions using the BOOST tool? A retrospective case note revi

  • Geraldine A. Lee
  • , Daniel Freedman
  • , Penelope Beddoes
  • , Emily Lyness
  • , Imogen Nixon
  • , Vivek Srivastava
  • King's College London
  • Kings College Hospitals Foundation NHS Trust

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Readmissions within 30-days of hospital discharge are a problem. The aim was to determine if the Better Outcomes for Older Adults through Safe Transitions (BOOST) risk assessment tool was applicable within the UK. Methods: Patients over 65 readmitted were identified retrospectively via a casenote review. BOOST assessment was applied with 1 point for each risk factor. Results: 324 patients were readmitted (mean age 77 years) with a median of 7 days between discharge and readmission. The median BOOST score was 3 (IQR 2-4) with polypharmacy evident in 88% and prior hospitalisation in 70%. The tool correctly predicted 90% of readmissions using two or more risk factors and 99.1% if one risk factor was included. Conclusion: The BOOST assessment tool appears appropriate in predicting readmissions however further analysis is required to determine its precision.

Original languageEnglish
Pages (from-to)119-123
Number of pages5
JournalAcute Medicine
Volume15
Issue number3
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • Audit
  • Hospital discharge
  • Predictive tool
  • Readmission

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