Open AccessPredicting length of stay for acute medical admissions using the ALICE score: a simple bedside tool
Author(s) -
Daniel Wilding,
Kate Evans
Publication year - 2017
Publication title -
acute medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.14
H-Index - 12
eISSN - 1747-4892
pISSN - 1747-4884
DOI - 10.52964/amja.0656
Subject(s) - medicine , alice (programming language) , medical diagnosis , medical record , emergency medicine , simple (philosophy) , medical emergency , retrospective cohort study , intensive care medicine , computer science , pathology , philosophy , epistemology , programming language
Background: Early identification of patients likely to have a short admission permits best use of limited resources to facilitate rapid discharge where possible. The ALICE score is a simple bedside tool developed in one hospital as a decision aid. This study sought to confirm its widespread applicability. Method: Retrospective review of 250 consecutive admissions at five acute hospitals. Clinical records were reviewed for a total of 1003 patients. ALICE score was calculated for each patient and compared to LoS data. Results: There was a statistically significant positive correlation between rising ALICE scores and increasing length of stay irrespective of final diagnoses. Conclusion: The ALICE score provides a simple bedside tool to predict length of stay.