z-logo
open-access-imgOpen Access
Predicting 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 journal
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) - alice (programming language) , simple (philosophy) , medicine , computer science , programming language , philosophy , epistemology
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom