@article {Cameron174, author = {Allan Cameron and Kenneth Rodgers and Alastair Ireland and Ravi Jamdar and Gerard A McKay}, title = {A simple tool to predict admission at the time of triage}, volume = {32}, number = {3}, pages = {174--179}, year = {2015}, doi = {10.1136/emermed-2013-203200}, publisher = {British Association for Accident and Emergency Medicine}, abstract = {Aim To create and validate a simple clinical score to estimate the probability of admission at the time of triage. Methods This was a multicentre, retrospective, cross-sectional study of triage records for all unscheduled adult attendances in North Glasgow over 2 years. Clinical variables that had significant associations with admission on logistic regression were entered into a mixed-effects multiple logistic model. This provided weightings for the score, which was then simplified and tested on a separate validation group by receiving operator characteristic (ROC) analysis and goodness-of-fit tests. Results 215 231 presentations were used for model derivation and 107 615 for validation. Variables in the final model showing clinically and statistically significant associations with admission were: triage category, age, National Early Warning Score (NEWS), arrival by ambulance, referral source and admission within the last year. The resulting 6-variable score showed excellent admission/discharge discrimination (area under ROC curve 0.8774, 95\% CI 0.8752 to 0.8796). Higher scores also predicted early returns for those who were discharged: the odds of subsequent admission within 28 days doubled for every 7-point increase (log odds=+0.0933 per point, p\<0.0001). Conclusions This simple, 6-variable score accurately estimates the probability of admission purely from triage information. Most patients could accurately be assigned to {\textquoteleft}admission likely{\textquoteright}, {\textquoteleft}admission unlikely{\textquoteright}, {\textquoteleft}admission very unlikely{\textquoteright} etc., by setting appropriate cut-offs. This could have uses in patient streaming, bed management and decision support. It also has the potential to control for demographics when comparing performance over time or between departments.}, issn = {1472-0205}, URL = {https://emj.bmj.com/content/32/3/174}, eprint = {https://emj.bmj.com/content/32/3/174.full.pdf}, journal = {Emergency Medicine Journal} }