1. R33: THE FRAILTY EARLY WARNING SCORE (FEWS) IS A BETTER PREDICTOR FOR VARIOUS PATIENT OUTCOMES THAN NEWS IN THE ELDERLY ACUTE MEDICAL SETTING
Lotte Dinesen1,2,Alan J Poots1, Federico Ciardi3, Lauren M Bell3, John Soong1, Derek Bell1,2
1 CLAHRC NWL/ Imperial College, 2 Chelsea and Westminster Hospital NHS FT, 3 Imperial College London
Aim
To compare the frailty scoring system (FEWS) deployed in Chelsea and Westminster against current standards in care escalation algorithms’ (NEWS) in the acute care setting.
Methods
Between 03 June 2015 and 08 Jan 2016, 1903 acutely admitted patients > 65 were reviewed. Data were collected from clinical information as part of the emergency admission process. All data were collected electronically (Thinkshield) and innate hospital system. We compared the correlation between FEWS and NEWS to mortality using point-biserial analysis.
Outcomes / Results
We have visualised the proportion of patients scoring ≤3 on NEWS as this would not trigger escalation, to various FEWS scores. We have shown that 1372 admissions scored < 3 on NEWS of which 1182 (86%) scored ≥1 on the frailty tool. Similarly of patients that would not be escalated with NEWS, 25% score > 7 on FEWS. Interestingly at high NEWS score >11, FEWS scores are also high.
A point-biserial correlation was run for all (1903 attendence) between FEWS/NEWS and mortality. A statistically significant (p<0.01) correlation was found between FEWS and mortality but importantly not between NEWS and mortality ( fig 1 and 2).
The relationship between NEWS vs FEWS comparing readmission shows no obvious trends observed.
Conclusion
This could indicate a potential novel threshold for frailty escalation. We are therefore proposing a novel algorithm for elderly escalation in the acute medical setting. FEWS appears a better predictor of overall mortality than NEWS in this patient cohort. More work is needed to refine the FEWS scoring system (subdomain weighting) and to calculate an appropriate FEWS score for escalation of care and relate to NEWS.
Figure 1. Relationship between FEWS and mortality
Figure 2. Relationship between NEWS and mortality