Using a local early warning scoring system as a model for the introduction of a national system.
BACKGROUND
Chelsea and Westminster Hospital introduced the Chelsea Early Warning Score (CEWS) in 2007 to aid the recognition of acutely unwell patients. The Royal College of Physicians subsequently recommended a National Early Warning Score (NEWS) for implementation across the NHS. The aim of this study was to evaluate local adherence to CEWS to identify potential obstacles to the consistent implementation of NEWS.


METHODS
Emergency Department (ED) and Acute Assessment Unit (AAU) notes were retrospectively reviewed for a convenience sample of 102 patients admitted to the AAU. Outcome measures were completeness of documentation of CEWS parameters, documentation and accuracy of aggregate CEWS scores. Aggregate NEWS scores were calculated from the documented observations and the calculated CEWS and NEWS scores were compared.


RESULTS
Physiological observations were documented for all patients attending the ED and AAU. Heart rate, blood pressure, respiratory rate, oxygen saturation and conscious level were documented in over 95% of ED and AAU patients. Urine output was recorded for only 48% of ED and 69% of AAU patients. Aggregate CEWS scores were documented for 66% of ED and 84% of AAU patients. These were calculated accurately in 73% of ED and 79% of AAU patients. Calculation errors were eleven times more likely to result in under-scoring than over-scoring. NEWS scores were significantly higher than CEWS for the same observations and would have resulted in a 71% increase in patients requiring escalation of care in the ED and a 116% increase in AAU.


CONCLUSIONS
Concerns highlighted with CEWS were the incomplete and inaccurate recording of aggregate scores, with underscoring resulting in the potential failure to recognise deteriorating patients. It is anticipated that NEWS will be accompanied by standardised documentation and training across the NHS which will support more complete and accurate recording of physiological data. Furthermore, NEWS appears from this study to be more sensitive than CEWS, thereby minimising the chance of missed deterioration.
St George’s, University of London, UK.
Charlotte
C
Austen
Caroline
C
Patterson
Alan
A
Poots
Stuart
S
Green
Theresa
T
Weldring
Derek
D
Bell
D000208:Acute Disease / Q000145:classification; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003422:Critical Care / Q000379:methods* / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006291:Health Policy; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D017063:Outcome Assessment, Health Care; D010343:Patient Admission / Q000706:statistics & numerical data; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D055815:Young Adult