Bedside electronic capture of clinical observations and automated clinical alerts to improve compliance with an Early Warning Score protocol.

BACKGROUND: Failure to comply with clinical protocols and failure of communication to ensure delivery of the most appropriate timely clinical responses to patients whose conditions are acutely deteriorating have been shown to be significant causative factors associated with inhospital adverse events.
OBJECTIVE: To determine whether automated clinical alerts increase compliance with an Early Warning Score (EWS) protocol and improve patient outcomes.
METHODS: We performed a historically controlled study of bedside electronic capture of observations and automated clinical alerts. The primary outcome measure was hospital length of stay (LOS); secondary outcome measures were compliance with the EWS protocol, cardiac arrest incidence, critical care utilisation and hospital mortality.
RESULTS: Between baseline and intervention, 1481 consecutive patients were recruited generating 13 668 observation sets. There was a reduction in hospital LOS between the baseline and alert phase (9.7 days v 6.9 days, P < 0.001). EWS accuracy improved from 81% to 100% with electronic calculation. Clinical attendance to patients with EWS 3, 4 or 5 increased from 29% at baseline to 78% with automated alerts (P < 0.001). For patients with an EWS > 5, clinical attendance increased from 67% at baseline to 96% with automatic alerts (P < 0.001).
CONCLUSIONS: Electronic recording of patient observations linked to a computer system that calculates patient risk and then issues automatic graded alerts can improve clinical attendance to unstable general medical ward patients.