The use of statistical process control (risk-adjusted CUSUM, risk-adjusted RSPRT and CRAM with prediction limits) for monitoring the outcomes of out-of-hospital cardiac arrest patients rescued by the EMS system.
OBJECTIVE
Based on previous experience from surgical surveillance, risk-adjusted cumulative sum (CUSUM)-type charts were applied to monitor out-of-hospital cardiac arrest (OHCA) patient mortality.


METHODS
Data from 2356 OHCA patients were collected by the Taipei County Fire Bureau from June 2006 to November 2007. Logistic regression analysis was applied to create a risk-adjusted model. Next, a risk-adjusted CUSUM chart, a risk-adjusted resetting sequential probability ratio test chart and a cumulative risk-adjusted mortality with prediction limits chart were used to detect excess deaths of the OHCA patients rescued by the emergency medical service (EMS) system.


RESULTS
The overall mortality rate, defined as having no return of spontaneous circulation, was 79.3%. These three charts signalled an increase in the death rate at similar sites, and also suggested a small process shift.


CONCLUSIONS
A visual approach to EMS systems monitoring that combines the risk-adjusted cumulative sum, Risk-adjusted resetting sequential probability ratio test and cumulative risk-adjusted mortality with prediction limits charts was established. It was found that this approach can be effectively used by the EMS community to monitor OHCA outcomes in real time.
Chen
Tsung-Tai
TT
Center for Health Insurance Research, College of Public Health, National Taiwan University, Taipei, Taiwan.
Chung
Kuo-Piao
KP
Hu
Fu-Chang
FC
Fan
Chieh-Min
CM
Yang
Ming-Chin
MC
D004632:Emergency Medical Services / Q000592:standards*; D005260:Female; D006323:Heart Arrest / Q000628:therapy*; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D020379:Risk Adjustment / Q000379:methods* / Q000706:statistics & numerical data