Literature DB >> 20807294

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.

Tsung-Tai Chen1, Kuo-Piao Chung, Fu-Chang Hu, Chieh-Min Fan, Ming-Chin Yang.   

Abstract

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.
MATERIALS AND 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.
CONCLUSION: 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.
© 2010 Blackwell Publishing Ltd.

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Year:  2010        PMID: 20807294     DOI: 10.1111/j.1365-2753.2010.01370.x

Source DB:  PubMed          Journal:  J Eval Clin Pract        ISSN: 1356-1294            Impact factor:   2.431


  1 in total

1.  Detecting change in comparison to peers in NHS prescribing data: a novel application of cumulative sum methodology.

Authors:  Alex J Walker; Seb Bacon; Richard Croker; Ben Goldacre
Journal:  BMC Med Inform Decis Mak       Date:  2018-07-09       Impact factor: 2.796

  1 in total

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