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Open Access Highly Accessed Research article

The CUSUM chart method as a tool for continuous monitoring of clinical outcomes using routinely collected data

Thabani Sibanda1* and Nokuthaba Sibanda2

Author Affiliations

1 Epsom & St Helier Univesity Hospitals NHS Trust, St Helier Hospital, Wrythe Lane, Carshalton, Surrey, SM5 1AA, UK

2 London School of Hygiene & Tropical Medicine, London WC2A 3PE, UK

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BMC Medical Research Methodology 2007, 7:46  doi:10.1186/1471-2288-7-46

Published: 3 November 2007

Abstract

Background

The lack of robust systems for monitoring quality in healthcare has been highlighted. Statistical process control (SPC) methods, utilizing the increasingly available routinely collected electronic patient records, could be used in creating surveillance systems that could lead to rapid detection of periods of deteriorating standards. We aimed to develop and test a CUmulative SUM (CUSUM) based surveillance system that could be used in continuous monitoring of clinical outcomes, using routinely collected data. The low Apgar score (5 minute Apgar score < 7) was used as an example outcome.

Method

A surveillance system based on the Observed minus Expected (O-E) as well as the 2-sided Log-Likelihood CUSUM charts was developed. The Log-Likelihood chart was designed to detect a 50% rise (deterioration) and halving (improvement) in the odds of low Apgar scores. Baseline rates were calculated from data for 2001 to 2004, and were used to monitor deliveries for 2005. Deliveries for nulliparous and multiparous women were monitored separately. All analyses were retrospective.

Results

The CUSUM system detected periods of increased rates of low Apgar scores for each of the nulliparous and multiparous cohorts. The overall rate for 2005 was eventually found to be 0.67%, which was higher than the baseline reference rate of 0.44% from 2001 to 2004.

Conclusion

CUSUM methods can be used in continuous monitoring of clinical outcomes using routinely collected data. Used prospectively, they could lead to the prompt detection of periods of suboptimal standards.