Email updates

Keep up to date with the latest news and content from BMC Pediatrics and BioMed Central.

Open Access Research article

The swiss neonatal quality cycle, a monitor for clinical performance and tool for quality improvement

Mark Adams*, Tjade Claus Hoehre, Hans Ulrich Bucher and the Swiss Neonatal Network

Author Affiliations

Division of Neonatology, University Hospital Zurich, Zurich, Switzerland

For all author emails, please log on.

BMC Pediatrics 2013, 13:152  doi:10.1186/1471-2431-13-152

Published: 28 September 2013

Abstract

Background

We describe the setup of a neonatal quality improvement tool and list which peer-reviewed requirements it fulfils and which it does not. We report on the so-far observed effects, how the units can identify quality improvement potential, and how they can measure the effect of changes made to improve quality.

Methods

Application of a prospective longitudinal national cohort data collection that uses algorithms to ensure high data quality (i.e. checks for completeness, plausibility and reliability), and to perform data imaging (Plsek’s p-charts and standardized mortality or morbidity ratio SMR charts). The collected data allows monitoring a study collective of very low birth-weight infants born from 2009 to 2011 by applying a quality cycle following the steps ′guideline – perform - falsify – reform′.

Results

2025 VLBW live-births from 2009 to 2011 representing 96.1% of all VLBW live-births in Switzerland display a similar mortality rate but better morbidity rates when compared to other networks. Data quality in general is high but subject to improvement in some units. Seven measurements display quality improvement potential in individual units. The methods used fulfil several international recommendations.

Conclusions

The Quality Cycle of the Swiss Neonatal Network is a helpful instrument to monitor and gradually help improve the quality of care in a region with high quality standards and low statistical discrimination capacity.

Keywords:
Very preterm infants; Very low birth weight infants; Quality assessment; Quality indicators; Benchmarking; Falsification; Mortality; Morbidity; Evidence based medicine