The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs

Scan statistics are concerned with clusters of events over time. In the realm of critical care medicine, such clusters might include the occurrence of ventilator-associated pneumonia (VAP). Given N patients over time, the number of observations in a “moving window” of fixed length can be counted and...

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Main Authors: Brian H. Nathanson, Thomas L. Higgins
Format: Article
Language:English
Published: Hindawi Limited 2010-01-01
Series:Journal of Healthcare Engineering
Online Access:http://dx.doi.org/10.1260/2040-2295.1.4.579
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spelling doaj-d446600a641149e2858a50ea1cdea3282020-11-24T21:07:21ZengHindawi LimitedJournal of Healthcare Engineering2040-22952010-01-011457959410.1260/2040-2295.1.4.579The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control ProgramsBrian H. Nathanson0Thomas L. Higgins1OptiStatim, LLC, Longmeadow, MA, USABaystate Medical Center, Springfield, MA, Tufts University School of Medicine, Boston, MA, USAScan statistics are concerned with clusters of events over time. In the realm of critical care medicine, such clusters might include the occurrence of ventilator-associated pneumonia (VAP). Given N patients over time, the number of observations in a “moving window” of fixed length can be counted and the maximum cluster value becomes a scan statistic for which both parametric and exact methods exist to calculate its rarity. A statistically unusual cluster may indicate a breakdown in quality. Another approach to monitoring rare events is a g-type statistical process control chart where prospectively observing unusually long periods of time between events can indicate a significant improvement in quality. Both methods are presented in detail and applied to a 24-bed medical/surgical ICU's experience with VAP during a 27-month period.http://dx.doi.org/10.1260/2040-2295.1.4.579
collection DOAJ
language English
format Article
sources DOAJ
author Brian H. Nathanson
Thomas L. Higgins
spellingShingle Brian H. Nathanson
Thomas L. Higgins
The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
Journal of Healthcare Engineering
author_facet Brian H. Nathanson
Thomas L. Higgins
author_sort Brian H. Nathanson
title The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
title_short The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
title_full The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
title_fullStr The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
title_full_unstemmed The Use of Scan Statistics and Control Charts in Assessing Ventilator-Associated Pneumonia Quality Control Programs
title_sort use of scan statistics and control charts in assessing ventilator-associated pneumonia quality control programs
publisher Hindawi Limited
series Journal of Healthcare Engineering
issn 2040-2295
publishDate 2010-01-01
description Scan statistics are concerned with clusters of events over time. In the realm of critical care medicine, such clusters might include the occurrence of ventilator-associated pneumonia (VAP). Given N patients over time, the number of observations in a “moving window” of fixed length can be counted and the maximum cluster value becomes a scan statistic for which both parametric and exact methods exist to calculate its rarity. A statistically unusual cluster may indicate a breakdown in quality. Another approach to monitoring rare events is a g-type statistical process control chart where prospectively observing unusually long periods of time between events can indicate a significant improvement in quality. Both methods are presented in detail and applied to a 24-bed medical/surgical ICU's experience with VAP during a 27-month period.
url http://dx.doi.org/10.1260/2040-2295.1.4.579
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