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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2010-01-01
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Series: | Journal of Healthcare Engineering |
Online Access: | http://dx.doi.org/10.1260/2040-2295.1.4.579 |
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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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