Details:

Alternative Title:
Emerg Infect Dis
Personal Author:
Brown, Samuel M. ; Benneyan, James C. ; Theobald, Daniel A. ; Sands, Kenneth ; Hahn, Matthew T. ; ... More +
Brown, Samuel M. ; Benneyan, James C. ; Theobald, Daniel A. ; Sands, Kenneth ; Hahn, Matthew T. ; Potter-Bynoe, Gail A. ; Stelling, John M. ; O'Brien, Thomas F. ; Goldmann, Donald A. Less -
Description:
Clusters of nosocomial infection often occur undetected, at substantial cost to the medical system and individual patients. We evaluated binary cumulative sum (CUSUM) and moving average (MA) control charts for automated detection of nosocomial clusters. We selected two outbreaks with genotyped strains and used resistance as inputs to the control charts. We identified design parameters for the CUSUM and MA (window size, k, alpha, Beta, p(0), p(1)) that detected both outbreaks, then calculated an associated positive predictive value (PPV) and time until detection (TUD) for sensitive charts. For CUSUM, optimal performance (high PPV, low TUD, fully sensitive) was for 0.1 < or = alpha < or = 0.25 and 0.2 < or = Beta < or = 0.25, with p(0) = 0.05, with a mean TUD of 20 (range 8-43) isolates. Mean PPV was 96.5% (relaxed criteria) to 82.6% (strict criteria). MAs had a mean PPV of 88.5% (relaxed criteria) to 46.1% (strict criteria). CUSUM and MA may be useful techniques for automated surveillance of resistant infections.
Subject:
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Cluster Analysis
Cross Infection
Disease Outbreaks
Electrophoresis, Gel, Pulsed-Field
Humans
Methicillin Resistance
Microbial Sensitivity Tests
Monte Carlo Method
Staphylococcus Aureus

Source:
Emerg Infect Dis. 8(12):1426-1432.
Document Type:
Journal Article
Place as Subject:
United States
Collection(s):
Emerging Infectious Diseases
Main Document Checksum:
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urn:sha256:4bf9b12c77a83fb9eccb789fe5cfc4f7e192c5005d0b1d43ebc2dc441fa4894c
File Type:

Supporting Files

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  	01-0514_FinalR.nxml	txt
  	license.txt	txt
  	01-0514-app-s1.pdf	pdf
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