Infection Control and Hospital Epidemiology: the Formal Review Process

1991 ◽  
Vol 12 (01) ◽  
pp. 11-13
Author(s):  
Robyn R. Hepker
Keyword(s):  
Infection Control ◽  
Review Process ◽  
Hospital Epidemiology

scholarly journals Hospital Epidemiology Beyond Infection Control

1980 ◽  
Vol 1 (06) ◽  
pp. 373-374 ◽  
Author(s):  
Walter J. Hierholzer
Keyword(s):  
Infection Control ◽  
Hospital Epidemiology

Brief Report: Biological Indicators

1988 ◽  
Vol 9 (11) ◽  
pp. 504-506 ◽  
Author(s):  
Patrick J. McCormick
Keyword(s):  
High Temperature ◽  
Infection Control ◽  
Significant Variation ◽  
Biological Indicators ◽  
Hospital Epidemiology ◽  
High Temperature Processing ◽  
Relevant Factors ◽  
Design And Construction

I read with great interest the article by Kotilainen and Gantz in Infection Control [now Infection Control and Hospital Epidemiology] regarding biological indicators (BIs) for use with flash sterilization processes. Although this study was conducted with greater care than previous investigations in this area, we believe that certain relevant factors regarding the effect of BI design on BI performance may have been overlooked. Because of differences in the design and construction of the BIs evaluated, a significant variation in response to flash sterilization or high temperature processing may result. Such an effect was first noted by Perkins et al and has been commented on by Reich and Fitzpartrick and Joslyn.

A Comparison of Infection Control Software for Use by Hospital Epidemiologists in Meeting the New JCAHO Standards

1990 ◽  
Vol 11 (4) ◽  
pp. 185-190 ◽  
Author(s):  
Sharon LaHaise
Keyword(s):  
North Carolina ◽  
Infection Control ◽  
Healthcare Organizations ◽  
Control Software ◽  
Hospital Epidemiology ◽  
Test Dataset ◽  
Software Packages ◽  
Statistical Analysis System ◽  
Microcomputer Software ◽  
Analysis System

AbstractTo choose a microcomputer software package for our hospital epidemiology division, the two leading commercial software packages for infection control, AICE (ICPA, Inc., Austin, Texas) and NOSO- (Epi Systematics, Inc., Ft. Meyers, Florida), were compared for the types of epidemiologic analysis likely to be required to satisfy new Joint Commission on Accreditation of Healthcare Organizations (JCAHO) 1990 Infection Control Standards. The test dataset was a surgical database of 3,235 operations with 292 (9%) wound infections. Though NOSO- was more flexible in terms of the amount of data items one could record, it required seven times longer to learn, nine times more disk space to store and two times as long to enter cases than AICE. Six simple infection control reports (i.e., line listings, crosstabulations, stratified rates and graphs) required only seven computing steps and approximately 11 minutes to process with AICE, but 22 steps and over two hours with NOSO-3. All analytic results from AICE agreed with the results obtained with the Statistical Analysis System (SAS, SAS Institute, Inc., Cary, North Carolina), but analyses such as service-specific rates performed with NOSO- differed because of a design flaw in the NOSO- data structure.

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