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Surveillance Objectives: Descriptive Epidemiology

Published online by Cambridge University Press:  02 January 2015

Frank S. Rhame*
Affiliation:
Department of Medicine and Graduate Faculty, Division of Epidemiology, School of Public Health, University of Minnesota Hospital and Clinic, University of Minnesota, Minneapolis
*
Box 421University of Minnesota Hospital and Clinic, Minneapolis, MN 55455

Extract

This paper addresses the problems associated with defining and classifying events as nosocomial infections, discusses the methods by which rates of nosocomial infection are calculated and their rationales, and presents some specific rates useful in nosocomial epidemiology. Previously unpublished data demonstrate important differences between antibiotic susceptibility tallies produced by clinical laboratories and similar tallies derived from nosocomial infection surveillance data.

Conversion of real world events into categorical data presents formidable difficulties. Surveillance personnel must classify a given series of clinical events as 0,1, or more infections and make a determination as to whether each infection is nosocomial or community acquired. High-quality research studies to validate these efforts should compare the sensitivity and specificity of methods used to some “gold standard.” The gold standard is usually a review of medical records or patients by an infectious diseases physician. But even the standard is flawed. In clinical practice this flaw presents less of a problem because therapy for infectious diseases is generally quite safe and may be instituted when the probability of infection is 10%, 5%, or even lower. For surveillance purposes a higher standard is required, which is particularly important when surveillance information is used to provide feedback data to physicians who understandably bridle at overestimates of infection rates in their patients. The overestimation of infections based on weak evidence under-cuts feedback efforts.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1987

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References

1. Garner, JS, Bennett, JV, Scheckler, WE, et al: Surveillance of Nosocomial infections. Proceedings of the International Conference of Nosocomial Infections, American Hospital Association, 1971, p 277281.Google Scholar
2. Appendix E: Algorithms for diagnosing infections. Am J Epidemiol 1980;111:635643.CrossRefGoogle Scholar
3. Haley, RW, Schaberg, DR, McClish, DK, et al: The accuracy of retrospective chart review in measuring nosocomial infection rates; Results of validation studies in hospitals. Am J Epidemiol 1980;111:516533.CrossRefGoogle Scholar
4. Rhame, FS, Sudderth, WD: Incidence and prevalence as used in the analysis of the occurrence of nosocomial infections. Am J Epidemiol 1981;113:111.CrossRefGoogle ScholarPubMed
5. National Academy of Sciences-National Research Council: Postoperative wound infections: The influence of ultraviolet irradiation of the operating room and of various other factors. Ann Surg 1964;160(suppl):1192.Google Scholar
6. Ehrenkranz, NJ: Surgical wound infection in clean operations: Risk stratification for interhospital comparisons. Am J Med 1981;70:909914.CrossRefGoogle ScholarPubMed