Volume 7, Number 2—April 2001
4th Decennial International Conference on Nosocomial and Healthcare-Associated Infections
Prevention is Primary
Automated Methods for Surveillance of Surgical Site Infections
|Control of clusters|
|Identify clusters of infection.||Real-time detection of events. Attack rates and case-mix adjustment are not a high priority. Should include all patients.|
|Support of quality improvement programs|
|Establish baseline infection rates.||Sufficient precision to identify absolute differences of a few percent. Typically includes all patients.|
|Comparison of institutions or surgical specialties.||Case-mix-adjusted attack rates. Identical detection methods that are applied and interpreted identically across sites. Sufficient precision.|
|Evaluate control measures (in the usual situation of no randomized trial).||Comparably ascertained rates over time.|
|Research on epidemiology of infection|
|Identify risk factors.||Detailed data on many attributes of patients and procedures. Population can be small, but must be representative.|
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¹The CDC Eastern Massachusetts Prevention Epicenter includes Blue Cross and Blue Shield of Massachusetts, CareGroup, Children's Hospital, Harvard Pilgrim Health Care, Partners Healthcare System, Tufts Health Plan, and Harvard Medical School. Investigators include L. Higgins, J. Mason, E. Mounib, C. Singleton, K. Sands, K. Kaye, S. Brodie, E. Perencevich, J. Tully, L. Baldini, R. Kalaidjian, K. Dirosario, J. Alexander, D. Hylander, A. Kopec, J. Eyre-Kelley, D. Goldmann, S. Brodie, C. Huskins, D. Hooper, C. Hopkins, M. Greenbaum, M. Lew, K. McGowan, G. Zanetti, A. Sinha, S. Fontecchio, R. Giardina, S. Marino, J. Sniffen, E. Tamplin, P. Bayne, T. Lemon, D. Ford, V. Morrison, D. Morton, J. Livingston, P. Pettus, R. Lee, C. Christiansen, K. Kleinman, E. Cain, R. Dokholyan, K. Thompson, C. Canning, D. Lancaster.