Surveillance for Ventilator-associated Pneumonia (VAP) Using Electronic Data Compared Closely with Clinician Detection
Abstract & Commentary
By Leslie A. Hoffman, PhD, RN, Department of Acute/Tertiary Care, School of Nursing, University of Pittsburgh, is Associate Editor for Critical Care Alert.
Dr. Hoffman reports no financial relationship to this field of study.
Synopsis: An algorithm applied to electronic data detected 20 of 21 cases of possible ventilator-associated pneumonia in 459 patients, in accordance with CDC criteria.
Source: Klompas, M, et al. Infect Control Hosp Epidemiol. 2008;29:31-37.
Using the criteria of the Centers for Disease Control and Prevention (CDC) to detect ventilator-associated pneumonia (VAP) is labor intensive and subjective. The goal of this study was to determine if the efficiency and objectivity of VAP surveillance could be improved by adapting CDC criteria to a format that allowed evaluation via an electronic clinical database. A total of 459 consecutive patients who received mechanical ventilation for a total of 2,540 days in 3 surgical and 2 medical ICUs in an academic medical center were enrolled in the study. VAP surveillance was performed using two methods: CDC criteria and an algorithm developed by the research team.
CDC criteria for VAP detection require that the patient fulfill 1 radiographic, 1 systemic, and 2 pulmonary criteria. The algorithm redefined assessment in a manner that allowed electronic monitoring. As examples, "new, progressive or persistent infiltrate" was redefined as "opacity, infiltrate, or consolidation that appears, evolves, or persists over ≥ 72 hours" and "worsening gas exchange, increased oxygen requirements or increased ventilatory demand" was redefined as "a sustained rise in ventilator settings relative to baseline." Baseline was defined as the patient's lowest setting after 48 hours or more of decreasing ventilator support. This decision was based on the rationale that ventilator settings are typically reduced as the patient recovers; therefore, a 48-hour sustained increase would suggest a complication.
The algorithm detected 20 (95%) of the 21 VAP cases. All cases identified by the algorithm met CDC criteria (100% positive predictive value). One additional case was not identified by the algorithm. In this situation, ventilator change criteria were not sufficient to meet criteria in the algorithm. In comparison, clinicians identified 17 (81%) of the 21 cases.
Commentary
Patients and politicians are increasingly advocating that hospitals provide data regarding their infection rates as a means of evaluating the quality of care. The "de facto" standard for identifying VAP is the definition published by the CDC. This definition is labor intensive and, hence, expensive to implement because it incorporates clinical criteria that require frequent detailed assessment at the bedside. CDC criteria are also subjective as they include statements such as "worsening gas exchange," "increased respiratory secretions," and "increased suctioning requirements."
The authors posited that routinely collected electronic clinical data could be used to increase the efficiency, objectivity, and reproducibility of VAP surveillance. The algorithm developed retained the central structure of CDC criteria, but was adapted in ways that allowed electronic monitoring based on radiology reports, laboratory values, and trend data. The algorithm was quite effective, identifying 20 of 21 cases of VAP. VAP surveillance had a higher positive predictive value and identified more cases than a prospective survey by clinicians. Although clinicians identified a majority of confirmed cases of VAP (17 of 21), only about half of the 33 cases they identified met formal CDC criteria. This error apparently resulted from incomplete knowledge of CDC criteria. For example, one patient met CDC criteria for hospital-acquired pneumonia but was not ventilated for 48 hours before onset of pneumonia and therefore did not meet VAP criteria. The single case of VAP missed by the algorithm met all criteria except for a sufficient increase in ventilator settings.
Use of this algorithm is attractive because it allows the capture of cases of VAP in a manner that is not labor intensive or subjective. It could easily be used as a clinical surveillance system to alert practitioners to likely cases of VAP or to provide trend data regarding the incidence of this complication. The major limitation to its use appears to be the requirement for an electronic data gathering system that systematically records and updates the necessary data.
Using the criteria of the Centers for Disease Control and Prevention (CDC) to detect ventilator-associated pneumonia (VAP) is labor intensive and subjective.You have reached your article limit for the month. Subscribe now to access this article plus other member-only content.
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