Objectives: The subjectivity and complexity of surveillance definitions for ventilator-associated pneumonia preclude meaningful internal or external benchmarking and therefore hamper quality improvement initiatives for ventilated patients. We explored the feasibility of creating objective surveillance definitions for ventilator-associated pneumonia.
Design: We identified clinical signs suitable for inclusion in objective definitions, proposed candidate definitions incorporating these objective signs, and then applied these definitions to retrospective clinical data to measure their frequencies and associations with adverse outcomes using multivariate regression models for cases and matched controls.
Setting: Medical and surgical intensive care units in eight U.S. hospitals (four tertiary centers, three community hospitals, and one Veterans Affairs institution).
Patients: Eight thousand seven hundred thirty-five consecutive episodes of mechanical ventilation for adult patients.
Interventions: We evaluated 32 different candidate definitions composed of different combinations of the following signs: three thresholds for respiratory deterioration defined by sustained increases in daily minimum positive end-expiratory pressure or FIO2 after either 2 or 3 days of stable or decreasing ventilator settings, abnormal temperature, abnormal white blood cell count, purulent pulmonary secretions defined by neutrophils on Gram stain, and positive cultures for pathogenic organisms.
Measurements and Main Results: Ventilator-associated pneumonia incidence, attributable ventilator days, hospital days, and hospital mortality. All candidate definitions were significantly associated with increased ventilator days and hospital days, but only definitions requiring objective evidence of respiratory deterioration were significantly associated with increased hospital mortality. Significant odds ratios for hospital mortality ranged from 1.9 (95% confidence interval 1.2–2.9) to 6.1 (95% confidence interval 2.2–17). Requiring additional clinical signs beyond respiratory deterioration alone decreased event rates, had little impact on attributable lengths of stay, and diminished sensitivity and positive predictive values for hospital mortality.
Conclusions: Objective surveillance definitions that include quantitative evidence of respiratory deterioration after a period of stability strongly predict increased length of stay and hospital mortality. These definitions merit further evaluation of their utility for hospital quality and safety improvement programs.
From the Department of Population Medicine (MK, KK, RP), Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA; Department of Medicine (MK, DSY, RP), Brigham and Women’s Hospital, Boston, MA; Division of Healthcare Quality Promotion (SM), Centers for Disease Control and Prevention, Atlanta, GA; Department of Medicine and Department of Quality (AR), Northshore University Health System, Evanston, IL; Veterans Affairs Boston Healthcare System (JMS), Boston, MA; Department of Biomedical Informatics (RSE), University of Utah School of Medicine, Salt Lake City, UT; Department of Medical Informatics (RSE, JFL), Intermountain Healthcare, Salt Lake City, UT; Department of Medicine (YK, KS), The Ohio State University Medical Center, Columbus, OH.
*See also p. 3311.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (http://journals.lww.com/ccmjournal).
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Supported by Prevention Epicenters Program of the Centers for Disease Control and Prevention.
Dr. Stevenson received funding from the CDC, and grant support from the Ohio Department of Public Safety. He also received speaking fees from the University of Iowa. The remaining authors have not disclosed any potential conflicts of interest.
Listen to the iCritical Care podcasts for an in-depth interview on this article. Visit http://www.sccm.org/iCriticalCare or search “SCCM” at iTunes.
For information regarding this article, E-mail: firstname.lastname@example.org