Effects of Rapid Detection of Bloodstream Infections on Length of Hospitalization and Hospital Charges

AUTOR(ES)
FONTE

American Society for Microbiology

RESUMO

Current automated continuous-monitoring blood culture systems afford more rapid detection of bacteremia and fungemia than is possible with non-instrument-based manual methods. Use of these systems has not been studied objectively with respect to impact on patient outcomes, including hospital charges and length of hospitalization. We conducted a prospective, two-center study in which the time from the obtainment of the initial positive blood culture until the Gram stain was called was evaluated for 917 cases of bloodstream infection. Factors showing univariate associations with a shorter time to notification included higher body temperature and respiratory rate and higher percentage of immature neutrophils. Multiple linear regression models determined that the primary predictors of both increased microbiology laboratory and total hospital charges for patients with bloodstream infection were nonmicrobiologic and included length of stay and host factors such as the admitting service and underlying illness score. Significant microbiologic predictors of increased charges included the number of blood cultures obtained, nosocomial acquisition, and polymicrobial bloodstream infections. Accelerated failure time regression analysis demonstrated that microbiologic factors, including time until notification, organism group, and nosocomial acquisition, were independently associated with length of hospitalization after bacteremia, as were the factors of admitting service, gender, and age. Our data suggest that an increased time to notification of bloodstream infection is independently associated with increased length of stay. We conclude that the time to notification is an obvious target for efforts to shorten length of stay. The newest generation of automated continuous-monitoring blood culture systems, which shorten the time required to obtain a positive result, should impact length of hospitalization.

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