Attributable Cost and Length of Stay Associated with Nosocomial Gram-Negative Bacterial Cultures.
Attributable Cost and Length of Stay Associated with Nosocomial Gram-Negative Bacterial Cultures.
复制标题
与院内革兰氏阴性细菌培养相关的可归因费用和住院时间。
DOI:
10.1128/aac.00462-18
复制
发表时间:
2018
影响因子:
4.9
通讯作者:
Samore,MatthewH
中科院分区:
文献类型:
--
作者:
Nelson,RichardE;Stevens,VanessaW;Jones,Makoto;Khader,Karim;Schweizer,MarinL;Perencevich,EliN;Rubin,MichaelA;Samore,MatthewH
Few studies have estimated the excess inpatient costs due to nosocomial cultures of Gram-negative bacteria (GNB), and those that do are often subject to time-dependent bias. Our objective was to generate estimates of the attributable costs of the underlying infections associated with nosocomial cultures by using a unique inpatient cost data set from the U.S. Department of Veterans Affairs that allowed us to reduce time-dependent bias. Our study included data from inpatient admissions between 1 October 2007 and 30 November 2010. Nosocomial GNB-positive cultures were defined as clinical cultures positive for Acinetobacter, Pseudomonas, or Enterobacteriaceae between 48 h after admission and discharge. Positive cultures were further classified by site and level of resistance. We conducted analyses using both a conventional approach and an approach aimed at reducing the impact of time-dependent bias. In both instances, we used multivariable generalized linear models to compare the inpatient costs and length of stay for patients with and without a nosocomial GNB culture. Of the 404,652 patients included in the conventional analysis, 12,356 had a nosocomial GNB-positive culture. The excess costs of nosocomial GNB-positive cultures were significant, regardless of specific pathogen, site, or resistance level. Estimates generated using the conventional analysis approach were 32.0% to 131.2% greater than those generated using the approach to reduce time-dependent bias. These results are important because they underscore the large financial burden attributable to these infections and provide a baseline that can be used to assess the impact of improvements in infection control.