BACKGROUND: Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS. METHODS: A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI. RESULTS: During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14-2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59-0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90-4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed. CONCLUSIONS: CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.
BACKGROUND: Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS. METHODS: A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI. RESULTS: During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14-2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59-0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90-4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed. CONCLUSIONS: CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.
Authors: Theodore R Pak; Kieran I Chacko; Timothy O'Donnell; Shirish S Huprikar; Harm van Bakel; Andrew Kasarskis; Erick R Scott Journal: Infect Control Hosp Epidemiol Date: 2017-11-06 Impact factor: 3.254
Authors: Yvette H van Beurden; Olaf M Dekkers; Marije K Bomers; Annie M Kaiser; Robin van Houdt; Cornelis W Knetsch; Armand R J Girbes; Chris J J Mulder; Christina M J E Vandenbroucke-Grauls Journal: PLoS One Date: 2016-08-17 Impact factor: 3.240
Authors: Ahmed Dirweesh; Chikezie Alvarez; Muhammad Khan; Bushra Ambreen; Rishitha Yelisetti; Shaikh Fawwad Hamiz; Sana Zia; Muhammad Tahir; Vincent A DeBari; Donald Christmas; Sara Wallach Journal: Gastroenterology Res Date: 2017-04-19
Authors: Thomas Heister; Martin Wolkewitz; Philip Hehn; Jan Wolff; Markus Dettenkofer; Hajo Grundmann; Klaus Kaier Journal: Cost Eff Resour Alloc Date: 2019-08-01