Estimating the Effect of Healthcare-Associated Infections on Excess Length of Hospital Stay Using Inverse Probability-Weighted Survival Curves.
Date
2020-12-03Author
Pouwels, KB
Vansteelandt, S
Batra, R
Edgeworth, J
Wordsworth, S
Robotham, JV
Improving the uptake and SusTainability of Effective interventions to promote Prudent antibiotic Use and Primary care (STEP-UP) Team,
Type
Journal Article
Metadata
Show full item recordAbstract
BACKGROUND: Studies estimating excess length of stay (LOS) attributable to nosocomial infections have failed to address time-varying confounding, likely leading to overestimation of their impact. We present a methodology based on inverse probability-weighted survival curves to address this limitation. METHODS: A case study focusing on intensive care unit-acquired bacteremia using data from 2 general intensive care units (ICUs) from 2 London teaching hospitals were used to illustrate the methodology. The area under the curve of a conventional Kaplan-Meier curve applied to the observed data was compared with that of an inverse probability-weighted Kaplan-Meier curve applied after treating bacteremia as censoring events. Weights were based on the daily probability of acquiring bacteremia. The difference between the observed average LOS and the average LOS that would be observed if all bacteremia cases could be prevented was multiplied by the number of admitted patients to obtain the total excess LOS. RESULTS: The estimated total number of extra ICU days caused by 666 bacteremia cases was estimated at 2453 (95% confidence interval [CI], 1803-3103) days. The excess number of days was overestimated when ignoring time-varying confounding (2845 [95% CI, 2276-3415]) or when completely ignoring confounding (2838 [95% CI, 2101-3575]). CONCLUSIONS: ICU-acquired bacteremia was associated with a substantial excess LOS. Wider adoption of inverse probability-weighted survival curves or alternative techniques that address time-varying confounding could lead to better informed decision making around nosocomial infections and other time-dependent exposures.
Collections
Subject
bacteremia
causal inference
confounding
excess length of stay
infection
Cross Infection
Delivery of Health Care
Humans
Intensive Care Units
Length of Stay
London
Probability
Language
eng
Date accepted
2020-02-07
License start date
2020-12-03
Citation
Clinical Infectious Diseases, 2020, 71 (9), pp. e415 - e420
Publisher
Oxford University Press (OUP)