Estimating the effect of healthcare-associated infections on excess length of hospital stay using inverse-probability weighted survival curves

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 (IPW) survival curves to address this limitation. Methods A case-study focusing on intensive care unit-acquired bacteraemia using data from two general ICUs from two London teaching hospitals were used to illustrate the methodology. The area under the curve (AUC) of a conventional Kaplan Meier curve applied to the observed data was compared with that of an IPW Kaplan Meier curve applied after treating bacteraemia as censoring events. Weights were based on the daily probability of acquiring bacteraemia. The difference between the observed average LoS and the average LoS that would be observed if all bacteraemia cases could be prevented was multiplied by the number of admitted patients to obtain the total excess LoS. Result The estimated total number of extra ICU days caused by 666 bacteraemia cases were estimated at 2453 (95% CI 1803 – 3103) days. The excess number of days were overestimated when ignoring time-varying confounding (2845, 95% CI 2276 – 3415) or when completely ignoring confounding (2838, 95% CI 2101 – 3575). Conclusion ICU-acquired bacteraemia was associated with a substantial excess LoS. Wider adoption of IPW 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