Estimation of adjusted expected excess length‐of‐stay associated with ventilation‐acquired pneumonia in intensive care: A multistate approach accounting for time‐dependent mechanical ventilation

Abstract

The expected excess length-of-stay is an established concept to assess the health and economic impact of nosocomial, that is, hospital-acquired infections such as ventilation-acquired pneumonia in intensive care. Estimation must account for the timing of infection as in a multistate perspective, because common retrospective comparisons yield inflated estimates due to time-dependent bias. Since occurrence of ventilation-acquired pneumonia is closely linked to ventilation status, we suggest a multistate model incorporating time-dependent mechanical ventilation as additional states. The appeal is that the expected excess length-of-stay decomposes into extra days spent under ventilation and not under ventilation. This is not only highly relevant from a patient's perspective regarding quality of life, but also from an economic point of view, because ventilation is a major cost driver. The challenge is that estimation involves complex functionals of the matrix of transition probabilities, which in turn are based on the transition hazards. To address heterogeneity between patients, which is a common phenomenon in observational hospital epidemiology, we apply pseudovalue regression to adjust the ventilation-specific quantities for baseline confounding. The performance of our proposal is assessed by simulation and the methods are illustrated on data provided by 12 French intensive care units. Preliminary results indicate that the expected excess length-of-stay associated with ventilation-acquired pneumonia is mainly triggered by extra days spent under mechanical ventilation, and that the excess is most pronounced for intensive care patients with fewer comorbidities at baseline. We also find that such a decomposition is challenging for early times. Example code is provided.

Impact of mechanical ventilation on the daily costs of ICU care: a systematic review and meta regression

“…However, if we instead assume that ventilation takes place during 75% of ICU stay, the cost of a single ventilated ICU day changes slightly to €1592. Further combination of this cost figure with Bluhmki's data [10] (3.52 days of excess LoS) then results in the financial burden of a single VAP of €5822 (95% CI €4012-€ 7632).…”

“…Bluhmki et al were aware of this fact and correctly estimated the excess LoS associated with VAP using multistate models accounting for the time-dynamics of ventilation status and VAP. At the same time, Bluhmki et al [10] considered that ignoring the time-dependency of VAP would lead to an excess LoS of 15 days, which represents a substantial overestimation in comparison with the more precise effect estimate of 3.52 days. This might also be the case in other studies, when cost figures are available, but ignoring the time-dependency of the exposure might have led to a substantial overestimation of the true effect [12 20-22].…”

“…Our cost calculations were based on the simplifying assumption that the entire excess LoS can be attributed to ventilation; thus, we may have slightly overestimated the costs. However, we refer to the result that this excess seems to be mainly triggered by ventilation [10]. While LoS may be of intrinsic interest as an indicator for the burden on the patient level, it is a rather incomplete proxy for costs as the care intensity of the respective patients is not taken into account.…”

“…In comparison with the endpoint costs, analysing LoS is advantageous as it enables accounting for the time-dynamic pattern of the exposure. In line with Bluhmki et al [10] excess LoS was derived using a multistate methodology, which accounted for the time-dynamic pattern of both VAP as well as ventilation status. Their precise formulation further allows decomposing the excess LoS into extra days spent under, and not under ventilation.…”

“…On the one hand, this decomposition expresses the disease burden and a patient's quality status in more detail but it is also highly relevant from an economic point of view, because ventilation is known to be a major cost driver in the ICU. Thus, we combine our results with summary measures provided by Bluhmki et al [10] in order to obtain a more precise estimate of the additional costs associated with VAP. For all statistical analyses Stata Version 14.0 (Stata Corp, College Station, Texas, USA) was used.…”