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Estimating the impact of healthcare-associated infections on length of stay and costs
|Published in||Clinical Microbiology and Infection. 2010, vol. 16, no. 12, p. 1729-1735|
|Abstract||Healthcare-associated infections (HAIs) unquestionably have substantial effects on morbidity and mortality. However, quantifying the exact economic burden attributable to HAIs still remains a challenging issue. Inaccurate estimations may arise from two major sources of bias. First, factors other than infection may affect patients' length of stay (LOS) and healthcare utilization. Second, HAI is a time-varying exposure, as the infection can impact on LOS and costs only after the infection has started. The most frequent mistake in previously published evidence is the introduction of time-dependent information as time-fixed, on the assumption that the impact of such exposure on the outcome was already present on admission. Longitudinal and multistate models avoid time-dependent bias and address the time-dependent complexity of the data. Appropriate statistical methods are important in analysis of excess costs and LOS associated with HAI, because informed decisions and policy developments may depend on them.|
|Keywords||Cross Infection/*economics — Data Interpretation, Statistical — Delivery of Health Care/*economics — Hospital Costs — Hospitalization/economics — Humans — Length of Stay/*economics — Time Factors|
|Research group||Groupe Harbarth Stephan (Staphylocoques dorés résistants à la méthicilline) (866)|
|DE ANGELIS, G. et al. Estimating the impact of healthcare-associated infections on length of stay and costs. In: Clinical Microbiology and Infection, 2010, vol. 16, n° 12, p. 1729-1735. https://archive-ouverte.unige.ch/unige:20876|