Estimating the impact of healthcare-associated infections on length of stay and costs.
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.
De Angelis
G
G
Infection Control Programme, University of Geneva Hospitals and Faculty of Medicine, 4 rue Gabrielle-Perret-Gentil, Geneva 4, Switzerland.
Murthy
A
A
Beyersmann
J
J
Harbarth
S
S
D003428:Cross Infection / Q000191:economics*; D003627:Data Interpretation, Statistical; D003695:Delivery of Health Care / Q000191:economics*; D017721:Hospital Costs; D006760:Hospitalization / Q000191:economics; D006801:Humans; D007902:Length of Stay / Q000191:economics*; D013997:Time Factors