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Nosocomial Infection, Length of Stay, and Time-Dependent Bias

  • Jan Beyersmann (a1) (a2), Thomas Kneib (a3), Martin Schumacher (a2) and Petra Gastmeier (a4)

Abstract

Nosocomial pneumonia and its impact on length of stay are major healthcare concerns. From an epidemiological perspective, nosocomial pneumonia is a time-dependent event. Any statistical analysis that does not explicitly model this time dependency will be biased. The bias is not redeemed by adjusting for baseline information.

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Corresponding author

Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, Freiburg, D-79104, Germany(jan.beyersmann@fdm.uni-freiburg.de)

References

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1.Suissa, S. Immortal time bias in pharmacoepidemiology. Am J Epidemiol 2008;167:492499.
2.Beyersmann, J, Gastmeier, P, Grundmann, H, et al.Use of multistate models to assess prolongation of intensive care unit stay due to nosocomial infection. Infect Control Hosp Epidemiol 2006;27:493499.
3.van Walraven, C, Davis, D, Forster, A, Wells, G. Time-dependent bias was common in survival analyses published in leading clinical journals. J Clin Epidemiol 2004;57:672682.
4.Beyersmann, J, Gastmeier, P, Wolkewitz, M, Schumacher, M. An easy mathematical proof showed that time-dependent bias inevitably leads to biased effect estimation. J Clin Epidemiol 2008;61:12161221.
5.Therneau, TM, Grambsch, PM. Modeling Survival Data: Extending the Cox Model (Statistics for Biology and Health). New York: Springer; 2000.
6.Beyersmann, J, Wolkewitz, M, Schumacher, M. The impact of time-dependent bias in proportional hazards modelling. Stat Med 2008;27:64396454.
7.Kneib, T, Hennerfeind, A. Bayesian semiparametric multi-state models. Stat Modelling 2008;8:169198.
8.Wolkewitz, M, Vonberg, R, Grundmann, H, et al.Risk factors for the development of nosocomial pneumonia and mortality on intensive care units: application of competing risks models. Crit Care 2008;12:R44.
9.Samore, MH, Shen, S, Greene, T, et al.A simulation-based evaluation of methods to estimate the impact of an adverse event on hospital length of stay. Med Care 2007;45(suppl 2):S108115.
10.Samore, M, Harbarth, S. A Methodologically Focused Review of the Literature in Hospital Epidemiology and Infection Control. 3rd ed. Philadelphia: Lippincott Williams & Wilkins; 2004:16451656.
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Infection Control & Hospital Epidemiology
  • ISSN: 0899-823X
  • EISSN: 1559-6834
  • URL: /core/journals/infection-control-and-hospital-epidemiology
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