A computer simulation model of the cost-effectiveness of routine Staphylococcus aureus screening and decolonization among lung and heart-lung transplant recipients

Clancy, C.; Bartsch, S.; Nguyen, M.; Stuckey, D.; Shields, R.; Lee, B.
June 2014
European Journal of Clinical Microbiology & Infectious Diseases;Jun2014, Vol. 33 Issue 6, p1053
Academic Journal
Our objective was to model the cost-effectiveness and economic value of routine peri-operative Staphylococcus aureus screening and decolonization of lung and heart-lung transplant recipients from hospital and third-party payer perspectives. We used clinical data from 596 lung and heart-lung transplant recipients to develop a model in TreeAge Pro 2009 (Williamsport, MA, USA). Sensitivity analyses varied S. aureus colonization rate (5-15 %), probability of infection if colonized (10-30 %), and decolonization efficacy (25-90 %). Data were collected from the Cardiothoracic Transplant Program at the University of Pittsburgh Medical Center. Consecutive lung and heart-lung transplant recipients from January 2006 to December 2010 were enrolled retrospectively. Baseline rates of S. aureus colonization, infection and decolonization efficacy were 9.6 %, 36.7 %, and 31.9 %, respectively. Screening and decolonization was economically dominant for all scenarios tested, providing more cost savings and health benefits than no screening. Savings per case averted (2012 $US) ranged from $73,567 to $133,157 (hospital perspective) and $10,748 to $16,723 (third party payer perspective), varying with the probability of colonization, infection, and decolonization efficacy. Using our clinical data, screening and decolonization led to cost savings per case averted of $240,602 (hospital perspective) and averted 6.7 S. aureus infections (4.3 MRSA and 2.4 MSSA); 89 patients needed to be screened to prevent one S. aureus infection. Our data support routine S. aureus screening and decolonization of lung and heart-lung transplant patients. The economic value of screening and decolonization was greater than in previous models of other surgical populations.


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