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The Economic Effect of Screening Orthopedic Surgery Patients Preoperatively for Methicillin-Resistant Staphylococcus aureus

  • Bruce Y. Lee (a1) (a2) (a3), Ann E. Wiringa (a1) (a2) (a3), Rachel R. Bailey (a1) (a2) (a3), Vishal Goyal (a1) (a2) (a3), Becky Tsui (a1) (a2) (a3), G. Jonathan Lewis (a1) (a2) (a3), Robert R. Muder (a4) and Lee M. Harrison (a5)...

Extract

Background and Objective.

Patients undergoing orthopedic surgery are susceptible to methicillin-resistant Staphylococcus aureus (MRSA) infections, which can result in increased morbidity, hospital lengths of stay, and medical costs. We sought to estimate the economic value of routine preoperative MRSA screening and decolonization of orthopedic surgery patients.

Methods.

A stochastic decision-analytic computer simulation model was used to evaluate the economic value of implementing this strategy (compared with no preoperative screening or decolonization) among orthopedic surgery patients from both the third-party payer and hospital perspectives. Sensitivity analyses explored the effects of varying MRSA colonization prevalence, the cost of screening and decolonization, and the probability of decolonization success.

Results.

Preoperative MRSA screening and decolonization was strongly cost-effective (incremental cost-effectiveness ratio less than $6,000 per quality-adjusted life year) from the third-party payer perspective even when MRSA prevalence was as low as 1%, decolonization success was as low as 25%, and decolonization costs were as high as $300 per patient. In most scenarios this strategy was economically dominant (ie, less costly and more effective than no screening). From the hospital perspective, preoperative MRSA screening and decolonization was the economically dominant strategy for all scenarios explored.

Conclusions.

Routine preoperative screening and decolonization of orthopedic surgery patients may under many circumstances save hospitals and third-party payers money while providing health benefits.

Copyright

Corresponding author

Public Health Computational and Operations Research (PHICOR) Group, University of Pittsburgh, 200 Meyran Avenue, Suite 200, Pittsburgh, PA 15213 (byll@pitt.edu)

References

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