title: Cost and effects of different admission screening strategies to control the spread of methicillin-resistant Staphylococcus aureus.
abstract: Nosocomial infection rates due to antibiotic-resistant bacteriae, e.g., methicillin-resistant Staphylococcus aureus (MRSA) remain high in most countries. Screening for MRSA carriage followed by barrier precautions for documented carriers (so-called screen and isolate (S&I)) has been successful in some, but not all settings. Moreover, different strategies have been proposed, but comparative studies determining their relative effects and costs are not available. We, therefore, used a mathematical model to evaluate the effect and costs of different S&I strategies and to identify the critical parameters for this outcome. The dynamic stochastic simulation model consists of 3 hospitals with general wards and intensive care units (ICUs) and incorporates readmission of carriers of MRSA. Patient flow between ICUs and wards was based on real observations. Baseline prevalence of MRSA was set at 20% in ICUs and hospital-wide at 5%; ranges of costs and infection rates were based on published data. Four S&I strategies were compared to a do-nothing scenario: S&I of previously documented carriers ("flagged" patients); S&I of flagged patients and ICU admissions; S&I of flagged and group of "frequent" patients; S&I of all hospital admissions (universal screening). Evaluated levels of efficacy of S&I were 10%, 25%, 50% and 100%. Our model predicts that S&I of flagged and S&I of flagged and ICU patients are the most cost-saving strategies with fastest return of investment. For low isolation efficacy universal screening and S&I of flagged and "frequent" patients may never become cost-saving. Universal screening is predicted to prevent hardly more infections than S&I of flagged and "frequent" patients, albeit at higher costs. Whether an intervention becomes cost-saving within 10 years critically depends on costs per infection in ICU, costs of screening and isolation efficacy.
authors: Julius Center for Health Research & Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. t.guryeva@gmail.com
authors: Tanya
authors: T
authors: Gurieva
authors: Martin C J
authors: MC
authors: Bootsma
authors: Marc J M
authors: MJ
authors: Bonten
mesh_terms: D000704:Analysis of Variance; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D003428:Cross Infection / Q000175:diagnosis* / Q000191:economics / Q000517:prevention & control; D006760:Hospitalization; D006801:Humans; D017053:Infection Control / Q000191:economics* / Q000379:methods* / Q000706:statistics & numerical data; D007362:Intensive Care Units; D007902:Length of Stay; D008403:Mass Screening / Q000191:economics / Q000379:methods; D055624:Methicillin-Resistant Staphylococcus aureus / Q000302:isolation & purification*; D015233:Models, Statistical; D010356:Patient Isolation; D015995:Prevalence; D013203:Staphylococcal Infections / Q000175:diagnosis* / Q000191:economics / Q000517:prevention & control; D013269:Stochastic Processes