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    In: Infection Control & Hospital Epidemiology, Cambridge University Press (CUP), Vol. 34, No. 2 ( 2013-02), p. 151-160
    Abstract: Implementation of contact precautions in nursing homes to prevent methicillm-resistant Staphylococcus aureus (MRSA) transmission could cost time and effort and may have wide-ranging effects throughout multiple health facilities. Computational modeling could forecast the potential effects and guide policy making. Design. Our multihospital computational agent-based model, Regional Healthcare Ecosystem Analyst (RHEA). Setting. All hospitals and nursing homes in Orange County, California. Methods. Our simulation model compared the following 3 contact precaution strategies: (1) no contact precautions applied to any nursing home residents, (2) contact precautions applied to those with clinically apparent MRSA infections, and (3) contact precautions applied to all known MRSA carriers as determined by MRSA screening performed by hospitals. Results. Our model demonstrated that contact precautions for patients with clinically apparent MRSA infections in nursing homes resulted in a median 0.4% (range, 0%–1.6%) relative decrease in MRSA prevalence in nursing homes (with 50% adherence) but had no effect on hospital MRSA prevalence, even 5 years after initiation. Implementation of contact precautions (with 50% adherence) in nursing homes for all known MRSA carriers was associated with a median 14.2% (range, 2.1%–21.8%) relative decrease in MRSA prevalence in nursing homes and a 2.3% decrease (range, 0%–7.1%) in hospitals 1 year after implementation. Benefits accrued over time and increased with increasing compliance. Conclusions. Our modeling study demonstrated the substantial benefits of extending contact precautions in nursing homes from just those residents with clinically apparent infection to all MRSA carriers, which suggests the benefits of hospitals and nursing homes sharing and coordinating information on MRSA surveillance and carriage status.
    Type of Medium: Online Resource
    ISSN: 0899-823X , 1559-6834
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2013
    detail.hit.zdb_id: 2106319-9
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