Simulation Shows Hospitals That Cooperate On Infection Control Obtain Better Results Than Hospitals Acting Alone

Health Affairs (Impact Factor: 4.64). 10/2012; 31(10):2295-303. DOI: 10.1377/hlthaff.2011.0992
Source: PubMed

ABSTRACT Efforts to control life-threatening infections, such as with methicillin-resistant Staphylococcus aureus (MRSA), can be complicated when patients are transferred from one hospital to another. Using a detailed computer simulation model of all hospitals in Orange County, California, we explored the effects when combinations of hospitals tested all patients at admission for MRSA and adopted procedures to limit transmission among patients who tested positive. Called "contact isolation," these procedures specify precautions for health care workers interacting with an infected patient, such as wearing gloves and gowns. Our simulation demonstrated that each hospital's decision to test for MRSA and implement contact isolation procedures could affect the MRSA prevalence in all other hospitals. Thus, our study makes the case that further cooperation among hospitals-which is already reflected in a few limited collaborative infection control efforts under way-could help individual hospitals achieve better infection control than they could achieve on their own.

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    • "In addition to providing a better understanding of the spread of nosocomial infections, mathematical models have been employed to assess the effects of infection control measures. Lee et al. (2012) showed that coordinated MRSA prevention practices can result in beneficial effects for all hospitals in a county or region, even for those that do not implement the intervention: The more hospitals that work together, the greater the benefit. These results are consistent with the theoretical analysis by Smith et al. (2005), which explored, in a theoretical multi-hospital setting, the impact of inter- ventions. "
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    International journal of medical microbiology: IJMM 03/2013; 303(6-7). DOI:10.1016/j.ijmm.2013.02.003 · 3.42 Impact Factor
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    ABSTRACT: Objective. Implementation of contact precautions in nursing homes to prevent methicillin-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.
    Infection Control and Hospital Epidemiology 02/2013; 34(2):151-60. DOI:10.1086/669091 · 3.94 Impact Factor
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    ABSTRACT: Objective As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare ‘ecosystem’ in infection control. Materials and methods We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases. Results To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity). Discussion Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities. Conclusions A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.
    Journal of the American Medical Informatics Association 04/2013; 20(E1). DOI:10.1136/amiajnl-2012-001107 · 3.93 Impact Factor
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