Antimicrobial Use and Control of Clostridium difficile transmission and infection
Michael Adam Rubin MD PhD
VA Salt Lake City Health Care System, Salt Lake City, UT
Salt Lake City, UT
Funding Period: July 2012 - June 2015

BACKGROUND/RATIONALE:
C. difficile is the predominant infectious cause of healthcare-associated diarrhea and one of the most common types of healthcare-acquired infection, resulting in prolonged hospital stays, higher mortality, and increased healthcare costs. Exposure to antibiotics is the most important risk factor for CDI, presumably through the disruption of the normal fecal flora. Although a number of approaches have been proposed to contain outbreaks of CDI, such as improved hand hygiene and antibiotic stewardship, little is understood about how these interventions alter the dynamics of C. difficile transmission and acquisition and contribute to its control.

OBJECTIVE(S):
C. difficile transmission is dependent on the interactions of innumerable factors and processes. The design of policies to control nosocomial CDI is aided by an understanding of these interactions and the relative impact of different control strategies on C. difficile transmission dynamics. With this in mind, our objectives are to (a) perform a facility-level analysis of associations between antibiotic use patterns and CDI rates at VA hospitals nationwide; (b) incorporate these patterns and associations into our agent-based simulation of nosocomial C. difficile transmission; (c) use the simulation to evaluate and compare alternative and novel policies for C. difficile control in VA hospitals, including antibiotic stewardship; and (d) explore the impact of these intervention strategies under varying conditions, including the introduction of an epidemic C. difficile strain.

METHODS:
We will refine and enhance a high-fidelity agent-based computer simulation of nosocomial C. difficile transmission created as part of a previous project. Our analyses of antibiotic prescribing and CDI rates will be based on a large, nationwide database of VA patient data that we have obtained from Patient Care Services. The combination of individual- and hospital-level data from more than 150 VA hospitals makes it feasible to fit models that separately estimate direct effects of antimicrobial agents on CDI risk from their indirect effects mediated through person-to-person spread. Hierarchical mixed effects models will be used to characterize the association of CDI rates to patient and hospital level factors. Results of these analyses will be incorporated into the simulation, which will then be used to assess the various strategies and factors that impact C. difficile transmission through a series of simulation experiments. Traditional quantitative epidemiologic methods will be used to analyze simulation results, with a focus on C. difficile incidence and transmission rates as outcomes. Dynamic cost-benefit analyses will also be performed by projecting C. difficile incidence rates and costs under the various alternative policy regimes.

FINDINGS/RESULTS:
This is the initial abstract for the start of the project.

IMPACT:
Our work will provide valuable information on the effectiveness and cost-benefit of different control policies for Clostridium difficile. By examining the associations between facility-level antibiotic prescribing and C. difficile infection (CDI) rates, and the impact and costs of various control strategies for CDI, we may gain a better understanding of the dynamics of C. difficile transmission in ways that will contribute to the implementation of VA-wide initiatives aimed at controlling CDI, such as antibiotic stewardship. The findings from this project have the potential to impact infection control practice throughout the VA healthcare system.

PUBLICATIONS:
None at this time.

DRA: Health Systems, Infectious Diseases
DRE: Prevention
Keywords: Computational Modeling, Computer Simulations, Healthcare Algorithms, Patient Safety
MeSH Terms: none