Dataset Information

Reducing C. difficile in children: An agent-based modeling approach to evaluate intervention effectiveness.

ABSTRACT: OBJECTIVE:Clostridioides difficile infection (CDI) is rapidly increasing in children's hospitals nationwide. Thus, we aimed to compare the effectiveness of 9 infection prevention interventions and 6 multiple-intervention bundles at reducing hospital-onset CDI and asymptomatic C. difficile colonization. DESIGN:Agent-based simulation model of C. difficile transmission. SETTING:Computer-simulated, 80-bed freestanding, tertiary-care pediatric hospital, including 8 identical wards with 10 single-bed patient rooms each. PARTICIPANTS:The model includes 5 distinct agent types: patients, visitors, caregivers, nurses, and physicians. INTERVENTIONS:Daily and terminal environmental disinfection, screening at admission, reduced intrahospital patient transfers, healthcare worker (HCW), visitor, and patient hand hygiene, and HCW and visitor contact precautions. RESULTS:The model predicted that daily environmental disinfection with sporicidal product, combined with screening for asymptomatic C. difficile at admission, was the most effective 2-pronged infection prevention bundle, reducing hospital-onset CDI by 62.0% and asymptomatic colonization by 88.4%. Single-intervention strategies, including daily disinfection, terminal disinfection, asymptomatic screening at admission, HCW hand hygiene, and patient hand hygiene, as well as decreasing intrahospital patient transfers, all also reduced both hospital-onset CDI and asymptomatic colonization in the model. Visitor hand hygiene and visitor and HCW contact precautions were not effective at reducing either measure. CONCLUSIONS:Hospitals can achieve substantial reduction in hospital-onset CDIs by implementing a small number of highly effective interventions.

SUBMITTER: Barker AK

PROVIDER: S-EPMC7461244 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Reducing <i>C. difficile</i> in children: An agent-based modeling approach to evaluate intervention effectiveness.

Barker Anna K AK Scaria Elizabeth E Alagoz Oguzhan O Sethi Ajay K AK Safdar Nasia N

Infection control and hospital epidemiology 20200213 5

<h4>Objective</h4>Clostridioides difficile infection (CDI) is rapidly increasing in children's hospitals nationwide. Thus, we aimed to compare the effectiveness of 9 infection prevention interventions and 6 multiple-intervention bundles at reducing hospital-onset CDI and asymptomatic C. difficile colonization.<h4>Design</h4>Agent-based simulation model of C. difficile transmission.<h4>Setting</h4>Computer-simulated, 80-bed freestanding, tertiary-care pediatric hospital, including 8 identical war ...[more]

PMID: 32052722

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Project description:BackgroundSustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods.MethodsWe used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables.ResultsHigher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years.ConclusionsHuman resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on population outcomes. Furthermore, this model demonstrates how ABMs may be leveraged to inform research design and assess the impact of EBI sustainability in practice.

Project description:BackgroundDepression is highly prevalent in the working population and is associated with significant loss of workdays; however, access to evidence-based treatment is limited.ObjectiveThis study evaluated the effectiveness of a Web-based intervention in reducing mild to moderate depression and sickness absence.MethodsIn an open-label randomized controlled trial, participants were recruited from a large-scale statutory health insurance and were assigned to two groups. The intervention group had access to a 12 week Web-based program consisting of structured interactive sessions and therapist support upon request. The wait-list control group had access to unguided Web-based psycho-education. Depressive symptoms were self-assessed at baseline, post-treatment, and follow-up (12 weeks after treatment) using the Patient Health Questionnaire (PHQ-9) and Beck Depression Inventory (BDI-II) as primary outcome measures. Data on sickness absence was retrieved from health insurance records. Intention-to-treat (ITT) analysis and per-protocol (PP) analysis were performed.ResultsOf the 180 participants who were randomized, 88 completed the post-assessment (retention rate: 48.8%, 88/180). ITT analysis showed a significant between-group difference in depressive symptoms during post-treatment in favor of the intervention group, corresponding to a moderate effect size (PHQ-9: d=0.55, 95% CI 0.25-0.85, P<.001, and BDI-II: d=0.41, CI 0.11-0.70, P=.004). PP analysis partially supported this result, but showed a non-significant effect on one primary outcome (PHQ-9: d=0.61, 95% CI 0.15-1.07, P=.04, and BDI-II: d=0.25 95% CI -0.18 to 0.65, P=.37). Analysis of clinical significance using reliable change index revealed that significantly more participants who used the Web-based intervention (63%, 63/100) responded to the treatment versus the control group (33%, 27/80; P<.001). The number needed to treat (NNT) was 4.08. Within both groups, there was a reduction in work absence frequency (IG: -67.23%, P<.001, CG: -82.61%, P<.001), but no statistical difference in sickness absence between groups was found (P=.07).ConclusionsThe Web-based intervention was effective in reducing depressive symptoms among adults with sickness absence. As this trial achieved a lower power than calculated, its results should be replicated in a larger sample. Further validation of health insurance records as an outcome measure for eHealth trials is needed.Trial registrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 02446836; http://www.isrctn.com/ISRCTN02446836 (Archived by WebCite at http://www.webcitation.org/6jx4SObnw).

Dataset Information

Reducing C. difficile in children: An agent-based modeling approach to evaluate intervention effectiveness.

Publications

Reducing <i>C. difficile</i> in children: An agent-based modeling approach to evaluate intervention effectiveness.

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