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      Estimated Methicillin-Resistant Staphylococcus aureus Decolonization in Intensive Care Units Associated With Single-Application Chlorhexidine Gluconate or Mupirocin

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          Abstract

          This mathematical modeling study estimates the decolonization of methicillin-resistant Staphylococcus aureus (MRSA) associated with chlorhexidine gluconate and mupirocin in a simulated intensive care unit (ICU).

          Key Points

          Question

          What is the estimated proportion of patients with methicillin-resistant Staphylococcus aureus (MRSA) decolonized per application of chlorhexidine and mupirocin?

          Findings

          This mathematical modeling study estimated that chlorhexidine and mupirocin were independently associated with a 15% likelihood of decolonization in patients with MRSA.

          Meaning

          This study found that, on a per-application basis, chlorhexidine and mupirocin were associated with decolonization; this suggests that there may be room for improvement and innovation in MRSA decolonization interventions.

          Abstract

          Importance

          Chlorhexidine gluconate (CHG) and mupirocin are widely used to decolonize patients with methicillin-resistant Staphylococcus aureus (MRSA) and reduce risks associated with infection in hospitalized populations. Quantifying the association of an application of CHG alone or in combination with mupirocin with risk of MRSA infection is important for studies evaluating alternative decolonization strategies or schedules and for identifying whether there is room for improved decolonizing agents.

          Objective

          To estimate the proportion of patients with MRSA decolonized per application of CHG and mupirocin from existing population-level studies.

          Design, Setting, and Participants

          A stochastic mathematical model of an 18-bed intensive care unit (ICU) in an academic medical center operating over 1 year was used to estimate parameters for the proportion of simulated patients with MRSA decolonized per application of CHG and mupirocin. The model was conducted using approximate bayesian computation with data from an existing meta-analysis of studies conducted from February 2005 through January 2015. Data were analyzed from January 2018 through November 2019.

          Exposure

          A universal decolonization protocol for colonized patients in the ICU using CHG or CHG and mupirocin in combination was simulated.

          Main Outcomes and Measures

          The proportion of patients with MRSA decolonized per application of CHG and mupirocin was estimated.

          Results

          The estimated proportion of patients with MRSA decolonized per application of CHG was 0.15 (95% credible interval, 0.01-0.42), and the estimated proportion per application of mupirocin in conjunction with CHG was 0.15 (95% credible interval, 0.01-0.54). A lag in colonization detection was associated with decreases in the CHG estimate (0.11; 95% credible interval, 0.01-0.30) and mupirocin estimate (0.10; 95% credible interval, 0.00-0.34), which were sensitive to the value of the modeled contact rate between nurses and patients. A 1% increase in the value of this parameter was associated with a 0.73% increase in the estimated combined outcomes associated with CHG and mupirocin (95% CI: 0.71, 0.75). Gaps longer than 24 hours in the administration of decolonizing agents were associated with a decrease of within-ICU MRSA transmission. Compared with a mean (SD) of 1.23 (0.27) acquisitions per 1000 patient-days in scenarios with no decolonizing bathing, a bathing protocol administering CHG and mupirocin every 120 hours was associated with a mean (SD) acquisition rate of 1.03 (0.24) acquisitions per 1000 patient days, a 16.3% decrease (95% CI, 14.7%-18.0%; P > .001).

          Conclusions and Relevance

          These findings suggest that there may be room for significant improvement in anti-MRSA disinfectants, including the compounds themselves and their delivery mechanisms. Despite the decolonization estimates found in this study, these agents are associated with robust outcomes after delays in administration, which may help in alleviating concerns over patient comfort and toxic effects.

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          Most cited references21

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          Vital Signs: Epidemiology and Recent Trends in Methicillin-Resistant and in Methicillin-Susceptible Staphylococcus aureus Bloodstream Infections — United States

          Introduction Staphylococcus aureus is one of the most common pathogens in health care facilities and in the community, and can cause invasive infections, sepsis, and death. Despite progress in preventing methicillin-resistant S. aureus (MRSA) infections in health care settings, assessment of the problem in both health care and community settings is needed. Further, the epidemiology of methicillin-susceptible S. aureus (MSSA) infections is not well described at the national level. Methods Data from the Emerging Infections Program (EIP) MRSA population surveillance (2005–2016) and from the Premier and Cerner Electronic Health Record databases (2012–2017) were analyzed to describe trends in incidence of hospital-onset and community-onset MRSA and MSSA bloodstream infections and to estimate the overall incidence of S. aureus bloodstream infections in the United States and associated in-hospital mortality. Results In 2017, an estimated 119,247 S. aureus bloodstream infections with 19,832 associated deaths occurred. During 2005–2012 rates of hospital-onset MRSA bloodstream infection decreased by 17.1% annually, but the decline slowed during 2013–2016. Community-onset MRSA declined less markedly (6.9% annually during 2005–2016), mostly related to declines in health care–associated infections. Hospital-onset MSSA has not significantly changed (p = 0.11), and community-onset MSSA infections have slightly increased (3.9% per year, p<0.0001) from 2012 to 2017. Conclusions and Implications for Public Health Practice Despite reductions in incidence of MRSA bloodstream infections since 2005, S. aureus infections account for significant morbidity and mortality in the United States. To reduce the incidence of these infections further, health care facilities should take steps to fully implement CDC recommendations for prevention of device- and procedure-associated infections and for interruption of transmission. New and novel prevention strategies are also needed.
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            Evidence that contaminated surfaces contribute to the transmission of hospital pathogens and an overview of strategies to address contaminated surfaces in hospital settings.

            Evidence that contaminated surfaces contribute to the transmission of hospital pathogens comes from studies modeling transmission routes, microbiologic studies, observational epidemiologic studies, intervention studies, and outbreak reports. This review presents evidence that contaminated surfaces contribute to transmission and discusses the various strategies currently available to address environmental contamination in hospitals. Copyright © 2013 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.
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              How much time do nurses have for patients? a longitudinal study quantifying hospital nurses' patterns of task time distribution and interactions with health professionals

              Background Time nurses spend with patients is associated with improved patient outcomes, reduced errors, and patient and nurse satisfaction. Few studies have measured how nurses distribute their time across tasks. We aimed to quantify how nurses distribute their time across tasks, with patients, in individual tasks, and engagement with other health care providers; and how work patterns changed over a two year period. Methods Prospective observational study of 57 nurses for 191.3 hours (109.8 hours in 2005/2006 and 81.5 in 2008), on two wards in a teaching hospital in Australia. The validated Work Observation Method by Activity Timing (WOMBAT) method was applied. Proportions of time in 10 categories of work, average time per task, time with patients and others, information tools used, and rates of interruptions and multi-tasking were calculated. Results Nurses spent 37.0%[95%CI: 34.5, 39.3] of their time with patients, which did not change in year 3 [35.7%; 95%CI: 33.3, 38.0]. Direct care, indirect care, medication tasks and professional communication together consumed 76.4% of nurses' time in year 1 and 81.0% in year 3. Time on direct and indirect care increased significantly (respectively 20.4% to 24.8%, P < 0.01;13.0% to 16.1%, P < 0.01). Proportion of time on medication tasks (19.0%) did not change. Time in professional communication declined (24.0% to 19.2%, P < 0.05). Nurses completed an average of 72.3 tasks per hour, with a mean task length of 55 seconds. Interruptions arose at an average rate of two per hour, but medication tasks incurred 27% of all interruptions. In 25% of medication tasks nurses multi-tasked. Between years 1 and 3 nurses spent more time alone, from 27.5%[95%CI 24.5, 30.6] to 39.4%[34.9, 43.9]. Time with health professionals other than nurses was low and did not change. Conclusions Nurses spent around 37% of their time with patients which did not change. Work patterns were increasingly fragmented with rapid changes between tasks of short length. Interruptions were modest but their substantial over-representation among medication tasks raises potential safety concerns. There was no evidence of an increase in team-based, multi-disciplinary care. Over time nurses spent significantly less time talking with colleagues and more time alone.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                4 March 2021
                March 2021
                4 March 2021
                : 4
                : 3
                : e210652
                Affiliations
                [1 ]Paul G. Allen School for Global Animal Health, Washington State University, Pullman, Washington
                [2 ]Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, North Carolina
                Author notes
                Article Information
                Accepted for Publication: January 21, 2021.
                Published: March 4, 2021. doi:10.1001/jamanetworkopen.2021.0652
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Lofgren ET et al. JAMA Network Open.
                Corresponding Author: Eric T. Lofgren, PhD, Paul G. Allen School for Global Animal Health, Washington State University, 240 SE Ott Rd, Room 311, Pullman, WA 99164-7090 ( Eric.Lofgren@ 123456wsu.edu ).
                Author Contributions: Dr Lofgren had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Lofgren, Mietchen.
                Acquisition, analysis, or interpretation of data: Lofgren, Dicks, Moehring, Anderson.
                Drafting of the manuscript: Lofgren.
                Critical revision of the manuscript for important intellectual content: All authors.
                Statistical analysis: Lofgren.
                Obtained funding: Lofgren.
                Administrative, technical, or material support: Lofgren, Mietchen, Anderson.
                Supervision: Lofgren, Dicks.
                Conflict of Interest Disclosures: Dr Lofgren reported receiving grants from the Centers for Disease Control and Prevention (CDC) during the conduct of this study. Dr Moehring reported receiving grants to her institution from the CDC and Agency for Healthcare Research and Quality (AHRQ). Dr Anderson reported receiving grants from the CDC and AHRQ and authorship royalties from UpToDate outside the submitted work and serving as co-owner of Infection Control Education for Major Sports. No other disclosures were reported.
                Funding/Support: This work was supported by the Centers for Disease Control and Prevention Cooperative Agreement RFA-CK-17-001-Modeling Infectious Diseases in Healthcare Program.
                Role of the Funder/Sponsor: The funding organization provided feedback and expert opinion in the design and conduct of the study, played no role in the collection and management of the data, provided feedback and expert opinion on the analysis and interpretation of the data, played no role in the preparation of the manuscript, provided feedback and opinion in reviewing the manuscript, and played no role in the decision to submit the manuscript for publication.
                Group Information: Members of the Centers for Disease Control Modeling Infectious Diseases in Healthcare Program are as follows: Eric T. Lofgren, PhD, Washington State University; Matthew Mietchen, MPH, Washington State University; Kristen V. Dicks, MD, Duke Center for Antimicrobial Stewardship and Infection Prevention; Rebekah Moehring, MD, Duke Center for Antimicrobial Stewardship and Infection Prevention; Deverick Anderson, MD, Duke Center for Antimicrobial Stewardship and Infection Prevention; Eili Klein MA, PhD, Johns Hopkins School of Medicine; Sarah Rhea DVM, MPH, PhD, RTI International; Matthew Samore, MD, University of Utah School of Medicine; Alberto Segre, MS, PhD, University of Iowa.
                Additional Contributions: Christopher Short, PhD (Washington State University) helped in the conceptual design of the model’s population structure and in the mathematical expression of the modeled interventions. This individual was not compensated for this work.
                Article
                zoi210035
                10.1001/jamanetworkopen.2021.0652
                7933999
                33662133
                36b3f119-75bc-4bd8-b3e1-50689da667c9
                Copyright 2021 Lofgren ET et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 28 July 2020
                : 13 January 2021
                Categories
                Research
                Original Investigation
                Online Only
                Infectious Diseases

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