Infection Control and Hospital Epidemiology最新文献

{"title":"Evaluation of Department of Defense hospital antimicrobial stewardship programs (ASPs) using a novel Core Elements scoring approach and modeling Core Elements scores with metrics related to ASP outcomes.","authors":"LeeAnne C Lynch, Katrin Mende, Rana F Hamdy, Cara H Olsen, Paige E Waterman, John M Young, David R Tribble","doi":"10.1017/ice.2025.33","DOIUrl":"https://doi.org/10.1017/ice.2025.33","url":null,"abstract":"<p><strong>Objective: </strong>Evaluate Department of Defense (DoD) antimicrobial stewardship programs (ASPs) by assessing the relationship between key clinical outcome metrics (antibiotic use, incidence of resistant pathogens, and incidence of <i>Clostridioides difficile</i> infections) and CDC Core Element (CE) adherence.</p><p><strong>Design: </strong>Retrospective, cross-sectional study of DoD hospitals in 2018 and 2021.</p><p><strong>Methods: </strong>National Healthcare Safety Network Standardized Antimicrobial Administration Ratios (SAARs) were used to measure antibiotic use and microbiology results to evaluate four types of pathogen incidence. A novel CE scoring approach used scores to quantitatively assess relationships with CE adherence and outcome metrics using correlation and regression models. Assessments were repeated with 2021 data for Priority CE adherence and to conduct adjusted regressions for CEs and Priority CEs controlling for categorical bed size.</p><p><strong>Results: </strong>Compared to 2022 national data, DoD hospitals in 2021 had a similar proportion of facilities with a SAAR statistically significantly > 1.0. Leadership, Action, and Tracking CEs followed a more normal score distribution, while Reporting and Education were somewhat left-skewed. Unadjusted models often showed a positive relationship with higher CE scores associated with worse outcomes for the SAAR and pathogen incidence. Adjusted models indicated that procedural CEs, particularly Priority Reporting, were associated with better ASP-related outcomes.</p><p><strong>Conclusions: </strong>CEs should be more quantitatively assessed. Results provide initial evidence to prioritize procedural CE implementation within the DoD; however, additional investigation for structural CEs is needed. Patient outcome data should be collected as an important indicator of ASP performance.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-11"},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mixed-methods study assessing the performance of a clinical decision support tool for <i>Clostridioides difficile</i> testing for patients receiving laxatives.","authors":"David R Peaper, Shardul N Rathod, L Scott Sussman, Marwan M Azar, Christina Murdzek, Scott C Roberts, Eric M Tichy, Jeffrey E Topal, Nitu Kashyap, Dayna McManus, Richard A Martinello","doi":"10.1017/ice.2025.30","DOIUrl":"https://doi.org/10.1017/ice.2025.30","url":null,"abstract":"<p><strong>Objective: </strong>To better understand clinicians' rationale for ordering testing for <i>C. difficile</i> infection (CDI) for patients receiving laxatives and the impact of the implementation of a clinical decision support (CDS) intervention.</p><p><strong>Design: </strong>A mixed-methods, case series was performed from March 2, 2017 to December 31, 2018.</p><p><strong>Setting: </strong>Yale New Haven Hospital, a 1,541 bed tertiary academic medical center.</p><p><strong>Participants: </strong>Hospitalized patients ≥ 18 years old, and clinicians who were alerted by the CDS.</p><p><strong>Intervention: </strong>CDS was triggered in real-time when a clinician sought to order testing for CDI for a patient who received one or more doses of laxatives within the preceding 24 hours.</p><p><strong>Results: </strong>A total of 3,376 CDS alerts were triggered during the 21-month study period from 2,567 unique clinician interactions. Clinicians bypassed the CDS alert 74.5% of the time, more frequent among residents (48.3% bypass vs. 39.9% accept) and advanced practice providers (APPs) (34.9% bypass vs. 30.6% accept) than attendings (11.3% bypass vs. 22.5% accept). Ordering clinicians noted increased stool frequency/output (48%), current antibiotic exposure (34%), and instructions by an attending physician to test (28%) were among the most common reasons for overriding the alert and proceeding with testing for CDI.</p><p><strong>Conclusions: </strong>Testing for CDI despite patient laxative use was associated with an increased clinician concern for CDI, patient risk for CDI, and attending physician instruction for testing. Attendings frequently accepted CDS guidance while residents and APPs often reinstated CDI test orders, suggesting a need for greater empowerment and discretion when ordering tests.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-7"},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of central line-associated bloodstream infection: focus on time of insertion.","authors":"Ari Moskowitz, Melissa Fazzari, Luke Andrea, Jianwen Wu, Arup Gope, Thomas Butler, Amira Mohamed, Christine Shen, Fran Ganz-Lord, Inessa Gendlina, Michelle Ng Gong","doi":"10.1017/ice.2025.1","DOIUrl":"https://doi.org/10.1017/ice.2025.1","url":null,"abstract":"<p><strong>Objective: </strong>Central line-associated bloodstream infections (CLABSIs) result in morbidity and mortality among hospitalized patients. Hospital interventions to reduce the incidence of CLABSI are often broadly applied to all patients with central venous access. Identifying central lines at high risk for CLABSI at time of insertion will allow for a more focused delivery of preventative interventions.</p><p><strong>Design: </strong>This was an observational cohort study conducted at three hospitals including all patients who received central venous access. CLABSIs were identified using an institutional CLABSI database maintained by the hospital epidemiology team. Logistic regression (LASSO) and machine learning (random forest, XGboost) techniques were applied for the prediction of CLABSI occurrence, adjusting for selected patent and insertion-level characteristics.</p><p><strong>Results: </strong>A total of 40,008 central venous catheters were included, of which 409 (1.02%) were associated with CLABSI. The random forest and the XGBoost models had the highest discrimination (Area Under the Received Operating Curve [AUC] 0.79) followed by LASSO (0.73). High illness severity, receipt of total parenteral nutrition, receipt of hemodialysis, pre-insertion hospital length-of-stay, and low albumin levels were all predictive of CLABSI occurrence. Precision for all models was poor owing to a high false-positive rate.</p><p><strong>Discussion: </strong>CLABSI can be predicted based upon patient and insertion level factors in the electronic health record. In this study, random forest and gradient-boosted models had the highest AUC. Prediction cut-offs for the identification of CLABSI can be adjusted based upon the acceptable rate of false-positives for a given CLABSI preventative intervention.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-8"},"PeriodicalIF":3.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of facility vaccination policy with influenza vaccination among healthcare personnel in acute care hospitals: national Healthcare Safety Network, 2021-22 influenza season.","authors":"Cam-Van T Huynh, Emily Haanschoten, Minn M Soe, Kira Barbre, Lu Meng, Jonathan R Edwards, Elizabeth J Kalayil, Megan C Lindley, Hannah E Reses, David T Kuhar, Matthew J Stuckey, Andrea Benin, Jeneita M Bell","doi":"10.1017/ice.2025.24","DOIUrl":"https://doi.org/10.1017/ice.2025.24","url":null,"abstract":"<p><p>We examined the association between influenza vaccination policies at acute care hospitals and influenza vaccination coverage among healthcare personnel for the 2021-22 influenza season. Mandatory vaccination and masking for unvaccinated personnel were associated with increased odds of vaccination. Hospital employees had higher vaccination coverage than licensed independent practitioners.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-5"},"PeriodicalIF":3.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-word utility of procalcitonin in patients hospitalized with community-acquired pneumonia: A matched cohort study.","authors":"Dan Ilges, Dylan Kosaski, Maria Teresa Seville, Alyssa K McGary, John C O'Horo, Christine L Snozek, Ryan W Stevens, Aditya Shah","doi":"10.1017/ice.2025.35","DOIUrl":"https://doi.org/10.1017/ice.2025.35","url":null,"abstract":"<p><strong>Objective: </strong>To retrospectively observe procalcitonin (PCT) and antibiotic ordering practices in patients hospitalized with community-acquired pneumonia (CAP).</p><p><strong>Design: </strong>Retrospective, exact matched, multicenter cohort study from October 1, 2018 - March 31, 2023.</p><p><strong>Setting: </strong>All hospitals across the Mayo Clinic Enterprise.</p><p><strong>Participants: </strong>Adult patients with CAP, identified using pneumonia diagnosis codes and receipt of systemic antibiotics with an indication of \"respiratory tract infection\" within 48 hours of hospitalization.</p><p><strong>Methods: </strong>PCT testing within the first 7 days of hospitalization was compared to non-PCT care (nPCT). The primary outcomes were treatment duration, antibiotic days of therapy (DOT), and length of stay (LOS).</p><p><strong>Results: </strong>15364 patients met inclusion criteria. PCT testing occurred in 42.4% (6515/15364) of encounters, totaling 8214 PCT results. 12880 unique patient encounters were matched 1:1, 6440 in each group. Treatment duration was longer in the PCT group compared to the nPCT group (5.1 vs 4.6 days, respectively, <i>P</i> < 0.001). Patients in the PCT group also received more DOT (8.6 vs 7.6 DOT, <i>P</i> < 0.001) and had a longer LOS (6.8 vs 5.9 days, <i>P</i> < 0.001), respectively. There was no difference in 30-day all-cause mortality or <i>C. difficile</i> infection between groups. In a sensitivity analysis of nPCT patients compared to those with a peak value <0.25 ng/mL (i.e. normal result) there was no difference in treatment duration (4.6 days nPCT vs 4.7 days normal PCT, <i>P</i> = 0.104) or LOS (5.9 days nPCT vs 6.0 days normal PCT, <i>P</i> = 0.134).</p><p><strong>Conclusion: </strong>PCT testing in patients hospitalized with CAP was not associated with reduced antimicrobial utilization, LOS, or 30-day all-cause mortality.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-7"},"PeriodicalIF":3.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143523270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hand hygiene opportunities in neonatal intensive care: a multicenter observational study to calibrate group electronic monitoring systems.","authors":"Eugene Lee, Stacey Clark, Paige Reason, Sarah Khan, Sabrina Fan, Michelle Li, Alex Cen, Asaph Rolnitsky, Alexander Kiss, Dominik Mertz, Jerome A Leis","doi":"10.1017/ice.2025.36","DOIUrl":"https://doi.org/10.1017/ice.2025.36","url":null,"abstract":"<p><p>Observers were randomized to time and location across two different Neonatal Intensive Care Units (NICUs) to count hand hygiene opportunities (HHOs). Mean hourly HHO was lower at night and during use of precautions, and higher in shared rooms. HHO benchmarks can support implementation of group electronic monitoring systems in NICUs.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":3.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143515532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High prevalence of multidrug-resistant bacteria on patient medical file surfaces at five critical care units in Kampala, Uganda: an explanatory sequential mixed-methods study.","authors":"Margaret Kyamulabi, Jonathan Izudi, Andrew Mujugira, Stephen Okoboi","doi":"10.1017/ice.2025.26","DOIUrl":"https://doi.org/10.1017/ice.2025.26","url":null,"abstract":"<p><strong>Introduction: </strong>Intensive care units (ICUs) and high-dependency units (HDUs) care for critically ill patients, many of whom have multi-drug-resistant (MDR) bacteria. We investigated the prevalence and distribution of MDR bacteria on the surfaces of patient medical files in three ICUs and two HDUs in Kampala.</p><p><strong>Method: </strong>We conducted a cross-sectional study that used simple random sampling to select patient medical files through unique codes recorded in a health information electronic system. MDR was defined as laboratory confirmation of the WHO priority pathogens following the 33rd edition of the Clinical Laboratory Standards Institute on Antimicrobial Susceptibility testing guidelines for antibiotic susceptibility interpretation. Quantitative data was descriptively analyzed, while qualitative was thematically analyzed.</p><p><strong>Results: </strong>Six of 33 files (18.2%) had MDR bacteria on their surfaces. Contamination was significantly associated with the type of medical diagnosis (p=0.014) and the file storage location (p=0.010). The MDR pathogens identified were Fastidious Acinetobacter (5/33; 15.2%) and methicillin-resistant Staphylococcus aureus (1/33; 3%).</p><p><strong>Conclusion: </strong>Nearly one in five patient medical files in ICUs and HDUs were contaminated with MDR bacteria. Most contaminated files belonged to patients treated with aminoglycoside or glycopeptide-based regimens.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":3.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143515535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated surveillance of hospital-onset bacteremia and fungemia: feasibility and epidemiological results from a Dutch multicenter study.","authors":"Manon A C M Brekelmans, Anne L M Vlek, Yvonne van Dijk, Annelies E Smilde, Annemarie J L Weersink, Herman F Wunderink, Hanneke Boon, Saara Vainio, Wendy S Bril, Jan A J W Kluytmans, Marc J M Bonten, Maaike S M van Mourik","doi":"10.1017/ice.2025.29","DOIUrl":"https://doi.org/10.1017/ice.2025.29","url":null,"abstract":"<p><strong>Objective: </strong>Hospital-onset bacteremia and fungemia (HOB) has been suggested as a suitable and automatable surveillance target to include in surveillance programs, however differences in definitions across studies limit interpretation and large-scale implementation. We aimed to apply an automated surveillance system for HOB in multiple hospitals using a consensus definition, and describe HOB rates.</p><p><strong>Design and setting: </strong>Retrospective cohort study in four Dutch hospitals: 1 tertiary hospital and 3 secondary hospitals.</p><p><strong>Patients: </strong>All patients admitted for at least one overnight stay between 2017 and 2021 were included, except patients in psychiatry wards.</p><p><strong>Methods: </strong>Data from the electronic health records and laboratory information system were used to identify HOBs based on the PRAISE consensus definition. HOB rates were calculated at ward and micro-organism-level.</p><p><strong>Results: </strong>Hospital-wide HOB rates varied from 1.0 to 1.9, and ICU rates varied from of 8.2 to 12.5 episodes per 1000 patient days. The median time between admission and HOB was 8-13 days. HOBs were predominantly caused by Enterobacterales, Enterococci, <i>S. aureus</i> and coagulase-negative staphylococci. Longitudinal HOB surveillance detected differences over time at ward and micro-organism level; for example increased HOB rates were observed during the COVID-19 pandemic. Sensitivity analyses demonstrated the impact of assumptions regarding the collection of confirmatory blood cultures for common commensals.</p><p><strong>Conclusions: </strong>Applying a fully automated definition for HOB surveillance was feasible in multiple centers with different data infrastructures, and enabled detection of differences over time at ward and micro-organism-level. HOB surveillance may lead to prevention initiatives in the future.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-9"},"PeriodicalIF":3.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143500996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elimination of <i>Legionella</i> colonization in a hospital water system: evidence from 23 years of chlorine dioxide use.","authors":"Natalie G Exum, Lindsay N Avolio, Gregory Bova, Clare Rock, Melanie S Curless, Lisa L Maragakis, Kellogg J Schwab","doi":"10.1017/ice.2025.25","DOIUrl":"https://doi.org/10.1017/ice.2025.25","url":null,"abstract":"<p><p>A hospital water system colonized with <i>Legionella</i> bacteria (three of four buildings, with > 50% of positive samples) was able to reduce detections to <1% positivity in the long term only after ClO₂ was iteratively added first to the cold-water and then hot-water systems followed by pipe replacements (n = 6835 total samples).</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":3.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ditching the defaults: Assessing the impact of default duration removal on antibiotic prescriptions originating in the emergency department.","authors":"Amy L Van Abel, Ryan W Stevens, Sara Ausman, Kellie Arensman Hannan, Dan Ilges, Kirstin Kooda, Sarah Lessard, Courtney M Willis, Christina G Rivera, Kelsey Jensen","doi":"10.1017/ice.2025.31","DOIUrl":"https://doi.org/10.1017/ice.2025.31","url":null,"abstract":"<p><p>Reducing antimicrobial exposure by limiting the duration of therapy is an effective antimicrobial stewardship strategy. In this article, we describe the impact of modification of the electronic health record to remove default durations of therapy on ambulatory antibiotic prescriptions issued from emergency departments in a large, multicenter health system.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":3.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}