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Objective. To examine the relationship between documented β-lactam allergy and cesarean delivery (CD) surgical site infection (SSI). Study Design. We conducted a retrospective cohort analysis of women who underwent CD at Ben Taub Hospital and Texas Children’s Pavilion for Women (Houston, TX) from August 1, 2011, to December 31, 2019. The primary exposure was a documented β-lactam allergy, and the second exposure of interest was the type of perioperative antibiotic received. The primary outcome was the prevalence of SSI. Maternal characteristics were stratified by the presence or absence of a documented β-lactam allergy, and significance was evaluated using Pearson’s chi-squared test for categorical variables and t -test for continuous variables. A logistic regression model estimated odds of SSI after adjusting for possible confounders. Results. Of the 12,954 women included, 929 (7.2%) had a documented β-lactam allergy while 12,025 (92.8%) did not. Among the 929 women with a β-lactam allergy, 495 (53.3%) received non-β-lactam perioperative prophylaxis. SSI occurred in 38 (4.1%) of women who had a β-lactam allergy versus 238 (2.0%) who did not ( p ≤ 0.001 ). β-Lactam allergy was associated with higher odds of SSI compared to no allergy ( adjusted odds ratio aOR = 1.97 ; 95 % confidence interval CI = 1.24 -3.14; p = 0.004 ) after controlling for age, race, ethnicity, insurance status, delivery body mass index (BMI), tobacco use, intra-amniotic infection in labor, duration of membrane rupture, preterm delivery, delivery indication, diabetes, hypertension, group B Streptococcus colonization, and type of perioperative antibiotic received. Conclusion. The presence of a β-lactam allergy is associated with increased odds of developing a CD SSI after controlling for possible confounders, including the type of perioperative antibiotic received.

BackgroundClostridioides difficile infection (CDI) is a leading cause of health care–associated infection and may result in organ dysfunction, colectomy, and death. Published risk scores to predict severe complications from CDI demonstrate poor performance upon external validation. We hypothesized that building and validating a model using geographically and temporally distinct cohorts would more accurately predict risk for complications from CDI.MethodsWe conducted a multicenter retrospective cohort study of adults diagnosed with CDI. After randomly partitioning the data into training and validation sets, we developed and compared 3 machine learning algorithms (lasso regression, random forest, stacked ensemble) with 10-fold cross-validation to predict disease-related complications (intensive care unit admission, colectomy, or death attributable to CDI) within 30 days of diagnosis. Model performance was assessed using the area under the receiver operating curve (AUC).ResultsA total of 3646 patients with CDI were included, of whom 217 (6%) had complications. All 3 models performed well (AUC, 0.88–0.89). Variables of importance were similar across models, including albumin, bicarbonate, change in creatinine, non-CDI-related intensive care unit admission, and concomitant non-CDI antibiotics. Sensitivity analyses indicated that model performance was robust even when varying derivation cohort inclusion and CDI testing approach. However, race was an important modifier, with models showing worse performance in non-White patients.ConclusionsUsing a large heterogeneous population of patients, we developed and validated a prediction model that estimates risk for complications from CDI with good accuracy. Future studies should aim to reduce the disparity in model accuracy between White and non-White patients and to improve performance overall.

Background Antimicrobial resistance is one of the major public health challenges in Ethiopia. However, there is no comprehensive summary of existing AMR data in the country. Aim To determine the prevalence of antimicrobial resistance and its clinical implications in Ethiopia. Methods A systematic literature search was performed on the PubMed/Medline database. Original studies on antimicrobial resistance conducted in Ethiopia between 1st January 2009 and 31st July 2019 were included. The outcome measure was the number of isolates resistant to antimicrobial agents in terms of specific pathogens, and disease condition. Data was calculated as total number of resistant isolates relative to the total number of isolates per specific pathogen and medication. Results A total of 48,021 study participants enrolled from 131 original studies were included resulting in 15,845 isolates tested for antimicrobial resistance. The most common clinical sample sources were urine (28%), ear, nose, and throat discharge collectively (27%), and blood (21%). All the studies were cross-sectional and 83% were conducted in hospital settings. Among Gram-positive bacteria, the reported level of resistance to vancomycin ranged from 8% (Enterococcus species) to 20% (S. aureus). E. coli, K. pneumoniae and P. aeruginosa were the most common Gram-negative pathogens resistant to key antimicrobial agents described in the national standard treatment guideline and were associated with diverse clinical conditions: urinary tract infections, diarrhea, surgical site infections, pneumonia, ocular infections, and middle ear infections. Conclusion Overall, there is a high prevalence of antimicrobial resistance in Ethiopia. Empirical treatment of bacterial infections needs to be guided by up-to-date national guidelines considering local antimicrobial susceptibility patterns. Equipping diagnostic laboratories with culture and drug susceptibility testing facilities, and establishing a strong antimicrobial stewardship program should be high priorities.

Background Many models have been developed to predict severe outcomes from Clostridioides difficile infection (CDI). These models are usually developed at a single institution and largely are not externally validated. Our aim in this study was to validate previously published risk scores in a multicenter cohort of patients with CDI. Methods This was a retrospective study on 4 inpatient cohorts with CDI from 3 distinct sites: the universities of Michigan (2010–2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive testing. Both within each cohort and combined across all cohorts, published CDI severity scores were assessed and compared to each other and the Infectious Diseases Society of America (IDSA) guideline definitions of severe and fulminant CDI. Results A total of 3646 patients were included for analysis. Including the 2 IDSA guideline definitions, 14 scores were assessed. Performance of scores varied within each cohort and in the combined set (mean area under the receiver operator characteristic curve [AuROC], 0.61; range, 0.53–0.66). Only half of the scores had performance at or better than IDSA severe and fulminant definitions (AuROCs of 0.64 and 0.63, respectively). Most of the scoring systems had more false than true positives in the combined set (mean, 81.5%; range, 0%–91.5%). Conclusions No published CDI severity score showed stable, good predictive ability for adverse outcomes across multiple cohorts/institutions or in a combined multicenter cohort.

Background: Although people who smoke cigarettes are overrepresented among hospital inpatients, few are connected with smoking cessation treatment during their hospitalization. Training, accountability for medication use, and monitoring of all patients position pharmacists well to deliver cessation interventions to all hospitalized patients who smoke. Methods: A large Midwestern University hospital implemented a pharmacist-led smoking cessation intervention. A delegation protocol for hospital pharmacy inpatients who smoked cigarettes gave hospital pharmacists the authority to order nicotine replacement therapy (NRT) during hospitalization and upon discharge, and for referral to the Wisconsin Tobacco Quit Line (WTQL) at discharge. Eligible patients received the smoking cessation intervention unless they actively refused (ie, “opt-out”). The program was pilot tested in phases, with pharmacist feedback between phases, and then implemented hospital-wide. Interviews, surveys, and informal mechanisms identified ways to improve implementation and workflows. Results: Feedback from pharmacists led to changes that improved workflow, training and patient education materials, and enhanced adoption and reach. Refining implementation strategies across pilot phases increased the percentage of eligible smokers offered pharmacist-delivered cessation support from 37% to 76%, prescribed NRT from 2% to 44%, and referred to the WTQL from 3% to 32%. Conclusion: Hospitalizations provide an ideal opportunity for patients to make a tobacco quit attempt, and pharmacists can capitalize on this opportunity by integrating smoking cessation treatment into existing inpatient medication reconciliation workflows. Pharmacist-led implementation strategies developed in this study may be applicable in other inpatient settings.

Objective:Influenza can be introduced and propagated in healthcare settings by healthcare workers (HCWs) working while ill with influenza. However, reasons driving this behavior are unclear. In this study, we examined barriers to and facilitators of absenteeism during the influenza season.Design:Cross-sectional mixed methods study.Setting:Ambulatory and inpatient settings in a large, tertiary-care healthcare system.Methods:An anonymous electronic survey was sent to HCWs between June 11 and July 13, 2018, asking participants to self-report influenza-like illness (ie, ILI symptoms of fever, chills, cough, or sore throat) during the 2017–2018 influenza season. We conducted a logistical regression analysis to identify factors associated with absenteeism.Results:Of 14,250 HCWs, 17% responded to the survey. Although 1,180 respondents (51%) reported symptoms of ILI, 575 (43%) did not stay home while ill. The most commonly perceived barriers to ILI absenteeism included being understaffed (odds ratio [OR], 1.78; P = .04), unable to find a replacement for work (OR, 2.26; P = .03), desiring not to use time off (OR, 2.25; P = .003), and paid by the hour or unable to afford being absent (OR, 2.05; P = .02). Common perceived facilitators of absenteeism included support from coworkers and management, clearer policy, better sick days availability, and lower perceived threat of disciplinary action.Conclusions:Reporting to work with ILI symptoms is common among HCWs. Most barriers and facilitators are related to systems. Addressing system factors, such as policies regarding sick days and sick leave and ensuring adequate backup staffing, is likely to facilitate absenteeism among ill HCWs.

BackgroundClostridioides difficile infection (CDI) is a leading cause of healthcare-associated infections and may result in organ dysfunction, colectomy, and death. We recently showed that published risk scores to predict severe complications from CDI demonstrate poor performance upon external validation. We hypothesized that building and validating a model using geographically and temporally distinct cohorts would more accurately identify patients at risk for complicated CDI.MethodsWe conducted a multi-center retrospective cohort study of adult subjects diagnosed with CDI in the US. After randomly partitioning the data into training/validation set, we developed and compared three machine learning algorithms (Lasso regression, random forest, stacked ensemble models) with 10-fold cross-validation that used structured EHR data collected within 48 hours of CDI diagnosis to predict disease-related complications from CDI (intensive care unit admission, colectomy, or death attributable to CDI within 30 days of diagnosis). Model performance was assessed using area under the receiver operating curve (AUC).ResultsA total of 3,762 patients with CDI were included of which 218 (5.8%) had complications. Lasso regression, random forest, and stacked ensemble models all performed well with AUC ranging between 0.89-0.9. Variables of importance were similar across models, including albumin, bicarbonate, change in creatinine, systolic blood pressure, non-CDI-related ICU admission, and concomitant non-CDI antibiotics. Sensitivity analyses indicated that model performance was robust even when varying derivation cohort inclusion and CDI testing approach.ConclusionUsing a large heterogeneous population of patients, we have developed and validated a prediction model based on structured EHR data that accurately estimates risk for complications from CDI.Key PointsMachine learning models using structured electronic health records can be leveraged to accurately predict risk of severe complications related to Clostridiodes difficile infection, including intensive care unit admission, colectomy, and/or death.

To examine the relationship between documentedOf the 12,954 women included, 929 (7.2%) had a documentedThe presence of a

To assess the clinical epidemiology and outcomes of patients hospitalized with COVID-19 who did not experience fever and cough during the early pandemic.Retrospective cohort of all patients admitted during March 13, 2020 through May 13, 2020 with laboratory-confirmed COVID-19 to 3 tertiary-care hospitals. Patient-level data (demographic, clinical manifestations, comorbid illnesses, inpatient treatment) were analyzed. The main outcome variable was atypical presentation, defined as any hospitalized patient with COVID-19 infection who did not experience both fever and cough. We identified risk factors for atypical presentation on univariate and multivariate analyses and assessed 30-day mortality differences via survival analysis.Of 163 patients in the study, 39 (24%) were atypical. On univariate analysis, atypical cases were significantly more likely to be older, reside in a long-term-care facility (LTCF), and have underlying diabetes mellitus, stroke, or cardiac disease; present without dyspnea or myalgia, have lower C-reactive proteins (CRP) and higher beta-natriuretic peptides. They were less likely to receive intensive care unit care or specific COVID-19 treatments (During the first pandemic surge, COVID-19 patients without inflammatory signs and symptoms were more likely to be LTCF residents and had higher mortality. Timely recognition of these atypical presentations may have prevented spread and improved clinical outcomes.

We aimed to apply the Systems Engineering Initiative for Patient Safety (SEIPS) model to increase effectiveness and sustainability of the World Health Organization’s (WHOs) hand hygiene (HH) guidelines within healthcare systems. Our cross-sectional, mixed-methods study took place at Jimma University Medical Center (JUMC), a tertiary care hospital in Jimma, Ethiopia, between November 2018 and August 2020 and consisted of three phases: baseline assessment, intervention, and follow-up assessment. We conducted questionnaires addressing HH knowledge and attitudes, interviews to identify HH barriers and facilitators within the SEIPS framework, and observations at the WHO’s 5 moments of HH amongst healthcare workers (HCWs) at JUMC. We then implemented HH interventions based on WHO guidelines and results from our baseline assessment. Follow-up HH observations were conducted months later during the Covid-19 pandemic. 250 HCWs completed questionnaires with an average knowledge score of 61.4% and attitude scores indicating agreement that HH promotes patient safety. Interview participants cited multiple barriers to HH including shortages and location of HH materials, inadequate training, minimal Infection Prevention Control team presence, and high workload. We found an overall baseline HH compliance rate of 9.4% and a follow-up compliance rate of 72.1%. Drastically higher follow-up compared to baseline compliance rates were likely impacted by our HH interventions and Covid-19. HCWs showed motivation for patient safety despite low HH knowledge. Utilizing the SEIPS model helped identify institution-specific barriers that informed targeted interventions beyond WHO guidelines aimed at increasing effectiveness and sustainability of HH efforts.

To determine barriers and facilitators to standardization of ultrasound probe disinfection at ambulatory sites, we conducted observations and interviews of staff. Variability was noted in disinfection practices and in the use of protective equipment even for procedures with the potential for the probe to contact sterile tissues. Standardization is needed.

BACKGROUND Community-onset Clostridium difficile infections (CDI) are increasingly common, but there is little data on outcomes. The purpose of this study is to describe the epidemiology and outcomes of CDI in the Veterans Health Administration (VHA) system and compare these variables between hospital-onset (HCF) and community-onset (CO) cases. METHODS We conducted a retrospective cohort study that included all patients with a positive test for C. difficile (toxin or toxin genes) within the VHA Corporate Data Warehouse between 2011 and 2014. RESULTS We identified 19270 episodes of CDI, involving 15972 unique patients; 95% were male, 44% of the cases were HCF, and 42% were CO. Regarding severity, 31% percent of cases were non-severe, 40% were severe, and 21% were fulminant. Exposure to proton pump inhibitors was found in 53% of cases (47% in CO, 62% in HCF). Overall, 40% of patients received antibiotics in the 90 days before CDI (44% in HCF, 36% in CO). Recurrence was 18.2%, and 30-day all-cause mortality was 9.2%. Risk factors for a fulminant case were exposure to clindamycin (odds ratio [OR]: 1.23, P = .01) or proton pump inhibitors (OR: 1.20, P < .001) in the 90 days prior to diagnosis. CONCLUSIONS CO accounts for a significant proportion of CDI in the VHA system. CO patients are younger and their cases are less severe, but recurrence is more common than in HCF CDI. Therefore CO CDI may account for a considerable reservoir of CDI cases, and prevention efforts should include interventions to reduce CO CDI.

Background The objective of this study was to investigate risk factors for multidrug-resistant organism (MDRO) infection within patients from a tertiary care hospital in Northern India. This case-control study examined MDRO infection risk factors, including diet, health history, and medical device use. We administered a diet questionnaire to collect data on usual diet and collected data on other risk factors from chart review. All participants were inpatients identified through hospital microbiology reports. A total of 39 MDRO patient cases and 91 controls were included. Methods Descriptive statistics, univariate analysis, and multivariate logistic regression were performed to evaluate the association between risk factors and MDRO infection. Results All cases had gram-negative MDRO infections. Univariate analyses found length of hospital stay, connective tissue disease, hospitalization in the last 12 months, hospitalization of a family member, in-hospital antibiotic use, antibiotic use in the last 12 months, and feeding tube, central venous line, and urinary catheter use to be significantly different between cases and controls. Logistic regression showed a >3-fold increase in the odds of infection with antibiotic use in the last 12 months (odds ratio [OR], 3.30; 95% confidence interval [CI], 1.22-8.91) and urinary catheter use (OR, 3.63; 95% CI, 1.14-11.58). Differences in dietary preferences and fruit, vegetable, and fiber consumption were not significantly associated with infection. Conclusions Antibiotic use is a major driver of MDRO infections. Our findings suggest that interventions optimizing antibiotic stewardship and reducing device use should be a priority to prevent MDRO infections.

There is a need for new, targeted smoking cessation interventions for smokers living with HIV. The Information-Motivation-Behavioral Skills (IMB) model has been applied effectively to HIV-related health behaviors and was used in this qualitative study to elicit factors that could lead to the development of innovative and successful cessation interventions for this population. Twenty individuals who smoked from two clinics providing care to people living with HIV participated in open-ended interviews, responding to questions covering the domains of the IMB model, as applied to smokers living with HIV. Participants were enrolled from a larger survey cohort to recruit into groups based on the impact of HIV diagnosis on smoking as well as attempting to enroll a mix of demographics characteristics. Interviews were recorded, transcribed, coded and thematically analyzed using a grounded theory qualitative approach. Interviews continued until thematic saturation was reached. Major themes included: Presence of knowledge deficits regarding HIV-specific health risks of smoking; use of smoking for emotional regulation, where many reported close contacts who smoke and concern with the effect of cessation on their social networks; Use of smoking cessation aids or a telephone-based wellness intervention were acceptable to most. Providing HIV-specific information in cessation advice is of the utmost importance for clinicians caring for smokers living with HIV, as this theme was noted consistently as a potential motivator to quit. Innovative and effective interventions must account for the social aspect of smoking and address other methods of emotional regulation in this population.

Background Fever and cough are frequently reported in COVID-19 infections, although little is known about the subgroup of symptomatic patients who do not manifest these classic symptoms. We aimed to compare clinical manifestations and outcomes for hospitalized COVID-19 patients with typical vs. atypical presentations and identify risk factors for atypical COVID-19 presentations. Methods We conducted a retrospective cohort of all patients hospitalized with laboratory-confirmed COVID-19 infections during 3/13- 5/13/2020 at UW Health, a network of 3 acute-care hospitals in Midwest. We defined atypical cases as patients hospitalized for COVID-19 related reasons presenting without fever and cough and compared them in univariate analysis with patients manifesting both symptoms (controls). We identified independent risk factors for atypical COVID-19 presentations by logistic regression. Results Among the 163 patients hospitalized during the 60-day study frame, 39 (24%) had atypical presentations. Table 1 shows demographic, clinical manifestations, and outcomes of atypical vs. typical cases. On univariate analysis, atypical cases were more likely to be older, reside in a long-term-care facility (LTCF), have underlying diabetes mellitus, stroke, cardiac disease, and deny myalgias or dyspnea, despite having no significant difference in the prevalence of hypoxia or radiological lung infiltrates. Atypical cases also had a significantly higher Beta-Natriuretic-Peptide and lower C-Reactive-Protein, although other inflammatory markers were not significantly different. They were less likely to be admitted to the ICU, and more likely to die within 30 days, as older patients with respiratory failure and multiple comorbidities opted for comfort measures and less aggressive care. On multivariate analysis, LTCF residence was the only independent predictor for atypical status (Table 2). Conclusion LTCF residents are more likely to experience COVID-19 respiratory illness (hypoxia, pneumonia) without classic symptoms (fever, cough, myalgias, dyspnea). Given the excessive pandemic burden in the LTCF setting, timely recognition and diagnosis of these atypical, more subtle presentations is critical. Disclosures All Authors: No reported disclosures

Background: Children attending daycare are at increased risk of carrying multidrug-resistant organisms (MDROs) compared to children not attending daycare. Carriage of MDROs greatly increases the risk of infection, not only in the child but also for others living in the household. Understanding the epidemiology of MDRO carriage in children is essential to devising effective containment strategies. Here, we present the findings from a cross-sectional study assessing MDRO carriage in daycare-attending and nonattending children in Wisconsin. Methods: We applied the following enrollment criteria: Children aged between 6 months and H. influenzae, S. pneumoniae, M. catarrhalis, and methicillin-resistant S. aureus (MRSA). Skin samples were cultured for MRSA, and stool samples were cultured for MRSA, C. difficile, vancomycin-resistant enterococci (VRE), and extended-spectrum β-lactamase–producing Gram-negative bacilli (ie, ESBL GNR). Results: In total, 44 children were enrolled in this study. The average age was 2.6 years and 50% were girls. Furthermore, 30 (68.2%) were identified by their parents as white, 9 (20.5%) as black, and 5 (11.3%) as other or multiracial. Incidentally, 23 children (52.3%) were enrolled in daycare. Overall, 18 children were positive for at least 1 organism, 9 of which had daycare exposure, and 5 children (1 in daycare) were positive for >1 organism (11.4%). From stool samples, 6 children (13.6%, 2 in daycare) were C. difficile carriers, 3 were VRE carriers (6.8%, 1 in daycare), 8 carried an ESBL GNR (18.2%, 4 in daycare), and 3 carried MRSA (6.8%, 1 in daycare). One child was positive for H. influenzae (2.3%, not in daycare) and 2 were positive for S. pneumoniae (4.6%, 1 in daycare) from nares swabs. One child was positive for MRSA (2.3%, not in daycare) from a skin swab. We detected no significant differences between children with and without daycare exposure for any organism. Conclusions: Children in this population had higher than expected rates of ESBL GNRs and MRSA for a community population. Daycare exposure was not correlated with increased carriage in this small pilot study, though larger longitudinal studies are needed.Funding: NoneDisclosures: None

Objective Complications of intravenous catheters remain a major contributor to health care costs and are a patient safety problem. An intravenous catheter not actively in use—an idle catheter—may increase the risk of infectious and noninfectious complications. We conducted an integrative review of the available literature to evaluate the prevalence, risk factors, and outcomes associated with idle intravenous catheters. Methods Searches of multiple computerized databases were conducted to identify studies on idle intravenous catheters. Data on definitions of idle catheter, type of catheter, prevalence, risk factors, and patient outcomes were extracted. Results Thirteen studies met inclusion criteria and were included in the review. The location and setting of the studies were diverse, including cross-sectional, retrospective, and prospective, and were conducted in varied geographic locations. The definition of an idle catheter was variable across studies. Although studies varied in terms of line-days or number of catheters placed, the primary definition of idle device was based on number of days or percent of devices left in situ without use. Four studies evaluated patient outcomes associated with idle catheters and found increased risk of infection, intensive care unit admission, and phlebitis. Conclusions Idle intravenous catheters are common and are associated with adverse outcomes. Prospective studies incorporating uniform definitions of idle catheters to test interventions to reduce idle catheter use are urgently needed.

Background: In the state of Wisconsin, 3%–4% of bats submitted for rabies testing are positive. Inpatient bat encounters at 2 affiliated healthcare facilities at nearly the same time were brought to the attention of the infection prevention and control (IPC) team. The first bat was captured in a patient room and was submitted for testing. Postexposure prophylaxis (PEP) was initiated for 1 patient before the bat testing results came back negative. The second bat was found in a transplant unit hallway and was released before we could request testing. We observed significant variations in responses, including decision to administer PEP and submission of bats for rabies testing. The IPC team developed a protocol to minimize unnecessary PEP, to prevent nosocomial rabies infection from bat exposure, and to limit associated panic. Methods: A systematic literature review of multiple databases was performed. A search of nonscientific articles using Google was also performed to assess unpublished inpatient bat encounters. A workgroup was established including IPC staff, physicians, and facilities management. The county animal services department and the state public health department veterinarian were consulted to aid in development of a protocol. Results: Literature review yielded a single report of a bat discovered in a neonatal intensive care unit (NICU). A lack of protocol resulted in PEP administration to 7 neonates without observed exposure after the bat was released instead of being submitted for testing. Of the first 100 articles retrieved via Google search of “bat in hospital,” 9 pertained to nosocomial discovery of bats in 5 different states over the past 7 years. Encounters included infestations requiring unit shutdowns and PEP administration. One tertiary-care referral center reported 10 encounters per year but did not elaborate on associated procedures. The county animal services staff assisted in training maintenance and engineering services (MES) personnel on how to secure bats for testing and helped develop a “bat kit” with protective gear and equipment to do so safely. In the new protocol, an inpatient bat encounter prompts personnel to capture the bat and begin an investigation into known or potential occult exposure. Known or potential exposures merit submission of the bat for rabies testing, the results of which guide PEP recommendations. All encounters are investigated for point of entry or roost. Conclusions: Inpatient bat encounters are not uncommon. Encounters should prompt systematic assessment for exposures and an investigation of the root cause. Following a protocol may limit unnecessary PEP administration, prevent nosocomial transmission of rabies from bat to patient, and attenuate associated anxiety.Funding: NoneDisclosures: None

Background Lack of hand hygiene (HH) amongst healthcare workers (HCWs) contributes to healthcare associated infections and the spread of multidrug-resistant organisms. We assessed HCW HH knowledge, attitudes, and compliance using WHO tools and applied the Systems Engineering Initiative for Patient Safety (SEIPS) model in interviews to help guide and increase sustainability of HH interventions. Methods We conducted a cross-sectional study at Jimma University Medical Center (JUMC) in Jimma, Ethiopia. We assessed HCW’s HH knowledge and attitudes using questionnaires adapted from WHO resources via systematic sampling. Observations of HH practices at WHO’s 5 Moments of HH were conducted by non-identified, trained observers via systematic sampling. 22 semi-structured interviews were conducted via convenience sampling with HCWs using an interview guide based on the SEIPS model. Results We observed 1,386 HH moments and found a compliance rate of 9.38%, with compliance highest after contact with patient surroundings (27.92%) compared to the other four HH moments (1.77 - 9.57%). Of 251 survey participants, 13.6% had prior HH training and 69.9% reported routine HH compliance. The average knowledge score was 61.4%, with no significant difference between participants that identified as trained vs untrained (p=0.41). 68% of interview participants stated they were unaware of JUMC’s Infection Prevention and Control (IPC) team and are more likely to perform HH if a patient appears infectious. Interview participants cited multiple barriers to HH (table 1). Table 1 Conclusion Baseline HH compliance and knowledge were low despite perceived compliance and regardless of prior HH training. Relatively higher compliance after patient contact may be due to perceptions of patient infectiousness. Utilizing the SEIPS model as an adjunct to WHO HH guidelines has provided actionable items upon which the JUMC IPC team can focus to improve HH practices: providing a sustainable supply of alcohol hand rub, ongoing HH education targeting knowledge deficits, and enhanced IPC presence and HH monitoring. Disclosures Meredith Kavalier, MD, University of Wisconsin-Madison Global Health Institute (Grant/Research Support)

OBJECTIVEIdentify factors referred to as barriers and facilitators that can prevent or assist safe injection practices in ambulatory care settings to guide quality improvement.DESIGNIn this mixed-methods study, we utilized observations and interviews.SETTINGThis study was conducted at ambulatory clinics at a midwestern academic medical center from May through August 2017. Sites included a variety of clinical settings that performed intramuscular, intradermal, intravenous, or intra-articular injections.PARTICIPANTS AND INTERVENTIONSDirect observations of injections and interviews of ambulatory care staff were conducted. An observation checklist was created, including standards of injection safety from nationally recognized guidelines. Interview questions were developed using the System Engineering Initiative for Patient Safety (SEIPS) model. Interviews were recorded, transcribed, and then coded by 2 investigators.RESULTSIn total, 106 observations and 36 interviews were completed at 21 clinics. Injection safety standards with the lowest adherence included using needleless access devices to prepare injections (33%) and the proper use of multidose vials (CONCLUSIONSPerceived barriers and facilitators to infection control elements of injection safety are interconnected with SEIPS elements of persons, organizations, technologies, tasks, and environment. Direct observations demonstrated that knowledge of safety injection standards does not necessarily translate to best practices and may not match self-reported data.Infect Control Hosp Epidemiol 2018;39:841–848

Background Annually in the US alone, Clostridioides difficile infection (CDI) afflicts nearly 500,000 patients causing 29,000 deaths. Since early and aggressive interventions could save lives but are not optimally deployed in all patients, numerous studies have published predictive models for adverse outcomes. These models are usually developed at a single institution, and largely are not externally validated. This aim of this study was to validate the predictability for severe CDI with previously published risk scores in a multicenter cohort of patients with CDI. Methods We conducted a retrospective study on four separate inpatient cohorts with CDI from three distinct sites: the Universities of Michigan (2010–2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive test. Structured query and manual chart review abstracted data from the medical record at each site. Published CDI severity scores were assessed and compared with each other and the IDSA guideline definition of severe CDI. Sensitivity, specificity, area under the receiver operator characteristic curve (AuROC), precision-recall curves, and net reclassification index (NRI) were calculated to compare models. Results We included 3,775 patients from the four cohorts (Table 1) and evaluated eight severity scores (Table 2). The IDSA (baseline comparator) model showed poor performance across cohorts(Table 3). Of the binary classification models, including those that were most predictive of the primary composite outcome, Jardin, performed poorly with minimal to no NRI improvement compared with IDSA. The continuous score models, Toro and ATLAS, performed better, but the AuROC varied by site by up to 17% (Table 3). The Gujja model varied the most: from most predictive in the University of Michigan 2010–2012 cohort to having no predictive value in the 2016 cohort (Table 3). Conclusion No published CDI severity score showed stable, acceptable predictive ability across multiple cohorts/institutions. To maximize performance and clinical utility, future efforts should focus on a multicenter-derived and validated scoring system, and/or incorporate novel biomarkers. Disclosures All authors: No reported disclosures.