Background:Clostridioides difficile infection (CDI), caused by toxigenic C. difficile and predominately manifested by moderate-to-severe diarrhea, is an important cause of morbidity and mortality in long-term care facilities (LTCFs). However, for CDI to be diagnosed in an LTCF resident, an LTCF resident with diarrhea must have a stool specimen collected for CDI diagnostic testing. The objective of this study was to define the frequency of stool specimen collection and testing for CDI in adult LTCF residents with diarrhea in Louisville, Kentucky. Methods: A cross-sectional study was conducted in 14 (31%) of the 45 LTCFs in Louisville (adults aged ≥18 years; population, 599,276) to identify LTCF residents with diarrhea and to observe the frequency of stool specimen collection for CDI diagnosis. For 14 consecutive days in February 2019, each LTCF was visited to identify new onset diarrhea (≥3 loose stools in 24 hours) by interviews of nursing staff. For residents with diarrhea, staff reviewed electronic medical records to determine whether a stool specimen was collected for CDI diagnosis and interviewed nurses about potential noninfectious causes of diarrhea. Results: The 14 participating LTCFs have 1,208 beds (median, 86 beds and 43 occupied beds per participating LTCF). Among 743 LTCF residents (with 10,402 patient days of surveillance), new-onset diarrhea was identified in 63 residents (21% male; median age 75 years); 0.6 diarrhea cases per 100 patient days (diarrhea attack rate, 0.6% per day). Nurses indicated that 16 (25%) of the 63 residents with diarrhea had a potential noninfectious cause of diarrhea (11 laxatives, 3 feeding tube, 1 colostomy, and 1 gastric surgery). Stool specimens were collected for CDI testing from 20 of 63 of residents (32%) with diarrhea; none with potential noninfectious cause of diarrhea and from 20 of 47 other residents (42%) with diarrhea. Of 20 stool specimens tested, 9 (47%) yielded toxigenic C. difficile (8.6 CDI cases per 10,000 patient days). During this survey, none of the 63 LTCF residents with diarrhea were transferred to a hospital or other healthcare facility. Conclusions: Diarrhea was common among LTCF residents, and toxigenic C. difficile was frequently identified in stool specimens collected from LTCF residents with diarrhea. The majority of non–laxative-receiving LTCF residents with diarrhea did not have a stool specimen collected for CDI diagnosis. The low frequency of CDI diagnostic testing of LTCF residents with diarrhea indicates that CDI may be underdiagnosed in these LTCFs and suggests that the CDI disease burden may be larger than currently appreciated.

Funding: Pfizer Vaccines provided support for this study.

Disclosures: Frederick Angulo, Kimbal D. Ford, Joann Zamparo, Elisa Gonzalez, Sharon Gray, David Swerdlow, and Catia Ferreira all report salary from Pfizer.

Background: Hand hygiene (HH) has long been a focus in the prevention of healthcare-associated infections. The limitations of direct observation, including small sample size (often 20–100 observations per month) and the Hawthorne effect, have cast doubt on the accuracy of reported compliance rates. As a result, hospitals are exploring the use of automated HH monitoring systems (AHHMS) to overcome the limitations of direct observation and to provide a more robust and realistic estimation of HH behaviors. Methods: Data analyzed in this study were captured utilizing a group-based AHHMS installed in a number of North American hospitals. Emergency departments, overflow units, and units with <1 year of data were excluded from the study. The final analysis included data from 58 inpatient units in 10 hospitals. Alcohol-based hand rub and soap dispenses HH events (HHEs) and room entries and exits (HH opportunities (HHOs) were used to calculate unit-level compliance rates. Statistical analysis was performed on the annual number of dispenses and opportunities using a mixed effects Poisson regression with random effects for facility, unit, and year, and fixed effects for unit type. Interactions were not included in the model based on interaction plots and significance tests. Poisson assumptions were verified with Pearson residual plots. Results: Over the study period, 222.7 million HHOs and 99 million HHEs were captured in the data set. There were an average of 18.7 beds per unit. The average number of HHOs per unit per day was 3,528, and the average number of HHEs per unit per day was 1,572. The overall median compliance rate was 35.2 (95% CI, 31.5%–39.3%). Unit-to-unit comparisons revealed some significant differences: compliance rates for medical-surgical units were 12.6% higher than for intensive care units (P < .0001). Conclusions: This is the largest HH data set ever reported. The results illustrate the magnitude of HHOs captured (3,528 per unit per day) by an AHHMS compared to that possible through direct observation. It has been previously suggested that direct observation samples between 0.5% to 1.7% of all HHOs. In healthcare, it is unprecedented for a patient safety activity that occurs as frequently as HH to not be accurately monitored and reported, especially with HH compliance as low as it is in this multiyear, multicenter study. Furthermore, hospitals relying on direct observation alone are likely insufficiently allocating and deploying valuable resources for improvement efforts based on the scant information obtained. AHHMSs have the potential to introduce a new era in HH improvement.

Funding: GOJO Industries, Inc., provided support for this study.

Disclosures: Lori D. Moore and James W. Arbogast report salary from GOJO.

Background: The CDC recommends that consultant pharmacists support antimicrobial stewardship programs (ASPs) in long-term care facilities (LTCFs). We studied CDC-recommended ASP core elements implementation and antibiotic use in LTCFs before and after training consultant pharmacists. Methods: Between August 2017 and October 2017, consultant pharmacists from a regional long-term care pharmacy attended 5 didactic sessions preparing them to assist LTCFs in implementation of CDC-recommended ASP core elements. Training also included creating a process for evaluating appropriateness of all systemic antibiotics and providing prescriber feedback during their monthly mandatory drug-regimen reviews. Once monthly “meet-the-expert” sessions were held with consultant pharmacists throughout the project (November 2017 to December 2018). LTCF enrollment began in November 2017 and >90% of facilities joined by January 2018. After enrollment, consultant pharmacists initiated ASP interventions including antibiotic reviews and feedback using standard templates. They also held regular meetings with infection preventionists to discuss Core Elements implementation and provided various ASP resources to LTCFs (eg, antibiotic policy template, guidance documents and standard assessment and communication tools). Data collection included ASP Core Elements, antibiotic starts, days of therapy (DOT), and resident days (RD). The McNemar test, the Wilcoxon signed-rank test, generalized estimating equation model, and the classic repeated measures approach were used to compare the presence of all 7 core elements and antibiotic use during the baseline (2017) and intervention (2018) year.Results: In total, 9 trained consultant pharmacists assisted 32 LTCFs with ASP implementation. When evaluating 27 LTCFs that provided complete data, a significant increase in presence of all 7 Core Elements after the intervention was noted compared to baseline (67% vs 0; median Core Elements, 7 vs 2; range, 6–7 vs 1–6; P < .001). Median monthly antibiotic starts per 1,000 RD and DOT per 1,000 RD decreased in 2018 compared to 2017: 8.93 versus 9.91 (P < .01) and 106.47 versus 141.59 (P < .001), respectively. However, variations in antibiotic use were detected among facilities (Table 1). When comparing trends, antibiotic starts and DOT were already trending downward during 2017 (Fig. 1A and 1B). On average, antibiotic starts decreased by 0.27 per 1,000 RD (P < .001) and DOT by 1.92 per 1,000 RD (P < .001) each month during 2017. Although antibiotic starts remained mostly stable in 2018, DOT continued to decline further (average monthly decline, 2.60 per 1,000 RD; P < .001). When analyzing aggregated mean, antibiotic use across all sites per month by year, DOT were consistently lower throughout 2018 and antibiotic starts were lower for the first 9 months (Fig. 1C and 1D). Conclusions: Consultant pharmacists can play an important role in strengthening ASPs and in decreasing antibiotic use in LTCFs. Educational programs should be developed nationally to train long-term care consultant pharmacists in ASP implementation.

Funding: Merck & Co., Inc, provided funding for this study.

Disclosures: Muhammad Salman Ashraf and Scott Bergman report receipt of a research grant from Merck.

Background: Hand hygiene by healthcare personnel is a critical infection prevention intervention. Direct observation, the most widely utilized method to observe hand hygiene practices, often provides an incomplete picture due to small sample size and altered behavior in the presence of observers. A growing number of healthcare facilities are employing electronic hand hygiene monitoring systems to capture overall compliance rates. These electronic systems can provide a wealth of data on hand hygiene practices within and across healthcare facilities. Objective: We used high-accuracy electronic monitoring data to perform a detailed analysis of hand hygiene practices across numerous facilities that varied in key hospital characteristics. Methods: In total, 11 tertiary-care facilities were equipped with an electronic hand hygiene monitoring system. Hospitals varied in size, region, area classification (urban vs rural), acuity level, and teaching status. The electronic monitoring system was composed of uniquely assigned employee badges and electronically monitored dispensers. Every recorded dispensing event was time stamped and associated with a specific healthcare worker, the location of the dispenser, and the specific product being dispensed (ie, alcohol-based hand rub [ABHR] or hand soap). The total number of dispensing events for each product type and the total number of hours worked were calculated for each healthcare worker and were used to determine hand hygiene frequency. Hospital attributes, such as size and area classification, were obtained from publicly available sources including but not limited to facility-owned websites and CMS data. Results: More than 15.7 million hand hygiene events, performed by nearly 11,000 healthcare workers, were captured by the electronic monitoring system and were included in the analysis. Overall, median hand hygiene frequency was 4.1 events per hour and ranged from 2.0 events per hour to 5.6 events per hour, depending on the facility. ABHR use (median, 3.6 events per hour) was more frequent than handwashing (median, 0.4 events per hour). Hospitals included in the analysis ranged from small (<20 beds) rural facilities to large (>600 beds) academic hospitals and provided a variety of services from general medical-surgical treatment to intensive care. Interfacility differences in observed hand hygiene frequency were analyzed. Conclusions: The current analysis reinforces and builds upon previous work that examined a smaller subset of 5 hospitals located in a single geographic region. Combined, these datasets represent >20 million hand hygiene events among ∼15,000 healthcare workers from 16 unique healthcare facilities. This analysis provides detailed information about hand hygiene practices across a diverse set of healthcare facilities.

Funding: Ecolab, Inc, provided support for this study.

Disclosures: Jessica Carol Albright and Cheryl A Littau report salary from Ecolab.

Background: Antimicrobials are used on dairy farms for preventing disease and treating common infections such as mastitis. Objective: We aimed to understand farmworker practices that potentially contribute to transmission of antimicrobial resistance bacteria and their genes (ARG) among animals and farm workers, and to identify human behavioral interventions to reduce risk. Methods: Focus groups with farm workers were held at 8 dairy farms across Wisconsin selected to represent a range of antibiotic use in cattle. We explored the nature of potentially high-risk practices and farm-worker knowledge and experiences with antibiotic use and resistance. Farm workers were asked to describe common tasks, including hand hygiene and eating practices, and the policies guiding these practices. Focus groups were conducted in English and Spanish guided by the Systems Engineering in Patient Safety (SEIPS) framework, adapted for an agricultural context. Discussions were recorded, transcribed, and translated. A content analysis was conducted to identify themes. Dedoose version 8.0.35 software was used to organize the data. Results: In total, 10 focus groups were conducted on 8 farms. Knowledge of when to use antibiotics for human health varied; upset stomach, headache, and flu symptoms were suggested as appropriate uses. Few workers had personal experience with antibiotic resistance at home or on the farm. Some displayed knowledge of the role of antibiotic stewardship in preventing the spread of ARG (“I guess all dairy farmers have a responsibility not to overdo it”). Others associated the risk of spread with the consumption of raw milk or meat from cows receiving antibiotics. Knowledge of personal protective equipment was stronger among workers who commonly reported glove use. Some perceived glove use to be mandatory, and others chose to wear gloves in the perceived absence of written rules. Some workers reported changing gloves numerous times throughout the day, and others did so less frequently or “only when they rip.” In general, hand hygiene practices are guided by individual knowledge of established rules, beliefs about risk, and personal discretion. Conclusions: Knowledge about mechanisms of spread of ARGs varies among workers on Wisconsin dairy farms and reflects a combination of farm-level rules, experience, individual knowledge, and beliefs. Applying knowledge from the healthcare setting to reduce ARG spread into agriculture is crucial to the tenets of One Health. Programs to reduce ARG spread on dairy farms should focus on proper hand hygiene and PPE use at the level of knowledge, beliefs, and practices.

Funding: Funding: was provided by the USDA-NIFA Food Safety Challenge (grant no. 2017-68003-26500).

Disclosures: None

Background: Infection prevention and control (IPC) workflows are often retrospective and manual. New tools, however, have entered the field to facilitate rapid prospective monitoring of infections in hospitals. Although artificial intelligence (AI)–enabled platforms facilitate timely, on-demand integration of clinical data feeds with pathogen whole-genome sequencing (WGS), a standardized workflow to fully harness the power of such tools is lacking. We report a novel, evidence-based workflow that promotes quicker infection surveillance via AI-assisted clinical and WGS data analysis. The algorithm suggests clusters based on a combination of similar minimum inhibitory concentration (MIC) data, timing of sample collection, and shared location stays between patients. It helps to proactively guide IPC professionals during investigation of infectious outbreaks and surveillance of multidrug-resistant organisms and healthcare-acquired infections. Methods: Our team established a 1-year workgroup comprised of IPC practitioners, clinical experts, and scientists in the field. We held weekly roundtables to study lessons learned in an ongoing surveillance effort at a tertiary care hospital—utilizing Philips IntelliSpace Epidemiology (ISEpi), an AI-powered system—to understand how such a tool can enhance practice. Based on real-time case discussions and evidence from the literature, a workflow guidance tool and checklist were codified. Results: In our workflow, data-informed clusters posed by ISEpi underwent triage and expert follow-up analysis to assess: (1) likelihood of transmission(s); (2) potential vector(s) identity; (3) need to request WGS; and (4) intervention(s) to be pursued, if warranted. In a representative sample (spanning October 17, 2019, to November 7, 2019) of 67 total isolates suggested for inclusion in 19 unique cluster investigations, we determined that 9 investigations merited follow-up. Collectively, these 9 investigations involved 21 patients and required 115 minutes to review in ISEpi and an additional 70 minutes of review outside of ISEpi. After review, 6 investigations were deemed unlikely to represent a transmission; the other 3 had potential to represent transmission for which interventions would be performed. Conclusions: This study offers an important framework for adaptation of existing infection control workflow strategies to leverage the utility of rapidly integrated clinical and WGS data. This workflow can also facilitate time-sensitive decisions regarding sequencing of specific pathogens given the preponderance of available clinical data supporting investigations. In this regard, our work sets a new standard of practice: precision infection prevention (PIP). Ongoing effort is aimed at development of AI-powered capabilities for enterprise-level quality and safety improvement initiatives.

Funding: Philips Healthcare provided support for this study.

Disclosures: Alan Doty and Juan Jose Carmona report salary from Philips Healthcare.

Background: Effective hand hygiene (HH) is an essential preventative measure for the reduction of hospital-acquired infections (HAIs). Commonly used HH products include alcohol-based hand rubs (ABHRs), antimicrobial soaps, and nonantimicrobial soaps. In vivo clinical studies have demonstrated that levels of bacterial reduction can vary based on the HH product type, formulation, and dose. It has been reported that ABHRs provide the greatest reduction in bacteria, followed by antimicrobial soaps. Objective: We examined the effects of products representative of 3 HH categories on artificially soiled hands, using a hand-stamp procedure. The hand-stamp images provide a clear visualization of product effectiveness and can be used as an educational tool to promote the importance of proper hand hygiene using different product formats. Method: Three commercially available formulations were evaluated in this study, a mild nonantimicrobial soap, an antimicrobial soap containing chloroxylenol (PCMX), and an ABHR containing 70% v/v ethanol. Prior to the hand stamp procedure, the participant’s hands were prewashed with 5 mL of a nonantimicrobial soap and dried. An inoculum of Serratia marcescens containing ∼1 × 109CFU/mL was prepared as described in ASTM E2755. A 0.2-mL aliquot of the inoculum was dispensed onto the palm of the subject’s hand and spread by rubbing over the entire surface of both hands. Following a 30-second dry time, one of the subject’s hands was gently pressed onto the surface of a large petri dish containing tryptic soy agar to obtain a baseline image. Following the baseline sample, 1 pump of the selected test product (∼0.9 mL for soap or 1.1 mL for ABHR) was applied to the participant’s hands. For soap applications, hands were vigorously rubbed for 30 seconds followed by a 30-second water rinse. For ABHR, product was rubbed by the user until dry. The hand-stamp procedure was repeated following product application using the participant’s other hand. Results: Clear qualitative reductions in bacteria were observed with each of the HH interventions. The greatest reduction was observed following the application of ABHR. Antimicrobial soap was less effective than ABHR but more effective than nonantimicrobial soap. Conclusions: The qualitative visual model demonstrates the effectiveness of various HH interventions and correlates with log reductions observed in traditional efficacy test methods. Future efforts should explore hand-stamp repeatability and image utilization to support HH improvement efforts in healthcare systems.

Funding: GOJO Industries provided support for this study.

Disclosures: Mary Rose Czaplicki reports salary from GOJO Industries.

Background:Clostridiodes difficile infection is considered an urgent antibiotic resistance threat by the CDC, accounting for ∼225,000 hospitalizations, 12,800 deaths, and ∼$1 billion in healthcare costs in the United States in 2017. The presence of the secreted toxins that cause the devastating symptoms of this gastrointestinal infection are diagnostic of C. difficile infection (CDI). However, the rapid testing methods currently used to detect CDI lack accuracy. Enzyme immunoassays are specific but lack sensitivity because they do not detect CDI patients that have low levels of the toxins. Nucleic acid amplification tests (NAATs) are sensitive, but they lack specificity because they detect patients colonized with C. difficile in the dormant spore form that does not produce the toxins. This insufficiency has resulted in the adoption of complex multitest algorithms for C. difficile diagnosis. We present results for a new toxin test that demonstrates both high clinical sensitivity and clinical specificity for C. difficile toxin B on a fully automated benchtop platform. Methods: The detection technology uses nonmagnified digital imaging to count single toxin molecules that tether together target-specific magnetic and fluorescent particles. The 30-minute method includes the use of a dye cushion to eliminate wash steps and the need for time-consuming specimen preparation steps. We determined analytical performance characteristics of the test using negative clinical stool samples spiked with purified toxin. To assess clinical performance, we tested 785 stool samples from 5 clinical sites and compared the results with the cellular cytotoxicity neutralization assay (CCNA). Results: The test’s limit of detection for toxin B was 60 pg/mL. A comparison of the new test to the CCNA reference method gave 98% positive percentage agreement (83 of 85 samples) and 95% negative percentage agreement (667 of 700 samples). Conclusions: The new method demonstrated 96% accuracy compared to the gold standard for C. difficile toxin tests. The results also demonstrate an analytical sensitivity (limit of detection, 60 pg/mL). Thus, the test has the potential to detect CDI patients missed by enzyme immunoassay (EIA) tests due to their low analytical sensitivity. Because the test detects toxins directly, it is expected to have a lower false-positive rate than NAAT methods, which detect patients colonized with the non–toxin-producing spore form. A single accurate test for toxin-producing C. difficile could eliminate the need for multitest algorithms.

Funding: First Light Diagnostics, Inc., provided support for this study.

Disclosures: Donald Straus reports that he is the founder and chief scientific officer of First Light Diagnostics (FLDx) with salary and ownership interest in the form of stocks, stock options, and warrants. Adam Williams reports salary from First Light Diagnostics.

Background: Technology and interest for use of automated hand hygiene monitoring systems (AHHMS) as a tool to help improve healthcare personnel hand hygiene has been advancing for the last decade. Emerging evidence indicates that the use of AHHMS plus complementary strategies improves hand hygiene (HH) performance rates and outcomes (eg, healthcare-associated infections). The WHO HH guideline “Multimodal Strategy” teaches the importance of multiple components as necessary to build and sustain HH compliance. Few published data compare the impact of different complementary behavioral strategies in combination with AHHMS on results. Methods: We utilized data from 1 AHHMS that records alcohol-based hand rub and soap dispensing and room entries and exits to provide group HH performance rates. Data were collected from 58 units in 10 hospitals in North America from July 2014 through August 2019. Hospitals were stratified into 4 categories based on their approach to hospital-initiated unit-level interventions and AHHMS vendor support (Table 1). Baseline data were defined for each unit as the initial 1–2 months of execution, before complementary strategies were initiated. Statistical analysis was performed on the annual number of dispenses and opportunities with a mixed-effects Poisson regression with random effects for facility, unit and year and fixed effects for intervention type and unit type. Interactions were not included in the model based on interaction plots and significance tests. Poisson assumptions were verified with Pearson residual plots. Results: HH performance rates overall and compared to the baseline are shown in Table 2. More than 8 million opportunities were achieved in all 58 units combined. An intervention strategy with multiple complementary components (ie, clinical support provided by the AHHMS vendor plus hospital-initiated unit level interventions) yielded significantly better HH performance than all other categories (>20% increase, P < .00001). Somewhat surprisingly, vendor clinical support or hospital-initiated, unit-level interventions alone with the AHHMS yielded a slight decrease in HH performance relative to AHHMS only (P < .00001). Conclusions: AHHMS is a useful tool in understanding HH performance and identifying unit-based initiatives that need attention. Implementation of an AHHMS by itself or with limited complementary behavior-change strategies does not drive improvement. Support provided by the vendor and hospital-initiated, complementary strategies were not sufficient additions to the AHHMS individually, but in combination they resulted in the greatest improvements in HH performance. These findings illustrate the value of a partnership between the hospital and the AHHMS vendor.

Funding: GOJO Industries, Inc., provided support for this study.

Disclosures: James W. Arbogast, Lori D. Moore and Megan DiGiorgio report salary from GOJO Industries.

Background: Identification of healthcare-associated infections (HAIs) is just a first step in the surveillance of HAIs. The other part is the analysis and interpretation of collected data, which should help to set up effective preventive measures targeted where they are needed the most. General risk factors of HAIs are mostly well known, but how do the environment and processes of each hospital affect risks of HAI? Can advanced methods of data analytics reveal hidden hospital-specific risk factors of surgical site infections (SSIs)? Methods: We analyzed data from electronic health records stored in the clinical information system of Hospital Jihlava, Czech Republic, with 650 beds and 7,500 surgeries performed annually. For each inpatient stay with a surgical procedure, we automatically observed almost 1,500 features that could lead to a higher incidence of SSIs. These features consist of patient demographic data, information from structured data (eg, patient diagnoses, departments, specific rooms, operating theaters, surgeons and other hospital staff participating in the surgery), and information extracted from clinical notes using natural language processing (eg, procedures, invasive devices, and comorbidities). We used a model based on survival analysis to reveal the risk factors that can increase the probability of SSI during the inpatient stay or outpatient care after discharge. Results: We automatically evaluated risk factors weekly for 4 months (July 2019–October 2019). We detected 16 distinct significant risk factors during this period—between 2 and 6 active risk factors each week. For example, patients visiting a specific department were up to 5 times more likely to develop an HAI than the rest of the patients (P < .001). Some of the risk factors revealed were significant only within a short time, and some of them occurred perpetually. When a feature became significant, it was considered an early warning of a problem that should be addressed by the infection prevention and control team. Trends in risk factors coefficients can also help in assessing the performance of the launched preventive measures. Conclusions: Advanced data analytics can effectively uncover hospital-specific risk factors affecting surgical site infections. Such systems can automatically deliver results that can be further explored and used as a basis for targeted preventive measures.

Funding: Datlowe provided support for this study.

Disclosures: Jakub Kozák reports salary from and ownership of Datlowe.

Background: Carbapenem-resistant Enterobacteriaceae (CRE) are an important cause of healthcare-associated infections (HAIs) in human hospitals. The Philadelphia Department of Public Health (PDPH) made CRE reportable in April 2018. In May 2019, the Matthew J. Ryan Veterinary Hospital (MJRVH) reported an NDM-5 Escherichia coli cluster in companion animals to the PDPH. In total, 15 infected animals (14 dogs and 1 cat) were reported between July 2018 and June 2019, with no new infections after June 2019. Limited literature is available on the prevalence of CRE in companion animals, and recommendations for dealing with CRE infections currently target human healthcare settings. Methods: A collaborative containment response included assessing interspecies transmission to veterinary staff and a comprehensive evaluation of the infection control program at MJRVH. MJRVH notified all owners of affected animals verbally and via notification letters with PDPH recommendations for CRE colonization screening of high-risk individuals. CRE screening of exposed high-risk employees was conducted by the University of Pennsylvania Occupational Health service and PDPH. Human rectal swabs were analyzed at the Antibiotic Resistance Laboratory Network (ARLN) Maryland Laboratory. PDPH were invited to conduct an onsite infection control assessment and to suggest improvements. Results: No pet owners self-identified in high-risk groups to be screened. In total, 10 high-risk staff were screened, and no colonized individuals were detected. Recommendations made by the PDPH to MJRVH included improvement of infection prevention and control policies (eg, consolidation of the infection control manual and identification of lead staff member), improvement in hand hygiene (HH) compliance (eg, increasing amount of HH supplies), improvement of environment of care (eg, decluttering and evaluation of mulched animal relief area), and improvement of respiratory care processes (eg, standardization of care policies). MJRVH made substantial improvements across recommendation areas including revision of infection control manual, creation of a full-time infection preventionist position, individual alcohol hand sanitizers for patient cages, and environmental decluttering and decontamination. PDPH and MJRVH maintained frequent communication about infection control improvements. Conclusions: No positive transmission to high-risk staff members suggest that, like in human healthcare facilities, transmission of CRE to caretakers may not be a common event. Stronger communication and collaboration is required from Departments of Public Health (DPH) to the veterinary profession regarding the reporting requirements of emerging pathogens such as CRE. Veterinary facilities should view DPH as a valuable resource for recommendations to fill in gaps that exist in infection control “best practices,” particularly for novel pathogens in veterinary settings.

Funding: None

Disclosures: Jane M. Gould reports that her spouse receives salary from Incyte.

Background: Data regarding outpatient antibiotic prescribing for urinary tract infections (UTIs) are limited, and they have never been formally summarized in Virginia. Objective: We describe outpatient antibiotic prescribing trends for UTIs based on gender, age, geographic region, insurance payer and International Classification of Disease, Tenth Revision (ICD-10) codes in Virginia. Methods: We used the Virginia All-Payer Claims Database (APCD), administered by Virginia Health Information (VHI), which holds data for Medicare, Medicaid, and private insurance. The study cohort included Virginia residents who had a primary diagnosis of UTI, had an antibiotic claim 0–3 days after the date of the diagnosis and who were seen in an outpatient facility in Virginia between January 1, 2016, and December 31, 2016. A diagnosis of UTI was categorized as cystitis, urethritis or pyelonephritis and was defined using the following ICD-10 codes: N30.0, N30.00, N30.01, N30.9, N30.90, N30.91, N39.0, N34.1, N34.2, and N10. The following antibiotics were prescribed: aminoglycosides, sulfamethoxazole/trimethoprim (TMP-SMX), cephalosporins, fluoroquinolones, macrolides, penicillins, tetracyclines, or nitrofurantoin. Patients were categorized based on gender, age, location, insurance payer and UTI type. We used χ2 and Cochran-Mantel-Haenszel testing. Analyses were performed in SAS version 9.4 software (SAS Institute, Cary, NC). Results: In total, 15,580 patients were included in this study. Prescriptions for antibiotics by drug class differed significantly by gender (P < .0001), age (P < .0001), geographic region (P < .0001), insurance payer (P < .0001), and UTI type (P < .0001). Cephalosporins were prescribed more often to women (32.48%, 4,173 of 12,846) than to men (26.26%, 718 of 2,734), and fluoroquinolones were prescribed more often to men (53.88%, 1,473 of 2,734) than to women (47.91%, 6,155 of 12,846). Although cephalosporins were prescribed most frequently (42.58%, 557 of 1,308) in northern Virginia, fluoroquinolones were prescribed the most in eastern Virginia (50.76%, 1677 of 3,304). Patients with commercial health insurance, Medicaid, and Medicare were prescribed fluoroquinolones (39.31%, 1,149 of 2,923), cephalosporins (56.33%, 1,326 of 2,354), and fluoroquinolones (57.36%, 5,910 of 10,303) most frequently, respectively. Conclusions: Antibiotic prescribing trends for UTIs varied by gender, age, geographic region, payer status and UTI type in the state of Virginia. These data will inform future statewide antimicrobial stewardship efforts.

Funding: None

Disclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.

Background: Carbapenemase-producing Enterobacterales (CPE) have rapidly become a global health concern and are associated with substantial morbidity and mortality due to limited treatment options. Travel to endemic areas, especially healthcare exposure in these areas, is an important risk factor for acquisition. We describe the evolving epidemiology, molecular features, and outcomes of CPE in Canada through surveillance by the Canadian Nosocomial Infection Surveillance Program (CNISP). Methods: CNISP has conducted surveillance for CPE among inpatients and outpatients of all ages since 2010. Participating acute-care facilities submit eligible specimens to the National Microbiology Laboratory for detection of carbapenemase production, and epidemiological data are collected. Incidence rates per 10,000 patient days are calculated based on inpatient data. Results: In total, 59 CNISP hospitals in 10 Canadian provinces representing 21,789 beds and 6,785,013 patient days participated in this surveillance. From 2010 to 2018, 118 (26%) CPE-infected and 547 (74%) CPE-colonized patients were identified. Few pediatric cases were identified (n = 18). Infection incidence rates remain low and stable (0.02 per 10,000 patient days in 2010 to 0.03 per 10,000 patient days in 2018), and colonization incidence rates have increased by 89% over the surveillance period. Overall, 92% of cases were acquired in a healthcare facility: 61% (n = 278) in a Canadian healthcare facility and 31% (n = 142) in a healthcare facility outside Canada. Of the 8% of cases not acquired in a healthcare facility, 50% (16 of 32) reported travel outside of Canada in the 12 months prior to positive culture. The distribution of carbapenemases varied by region; New Delhi metallo-B-lactamase (NDM) was dominant (59%) in western Canada and Klebsiella pneumoniae carbapenemase (KPC) (66%) in central Canada. NDM and class D carbapenemase OXA-48 were more commonly identified among those who traveled outside of Canada, whereas KPC was more commonly identified among patients without travel. In addition, 30-day all-cause mortality was 14% (25 of 181) among CPE infected patients and 32% (14 of 44) among those with bacteremia. Conclusions: CPE rates remain low in Canada; however, national surveillance data suggest that the increase in CPE in Canada is now being driven by local nosocomial transmission as well as travel and healthcare within endemic areas. Changes in screening practices may have contributed to the increase in colonizations; however, these data are currently lacking and will be collected moving forward. These data highlight the need to intensify surveillance and coordinate infection control measures to prevent further spread of CPE in Canadian acute-care hospitals.

Funding: None

Disclosures: Susy Hota reports contracted research for Finch Therapeutics. Allison McGeer reports funds to her institution for projects for which she is the principal investigator from Pfizer and Merck, as well as consulting fees from the following companies: Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara.

Background: Nearly 1 in 25 patients has a hospital infection at any given time, and 1 in 25 nurses suffers and bloodborne exposure every year. Basic procedures, termed standard precautions (SP) may prevent these outcomes, but they are not often used by healthcare workers. Unfortunately, data are largely limited by self-reporting because no standardized tools exist to capture observational data. Objective: The specific aim of this study was to describe the relationship between self-reported and observed SP adherence. Methods: This multisite, cross-sectional study included 2 elements: (1) surveys of nurses in US hospital units on perceptions of patient safety climate and reported SP adherence and (2) observational SP data. Survey data included 12 items on SP practices (eg, “how often you perform hand hygiene before touching a patient”) and 10 items on SP environment (eg, “my work area is not cluttered”), rated on a 5-point scale from “never” to “always” or from “strongly disagree” to ”strongly agree,” respectively. Using novel tools developed and previously pilot tested, we recruited and trained hospital-based staff on observational surveillance methodology to foster the National Occupational Research Agenda goals. The 10 observational SP items represented the following 4 categories: (1) hand hygiene, (2) personal protective equipment (PPE), (3) sharps, and (4) soiled linen handling. Observations of healthcare worker–patient interactions followed training and interrater reliability testing. All data were aggregated, and analyses were conducted at the unit level. Pearson correlation coefficients were calculated to determine the relationship between reported and observed SP practices (level of significance, P < .05). Results: In total, 6,518 SP indications were observed and 500 surveys were collected from nurses on 54 units in 15 hospitals from 6 states. The final analytic sample included 5,285 SP indications and 452 surveys from 43 units in 13 hospitals that provided both types of data. Most indications observed were of HH (72.6%). Overall SP adherence was 64.4%. In descending order, adherence rates were PPE (81.8%), sharps handling (80.9%), linen handing (68.3%), and hand hygiene (58.3%). The aggregate of positive self-reported SP practices was 95.8%, and 77.3% rated unit environment for SP adherence positively. There was no correlation between observed adherence and reported adherence (r (41) = (−).024, P = .879). Conclusions: In this study, the largest study of SP adherence, observed practice was grossly suboptimal, particularly hand hygiene. Conversely, nurses on the same units rated adherence as high, despite the environment. In combination, both sources of surveillance data provide valuable and actionable insight to target interventions.

Funding: and Disclosure Amanda Hessels reports that she is the principal investigator for the following studies: “Impact of Patient Safety Climate on Infection Prevention Practices and Healthcare Worker and Patient Outcomes” (grant no. DHHS/CDC/NIOSH 1K01OH011186 to Columbia University) and “Simulation to Improve Infection Prevention and Patient Safety: The SIPPS Trial” (AHRQ grant no. R18: 1R18HS026418 to Columbia University).

Background: The movement of healthcare professionals (HCPs) induces an indirect contact network: touching a patient or the environment in one area, then again elsewhere, can spread healthcare-associated pathogens from 1 patient to another. Thus, understanding HCP movement is vital to calibrating mathematical models of healthcare-associated infections. Because long-term care facilities (LTCFs) are an important locus of transmission and have been understudied relative to hospitals, we developed a system for measuring contact patterns specifically within an LTCF. Methods: To measure HCP movement patterns, we used badges (credit-card–sized, programmable, battery-powered devices with wireless proximity sensors) worn by HCPs and placed in 30 locations for 3 days. Each badge broadcasts a brief message every 8 seconds. When received by other badges within range, the recipients recorded the time, source badge identifier, and signal strength. By fusing the data collected by all badges with a facility map, we estimated when and for how long each HCP was in any of the locations where instruments had been installed. Results: Combining the messages captured by all of our devices, we calculated the dwell time for each job type (eg, nurses, nursing assistants, physical therapists) in different locations (eg, resident rooms, dining areas, nurses stations, hallways, etc). Although dwell times over all job and area types averaged ∼100 seconds, the standard deviation was large (115 seconds), with a mean of maximums by job type of ∼450 seconds. For example, nursing assistants spent substantially more time in resident rooms and transitioned across rooms at a much higher rate. Overall, each distribution exhibits a power-law–like characteristic. By aggregating the data from devices with location data extracted from the floor plan, we were able to produce an explicit trace for each individual (identified only by job type) for each day and to compute cross-table transition probabilities by area for each job type. Conclusions: We developed a portable system for measuring contact patterns in long-term care settings. Our results confirm that frequent interactions between HCPs and LTC residents occur, but they are not uniform across job types or resident locations. The data produced by our system can be used to better calibrate mathematical models of pathogen spread in LTCs. Moreover, our system can be easily and quickly deployed to any healthcare settings to similarly inform outbreak investigations.

Funding: None

Disclosures: Scott Fridkin reports that his spouse receives a consulting fee from the vaccine industry.

Background: Bloodstream infections are one of the main adverse effects of healthcare in Spain. In our hospital, we have reported that the mean incremental cost of patients who develop bacteremia during admission was €15,526 (US$18,314.62) per discharge, representing an annual increment in hospital cost of €1,108,190 (US$1,307,232) in 2005–2012. Moreover, we have also observed that only 15.4% of episodes of our bacteremia occur in intensive care units, with most of these infections (67%) occurring in conventional units.1 Therefore, we started several initiatives to reduce healthcare-associated bloodstream infections. Herein, we describe one of these initiatives, which is the implementation of the intravascular therapy team (ITT) and its effect on the observed healthcare-associated bloodstream infections. Methods: This retrospective analysis evaluated the incidence of healthcare-associated bloodstream infections in a University Hospital of 520 beds from January 2014 to June 2019. The ITT was implemented in 2017. This is a multidisciplinary team with 2 specialists in infection control and 2 specialists in intravascular therapy. We evaluated the annual incidence rate of healthcare-associated bloodstream infections (number of bacteremia episodes per 1,000 days of hospital stay) and its relation with the interventions carried out by the multidisciplinary team. Results: The annual incidences of healthcare-associated bloodstream infections (episodes per 1,000 days of hospital stay) were 0.50 (2014), 0.46 (2015), 0.58 (2016), 0.69 (2017), 0.60 (2018), 0.51 (first quarter 2019), and 0.38 (second quarter 2019, 0.38), respectively. The highest incidence of bacteremia was observed in 2017 when the ITT started the following actions: (1) following a clinical protocol to improve the appropriateness in the utilization of new devices such as a peripherally inserted central catheter (PICC) and Medline; (2) continuous training of healthcare professionals, particularly young staff; (3) feedback with hospitalization units; and (4) proactive surveillance of venous access manipulation and maintenance. The interventions were designed, implemented, and evaluated by the ITT and were well accepted by healthcare professionals. After the implementation of the ITT, the incidence of healthcare-associated bloodstream infections decreased. This trend was particularly relevant for parenteral nutrition catheters (episodes per 1,000 days of parenteral nutrition) (Fig. 1). Conclusions: The implementation of the ITT in our center has allowed us to considerably reduce the incidence of healthcare-associated bloodstream infections. From our experience, the interventions related to systematic evaluation, education, and feedback are key to obtain and maintain this improvement.

Funding: None

Disclosures: Carlota Hidalgo-Lopez reports that this study was partly funded by Diversey. The authors did not receive direct Funding: from the sponsor, Juan Pablo Horcajada reports consulting fees from MSD, Pfizerand, and Menarini, as well as speaker fees from MSD, Pfizer, and Zambon.

Background: Ebola virus disease (EVD) is highly transmissible and has a high mortality rate. During outbreaks, EVD can spread across international borders. Inadequate hand hygiene places healthcare workers (HCWs) at increased risk for healthcare-associated infections, including EVD. In high-income countries, alcohol-based hand rub (ABHR) can improve hand hygiene compliance among HCWs in healthcare facilities (HCF). We evaluated local production and district-wide distribution of a WHO-recommended ABHR formulation and associations between ABHR availability in HCF and HCW hand hygiene compliance. Methods: The evaluation included 30 HCF in Kabarole District, located in Western Uganda near the border with the Democratic Republic of the Congo, where an EVD outbreak has been ongoing since August 2018. We recorded baseline hand hygiene practices before and after patient contact among 46 healthcare workers across 20 HCFs in August 2018. Subsequently, in late 2018, WHO/UNICEF distributed commercially produced ABHR to all 30 HCFs in Kabarole as part of Ebola preparedness efforts. In February 2019, our crossover evaluation distributed 20 L locally produced ABHR to each of 15 HCFs. From June 24–July 5, 2019, we performed follow-up observations of hand hygiene practices among 68 HCWs across all 30 HCFs. We defined hand hygiene as handwashing with soap or using ABHR. We conducted focus groups with healthcare workers at baseline and follow-up. Results: We observed hand hygiene compliance before and after 203 and 308 patient contacts at baseline and follow-up, respectively. From baseline to follow-up, hand hygiene compliance before patient contact increased for ABHR use (0% to 17%) and handwashing with soap (0% to 5%), for a total increase from 0% to 22% (P < .0001). Similarly, hand hygiene after patient contact increased from baseline to follow-up for ABHR use (from 3% to 55%), and handwashing with soap decreased (from 12% to 7%), yielding a net increase in hand hygiene compliance after patient contact from 15% to 62% (P < .0001). Focus groups found that HCWs prefer ABHR to handwashing because it is faster and more convenient. Conclusions: In an HCF in Kabarole District, the introduction of ABHR appeared to improve hand hygiene compliance. However, the confirmation of 3 EVD cases in Uganda 120 km from Kabarole District 2 weeks before our follow-up hand hygiene observations may have influenced healthcare worker behavior and hand hygiene compliance. Local production and district-wide distribution of ABHR is feasible and may contribute to improved hand hygiene compliance among healthcare workers.

Funding: None

Disclosures: Mohammed Lamorde, Contracted Research - Janssen Pharmaceutica, ViiV, Mylan

Background: Central-line–associated blood stream infections (CLABSIs) are linked with significant morbidity and mortality. A NHSN laboratory-confirmed bloodstream infection (LCBSI) has specific criteria to ascribe an infection to the central line or not. The criteria used to associate the pathogen to another site are restrictive. This objective to better classify CLABSIs using enhanced criteria to gain a comprehensive understanding of the error so that appropriate reduction efforts are utilized. Methods: We conducted a retrospective review of medical records with NHSN-identified CLABSI from July 2017 to December 2018 at 2 geographically proximate hospitals. Trained infectious diseases personnel from tertiary-care academic medical centers, the University of Virginia Health System, a 600-bed medical center in Charlottesville, Virginia, and Virginia Commonwealth University Health System with 865 beds in Richmond, Virginia, reviewed charts. We defined “overcaptured” or O-CLABSI into different categories: O-CLABSI-1 is bacteremia attributable to a primary infectious source; O-CLABSI-2 is bacteremia attributable to neutropenia with gastrointestinal translocation not meeting mucosal barrier injury criteria; O-CLABSI-3 is a positive blood culture attributable to a contaminant; and O-CLABSI-4 is a patient injecting line, though not officially documented. Descriptive analyses were performed using the χ2 and the Fisher exact tests. Results: We found a large number of O-CLABSIs on chart review (79 of 192, 41%). Overall, 56 of 192 (29%) LCBSIs were attributable to a primary infectious source not meeting NHSN definition. O-CLABSI proportions between the 2 hospitals were statistically different; hospital A identified 34 of 59 (58%) of their NHSN-identified CLABSIs as O-CLABSIs, and hospital B identified a 45 of 133 (34%) as O-CLABSIs (P = .0020) (Table 1). When comparing O-CLABSI types, hospital B had a higher percentage of O-CLABSI-1 compared to hospital B: 76% versus 64%. Hospital A had a higher proportion of O-CLABSI-2: 21 versus 7%. Hospitals A and B had similar proportion of O-CLABSI-3: 15% versus 18%. These values were all statistically significant (P < .0001). Discussions: The results of these 2 geographically proximate systems indicate that O-CLABSIs are common. Attribution can vary significantly between institutions, likely depending on differences in incidence of true CLABSI, patient populations, protocols, and protocol compliance. These findings have implications for interfacility comparisons of publicly reported data. Most importantly, erroneous attribution can result in missed opportunity to direct patient safety efforts to the root cause of the bacteremia and could lead to inappropriate treatment.

Funding: None

Disclosures: Michelle Doll, Research Grant from Molnlycke Healthcare

Background: In April 2019, Nebraska Public Health Laboratory identified an NDM-producing Enterobacter cloacae from a urine sample from a rehabilitation inpatient who had recently received care in a specialized unit (unit A) of an acute-care hospital (ACH-A). After additional infections occurred at ACH-A, we conducted a public health investigation to contain spread. Methods: A case was defined as isolation of NDM-producing carbapenem-resistant Enterobacteriaceae (CRE) from a patient with history of admission to ACH-A in 2019. We conducted clinical culture surveillance, and we offered colonization screening for carbapenemase-producing organisms to all patients admitted to unit A since February 2019. We assessed healthcare facility infection control practices in ACH-A and epidemiologically linked facilities by visits from the ICAP (Infection Control Assessment and Promotion) Program. The recent medical histories of case patients were reviewed. Isolates were evaluated by whole-genome sequencing (WGS). Results: Through June 2019, 7 cases were identified from 6 case patients: 4 from clinical cultures and 3 from 258 colonization screens including 1 prior unit A patient detected as an outpatient (Fig. 1). Organisms isolated were Klebsiella pneumoniae (n = 5), E. cloacae (n = 1), and Citrobacter freundii (n = 1); 1 patient had both NDM-producing K. pneumoniae and C. freundii. Also, 5 case patients had overlapping stays in unit A during February–May 2019 (Fig. 2); common exposures in unit A included rooms in close proximity, inhabiting the same room at different times and shared caregivers. One case-patient was not admitted to unit A but shared caregivers, equipment, and devices (including a colonoscope) with other case patients while admitted to other ACH-A units. No case patients reported travel outside the United States. Screening at epidemiologically linked facilities and clinical culture surveillance showed no evidence of transmission beyond ACH-A. Infection control assessments at ACH-A revealed deficiencies in hand hygiene, contact precautions adherence, and incomplete cleaning of shared equipment within and used to transport to/from a treatment room in unit A. Following implementation of recommended infection control interventions, no further cases were identified. Finally, 5 K. pneumoniae of ST-273 were related by WGS including carriage of NDM-5 and IncX3 plasmid supporting transmission of this strain. Further analysis is required to relate IncX3 plasmid carriage and potential transmission to other organisms and sequence types identified in this study. Conclusions: We identified a multiorganism outbreak of NDM-5–producing CRE in an ACH specialty care unit. Transmission was controlled through improved infection control practices and extensive colonization screening to identify asymptomatic case-patients. Multiple species with NDM-5 were identified, highlighting the potential role of genotype-based surveillance.

Funding: None

Disclosures: Muhammad Salman Ashraf reports that he is the principal investigator for a study funded by an investigator-initiated research grant.

Background: Nearly half of hospitalized patients with bacteriuria or treated for pneumonia receive unnecessary antibiotics (noninfectious or nonbacterial syndrome such as asymptomatic bacteriuria), excess duration (antibiotics prescribed for longer than necessary), or avoidable fluoroquinolones (safer alternative available) at hospital discharge.1–3 However, whether antibiotic overuse at discharge varies between hospitals or is associated with patient outcomes remains unknown. Methods: From July 2017 to December 2018, trained abstractors at 46 Michigan hospitals collected detailed data on a sample of adult, non–intensive care, hospitalized patients with bacteriuria (positive urine culture with or without symptoms) or treated for community-acquired pneumonia (CAP; includes those with the disease formerly known as healthcare-associated pneumonia [HCAP]). Antibiotic prescriptions at discharge were assessed for antibiotic overuse using a previously described, guideline-based hierarchical algorithm.3 Here, we report the proportion of patients discharged with antibiotic overuse by the hospital. We also assessed hospital-level correlation (using Pearson’s correlation coefficient) between antibiotic overuse at discharge for patients with bacteriuria and patients treated for CAP. Finally, we assessed the association of antibiotic overuse at discharge with patient outcomes (mortality, readmission, emergency department visit, and antibiotic-associated adverse events) at 30 days using logit generalized estimating equations adjusted for patient characteristics and probability of treatment. Results: Of 17,081 patients (7,207 with bacteriuria; 9,874 treated for pneumonia), nearly half (42.2%) had antibiotic overuse at discharge (36.3% bacteriuria and 51.1% pneumonia). The percentage of patients discharged with antibiotic overuse varied 5-fold among hospitals from 14.7% (95% CI, 8.0%–25.3%) to 74.3% (95% CI, 64.2%–83.8%). Hospital rates of antibiotic overuse at discharge were strongly correlated between bacteriuria and CAP (Pearson’s correlation coefficient, 0.76; P ≤ .001) (Fig. 1). In adjusted analyses, antibiotic overuse at discharge was not associated with death, readmission, emergency department visit, or Clostridioides difficile infection. However, each day of overuse was associated with a 5% increase in the odds of patient-reported antibiotic-associated adverse events after discharge (Fig. 2). Conclusions: Antibiotic overuse at discharge was common, varied widely between hospitals, and was associated with patient harm. Furthermore, antibiotic overuse at discharge was strongly correlated between 2 disparate diseases, suggesting that prescribing culture or discharge processes—rather than disease-specific factors—contribute to overprescribing at discharge. Thus, discharge stewardship may be needed to target multiple diseases.

Funding: This study was supported by the Society for Healthcare Epidemiology of America and by Blue Cross Blue Shield of Michigan and Blue Care Network.

Disclosures: Valerie M. Vaughn reports contracted research for Blue Cross and Blue Shield of Michigan, the Department of VA, the NIH, the SHEA, and the APIC. She also reports receipt of funds from the Gordon and Betty Moore Foundation Speaker’s Bureau, the CDC, the Pew Research Trust, Sepsis Alliance, and the Hospital and Health System Association of Pennsylvania.