bluuebunny/crossref_metadata_2025 huggingface dataset:
Supporting Healthcare-Associated Infection (HAI) Surveillance in Resource-Limited Settings: Lessons Learned, 2015–2019
Authors: Westercamp Matthew , Malpiedi Paul , Vasquez Amber , Gomes Danica , Hazim Carmen , Park Benjamin J. , Smith Rachel
Published: November 2020

Background: Since 2015, the CDC has supported the development and implementation of healthcare-associated infection (HAI) surveillance in resource-limited settings through technical support of case definitions and methods that are feasible with existing surveillance capacity and integration with clinical care to maximize sustainability and data use for action. Methods: Surveillance initiatives included facility-level implementation programs in Kenya, Sierra Leone, Thailand, and Georgia; larger national or regional network-level projects in India and Vietnam were also supported. For assessment and planning, surveillance capacities were grouped into 3 domains: staff, informatics, and diagnostic capacities. Based on these capacities, simplified case definitions surveillance methodologies were devised to balance resources and effort with the anticipated value and use of findings. Results: There was broad understanding of the importance of HAI surveillance; however, the required resources and other challenges (eg, training, staffing, quality of available data) were underappreciated. Staff capacities were often influenced by a lack of dedicated surveillance staff and limited experience in systematic data collection and analysis. Informatics capacities were generally limited by the lack of digital data management, nonstandardized clinical data collection and storage, and the inability to assign and maintain unique patient identifiers. We found that capacity for diagnostics, a critical component of traditional HAI surveillance systems, was limited by its availability, frequency of use, and inconsistent rationale in clinical care. We found that successful surveillance strategies were generally simple, matched existing capacities, and targeted specific HAI priorities identified by clinical teams. For example, in Kenya and Sierra Leone, participating facilities established, with minimal external support, simplified SSI surveillance among post–caesarean-delivery patients. These initiatives improved integration of surveillance with clinical care through encouraging participation of the clinical team in surveillance and planning. Furthermore, these models directly linked surveillance activities to improved patient care (eg, combined clinical checklists with surveillance data collection forms). Discussion: In resource-limited settings, the local cost and effort required to establish and sustain the necessary infrastructure for HAI surveillance can be substantial. Establishing actionable and sustainable HAI surveillance can be achieved through simplifying HAI surveillance to match existing capacities and can result in valuable surveillance programs, even in very resource-limited settings.

Funding: None

Disclosures: None
Surgical Site Infection Prevention: An Analysis of Compliance With Good Practice in Large Hospitals
Authors: Oliveira Adriana
Published: November 2020

Background: Surgical site infection (SSI) is considered one of the most frequent adverse events globally. One of the strategies to mitigate its occurrence was proposed by the WHO in 2008 as part of the Safe Surgery Saves Lives program to reduce the rate of SSI by 25% by 2020. Objectives: To evaluate adherence to SSI prevention and control actions in large hospitals using a score. Methods: This cross-sectional study was conducted in 30 hospitals in Minas Gerais, Brazil, from February 2018 to April 2019. Data collection was performed through interviews with the coordinator of the hospital infection control service (HICS), situational diagnoses, and observation of a surgical procedures at the time of the visit. Data were analyzed using SPSS software. The variables were described using descriptive statistics. The project was approved by the Research Ethics Committee of the Federal University of Minas Gerais (COEP/UFMG) (CAAE: 30782614.3.00005149). A score was determined to identify the degree of compliance of institutions to SSI prevention practices. Results: In 93.3% of the HICSs, routines or protocols for the use of prophylactic antibiotic in surgery and compliance audits were mentioned, 69% reported hair removal with a clipper. SSI surveillance occurred in all institutions; however, only 63.3% disclosed SSI rates. In the situational observations, 60% of the professionals performed hand antisepsis within 3–5 minutes. Most frequently, hair removal was performed inside the operating room in 76.7% of the observed procedures and an electric clipper was used 56.7% of the time. In the surgery audit, prophylactic antimicrobial administration occurred between 30 and 60 minutes before surgical incision in only 63.3% of the observed procedures. The traffic in the operation room was limited to the necessary minimum in only 53.3% of observed procedures and unnecessary opening of the doors occurred in 76.7% of the observations. Patient temperature was not monitored in 70% of the audited procedures. Conclusions: According to the proposed score, 1 of the institutions (3.3%) complied with SSI prevention and control measures sufficiently; 25 complied partially (83.3%); and 4 (13.3%) demonstrated poor compliance.

Funding: None

Disclosures: None
Surveillance of ICU Patients for Candida auris in a Suburban Chicago Hospital System: Results of a Limited Trial
Authors: Lavin Mary Alice , Schora Donna , Fisher Adrienne , Kufner Bridget , Lim Rachel , Monsalud Cherie Faith , Shah Mona , Zelencik Shane , Singh Kamaljit
Published: November 2020

Background:Candida auris prevalence in Illinois, particularly in the metropolitan Chicago area, is high. The Illinois Department of Public Health recommends empiric contact precautions for patients with a tracheostomy or requiring mechanical ventilation from skilled nursing facilities (vSNFs) or long-term acute-care hospitals (LTACHs) who are admitted to an acute-care hospital. Cases of C. auris infection and colonization are reportable to the Illinois Extensively Drug Resistant Organism Registry (XDRO Registry). NorthShore University HealthSystem (NSUHS) actively screens adult intensive care unit (ICU) admissions from LTACHs and vSNFs for CA. Methods: NSUHS is a 4-hospital system located north of Chicago with 750 beds, 4 ICUs and ∼64,000 annual admissions. Beginning in April 2019, a composite axilla–groin swab was collected from all ICU LTACH or vSNF admissions. Composite swabs are cultured on Inhibitory Mold Agar. In July 2019, an ICU clinical case of C. auris was identified from a ventilated patient admitted from an outside hospital prompting the expansion of screening to include acute-care hospital transfers. To evaluate the value of screening criteria, a medical record review and retrospective query of the XDRO Registry was performed for all screened patients. Because cocolonization with carbapenemase-producing organisms (CPO) has been reported, CPO status was also queried. Results: Between April 1 and October 31, 2019, 70 patients were screened. Two screened patients did not meet the screening criteria (Fig. 1). No patients, with the exception of the clinical case, were found to be colonized with CA. The XDRO Registry query identified no patients with C. auris. Of the 70 patients, 9 (13%) had a CPO. Of those screened, 14 (20%) had a tracheostomy and/or mechanical ventilation (Table 1). Conclusions: Querying the XDRO registry at admission in combination with a medical record review appears adequate to identify patients admitted to a NSUHS ICU with C. auris and CPOs. Targeting patients admitted with a tracheostomy and/or mechanical ventilation may further reduce the number of screening cultures performed.

Funding: None

Disclosures: None
Use of Varying Single-Nucleotide Polymorphism Thresholds to Identify Strong Epidemiologic Links Among Patients with Methicillin-Resistant Staphylococcus aureus (MRSA)
Authors: Zacharioudakis Ioannis , Ding Dan , Zervou Fainareti , Stachel Anna , Hochman Sarah , Sterling Stephanie , Lighter Jennifer , Aguero-Rosenfeld Maria , Shopsin Bo , Phillips Michael
Published: November 2020

Background: Whole-genome sequencing (WGS) has a high discriminatory power in confirming outbreaks. Outbreak investigation models that categorize the possibility of an outbreak based on the degree of genetic relatedness of isolates are highly dependent on the single-nucleotide polymorphism (SNP) threshold used. Methods: NYU Langone Medical center is a 725-bed academic center that has implemented WGS of methicillin-resistant Staphylococcus aureus (MRSA) isolates since 2016. Patients admitted to a medical or intensive care unit were screened on admission and transfer. The first surveillance and clinical MRSA isolate during each hospitalization was sequenced. We conducted a retrospective analysis to identify strong epidemiologic links among patients involved in genetically related clusters. We used different SNP thresholds to define genetic relatedness to identify the optimal threshold that should prompt an outbreak investigation. We considered strong hospital epidemiologic links sharing the same room or unit or having resided in the same room or unit within 7 days. A pairwise analysis was conducted to compare the epidemiologic links among patients involved in genetically related clusters. Results: Among 1,070 isolates, our analysis focused on 777 belonging to USA100 and USA300 clones. For USA100 isolates, we identified 8, 14, and 20 clusters comprising of 16, 29, and 42 patients when the threshold for genetic relatedness was set at 20, 40, and 60 SNP differences, respectively. Patients identified in a cluster yielded a strong hospital epidemiologic link in 62.5%, 87.5%, and 91.7% of cases (Fig. 1). For USA300 isolates, SNP differences of 10, 20, and 30 were used, identifying 20, 34, and 40 clusters of 43, 79, and 127 patients. The expansion of the threshold from 10 to 30 resulted in a decrease of the percentage of pairwise analyses with a strong hospital epidemiologic link from 57.7% to 13.6% by increasing 13-fold the number of analyses that were conducted to identify only 3 times more cases with strong epidemiologic links (Fig. 2). Conclusions: The results of our study indicate that SNPs thresholds determined by intrapatient variability of MRSA isolates might need to be tailored to the individual setting to guide infection control interventions because optimal thresholds might vary depending on characteristics of the population, MRSA isolates, and screening practices. Establishing conservative thresholds might allow the identification and quantification over time of the locations (eg, rooms or units) where transmission is occurring as well as the investigation of the clusters without strong epidemiologic links that might be valuable in elucidating unrecognized routes of transmission.

Funding: None

Disclosures: None
Utilizing a Risk-Based Criteria Framework to Identify Infection Prevention and Control Risks in Australian Dental Settings
Authors: Robb Kylie
Published: November 2020

Background: A dental practitioner must comply with the Dental Board of Australia’s guidelines on infection control. In this project, we developed a risk-based criteria framework to assess a practitioner’s infection prevention and control (IPC) systems and processes. This project allowed for the provision of the highest standard of infection control continuing education and advice relevant to the needs of members of the Australian Dental Association (NSW Branch). Methods: A review of 1,050 continuing professional development (CPD) IPC course evaluation forms was conducted to determine the key IPC areas that participants have the most difficulty with. All core IPC documents that practitioners are expected to understand and comply with were determined and any regulator- and profession-led compliance checklists were collated. These data were consolidated to generate a risk-based criteria framework that was then applied to 99 private, office-based, dental practices to determine IPC compliance. Results: After the review of 99 dental practices, the total aggregate compliance score was 78%, and the 15 key IPC areas were ranked from highest to lowest. These data assisted with the development of a full-day IPC course focusing on the top 5 risks in each category. The five areas of opportunity identified were Hand Hygiene (52%), Surgical Procedures and Aseptic Technique (59%), Documentation, Policy and Knowledge (61%), Sharps (72%), Steam Sterilisers (72%). Conclusions: This project identified key IPC risks for office-based dental practices from the capture of performance-based data. This data formed a targeted education framework that prioritized areas of opportunity to improve IPC standards in Australian dental practices.

Funding: None

Disclosures: None
Variability and Trends in Blood Culture Utilization, US Hospitals, 2012–2017
Authors: Hatfield Kelly , McCarthy Natalie , Reddy Sujan , Baggs James , Epstein Lauren , Kazakova Sophia , Olubajo Babatunde , Wolford Hannah , Jernigan John
Published: November 2020

Background: Microbiology data are utilized to quantify epidemiology and trends in pathogens, antimicrobial resistance, and bloodstream infections. Understanding variability and trends in rates of hospital-level blood culture utilization may be important for interpreting these findings. Methods: We used clinical microbiology results and discharge data to identify monthly blood culture rates from US hospitals participating in the Premier Healthcare Database during 2012–2017. We included all discharges from months where a hospital reported at least 1 blood culture with microbiology and antimicrobial susceptibility results. Blood cultures drawn on or before day 3 were defined as admission cultures (ACs); blood cultures collected after day 3 were defined as a postadmission cultures (PACs). The AC rate was defined as the proportion of all hospitalizations with an AC. The PAC rate was defined as the number of days with a PAC among all patient days. Generalized estimating equation regression models that accounted for hospital-level clustering with an exchangeable correlation matrix were used to measure associations of monthly rates with hospital bed size, teaching status, urban–rural designation, region, month, and year. The AC rates were modeled using logistic regression, and the PAC rates were modeled using a Poisson distribution. Results: We included 11.7 million hospitalizations from 259 hospitals, accounting for nearly 52 million patient days. The median annual hospital-level AC rate was 27.1%, with interhospital variation ranging from 21.1% (quartile 1) to 35.2% (quartile 3) (Fig. 1). Multivariable models revealed no significant trends over time (P = .74), but statistically significant associations between AC rates with month (P < .001) and region (P = .003), associations with teaching status (P = .063), and urban-rural designation (P = .083) approached statistical significance. There was no association with bed size (P = .38). The median annual hospital-level PAC rate was 11.1 per 1,000 patient days, and interhospital variability ranged from 7.6 (quartile 1) to 15.2 (quartile 3) (Fig. 2). Multivariable models of PAC rates showed no significant trends over time (P = .12). We found associations between PAC rates with month (P = .016), bed size (P = .030), and teaching status (P = .040). PAC rates were not associated with urban–rural designation (P = .52) or region (P = .29). Conclusions: Blood culture utilization rates in this large cohort of hospitals were unchanged between 2012 and 2017, though substantial interhospital variability was detected. Although both AC and PAC rates vary by time of year and potentially by teaching status, AC rates vary by geographic characteristics whereas PAC rates vary by bed size. These factors are important to consider when comparing rates of bloodstream infections by hospital.

Funding: None

Disclosures: None
Verification of Healthcare Personnel Immunity as a Strategy for Measles Preparedness
Authors: Snyders Rachael , Babcock Hilary , Blank Christopher
Published: November 2020

Background: Immunization resistance is fueling a resurgence of vaccine-preventable diseases in the United States, where several large measles outbreaks and 1,282 measles cases were reported in 2019. Concern about these measles outbreaks prompted a large healthcare organization to develop a preparedness plan to limit healthcare-associated transmission. Verification of employee rubeola immunity and immunization when necessary was prioritized because of transmission risk to nonimmune employees and role of the healthcare personnel in responding to measles cases. Methods: The organization employs ∼31,000 people in diverse settings. A multidisciplinary team was formed by infection prevention, infectious diseases, occupational health, and nursing departments to develop the preparedness plan. Immunity was monitored using a centralized database. Employees without evidence of immunity were asked to provide proof of vaccination, defined by the CDC as 2 appropriately timed doses of rubeola-containing vaccine, or laboratory confirmation of immunity. Employees were given 30 days to provide documentation or to obtain a titer at the organization’s expense. Staff with negative titers were given 2 weeks to coordinate with the occupational heath department for vaccination. Requests for medical or religious accommodations were evaluated by occupational heath staff, the occupational heath medical director, and the human resources department. All employees were included, though patient-interfacing employees in departments considered higher risk were prioritized. These areas were the emergency, dermatology, infectious diseases, labor and delivery, obstetrics, and pediatrics departments. Results: At the onset of the initiative in June 2019, 4,009 employees lacked evidence of immunity. As of November 2019, evidence of immunity had been obtained for 3,709 employees (92.5%): serological evidence of immunity was obtained for 2,856 (71.2%), vaccine was administered to 584 (14.6%), and evidence of previous vaccination was provided by 269 (6.7%). Evidence of immunity has not been documented for 300 (7.5%). The organization administered 3,626 serological tests and provided 997 vaccines, costing ∼$132,000. Disposition by serological testing is summarized in Table 1. Conclusions: A measles preparedness strategy should include proactive assessment of employees’ immune status. It is possible to expediently assess a large number of employees using a multidisciplinary team with access to a centralized database. Consideration may be given to prioritization of high-risk departments and patient-interfacing roles to manage workload.

Funding: None

Disclosures: None
You Cannot Manage What You Cannot Measure—Developing Central Sterilizing Performance Metrics
Authors: Stout Savanna , Helms Angela , Murphy Rebecca
Published: November 2020

Background: Metrics are critical to healthcare, particularly in areas that are highly process oriented. Our hospital’s central sterilizing department functions on standardized processes that have almost no industry specific measurements. Furthermore, the department had no formal internal method for process performance evaluation. A multiphase 6 Sigma DMAIC project was initiated in February 2019 in the central sterilizing department, with ‘phase 1’ being the development of performance metrics to evaluate current state and track future improvement. Methods: A DMAIC team was formed and completed a data inventory that included identifying all existing data sources pertaining to central sterilizing. Sources identified as reliable included count of daily surgical cases, counts of defects based on surgical services communication logs, number of surgical trays processed in the central sterilizing department, and the number of unsterile trays in the department at the start of each 7:00 a.m. shift. Results: A multidisciplinary team including surgeons and senior leadership formed the DMAIC team. Using identified data sources and input from frontline staff and leadership, official metric definitions were created. Weekly defect rates were chosen as a measurement and translated into the number of ready-for-use surgical trays at the time of case setup for every 100 surgical cases. Data from November 2018 through January 20, 2019, demonstrated the mean ready-for-use surgical trays at the time of case setup: for every 100 surgical cases, 96 the surgical trays was ready for use. Further analysis of the data over time demonstrated that variability was out of control. Defects were stratified into 12 categories. Moreover, 6 defects were creating 80% of the issues in trays not being ready: ‘hole in wrapper,’ ‘biohazardous debris,’ ‘nonbiohazardous debris,’ ‘missing instrument,’ ‘incorrect/mislabeled instrument trays,’ and ‘missing indicators.’ Results for unsterile trays at 7:00 a.m. showed that, on average, the central sterilizing department had 100 or more trays at the start of each 7:00 a.m. shift. Conclusions: Without a formal method for data collection, defined metrics, and ongoing analysis, evaluation of performance is based on anecdotal conclusions resulting in missed opportunities for improvement and, subsequently, opportunities for improved patient safety. Regularly published visible dashboards provide a true picture of performance, allowing staff to identify unwanted variation and to put interventions in place so that future variation is better controlled and or prevented. Additionally, having solid metrics, even when no industry ones exist, aid in measuring the effectiveness of improvement efforts, such as the DMAIC project, as they move into subsequent phases.

Funding: None

Disclosures: None
Evaluation of Autoclaving CAT: A Infectious Substance Packaging during the Ebola Crisis in the United States
Authors: Krisiunas Edward , Vallone-Hood Gina , Woodard Alan , Norrell Neil
Published: November 2020

Background: During the 2014 US Ebola crisis, an unprecedented amount of biohazardous waste was generated during patient care; healthcare facilities were overwhelmed by large volumes of waste. Few facilities had on-site waste treatment; therefore, waste was packaged and sent off site for incineration and disposal in Port Arthur, Texas, at a significant cost. Shipping this waste off site required the use of the US Department of Transportation (USDOT) Hazardous Materials (HMR 49 CFR) category A triple packaging for infectious substances. The most common treatment method for biohazardous waste in the United States is via commercial autoclaves. Because Category A waste packaging had not been tested to ensure effective treatment, we conducted autoclave efficacy studies to evaluate the various types of Category A packaging containing surrogate Ebola waste. If successful, this would potentially provide additional treatment options in the United States. Methods: Testing was conducted at commercial locations in 3 states: New York, Pennsylvania, and Florida. Various types of Category A packaging were obtained (Fig. 1). Waste loads were comprised of Ebola patient treatment material and included personal protective equipment, sharps containers, suction canisters, drapes, and associated items. Configured packaging was placed into autoclave bins to be processed. Each package tested included a biological indicator, a class 5 integrator. Where possible, thermocouples were added to record the thermoprofile of the waste. Initially, a modified cycle was tested (a prevacuum cycle followed by exposure to steam at 138°C for 60 minutes) and a postvacuum cycle. Cycle times were adjusted based upon initial results. Results: The initial New York autoclave was tested from a cold start (no vessel preheating) resulting in a failure to obtain efficacy (Fig. 1). Successful results were no growth in recovered biological indicators, acceptable color change in integrators, and reaching and holding temperatures >121°C for 30 minutes. After making modifications to treatment cycles, which included preheating of vessels, multiple prevacuum steps and a hold time of 60 minutes, successful results were achieved in testing conducted at the treatment plants in Pennsylvania and Florida. Conclusions: Commercial autoclaves can be effective in treating Category A biohazardous waste. Each autoclave considered for treatment requires a validation process using the types of packaging containing the waste, biological indicators, integrators, and thermocouples to present a complete assessment of the treatment process.

Funding: Three companies provided support for this study: Approved Storage & Waste Hauling, Daniels International, and ProMed Solutions.

Disclosures: Edward Krisiunas reports contracted research for Future Health Care Systems, Daniels Sharpsmart, and ProMed Solutions.
Hand Hygiene in the Era of Big Data: We Can Now See What We Have Been Missing
Authors: DiGiorgio Megan , Moore Lori , Robbins Greg , Parker Albert , Arbogast James
Published: November 2020

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.
Accuracy of the NHSN Central-Line–Associated Bloodstream Infections (CLABSIs) Definition: The Experience of Two Geographically Proximal Hospitals
Authors: Muto Carlene , Bailey Pamela Louise , Patrick Amie , Rittmann Barry John , Pryor Rachel , Cooper Kaila , Doll Michelle Elizabeth , Stevens Michael , Bearman Gonzalo
Published: November 2020

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
Estimating the Contribution of a Contaminated Wheelchair to Pathogen Spread With an Agent-Based Model
Authors: Wilson Amanda , Donskey Curtis , Verhougstraete Marc , Reynolds Kelly
Published: November 2020

Background: Wheelchairs can contribute to healthcare-associated infection transmission due to direct contact with patients and healthcare workers and due to wide spatial movement in facilities. Objective: We utilized location data of a wheelchair to inform an agent-based model for estimating the contribution of a single contaminated patient ride in a wheelchair to subsequent environmental contamination and to estimate the potential for wheelchair disinfection between patients to disrupt this spread. Methods: The destination and origin of wheelchairs were tracked in several facility locations: specialty care services, long-term care, radiology, acute care, common spaces, domiciliary, and outpatient clinics. An agent-based model was developed in which the probability of the wheelchair traveling directly from one location to another was informed by wheelchair origin and destination data. We assumed that the first patient’s hands were contaminated with methicillin-resistant Staphylococcus aureus (MRSA). For each patient trip, each simulated patient made contact with the wheelchair arm rests and a surface in the destination location. To evaluate potential exposures of uninfected patients, all patients riding in the wheelchair after the contaminated patient were assumed to be uncontaminated. In total, 50 patient rides were simulated. The concentration and number of contaminated surfaces in each hospital area were compared in addition to the average concentration of MRSA on patient hands over time. The intervention simulation involved a disinfection of wheelchair armrests with 90%, 70%, or 50% efficacy. Results: The 3 areas that had the largest estimated number of contaminated surfaces after 50 wheelchair trips following the first patient assumed to be infected were specialty care services, long-term care, and acute care. This finding was consistent with the paths that were most frequented by the wheelchair. Without cleaning between patients, the fiftieth patient to use the wheelchair had an average MRSA concentration of 41.5 CFU/cm2. With cleaning between patients, assuming a 50% cleaning efficacy, average MRSA concentration on the hands for the fiftieth patient was reduced to 7.4 ×10-14 CFU/cm2. Conclusions: We have demonstrated that cleaning, even with efficacies as low as 50%, may protect patients using contaminated wheelchairs from potential pathogen exposures. This study also demonstrates that tracking portable equipment can be useful not only for exposure modeling but also for predicting where the largest number of surfaces contaminated via portable equipment routes may be found. Future steps include performing a sensitivity analysis to evaluate the influence of spatial assumptions.

Funding: None

Disclosures: None
Genomic Epidemiology of Carbapenemase-Producing Enterobacterales (CPE) in Toronto, Canada
Authors: Jamal Alainna Juliette , Williams Victoria , Leis Jerome , Tijet Nathalie , Zittermann Sandra , Melano Roberto , Mataseje Laura , Mulvey Michael , McGeer Allison
Published: November 2020

Objective:
We investigated whether whole-genome sequencing (WGS) data altered interpretations of clonal transmission as determined by conventional epidemiology and pulsed-field gel electrophoresis (PFGE) at a tertiary-care hospital (hospital Z, HZ). Methods: We included all carbapenemase-producing Enterobacterales (CPE)–colonized or –infected patients identified via population-based surveillance from 2007 through 2018, who were admitted to HZ during and/or in the year prior to or following CPE detection. HZ reported clonal transmission clusters using epidemiology and PFGE for CPE identified at HZ or reported to HZ by other hospitals as potentially acquired at HZ. We assessed single-nucleotide polymorphism (SNP) phylogenies and case epidemiology. Results: Overall, 85 CPE-colonized or -infected patients were included: 50 were detected at HZ and 35 were detected at another local hospital but were admitted to HZ in the previous or following year. HZ reported 6 transmission clusters (Table 1). SNP analyses confirmed clusters B, C, E, and F. In cluster A, SNP analyses cast doubt on 2 of 9 cases (possibly representing plasmid transmission) but also identified 2 additional cases with isolates highly related (0–3 SNP differences) to other isolates. One case may be the index case: a travel-related case who stayed on the same unit as case 1, 4 months before case 1 detection. The second case stayed in a room previously occupied by 5 cluster A cases. In cluster D, SNP analyses found 1 additional case whose isolate was highly related (ie, 17–19 SNP differences) to other isolates. This case was identified a year before cluster D at another hospital that shares patients with HZ; however, the case’s admission to HZ was after all cluster D cases were detected and no direct epidemiologic link was identified. Conclusions: WGS data can identify cases belonging to transmission clusters that conventional epidemiologic methods missed.

Funding: None

Disclosures: Allison McGeer reports funds to her institution from Pfizer and Merck for projects for which she is the principal investigator. She also reports consulting fees from Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara
Molecular Epidemiology and Outcomes of Patients with Carbapenem-Resistant Enterobacteriaceae Bacteriuria, Atlanta 2012–2015
Authors: Howard-Anderson Jessica , Petit Robert , Bower Chris , Smith Gillian , Ansari Uzma , Halpin Alison , Karlsson Maria , Lawson Adrian , Lutgring Joseph , McAllister Gillian , Farley Monica , Jacob Jesse , Satola Sarah
Published: November 2020

Background: Carbapenem-resistant Enterobacteriaceae (CRE) represent a significant antibiotic resistance threat, in part because carbapenemase genes can spread on mobile genetic elements. Here, we describe the molecular epidemiology and outcomes of patients with CRE bacteriuria from the same city in a nonoutbreak setting. Methods: The Georgia Emerging Infections Program performs active, population-based CRE surveillance in Atlanta. We studied a cohort of patients with CRE (resistant to all tested third-generation cephalosporins and ≥1 carbapenem, excluding ertapenem) first identified in urine, and not in a prior or simultaneous sterile site, between 2012 and 2015. Whole-genome sequencing (WGS) was performed on a convenience sample. We obtained epidemiologic and outcome data through chart review and Georgia Vital Statistics records (90-day mortality). Using WGS, we created a core-genome alignment-based phylogenetic tree of the Klebsiella pneumoniae isolates and calculated the SNP difference between each sample. Using SAS version 9.4 software, we performed the Fisher exact test and univariable odds ratios (OR) with 95% CI to compare patient isolates with and without a carbapenemase gene. Results: Among 81 patients included, the median age was 68 (IQR, 57–74) years, and most were female (58%), black (60%), and resided in a long-term care facility 4 days prior to culture isolation (53%). Organisms isolated were K. pneumoniae (84%), Escherichia coli (7%), Enterobacter cloacae (7%), and Klebsiella oxytoca (1%). WGS identified at least 1 β-lactamase gene in 91% of the isolates; 85% contained a carbapenemase gene, the most frequent of which was blaKPC-3 (94%). Patients with CRE containing a carbapenemase gene were more likely to be black (OR, 3.7; 95% CI, 1.0–13.8) and to have K. pneumoniae (OR, 8.9; 95% CI, 2.2–35.0). Using a core-genome alignment of 3,708 genes (~63% of the complete genome), we identified a median of 67 (IQR, 23–3,881) SNP differences between each K. pneumoniae isolate. A phylogenetic tree identified clustering around carbapenemase gene and multilocus sequence type (84% were ST 258) but not based on referring laboratory or county of residence (Fig. 1). Although 7% of patients developed an invasive CRE infection within 1 year and 21% died within 90 days, having a carbapenemase gene was not associated with these outcomes. Conclusions: Molecular sequencing of a convenience sample of CRE bacteriuria support K. pneumoniae ST258 harboring blaKPC-3 being distributed throughout the Atlanta area, across the healthcare continuum. Overall mortality was high in this population, but the presence of carbapenemase genes was not associated with worse outcomes.

Funding: None

Disclosures: None

Disclosures: None

Funding: None
Point-Prevalence Survey on Antibiotics Use in Six Regional Hospitals in Sierra Leone
Authors: Williams Ralph , Conteh Christiana , Kanu Joseph Sam
Published: November 2020

Background: Antibiotic resistance (AMR) is a safety concern for patients in Sierra Leone. AMR can occur in communities and as well in the process of receiving treatments in healthcare settings, and it can pose a major threat to patient safety. Healthcare-associated infections and AMR result in longer duration of illness, longer treatment, higher mortality, increased costs, and increased burden to health facilities. Objective: The purpose of this study was to generate more reliable estimates of the risk factors for the prevalence of HAI and to investigate patterns of antibiotic prescriptions done. Methods: The survey was conducted in 6 regional hospitals in Sierra Leone (Kono, Kambia, BO, Makeni, Moyamba, and Kenema) from June 16 to July 10 2019. The survey targeted inpatients in the pediatric, maternity, medical, and surgical wards. A structured questionnaire adopted from the WHO PPS form was used to collect information from patient medical charts and care notes. Results: Data were collected from 156 patients, of whom 140 patients were on antibiotics, 100 were women, and 40 were men. Patients on 1 antibiotic regimen accounted for 8.6% (n = 12) and 91.4% (n = 128) on a regimen of 2 or 3 antibiotics. Only 5 patients (3.6%) were on oral antibiotics and 135 (96.4%) were on IV antibiotics. In the maternity ward, 28 of 40 patients (70%) had had a caesarian section and were on 2 or more antibiotics; 18 patients with caesarian sections (64.3%) developed complications and continued on an antibiotic regimen for >1 week. The remaining 12 patients (30%) in the maternity ward were admitted for anemia and hypertension (ie, preeclampsia), and these patients were on 1 antibiotic regimen for which they had no clinical indication. Conclusions: The survey results show that every patient admitted to the hospital was covered with antibiotics with or without indications; no laboratory investigations were performed before antibiotics were initiated. These findings further reveal a large number of patients who were exposed to intravenous cannulation, which predisposes catheter-associated bloodstream infections. The survey results justify the need for an antibiotic stewardship program to guide use of antibiotics.

Funding: None

Disclosures: None

If I am discussing specific healthcare products or services, I will use generic names to extent possible. If I need to use trade names, I will use trade names from several companies when available, and not just trade names from any single company.

Disagree

Christiana Kallon
Measuring Empiric Antibiotic Spectrum Patterns Across Space and Time
Authors: Yarrington Michael , Moehring Rebekah , Anderson Deverick John , Wrenn Rebekah , Sarubbi Christina , Spivey Justin
Published: November 2020

Background: Quantitative evaluation of antibiotic spectrum is an important, underutilized metric in measuring antibiotic use (AU) and may assist antimicrobial stewards in identifying targets and strategy for intervention. We evaluated the spectrum of initial antibiotic choices by hospital location, day of the week, and time of day to determine whether these factors may be associated with broad-spectrum antibiotic choices. Methods: We identified all admissions with antibiotic exposure in medical and surgical wards and critical care units in a tertiary academic medical center between July 1, 2014, and July 1, 2019. The antibiotic spectrum index (ASI), proposed by Gerber et al, is a numeric score based on the number of pathogens covered by a particular agent. We defined ASI for initial antibiotic choice as follows: ASI for each unique antibiotic administered within 24 hours of the first antibiotic administration was summed and assigned to the administration time of the first dose. We categorized time into 4 distinct categories: weekday days (Monday–Friday, 7 a.m.–7 p.m.), weekday nights, weekend days, and weekend nights. Weekend time began 7 p.m. Friday and ended 7 a.m. Monday. We constructed heatmaps stratified by hospital location. Mann-Whitney U tests were applied to evaluate differences in the distributions of ASI using weekday days as a reference. Results: Data included 90,455 unique antibiotic admissions with initial antibiotic starts in medical and surgical wards and critical care units. Patterns of ASI for initial antibiotic choice varied between unit locations and time (Figs. 1 and 2). Mean and median ASIs for initial antibiotic choices were higher for medical ward and medical ICUs than for surgical wards and surgical ICUs. Initial antibiotic choices had higher ASIs during overnight hours for all units except the surgical ICU. Notable differences in ASIs were identified between weekday and weekend prescribing for surgical units, whereas medical units demonstrated less extreme differences. Conclusion: We observed a “weekend effect” across hospital units; the most extreme occurred in surgical wards. This observation may be due to differences in patient volume and rounding patterns. For example, hospitalist and critical care units have 7-day schedules, whereas surgical wards are highly influenced by operating room schedules. Antimicrobial stewardship teams may use these data to identify strategies targeting the most opportune time and place to intervene on the spectrum of initial antibiotic choice.

Funding: None

Disclosures: None
Evaluating Facility Characteristics and Connectivity Metrics as Predictors of Clostridioides difficile Rates in Nursing Homes, Atlanta, GA
Authors: Sefton Samantha , Goodenough Dana , Saiyed Sahebi , Fridkin Scott
Published: November 2020

Background: Nursing home (NH) residents are at high risk for Clostridioides difficile infection (CDI) due to older age, frequent antibiotic exposure, and previous healthcare exposure. Incidence of CDI attributed to NHs is not well established, but it is hypothesized to be related to the magnitude of transfers. We evaluated the relationship between NH CDI incidence and facility characteristics to explain variability in rates in Atlanta, Georgia. Methods: Incident C. difficile cases from 2016 to 2018 were identified through the Georgia Emerging Infections Program (funded by the Centers for Disease Control and Prevention), which conducts active population-based surveillance in the 8-county metro Atlanta area. An incident case was defined as an NH resident with a toxin-positive stool specimen (without a positive test within 8 weeks). Sampled (1 to 3 on age and gender) incident cases were attributed to a NH if a patient was an NH resident within 4 days of specimen collection. Facility characteristics (beds, resident days, admissions, and average length of stay [ALOS]) were obtained from NH cost reports, and facility-specific connectivity metrics were calculated (indegree and betweenness) from 2016 Medicare claims data. Case counts were aggregated to estimate yearly incidence and correlated with facility characteristics and location within the healthcare network using the Spearman correlation. A negative binomial model was used to assess residual variability in NH CDI incidence. Results: In total, 386 incident CDI cases were attributed to 64 NHs (range, 0–27). Approximately half (54.7%) resided in the NH at the time of specimen collection; however, 33.7% were in inpatient units (≤4 days of admission), and 10.9% were in an emergency room (ER). The frequency of NH CDI cases correlated strongly with admissions (r = .70; P < .01), inversely with ALOS (r = −0.53; P < .01), and moderately with resident days (r = .38; P < .01). After accounting for admissions, incidence (per 1,000 admissions) still varied (Fig. 1) (median 14; range, 0–34). The inverse association with ALOS decreased and incidence no longer correlated with the remaining facility characteristics or location within the healthcare transfer network (P > .05, all comparisons). However, there was residual correlation with connectivity metrics (indegree r = 0.26; P = .04). Conclusions: Our data suggest that attributing CDI to NHs requires the inclusion of hospital and ER-based specimen collection. NH CDI incidence appears highest among facilities with a low ALOS and a high number of admissions; incidence rates calculated per 1,000 admissions may best account for infection risk inherent early in a resident’s stay. Residual variability attributed to connectivity to the healthcare network was of borderline significance and should be further explored in the NH setting.

Funding: None

Disclosures: Scott Fridkin, consulting fee, vaccine industry (spouse)