Background: On December 14, 3 unvaccinated siblings with recent international travel presented to Children’s Hospital Colorado emergency department (CHCO-ED) with fever, rash, conjunctivitis, coryza, and cough. Measles was immediately suspected; respiratory masks were placed on the patients before they entered an airborne isolation room, and public health officials (PH) were promptly notified. Notably, on December 12, 1 ill sibling presented to CHCO-ED with fever only. We conducted an investigation to confirm measles, to determine susceptibility of potentially exposed ED contacts and healthcare workers (HCWs), and to implement infection prevention measures to prevent secondary cases. Methods: Measles was confirmed using polymerase chain reaction testing. Through medical record review and CHCO-ED unit-leader interviews, we identified patients and HCWs in overlapping ED areas with the first sibling, until 2 hours after discharge. Measles susceptibility was assessed through interviews with adults accompanying pediatric patients and HCW immunity record reviews. Potentially exposed persons were classified as immune (≥1 documented measles-mumps-rubella (MMR) vaccination or serologic evidence of immunity), unconfirmed immune (self-reported MMR or childhood vaccination without documentation), or susceptible (no MMR vaccine history or age <12 months). Susceptibility status directed disease control intervention, and contact follow-up was 21 days. Results: On December 14, all 3 siblings (ages 8–11 years) had laboratory-confirmed measles and were hospitalized. CHCO’s rapid isolation of the 3 cases within 5 minutes after presentation to the ED eliminated the need for exposure assessment on the day of hospitalization. However on December 12, the 1 ill sibling potentially exposed 258 ED contacts (90 patients, 168 accompanying adults) and 22 HCWs. The PH department identified 158 immune contacts (61%), 75 unconfirmed immune contacts (29%), and 19 susceptible contacts (8%); 6 contacts (2%) were lost to follow-up. Overall, 15 susceptible contacts received immune globulin (IG) postexposure prophylaxis and 4 contacts were placed on 21-day quarantine. Unconfirmed immune contacts self-monitored for measles symptoms and were contacted weekly by PH for 21 days. Moreover, 20 immune HCWs monitored symptoms daily; 2 susceptible HCWs were placed on 21-day quarantine. No secondary cases were identified. Conclusions: Rapid measles identification and isolation, high levels (90%) of immunity among contacts, prompt administration of IG, and effective collaboration between PH and CHCO prevented transmission.

Funding: None

Disclosures: None

Background: Sensitive diagnostic testing is critical in responses to mumps outbreaks. PCR testing of buccal swabs is the most sensitive diagnostic test, but IgM serology remains standard in much of the United States. We provided testing guidance stressing use of mumps PCR to ambulatory clinics and emergency departments in addition to the standard serologic testing for acute mumps beginning in 2018. We compared the performance of PCR and IgM serology to assess cases of parotitis presenting during a community outbreak of mumps in fall 2019 associated with a university in Charleston, SC. Methods: All patients tested for mumps who presented to our facility (ER and ambulatory clinics) with mumps PCR and/or mumps IgM ordered between September 2019 and January 2020 were included. Mumps PCRs were sent to a commercial reference laboratory (ARUP). Confirmed cases were defined as having a positive mumps PCR and/or IgM with parotitis. Clinical characteristics of mumps patients including age, duration of symptoms, MMR history, and association with the university were obtained by chart review. Results: Mumps was confirmed in 15 of 44 tested patients (34%), with 15 of 15 mumps patients (100%) having positive PCR and 1 of 15 patients (7%) and 1 of 15 patients (7%) having positive and equivocal mumps IgM serologies, respectively. Only 1 patient who did not meet our mumps case definition (no CT imaging evidence of parotitis, no fevers, chronic sinus symptoms) had a positive PCR and had recent receipt of a third MMR dose in response to the ongoing outbreak. Median age for mumps patients was 22 years (range, 15–48) with 8 of 15 cases (53%) detected among university students and an additional 2 cases having close connections to the university associated with the outbreak. Only 1 of 15 mumps patients (6.7%) was febrile at presentation (median temperature, 37.2°C) and mumps cases presented for testing ≤3 days for 7 of 15 cases (47%) (range, 0–13 days from symptom onset). No cases were diagnosed by IgM only, and 10 of 15 mumps cases had some recollection of remote MMR immunization, whereas 6 of 15 (40%) had 2 documented MMR doses at <5 years of age. Conclusion: Serologic IgM testing for diagnosis of mumps appears insensitive for detection of cases in outbreaks within highly immunized adult patients. Although our recommended shift to PCR likely enhanced case finding during this outbreak, the potential for false-positive PCRs due to vaccine strain shedding following third-dose MMR immunization may also be considered a threat to the specificity of the test during outbreak situations.

Funding: None

Disclosures: None

Background: We previously showed that ~25% of Veterans’ Affairs (VA) long-term care facility (LTCF) residents had 1 or more indwelling medical devices. Of these devices, 36% were indwelling urinary catheters, 18% were percutaneous gastrostomy tubes, 12% were peripherally inserted central catheters, 8% were suprapubic urinary catheters, and 6% were peripheral intravenous catheters. Approximately 11% of those with an indwelling device developed an LTCF-acquired infection, compared to 3.5% of those without a device. Methicillin-resistant Staphylococcus aureus (MRSA) is a targeted multidrug-resistant organism (MDRO) in all VA LTCFs nationwide. All admissions to VA LTCFs are screened for MRSA carriage upon admission and, since 2013, those that screen positive (~21%) are placed in VA enhanced barrier precautions (EBPs). VA EBPs require that all healthcare workers entering a resident’s bedroom don gowns and gloves for specific activities likely to be associated with contamination of the worker’s hands and clothes. With proper hand hygiene and clean clothing, the colonized resident is encouraged to leave their bedroom and participate fully in all LTCF activities. In July 2019, the US Centers for Disease Control and Prevention (CDC) recommended the use of EBPs for all residents in LTCFs with a wound or device regardless of their colonization status if a resident is identified within the facility with novel or targeted MDROs including panresistant organisms, carbapenemase-producing gram-negative bacteria, and Candida auris. Methods: We assessed the potential impact of this recommendation on VA LTCFs by asking our 133 LTCFs to do a 1-day point-prevalence survey. Results: In total, 63 sites (47%) responded. On the survey day, there were 4,777 residents in the participating facilities, of whom 891 (18.7%) were under EBPs or contact precautions (CPs) for MRSA or other MDROs. Moreover, 963 (20.2%) residents (not already in EBP or CP) had a wound or an indwelling device such as central venous catheter, urinary catheter, feeding tube, tracheostomy or were on a ventilator (if >1 device, resident counted only once). If newly published CDC recommendations were implemented for novel or targeted MDRO precautions in VA LTCFs nationwide, 1,854 residents (38.8%) in VA LTCFs would be placed under EBPs or CPs. Conclusions: In VA LTCFs, adopting the CDC recommendation to place all patients with wounds or indwelling devices under EBPs regardless of colonization status would increase the percentage of residents on transmission-based precautions to ~40% (nearly doubling those in an isolation precaution status).

Funding: None

Disclosures: None

Background: Inappropriate use of antibiotics in hospitalized settings contributes to the selection and emergence of antimicrobial-resistant pathogens. This trend is particularly challenging in resource-constrained settings where the high burden of infectious diseases, combined with suboptimal infection prevention and control measures, are further complicated by limited access to reliable microbiological services to inform antimicrobial prescription at the patient level. In this study, we describe the use of antibiotics in selected Haitian hospitals; we aimed to create a baseline to inform antimicrobial stewardship interventions. Methods: WHO/PAHO Hospital Antibiotic Use Point Prevalence Survey (HAMU-PPS) were conducted in 6 acute-care Haitian hospitals: La-Paix and Hospital-Albert (June 2019) and Hospital-Universitaire-Justinien, Hospital-Bienfaisance-de-Pignon, Hospital-Sacre-Coeur-de-Milot, and Hospital Immaculee-Conception-des-Cayes (July-August 2019) in 6 different cities. Trained data collectors completed electronic forms using REDCap software including data related to antibiotic use, indications, and utilization of laboratory services from medical records of all inpatients meeting study inclusion criteria. Analyses were done using Microsoft Excel software (v2016). Results: In total, 510 inpatients records were surveyed. Patients ages ranged from 0 to 92, with median age of 27 years (IQR, 4–47); 269 were women (57.7%) and 239 were men (46.9%). The prevalence of antibiotic use was 73% (95% CI, 68.2%–81.8 %); this prevalence was 74.5% among men (178 of 239) and 70.6% among women (190 of 269). The highest antibiotic use was observed among children aged <1 year (98 of 108, 90.7%). Of the patients on antibiotics, 63% were treated with >1 antibiotic. In addition, 384 indications for antibiotic prescription were reported. Of the indications for antibiotics therapy, 49.7% (191 of 384) were for treatment, and 49% (188 of 384) were for prophylaxis. Of the treatments, 92% were empiric with 6% reported as targeted. Only 13% (50 of 370) of the patient records indicated that samples were taken for microbiological identification. Of those, 9 had results for culture, and 1 had results for drug susceptibility. The most commonly reported antibiotic was ceftriaxone (n = 110, 23%) followed by ampicillin (n = 153, 21.4%) and metronidazole (n = 135, 20%). Conclusions: This study shows high use of antibiotics among hospitalized patients in Haitian hospitals, especially in children aged <1 year. Almost all the antibiotics were prescribed as either empiric or prophylaxis therapy, with very few microbiology samples collected. These results suggest limited laboratory corroboration across hospitals to inform antibiotic use. Implementation of antimicrobial stewardship interventions is recommended to optimize antibiotic therapy and to mitigate antimicrobial resistance in hospital care settings, but adaptation of the methodology should be done in settings with limited laboratory capacity.

Funding: None

Disclosures: None

Background: The emergence of carbapenem-resistant Enterobacteriaceae (CRE) in companion animals will be a game changer for infection prevention and control strategies in veterinary and human healthcare facilities. CRE have emerged as an important cause of human healthcare-associated infections and are a major clinical and public health problem. Although reports of CRE from animals are still very rare, they have been documented in China, Europe, and the United States. Methods: In April 2019, a passive veterinary surveillance system identified the blaNDM-5 gene in an E. coli isolated from a dog in Philadelphia in July 2018. CRE are reportable to the Philadelphia Department of Public Health (PDPH), and in May 2019, the Matthew J. Ryan Veterinary Hospital at the University of Pennsylvania (MJRVH) reported a cluster of carbapenem-resistant E. coli (CR-E. coli) isolated from 14 animals to the PDHP. This cluster of 17 isolates, that all contained a blaNDM-5 gene, was the first report of a CR-E. coli outbreak at a US veterinary facility. The first isolate, E. coli 24213-18, was sequenced on the Pacific Biosciences (PacBio) Sequel Sequencer and has been uploaded to GenBank. Whole genome sequencing was performed on all 17 isolates using the Illumina MiSeq platform. Antimicrobial resistance genes were identified from the National Center for Biotechnology Information Pathogen Detection Isolates Browser using AMRFinder. Results: PacBio sequencing confirmed E. coli ST167 and identified a circular IncFII plasmid of 139,547 bp that contained the blaNDM-5 gene, along with many additional resistance genes. In June 2019, a retrospective review of hospital records was completed and showed that, from July 2018, 17 CR- E. coli were isolated from 14 animals. Conclusions: Control of CRE infections in human healthcare settings is challenging because the organisms colonize the gastrointestinal tract and can go undetected. The same issue is to be expected with companion animals. Healthcare-associated spread of CRE E. coli in a veterinary facility emphasizes the importance of rapidly identifying and characterizing carbapenem-resistant isolates from animals. Methods to control the spread of CRE in veterinary medical settings have not yet been studied, and related investigations will be critically important to limit the transmission of these pathogens in animal populations. The risk of transmission of CRE from animals to people is currently poorly understood. CRE will be a major challenge across all health fields as these organisms become more prevalent in the community. It is likely that a ‘One Health’ approach to surveillance, infection prevention, and antimicrobial stewardship will be required to limit the spread and potential global dominance of CRE.

Funding: None

Disclosures: None

Background: Orthopedic procedures are performed at high volumes in Australia. Thus, they are a commonly audited procedure group when measuring surgical antimicrobial prophylaxis (SAP) appropriateness and compliance in Australia and internationally. Recent analysis of the Surgical National Antimicrobial Prescribing Survey (Surgical NAPS) revealed high rates of inappropriateness, both procedurally (39.5%) and postprocedurally (53.0%). Inappropriate use can lead to patient harm and further increases the risk of antimicrobial resistance (AMR). Identification of factors associated with inappropriate orthopedic SAP prescribing may support the development of antimicrobial stewardship (AMS) interventions that are tailored to the orthopedic surgical setting to improve SAP. Methods: Surgical NAPS has been available to all Australian hospitals to complete from 2016; it supports the assessment of SAP appropriateness. Appropriateness is a composite measure based on antibiotic choice, timing of administration, dose and duration, applying the standardized Surgical NAPS Appropriateness Assessment Guide. Logistic regression was used to identify hospital, patient, and surgical factors associated with appropriateness. Adjusted appropriateness (AA) was calculated by generating marginal means from the multivariable model and averaging across all available covariates. Significance for multivariable analysis was determined as P < .05. Additional subanalyses were conducted on smaller subsets to calculate the AA for specific orthopedic procedures. Results: In total, 140 facilities contributed to orthopedic audits in the Surgical NAPS from January 1, 2016, to April 15, 2019, including 4,032 orthopedic surgical episodes and 6,709 prescribed doses. Overall appropriateness for prescribed procedural doses (n = 3,978) was 64.7% and was lower for prescribed postprocedural doses (n = 2,731, 48.3%). When antimicrobials were not prescribed, appropriateness was higher procedurally (n = 350, 89.7%) and postprocedurally (n = 1,127, 97.8%). When SAP was indicated, the most common reasons for inappropriateness, when prophylaxis was indicated, were timing for procedural doses (50.9%) and duration for postprocedural prescriptions (49.8%). The AA of each orthopedic procedure group was low for procedural SAP, ranging from 54.1% for knee surgery to 74.1% for total knee joint replacement. The adjusted appropriateness of postprocedural prescriptions was also low, ranging from 40.7% for hand surgery to 68.7% for closed reduction fractures. Conclusions: Orthopedic surgical specialties demonstrated differences across procedural and postprocedural appropriateness. The metric of appropriateness is meaningful for both orthopedic surgeons and AMS programs. Targeted quality improvement projects are needed for orthopedic surgical procedures and to study the engagement between orthopedic surgeons, AMS, and guideline developers to support optimization of antimicrobial use in the surgical setting.

Funding: None

Disclosures: None

Background: Probiotics are protective against Clostridioides difficile infection and antibiotic-associated diarrhea, and they may decrease risk of infections following complex abdominal surgeries. Infectious risks associated with probiotic use are not well described in the literature. We describe probiotic use among patients with bloodstream infections (BSIs) due to organisms typically found in probiotics. Methods: Patients with positive blood cultures with Lactobacillus spp, Saccharomyces spp, and Bifidobacterium spp at our large academic hospital from October 2016 through October 2019 were identified using Theradoc, a clinical surveillance tool. Clinical data and orders for probiotics, including probiotic capsules, probiotic yogurt, and kefir, were extracted from the electronic medical record. Cases were considered distinct if the cultures were collected 7 or more days apart. True infections were defined as positive cultures which were treated with antimicrobials and had provider documentation outlining clinical relevance of culture data. Results: Among 26 distinct episodes of BSI, 16 (62%) were considered true infections. The remaining 10 cases were interpreted as contaminants or of unclear significance. Of the 16 cases representing true infection in 14 patients, 6 (38%) had received probiotics in the hospital in the preceding month. Among these patients, 5 had Lactobacillus bacteremia and had received Lactobacillus capsules, probiotic yogurt, and/or kefir. One patient had Saccharomyces fungemia following receipt of probiotic yogurt and kefir. All 6 patients with BSI possibly related to probiotic use had an antecedent gastrointestinal procedure or surgery within a month of the BSI, and 2 had intra-abdominal abscesses from which the same organism was cultured. Of the 16 true BSIs, 9 occurred in immunocompromised hosts, but antecedent probiotic use was confirmed in only 1 of these cases. Two episodes caused by different organisms occurred within the same month; all other episodes were >60 days apart. Conclusions: In our retrospective review of BSIs with organisms typically found in probiotics over a 3-year period at a large academic hospital, more than one-third of those with clinically relevant BSIs had antecedent probiotic use within the hospital. All patients with infections possibly related to probiotic use had recent gastrointestinal procedures or surgery, raising concern for probiotic use following interventions that increase the risk for gastrointestinal tract leakage or translocation. Further research is necessary to assess the risk of bloodstream infection in postoperative patients treated with probiotics.

Funding: None

Disclosures: None

Background: Blood cultures are essential diagnostic tools used to identify bloodstream infections and to guide antimicrobial therapy. However, collecting cultures without clear indications or that do not inform management can lead to false-positive results and unnecessary use of antibiotics. Blood culture practices vary significantly in critically ill children. Our objective was to create a consensus guideline focusing on when to safely avoid blood cultures in pediatric intensive care unit (PICU) patients. Methods: A panel of multidisciplinary experts, many participating in the Blood Culture Improvement Guidelines and Diagnostic Stewardship for Antibiotic Reduction in Critically Ill Children (Bright STAR) Collaborative, engaged in a 2-part modified Delphi process. Round 1 consisted of a preparatory literature summary and an electronic survey sent to subject matter experts (SMEs). In the survey, SMEs rated a series of recommendations about when to avoid blood cultures on a 5-point Likert scale, 1 being the lowest score and 5 being the highest score. Consensus was achieved for each recommendation if 75% of respondents chose a score of 4 or 5, and these were included in the final guideline. Any recommendations that did not meet these a priori criteria for consensus were set aside for discussion during the in-person expert panel review (round 2). An outside expert in consensus methodology facilitated round 2. After a review of the survey results and comments from round 1 and group discussion, the SMEs voted on these recommendations in real time. Voting was blinded. Participants included Bright STAR site leads, national content experts, and representatives from relevant national societies. Results: We received 29 completed surveys from 34 invited participants for an 85% response rate. Of the 27 round 1 recommendations, 18 met predetermined criteria for consensus. Round 2 included 26 in-person voting participants who (1) discussed and modified the 9 recommendations that had not met round 1 consensus, and (2) modified for clarity or condensed from multiple into single recommendations the 18 recommendations that had met the round 1 consensus. The final document contains 19 recommendations that provide guidance on how to safely improve blood culture use in PICU patients (Table 1). Also, 8 recommendations discussed did not reach consensus for inclusion. Conclusions: Using a modified Delphi process, we created consensus recommendations on when to avoid blood cultures and prevent overuse in critically ill children. These guidelines are a critical step in disseminating diagnostic stewardship and reducing unnecessary testing on a wider scale.

Funding: Agency for Healthcare Research and Quality, R18 HS025642-01, 9/2017 – 9/2020 (Aaron Milstone, PI)

Disclosures: None

Background: When control mechanisms such as water temperature and biocide level are insufficient, Legionella, the causative bacteria of Legionnaires’ disease, can proliferate in water distribution systems in buildings. Guidance and oversight bodies are increasingly prioritizing water safety programs in healthcare facilities to limit Legionella growth. However, ensuring optimal implementation in large buildings is challenging. Much is unknown, and sometimes assumed, about whether building and campus characteristics influence Legionella growth. We used an extensive real-world environmental Legionella data set in the Veterans Health Administration (VHA) healthcare system to examine infrastructure characteristics and Legionella positivity. Methods: VHA medical facilities across the country perform quarterly potable water sampling of healthcare buildings for Legionella detection as part of a comprehensive water safety program. Results are reported to a standardized national database. We did an exploratory univariate analysis of facility-reported Legionella data from routine potable water samples taken in 2015 to 2018, in conjunction with infrastructure characteristics available in a separate national data set. This review examined the following characteristics: building height (number of floors), building age (reported construction year), and campus acreage. Results: The final data set included 201,936 water samples from 819 buildings. Buildings with 1–5 floors (n = 634) had a Legionella positivity rate of 5.3%, 6–10 floors (n = 104) had a rate of 6.4%, 11–15 floors (n = 36) had a rate of 8.1%, and 16–22 floors (n = 9) had a rate of 8.8%. All rates were significantly different from each other except 11–15 floors and 16–22 floors (P < .05, χ2). The oldest buildings (1800s) had significantly less (P < .05, χ2) Legionella positivity than those built between 1900 and 1939 and between 1940 and 1979, but they were no different than the newest buildings (Fig. 1). In newer buildings (1980–2019), all decades had buildings with Legionella positivity (Fig. 1 inset). Campus acreage varied from ~3 acres to almost 500 acres. Although significant differences were found in Legionella positivity for different campus sizes, there was no clear trend and campus acreage may not be a suitable proxy for the extent or complexity of water systems feeding buildings. Conclusions: The analysis of this large, real-world data set supports an assumption that taller buildings are more likely to be associated with Legionella detection, perhaps a result of more extensive piping. In contrast, the assumption that newer buildings are less associated with Legionella was not fully supported. These results demonstrate the variability in Legionella positivity in buildings, and they also provide evidence that can inform implementation of water safety programs.

Funding: None

Disclosures: Chetan Jinadatha, principal Investigator/Co-I: Research: NIH/NINR, AHRQ, NSF principal investigator: Research: Xenex Healthcare Services. Funds provided to institution. Inventor: Methods for organizing the disinfection of one or more items contaminated with biological agents. Owner: Department of Veterans Affairs. Licensed to Xenex Disinfection System, San Antonio, TX.

Background: The burden of C. difficile infection (CDI) on healthcare facilities is well recognized. However, studies focusing on inpatient settings, in addition to ascertainment bias in general, have led to a paucity of data on the true burden of CDI across whole healthcare economies. Methods: Sites testing both inpatient and community samples were recruited from 12 European countries (1 site per 3 million population). On 2 selected days, all diarrheal fecal samples (regardless of tests requested) were sent to the European Coordinating Laboratory (ECL) for C. difficile toxin testing and culture. The CDI results and tests not requested at each submitting site were compared with the ECL results to determine the number of missed CDIs. Contemporaneous C. difficile isolates from food and animal sources were collected. All isolates underwent PCR ribotyping and toxinotyping; prevalences of ribotypes among regions of Europe and reservoir settings were compared. Results: Overall, 3,163 diarrheal fecal samples were received from 119 sites. The burden of CDI varied by country (positivity rates, 0–15.8%) and by European region; the highest positivity rate in Eastern Europe was 13.1%. The testing and positivity rates in community samples were 29.6% and 1.4% vs 74.9% and 5.0% in hospital samples; 16% and 55% of samples positive for CDI at ECL were not diagnosed in hospitals and the community. The most common C. difficile ribotypes from hospital samples were 027 (11%), 181 (12%), and 014 (8%), although prevalence varied by country. The highest prevalence of toxinotype IIIb (ribotypes 027, 181, and 176) was seen in Eastern Europe (55% of all isolates), which also had the lowest testing rate. For hospital samples, the proportion of toxinotype IIIb was inversely related to the testing rate (r = −0.79) (Fig. 1). The most common ribotypes from food sources were 078 (23%) and 126 (13%) (toxinotype V), and most common ribotypes from community samples were 078 (9%) and 039 (9%). Overall, 106 different ribotypes were identified: 25 in both the hospital and community and 16 in the hospital, community, and food chain. Conclusions: The diagnosed burden of CDI varies markedly among countries in both hospital and community settings. Reduced sampling/testing in Eastern Europe is inversely related to the proportion of toxinotype IIIb strains identified, suggesting that lack of suspicion leads to underdiagnosis and outbreaks of infection. The proportion of missed CDIs in the community was ~3.5× higher than in hospitals, indicating major underrecognition in the former setting. There were marked differences in ribotypes in different reservoir settings, emphasizing the complex epidemiology of C. difficile.

Funding: Proprietary organization: COMBACTE-CDI is an EU funded (Horizon2020) consortium of academic and EFPIA partners (bioMerieux, GSK, Sanofi Pasteur, Astra Zeneca, Pfizer, Da Volterra) with additional Funding: from the EFPIA partners.

Disclosures: Submitter: Kerrie Davies; the work presented is funded via the EU and EFPIA (commercial) partners in a consortium.

Background: Due to limited therapeutic options and potential for spread, carbapenem-resistant Enterobacteriaceae (CRE)-producing New Delhi metallo-β-lactamases (NDMs) are a public health priority. We investigated the epidemiology of NDM-producing CRE reported to the CDC to clarify its distribution and relative prevalence. Methods: The CDC’s Antibiotic Resistance Laboratory Network supports molecular testing of CRE for 5 carbapenemases nationally. Although KPC is the most common carbapenemase in the United States, non-KPC carbapenemases are a growing concern. We analyzed CRE with any of 4 non-KPC plasmid-mediated carbapenemases (NDM, VIM, IMP, or OXA-48 type) isolated from specimens collected from January 1, 2017, through June 30, 2019; only a patient’s first isolate per organism–carbapenemase combination was included. We excluded isolates from specimen sources associated with colonization screening (eg, perirectal). We compared the proportion of NDM-producing CRE to all non-KPC–producing CP-CRE between period A (January to June 2018) and period B (January to June 2019). Health departments and the CDC collected additional exposure and molecular information in selected states to better describe current NDM-producing CRE epidemiology. Results: Overall, 47 states reported 1,013 non–KPC-producing CP-CRE (range/state, 1–109 isolates; median, 11 isolates); 46 states reported 631 NDM-producing CRE (range/state, 1–84; median, 6). NDM-producing CRE increased quarterly from the third quarter of 2018 through the second quarter of 2019; CP-CRE isolates with other non-KPC carbapenemases remained stable (Fig. 1). In period A, 124 of 216 emerging CP-CRE had NDM (57.1%), compared with 255 of 359 emerging CP-CRE (71.0%) during period B (P = .1179). Among NDM-producing CRE, the proportion of Enterobacter spp increased from 10.5% in 2018 to 18.4% in 2019 (P = .0467) (Fig. 2). In total, 18 states reported more NDM-producing CRE in the first 6 months of 2019 than in all of 2018. Connecticut, Ohio, and Oregon were among states that conducted detailed investigations; these 3 states identified 24 NDM-producing CRE isolates from 23 patients in period B. Overall, 5 (21.7%) of 22 patients with history available traveled internationally ≤12 months prior to culture; 17 (73.9%) acquired NDM-producing CRE domestically. Among 15 isolates sequenced, 8 (53.3%) carried NDM-5 (6 E. coli, 1 Enterobacter spp and 1 Klebsiella spp) and 7 (46.7%) carried NDM-1 (6 Enterobacter spp and 1 Klebsiella spp). Species were diverse; no single strain type was shared by >2 isolates. Conclusions: Detection of NDM-producing CRE has increased across the AR Lab Network. Among states with detailed information available, domestic acquisition was common, and no single variant or strain predominated. Aggressive public health response and further understanding of current US NDM-CRE epidemiology are needed to prevent further spread.

Disclosures: None

Funding: None

Background: Chlorhexidine bathing reduces bacterial skin colonization and prevents infections in specific patient populations. As chlorhexidine use becomes more widespread, concerns about bacterial tolerance to chlorhexidine have increased; however, testing for chlorhexidine minimum inhibitory concentrations (MICs) is challenging. We adapted a broth microdilution (BMD) method to determine whether chlorhexidine MICs changed over time among 4 important healthcare-associated pathogens. Methods: Antibiotic-resistant bacterial isolates (Staphylococcus aureus from 2005 to 2019 and Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae complex from 2011 to 2019) were collected through Emerging Infections Program surveillance in 2 sites (Georgia and Tennessee) or through public health reporting in 1 site (Orange County, California). A convenience sample of isolates were collected from facilities with varying amounts of chlorhexidine use. We performed BMD testing using laboratory-developed panels with chlorhexidine digluconate concentrations ranging from 0.125 to 64 μg/mL. After successfully establishing reproducibility with quality control organisms, 3 laboratories performed MIC testing. For each organism, epidemiological cutoff values (ECVs) were established using ECOFFinder. Results: Among 538 isolates tested (129 S. aureus, 158 E. coli, 142 K. pneumoniae, and 109 E. cloacae complex), S. aureus, E. coli, K. pneumoniae, and E. cloacae complex ECVs were 8, 4, 64, and 64 µg/mL, respectively (Table 1). Moreover, 14 isolates had an MIC above the ECV (12 E. coli and 2 E. cloacae complex). The MIC50 of each species is reported over time (Table 2). Conclusions: Using an adapted BMD method, we found that chlorhexidine MICs did not increase over time among a limited sample of S. aureus, E. coli, K. pneumoniae, and E. cloacae complex isolates. Although these results are reassuring, continued surveillance for elevated chlorhexidine MICs in isolates from patients with well-characterized chlorhexidine exposure is needed as chlorhexidine use increases.

Funding: None

Disclosures: None

Background: The Tennessee (TN) Department of Health (TDH) has been identifying clusters of reportable conditions using the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), a cluster detection method using space-time scan permutation statistics based on patient ZIP code. CRE are reportable in Tennessee; isolate submission is required for carbapenemase (CP) production and resistance mechanism (eg, KPC gene) testing. The Council for Outbreak Response: Healthcare-Associated Infections (HAI) and Antimicrobial-Resistant (AR) Pathogens (CORHA) released proposed thresholds of reporting CRE to public health. Thresholds vary by healthcare facility type and regional epidemiology. The TDH HAI/AR program currently runs a daily automated SAS code using the CORHA reporting threshold to help public health identify suspect KPC clusters. We evaluated our rule-based CORHA method against 2 space-time statistic-based methods for KPC cluster detection in Tennessee. Methods: Simulations for each cluster detection method were performed using retrospective CP-CRE surveillance data for 2018. Simulations were conducted using (1) CORHA reporting thresholds by facility case count to flag clusters of 2 or more cases within 28 days, (2) ESSENCE using patient residence ZIP code and the earliest of collection date or symptom onset date as is used for other reportable conditions in Tennessee, and (3) a modified space-time statistical method using SaTScan in which reporting facility, rather than a geographic location, was used as space variable to detect within-facility clusters within 1–28 days. We compared the number and overlap of cases and clusters identified with each method. Univariate logistic regression with CORHA flagging as predictor and flagging by each ESSENCE or CORHA method as outcome variables, were used to compare cases tagged by each method pair, respectively. Results: Of 183 KPC CP-CRE cases, 54 (30.6%) were flagged as part of suspect clusters by at least 1 method. Simulations generated 16 alerts (36 cases) using CORHA, 10 clusters (25 cases) using modified SaTScan, and 10 clusters (20 cases) using standard ESSENCE protocol. Among KPC CP-CRE cases flagged by CORHA, 12 (33.3%) were also flagged by modified SaTScan and 2 (5%) by ESSENCE. A case flagged using CORHA method has 5.15 (95% CI, 2.10–12.64) times higher odds of also being flagged by the modified SaTScan method compared to cases not flagged by CORHA. Conclusions: An algorithm based on CORHA thresholds for reporting CRE to public health had strong agreement with modified SaTScan, a space-time method. We intend to explore the extension of the time interval for ESSENCE.

Funding: None

Disclosures: None

Background: Estimates of contamination of healthcare personnel (HCP) gloves and gowns with methicillin-resistant Staphylococcus aureus (MRSA) following interactions with colonized or infected patients range from 17% to 20%. Most studies were conducted in the intensive care unit (ICU) setting where patients had a recent positive clinical culture. The aim of this study was to determine the rate of MRSA transmission to HCP gloves and gown in non-ICU acute-care hospital units and to identify associated risk factors. Methods: Patients on contact precautions with history of MRSA colonization or infection admitted to non-ICU settings were randomly selected from electronic health records. We observed patient care activities and cultured the gloves and gowns of 10 HCP interactions per patient prior to doffing. Cultures from patients’ anterior nares, chest, antecubital fossa and perianal area were collected to quantify bacterial bioburden. Bacterial counts were log transformed. Results: We observed 55 patients (Fig. 1), and 517 HCP–patient interactions. Of the HCP–patient interactions, 16 (3.1%) led to MRSA contamination of HCP gloves, 18 (3.5%) led to contamination of HCP gown, and 28 (5.4%) led to contamination of either gloves or gown. In addition, 5 (12.8%) patients had a positive clinical or surveillance culture for MRSA in the prior 7 days. Nurses, physicians and technicians were grouped in “direct patient care”, and rest of the HCPs were included in “no direct care group.” Of 404 interactions, 26 (6.4%) of providers in the “direct patient care” group showed transmission of MRSA to gloves or gown in comparison to 2 of 113 (1.8%) interactions involving providers in the “no direct patient care” group (P = .05) (Fig. 2). The median MRSA bioburden was 0 log 10CFU/mL in the nares (range, 0–3.6), perianal region (range, 0–3.5), the arm skin (range, 0-0.3), and the chest skin (range, 0–6.2). Detectable bioburden on patients was negatively correlated with the time since placed on contact precautions (rs= −0.06; P < .001). Of 97 observations with detectable bacterial bioburden at any site, 9 (9.3%) resulted in transmission of MRSA to HCP in comparison to 11 (3.6%) of 310 observations with no detectable bioburden at all sites (P = .03). Conclusions: Transmission of MRSA to gloves or gowns of HCP caring for patients on contact precautions for MRSA in non-ICU settings was lower than in the ICU setting. More evidence is needed to help guide the optimal use of contact precautions for the right patient, in the right setting, for the right type of encounter.

Funding: None

Disclosures: None

Background: Greater than 10% of hospitalized MRSA carriers experience serious MRSA infection in the year following discharge. Prevention opportunities have primarily focused on hospital stays; however postdischarge interventions have the potential to reduce morbidity, mortality and healthcare costs. The CLEAR trial found a 30% hazard reduction in postdischarge MRSA infections among patients who had inpatient MRSA cultures and were given postdischarge decolonization (5 days twice-a-month for 6 months) relative to hygiene education alone. We conducted a cost analysis of the CLEAR intervention to quantify the economic implications and understand the value of adopting this MRSA decolonization strategy. Methods: We constructed a decision model to estimate the one-year healthcare utilization and costs associated with postdischarge decolonization relative to hygiene education. Trial results for MRSA infection risk and downstream outcomes (including outpatient and emergency room visits, hospitalizations, related nursing home stays, and postdischarge antibiotics) were used to parameterize the model. Other medical care and prescription drug costs were based on Medicare Fee Schedules, Red Book and the literature. Patient out-of-pocket costs and time costs associated with subsequent infections were from a survey of trial participants experiencing infection (n=405). All costs were reported in 2019 US dollars. The analysis was conducted using healthcare system and societal perspectives. Sensitivity analyses were conducted on key parameters. Results: Among a hypothetical cohort of 1,000 hospitalized MRSA carriers, we estimated that a postdischarge decolonization intervention versus hygiene education would result in at least 36 fewer subsequent MRSA infections (130 vs 93 of 1,000, respectively) and >40 fewer MRSA-attributable healthcare events including 32 hospitalizations and 6 postdischarge nursing home visits over the course of a year. Assuming an intervention cost of $185 per individual, the program would result in an overall cost savings of $469,000 per 1,000 MRSA carriers undergoing decolonization. This translates to an overall savings of $13,200 per infection averted and $9,000 per infection averted from the healthcare system perspective. Even assuming a lower infection rate or a less effective intervention (15% reduction in infections vs 30% in the CLEAR trial), or a more expensive (up to $653 per patient) intervention, a decolonization program would still result in cost-savings for society, the healthcare system and patients. Conclusions: In addition to health benefits of preventing infections, postdischarge decolonization of MRSA carriers yields substantial savings to society and the healthcare system. Future recommendations for reducing postdischarge MRSA-related disease among MRSA carriers should consider routine decolonization at hospital discharge.

Funding: This study was supported by a grant from the AHRQ Healthcare-Associated Infections Program (R01HS019388) and by the University of California Irvine Institute for Clinical and Translational Science, which was funded by a grant from the NIH Clinical and Translational Sciences Award program (UL1 TR000153).

Disclosures: Dr. Huang reports conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), Mölnlycke, 3M, Clorox, Xttrium Laboratories, and Medline. Ms. Singh reports conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories, and Medline. Dr. Rashid, conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker(Sage Products), Clorox, and Medline. Dr. McKinnell reports receiving grant support to his institution from Melinta Therapeutics, and fees for serving as a research investigator from Lightship, conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories and Medline, and serving as cofounder of Expert Stewardship. Dr. Miller reports receiving grant support from Gilead Sciences, Merck, Abbott, Cepheid, Genentech, Atox Bio, and Paratek Pharmaceuticals, grant support and fees for serving on an advisory board from Achaogen and grant support, consulting fees, and fees for serving on an advisory board from Tetraphase and conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories, and Medline.

Background: Readmissions to hospitals are common, costly and often preventable, notably readmissions due to infections. A 30-day readmission analysis following hospital discharges, found much of the variation in Medicare spending between hospitals was related to readmissions and skilled nursing facility (SNF) care. Although some readmissions of patients with advanced disease are not preventable, efforts to decrease readmission are most effectively directed towards those patients with intermediate levels of a specific risk. A prediction model to identify patients at highest (or intermediate) risk of infection readmission will help healthcare administrators and providers to allocate appropriate resources. Hospitals should use electronic health record (EHR) data with modern data mining techniques to create more curated, sophisticated models as part of a comprehensive transitional care program. We propose using the risk estimates of a validated prediction model to notify stakeholders and develop readmission rate reports by SNF or discharging physician. Methods: We applied machine learning (ML) methods to predict the risk of 30-day readmission due to sepsis and pneumonia of patients discharged to SNF. We used our EHR data during 2012–2017 to train and data from 2018 to validate. We applied ML algorithms to data including logistic regression, random forest, gradient boosting trees, and support vector machine. Data from EDW and EPIC clarity tables were extracted and managed using SAS Base 9.4 and Enterprise Miner 14.3 (SAS Institute, Cary, NC). We assessed the discrimination and calibration to select the most effective prediction model. Using the resulted risk estimates, we created a notification system and reports for key stakeholders. Results: Figures 1 and 2 show the discrimination and calibration results of the final selected gradient boosting model (GBM). For predicting unplanned readmissions with sepsis and with pneumonia within 30 days after discharge to SNF, the c-statistic for final GBM model with 140 features was 0.69 (95% CI 0.65-0.73) and 73 features was 0.71 (95% CI 0.66-0.75), respectively. Table 1 lists features important to the validation set of the prediction model. We used estimates from these models to develop a daily email notification of patients discharged to SNF stratified into a low, medium, and high risk group for sepsis and pneumonia. We additionally created reports with case-mix adjustments to benchmark SNFs and discharging physicians to monitor and understand performance. Conclusions: Hospitals should leverage the plethora of data found in EHRs to curate readmission prediction models, and promote collaboration among transitional care teams and IPC to ultimately reduce readmissions due to sepsis and pneumonia.

Funding: None

Disclosures: None

Background: Medications, medical devices, biological products, and other medical products can cause healthcare-associated infections related to contamination in production or transportation (intrinsic contamination) or contamination at the point of use (extrinsic contamination). Rapid identification of contaminated medical products can lead to actions to decrease further patient harm. We sought to describe events that prompted public health investigations of contaminated medical products in healthcare facilities. Methods: We reviewed records of CDC consultations with health departments and healthcare facilities from January 2015 through August 2019 to identify public health investigations in which medical products were identified as a likely source of patient infection or pathogen transmission to at least 1 patient. We collected data on products, contamination type, pathogens, route of patient exposure, healthcare setting where exposure occurred, and resulting actions. Results: There were 34 investigations involving medications (n = 15, 44%), medical devices (n = 12, 35%), biological products (n = 3, 9%), and other medical products (n = 4, 12%). Intrinsic contamination was suspected in 15 investigations (44%), with 13 (87%) based on isolation of a pathogen from unopened products and 2 (13%) based on isolation of similar pathogens from patients in contact with a medical product at multiple facilities. Extrinsic contamination was suspected in 19 investigations (56%) based on evidence of pathogen transmission at a single healthcare facility and concurrent infection control gaps at that facility supporting a mechanism of contamination. The most common pathogens prompting investigation were nontuberculous mycobacteria (n = 9, 26%), Burkholderia spp (n = 7, 21%), Klebsiella spp (n = 3, 9%), Serratia spp (n = 2, 6%), and other environmental and commensal organisms. Patients were most commonly exposed in hospitals (n = 19, 56%) and outpatient settings (n = 9, 26%). The most common patient exposures that resulted in transmission of the pathogen were infusions and injections (n = 15, 44%), diagnostic and therapeutic procedures (n = 9, 26%), and surgery (n = 5, 15%). Patient were notified and offered testing in at least 6 investigations (18%) . Interventions included product removal, healthcare provider alerts, patient notification and testing, modification of injection safety practices and other general infection control practices, correction of improper storage and handling, and changes in product design, manufacturing processes, or instructions for use. Conclusions: Public health investigations identified intrinsic and extrinsic contamination of medications, devices, and other products as a cause of healthcare-associated infections. Healthcare facilities should consider contaminated products in investigations of healthcare-associated infections, take steps to identify local infection control concerns, and alert public health authorities to events that could suggest widespread contamination.

Funding: None

Disclosures: None

Background: Hospital-onset bacteremia and fungemia (HOB) may be a preventable hospital-acquired condition and a potential healthcare quality measure. We developed and evaluated a tool to assess the preventability of HOB and compared it to a more traditional consensus panel approach. Methods: A 10-member healthcare epidemiology expert panel independently rated the preventability of 82 hypothetical HOB case scenarios using a 6-point Likert scale (range, 1= “Definitively or Almost Certainly Preventable” to 6= “Definitely or Almost Certainly Not Preventable”). Ratings on the 6-point scale were collapsed into 3 categories: Preventable (1–2), Uncertain (3–4), or Not preventable (5–6). Consensus was defined as concurrence on the same category among ≥70% expert raters. Cases without consensus were deliberated via teleconference, web-based discussion, and a second round of rating. The proportion meeting consensus, overall and by predefined HOB source attribution, was calculated. A structured HOB preventability rating tool was developed to explicitly account for patient intrinsic and extrinsic healthcare-related risks (Fig. 1). Two additional physician reviewers independently applied this tool to adjudicate the same 82 case scenarios. The tool was iteratively revised based on reviewer feedback followed by repeat independent tool-based adjudication. Interrater reliability was evaluated using the Kappa statistic. Proportion of cases where tool-based preventability category matched expert consensus was calculated. Results: After expert panel round 1, consensus criteria were met for 29 cases (35%), which increased to 52 (63%) after round 2. Expert consensus was achieved more frequently for respiratory or surgical site infections than urinary tract and central-line–associated bloodstream infections (Fig. 2a). Most likely to be rated preventable were vascular catheter infections (64%) and contaminants (100%). For tool-based adjudication, following 2 rounds of rating with interim tool revisions, agreement between the 2 reviewers was 84% for cases overall (κ, 0.76; 95% CI, 0.64–0.88]), and 87% for the 52 cases with expert consensus (κ, 0.79; 95% CI, 0.65–0.94). Among cases with expert consensus, tool-based rating matched expert consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewer 1 and reviewer 2, respectively. The proportion of cases rated “uncertain“ was lower among tool-based adjudicated cases with reviewer agreement (15 of 69) than among cases with expert consensus (23 of 52) (Fig. 2b). Conclusions: Healthcare epidemiology experts hold varying perspectives on HOB preventability. Structured tool-based preventability rating had high interreviewer reliability, matched expert consensus in most cases, and rated fewer cases with uncertain preventability compared to expert consensus. This tool is a step toward standardized assessment of preventability in future HOB evaluations.

Funding: None

Disclosures: None

Background: Antibiotic resistance has increased at alarming rates, driven predominantly by antibiotic overuse. Although most antibiotic use occurs in outpatients, antimicrobial stewardship programs have primarily focused on inpatient settings. A major challenge for outpatient stewardship is the lack of accurate and accessible electronic data to target interventions. We sought to develop and validate an electronic algorithm to identify inappropriate antibiotic use for outpatients with acute bronchitis. Methods: This study was conducted within the University of Pennsylvania Health System (UPHS). We used ICD-10 diagnostic codes to identify encounters for acute bronchitis at any outpatient UPHS practice between March 15, 2017, and March 14, 2018. Exclusion criteria included underlying immunocompromising condition, other comorbidity influencing the need for antibiotics (eg, emphysema), or ICD-10 code at the same visit for a concurrent infection (eg, sinusitis). We randomly selected 300 (150 from academic practices and 150 from nonacademic practices) eligible subjects for detailed chart abstraction that assessed patient demographics and practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for assessment of the electronic algorithm. Because antibiotic use is not indicated for this study population, appropriateness was assessed based upon whether an antibiotic was prescribed or not. Results: Of 300 subjects, median age was 61 years (interquartile range, 50–68), 62% were women, 74% were seen in internal medicine (vs family medicine) practices, and 75% were seen by a physician (vs an advanced practice provider). On chart review, 167 (56%) subjects received an antibiotic. Of these subjects, 1 had documented concern for pertussis and 4 had excluding conditions for which there were no ICD-10 codes. One received an antibiotic prescription for a planned dental procedure. Thus, based on chart review, 161 (54%) subjects received antibiotics inappropriately. Using the electronic algorithm based on diagnostic codes, underlying and concurrent conditions, and prescribing data, the number of subjects with inappropriate prescribing was 170 (56%) because 3 subjects had antibiotic prescribing not noted based on chart review. The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were the following: sensitivity, 100% (161 of 161); specificity, 94% (130 of 139); positive predictive value, 95% (161 of 170); and negative predictive value, 100% (130 of 130). Conclusions: For outpatients with acute bronchitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. This algorithm could be used to efficiently assess prescribing among practices and individual clinicians. The impact of interventions based on this algorithm should be tested in future studies.

Funding: None

Disclosures: None

Background: Bundles have been proven to reduce the risk of healthcare-associated infections and to provide for rapid recognition and response for the best outcome in patients with sepsis. Each element alone does not provide the statistical significance that all elements together allow. Providing near real-time compliance with bundle measures to clinical staff can drive performance improvement with the bundle during the patient’s hospital stay, resulting in improved clinical care and prevention of infection. Methods: In 2019, 3 clinical initiatives were chartered that applied evidence-based bundles for early identification and treatment of sepsis, prevention of healthcare-associated pneumonia (HAP), and prevention of surgical site infection. The bundle included the following elements: assessment of sepsis, measurement of lactic acid, collection of blood culture, timely administration of antibiotics. The HAP bundle included the following elements: assessment of aspiration risk, elevation of the head of the bed, oral care twice daily and preoperatively, and incentive spirometry postoperatively. And the SSI bundle included the following elements: preoperative CHG bath, appropriate preoperative antibiotic, perioperative glucose control, and perioperative temperature control. A multidisciplinary team developed and implemented dashboards that extracted bundle elements from the electronic medical record (EMR) nightly. Bundle compliance was calculated at the individual element level as well as the aggregate. Bundle failure data were available at the patient level as well as in aggregate by care location and provider, allowing for real-time feedback to staff and creation of improvement plans. An unanticipated benefit was the identification and correction of charting inconsistencies. Results: Collection, aggregation, and analysis of bundle compliance data were displayed in a system dashboard, and data were refreshed nightly. This approach allowed us to display overall bundle compliance at the facility and system level, including a heat map showing each facility’s compliance with the bundle and each associated element. Utilization of an EMR dashboard allowed for performance review on 100% of eligible patients rather than a sample, as occurs with manual review and abstraction processes. Routine review of performance via the dashboards with frontline staff, clinical leaders, medical staff, and executives has resulted in month-by- month improvement in bundle compliance. Conclusions: Direct data mining, data aggregation and analysis, followed by direct feedback to frontline staff, has resulted in steady improvement in overall bundle compliance, compliance with individual bundle components, and standardization of charting in the EMR. This approach has ultimately resulted in better outcomes for sepsis patients, reduction in healthcare-associated pneumonia, and reduction in surgical site infections.

Funding: None

Disclosures: None