Background: Despite introduction of mandatory vaccination of healthcare workers (HCWs) in 2011, we continued to see occasional cases of nosocomial influenza. We sought to understand the characteristics of patients who acquired nosocomial influenza to better target prevention efforts. Methods: The study population was a retrospective cohort of all patients aged ≥18 years admitted to an academic medical center between September 2012 and August 2018. Patient data obtained included age, admission/discharge date, service line, influenza vaccination status on admission, and virus serotype. Nosocomial influenza was defined as positive polymerase chain reaction (PCR) or antigen testing for influenza A/B >3 days after admission. Each influenza season, patients with nosocomial influenza or community-acquired influenza (CA-I) were censored after the positive test. Means with standard deviations are reported (SAS version 9.4). Results: Overall, 223,005 patient admissions occurred during the study period: 222,154 (99.6%) were without confirmed influenza infection, 788 (0.35%) had CA-I, and 63 (0.03%) had nosocomial influenza (Fig. 1). The mean age of patients without influenza infection was 57.6 ± 19.3 years compared to 66.5 ± 18.8 years for those with CA-I and 67.1 ± 13.5 with nosocomial influenza. Influenza A accounted for 630 cases (80%) of CA-I, and 58 cases (92%) of nosocomial influenza. Also, 31 (48%) with nosocomial influenza had been vaccinated against influenza prior to admission (Table 1). Most nosocomial influenza cases (78%) occurred on medicine and oncology units. Conclusions: Influenza A represented a larger percentage of nosocomial influenza compared to CA-I. The proportion of nosocomial influenza cases remained stable during the study period, even after introduction of PCR tests in the 2014–2015 season. The mean age of the nosocomial influenza group was greater compared to the CA-I and no influenza groups. More than half of nosocomial influenza cases were unvaccinated at the time of admission, demonstrating the importance of improving vaccine uptake among vulnerable populations.

Funding: None

Disclosures: None

Background: Central-line–associated bloodstream infections (CLABSIs) are a major source of healthcare-associated infections (HAIs) in neonatal intensive care unit (NICU) patients, and they are associated with increased morbidity, mortality, and costs. CLABSI surveillance has been a critical component for hospitals participating in the Center for Disease Control and Prevention’s National Healthcare Safety Network (NHSN) for many years. CLABSI reporting grew substantially as a result of state reporting mandates first introduced in 2005 and federal reporting requirements for all intensive care units that began in 2011. However, no recent assessment of NHSN CLABSI incidence rate changes have been performed. The objective of this analysis was to estimate the overall trends in annual CLABSI incidence rates in NICUs from 2009 to 2018. Methods: We analyzed NHSN CLABSI data reported from NICUs during 2009–2018. CLABSIs further classified as mucosal barrier injury were included in this analysis. To evaluate the trends of CLABSI incidence (per 1,000 central-line days), and to account for the potential impact of definition changes introduced in 2015, we conducted an interrupted time-series analysis using mixed-effects negative binomial regression modeling. Birth weight category, patient care location type and hospital-level characteristics such as hospital type, medical affiliation, teaching status, bed size, and average length of inpatient stay) were assessed as potential covariates in regression analysis. Random intercept and slope models were evaluated with covariance tests and used to account for differential baseline incidence and trends among reporting NICUs. Results: The number of NICUs reporting to NHSN increased significantly following the federal mandate and has remained slightly >1,000 NICUs since 2013. The crude incidence of CLABSI dropped from 2.24 in 2009 to 0.98 infections per 1,000 central-line days in 2018, except for an increase in 2015 (Table 1). The CLABSI incidence, adjusted for birth weight category, decreased by an average of 11.6% per year from 2009 to 2018 except for a 35.8% increase in 2015 (Table 2). Conclusion: These findings suggest that hospitals have made significant strides in reducing the occurrence of CLABSIs in NICUs over the last 10 years. The increase in 2015 could be explained in part by the implementation and application of new definitional changes. Continued practices and policies that target, assess and prevent CLABSI in this setting may have been effective and remain vital to sustaining this decline nationally in subsequent years.

Funding: None

Disclosures: None

Background: The Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN) has included surveillance of laboratory-identified (LabID) methicillin-resistant Staphylococcus aureus (MRSA) bacteremia events since 2009. In 2013, the Centers for Medicare & Medicaid Services (CMS) began requiring acute-care hospitals (ACHs) that participate in the CMS Inpatient Quality Reporting program to report MRSA LabID events to the NHSN and, in 2015, ACHs were required to report MRSA LabID events from emergency departments (EDs) and/or 24-hour observation locations. Prior studies observed a decline in hospital-onset MRSA (HO-MRSA) rates in national studies over shorter periods or other surveillance systems. In this analysis, we review the national reporting trend for HO-MRSA bacteremia LabID events, 2010–2018. Method: This analysis was limited to MRSA bacteremia LabID event data reported by ACHs that follow NHSN surveillance protocols. The data were restricted to events reported for overall inpatient facility-wide and, if applicable, EDs and 24-hour observation locations. MRSA events were classified as HO (collected >3 days after admission) or inpatient or outpatient community onset (CO, collected ≤3 days after admission). An interrupted time series random-effects generalized linear model was used to examine the relationship between HO-MRSA incidence rates (per 1,000 patient days) and time (year) while controlling for potential risk factors as fixed effects. The following potential risk factors were evaluated: facility’s annual survey data (facility type, medical affiliation, length of facility stay, number of beds, and number of intensive care unit beds) and quarterly summary data (inpatient and outpatient CO prevalence rates). Result: The number of reporting ACHs increased during this period, from 473 in 2010 to 3,651 in 2018. The crude HO-MRSA incidence rates (per 1,000 patient days) have declined over time, from a high of 0.067 in 2011 to 0.052 in 2018 (Table 1). Compared to 2014, the adjusted annual incidence rate increased in 2015 by 16.38%, (95% confidence interval [CI], 10.26%–22.84%; P < .0001). After controlling for all significant risk factors, the estimated annual HO-MRSA incidence rates declined by 5.98% (95% CI, 5.17%–6.78%; P < .0001) (Table 2). Conclusions: HO-MRSA bacteremia incidence rates have decreased over the past 9 years, despite a slight increase in 2015. This national trend analysis reviewed a longer period while analyzing potential risk factors. The decline in HO-MRSA incidence rates has been gradual; however, given the current trend, it is not likely to meet the Healthy People 2020 objectives. This analysis suggests the need for hospitals to continue and/or enhance HO-MRSA infection prevention efforts to reduce rates further.

Funding: None

Disclosures: None

Background: Including infection preventionists (IPs) in hospital design, construction, and renovation projects is important. According to the Joint Commission, “Infection control oversights during building design or renovations commonly result in regulatory problems, millions lost and even patient deaths.” We evaluated the number of active major construction projects at our 800-bed hospital with 6.0 IP FTEs and the IP time required for oversight. Methods: We reviewed construction records from October 2018 through October 2019. We classified projects as active if any construction occurred during the study period. We describe the types of projects: inpatient, outpatient, non–patient care, and the potential impact to patient health through infection control risk assessments (ICRA). ICRAs were classified as class I (non–patient-care area and minimal construction activity), class II (patients are not likely to be in the area and work is small scale), class III (patient care area and work requires demolition that generates dust), and class IV (any area requiring environmental precautions). We calculated the time spent visiting construction sites and in design meetings. Results: During October 2018–October 2019, there were 51 active construction projects with an average of 15 active sites per week. These sites included a wide range of projects from a new bone marrow transplant unit, labor and delivery expansion and renovation, space conversion to an inpatient unit to a project for multiple air handler replacements. All 51 projects were classified as class III or class IV. We visited, on average, 4 construction sites each week for 30 minutes per site, leaving 11 sites unobserved due to time constraints. We spent an average of 120 minutes weekly, but 450 minutes would have been required to observe all 15 sites. Yearly, the required hours to observe these active construction sites once weekly would be 390 hours. In addition to the observational hours, 124 hours were spent in design meetings alone, not considering the preparation time and follow-up required for these meetings. Conclusions: In a large academic medical center, IPs had time available to visit only a quarter of active projects on an ongoing basis. Increasing dedicated IP time in construction projects is essential to mitigating infection control risks in large hospitals.

Funding: None

Disclosures: None

Background: When healthcare providers lack infection prevention and control (IPC) knowledge and skills, patient safety and quality of care can suffer. For this reason, state laws sometimes dictate IPC training; these requirements can be expressed as applying to various categories of healthcare personnel (HCP). We performed a preliminary assessment of the laws requiring IPC training across the United States. Methods: During February–July 2018, we searched WestlawNext, a legal database, for IPC training laws in 51 jurisdictions (50 states and Washington, DC). We used standard legal epidemiology methods, including an iterative search strategy to minimize results that were outside the scope of the coding criteria by reviewing results and refining search terms. A law was defined as a regulation or statute. Laws that include IPC training for healthcare personnel were collected for coding. Laws were coded to reflect applicable HCP categories and specific IPC training content areas. Results: A total of 278 laws requiring IPC training for HCP were identified (range, 1–19 per jurisdiction); 157 (56%) did not specify IPC training content areas. Among the 121 (44%) laws that did specify IPC content, 39 (32%) included training requirements that focused solely on worker protections (eg, sharps injury prevention and bloodborne pathogen protections for the healthcare provider). Among the 51 jurisdictions, dental professionals were the predominant targets: dental hygienists (n = 22; 43%), dentists (n = 20; 39%), and dental assistants (n = 18; 35%). The number of jurisdictions with laws requiring training for other HCP categories included the following: nursing assistants (n = 25; 49%), massage therapists (n = 11; 22%), registered nurses (n = 10; 20%), licensed practical nurses (n = 10; 20%), emergency medical technicians and paramedics (n = 9; 18%), dialysis technicians (n = 8; 18%), home health aides (n = 8;16%), nurse midwives (n = 7; 14%), pharmacy technicians (n = 7; 14%), pharmacists (n = 6; 12%), physician assistants (n = 4; 8%), podiatrists (n = 3; 6%), and physicians (n = 2; 4%). Conclusions: Although all jurisdictions had at least 1 healthcare personnel IPC training requirement, many of the laws lack specificity and some focus only on worker protections, rather than patient safety or quality of care. In addition, the categories of healthcare personnel regulated among jurisdictions varied widely, with dental professionals having the most training requirements. Additional IPC training requirements exist at the facility level, but this information was not analyzed as a part of this project. Further analysis is needed to inform our assessment and identify opportunities for improving IPC training requirements, such as requiring IPC training that more fully addresses patient protections.

Funding: None

Disclosures: None

Background: Previous work suggests an intermingling of community and hospital transmission networks driving the MRSA epidemic, but how those with CO-HA infections fit into the network remains unclear. We integrated epidemiologic data and whole-genome sequencing (WGS) from existing MRSA clinical isolates to determine whether there were distinguishable features of CO-HA MRSA infections that could guide interventions. Methods: We examined 955 existing clinical MRSA isolates from 2011 to 2013 from patients at Cook County Health, the major public healthcare network in Chicago, Illinois. We performed electronic and manual chart review to ascertain community (eg, illicit drug use, incarceration history) and healthcare exposures and comorbidities. WGS was performed on all sequences, and sequences were typed with multilocus sequence typing (MLST). We assessed the distribution of epidemiological factors and sequence type (ST) across onset type. Results: Infections were more frequent in males (70%); 61% of individuals with infection were African American and 21% were Hispanic. Overall, wound infections were the most common (81%) followed by blood (7%) and respiratory (6%). 82% of infections were ST8 (most USA300), 8% were ST5 (USA100) and 10% were other STs (Fig. 1a). Using standard epidemiologic definitions, we identified 523 CO, 295 CO-HA, and 137 HO infections. USA300 infections were common across CO, CO-HA, and HO categories, whereas USA100 was more frequently observed among CO-HA and HO. Current illicit drug use and history of incarceration—factors typically associated with CO-MRSA—were observed among both CO-HA and HO infections. 38% of CO-HA and 36% of HO had a history of MRSA infection or nasal colonization in the prior 6 months. As expected, 73% of CO-HA had a history of recent hospitalization, but this was also true for 44% of HO cases; points for intervention for both groups, especially CO-HA patients, include outpatient, inpatient, and ER care. Diabetes was common across categories, and HIV was more commonly observed among CO-HA cases (Fig. 1b). Conclusions: We characterized the genomic and epidemiologic features of CO-HA MRSA infections relative to CO and HO. By MLST and epidemiological analysis, CO-HA infections share similarities to both CO and HO. Although USA300 infections were the most common strain type, our findings highlight the need for WGS to discern relationships between individuals to understand the intermixing of healthcare and community networks for CO-HA infections. Higher resolution genomic analysis may help guide whether interventions need to be at hospital discharge or in the community to have the most impact on decreasing CO-HA MRSA infections.

Funding: Funding: from CDC Broad Agency Announcement: Genomic Epidemiology of Community-Onset Invasive USA300 MRSA Infections; Contract ID: 75D30118C02923

Disclosures: None

Background: The CDC has performed surveillance for invasive Staphylococcus aureus (iSA) infections through the Emerging Infections Program (EIP) since 2004. SCCmec and spa typing for clonal complex (CC) assignment and genomic markers have been used to characterize isolates. In 2019, whole-genome sequencing (WGS) of isolates began, allowing for high-resolution assessment of genomic diversity. Here, we evaluate the reliability of SCCmec typing, spa typing, and CC assignment using WGS data compared to traditional methods to ensure that backwards compatibility is maintained. Methods:S. aureus isolates were obtained from a convenience sample of iSA cases reported through the EIP surveillance system. Overall, 78 iSA isolates with diverse spa repeat patterns, CCs, SCCmec types, and antimicrobial susceptibility profiles were sequenced (MiSeq, Illumina). Real-time PCR and Sanger sequencing were used as the SCCmec and spa typing reference methods, respectively. spa-MLST mapping (Ridom SpaServer) served as the reference method for CC assignment. WGS assembly and multilocus sequence typing (MLST) were performed using the CDC QuAISAR-H pipeline. WGS-based MLST CCs were assigned using eBURST and SCCmec types using SCCmecFinder. spa types were assigned from WGS assemblies using BioNumerics. For isolate subtyping, previously published and validated canonical single-nucleotide polymorphisms (canSNPs) as well as the presence of the Panton-Valentine leukocidin (PVL) toxin and arginine catabolic mobile element (ACME) virulence factor were assessed for all genome assemblies. Results: All isolates were assigned WGS-based spa types, which were 100% concordant (78 of 78) with Sanger-based spa typing. SCCmecFinder assigned 91% of isolates (71 of 78) SCCmec types, which were 100% concordant with reference method results. Also, 7 isolates had multiple cassettes predicted or an incomplete SCCmec region assembly. Using WGS data, 96% (75 of 78) of isolates were assigned CCs; 3 isolates had unknown sequence types that were single-locus variants of established sequence types. Overall, 70 isolates had CCs assigned by the reference method; 100% (70 of 70) concordance was observed with WGS-based CCs. Analysis of canSNPs placed 42% (33 of 78) of isolates into CC8, with 17 (52%) of these isolates classified as USA300. PVL and ACME were not accurate markers for inferring the USA300 subtype as 24% (4 of 17) of isolates did not contain these markers. Conclusions:S. aureus CCs, SCCmec, and spa types can be reliably determined using WGS. Incorporation of canSNP analysis represents a more efficient method for CC8 assignment than the use of genomic markers alone. WGS allows for the replacement of multiple typing methods for increased laboratory efficiency, while maintaining backward compatibility with historical typing nomenclature.

Funding: None

Disclosures: None

Background: Bloodstream infections (BSIs) due to methicillin-resistant Staphylococcus aureus (MRSA) are important causes of morbidity and mortality in hospitalized patients. Long-term national MRSA BSI surveillance establishes rates for internal and external comparison and provide insight into epidemiologic, molecular, and resistance trends. Here, we present and discuss National MRSA BSI incidence rates and trends over time in Canadian acute-care hospitals from 2008 to 2018. Methods: The Canadian Nosocomial Infection Surveillance Programme (CNISP) is a collaborative effort of the Association of Medical Microbiology and Infectious Disease Canada and the Public Health Agency of Canada. Since 1995, the CNISP has conducted hospital-based sentinel surveillance of MRSA BSIs. Data were collected using standardized definitions and forms from hospitals that participate in the CNISP (48 hospitals in 2008 to 62 hospitals in 2018). For each MRSA BSI identified, the medical record was reviewed for clinical and demographic information and when possible, 1 blood-culture isolate per patient was submitted to a central laboratory for further molecular characterization and susceptibility testing. Results: From 2008 to 2013, MRSA BSI rates per 10,000 patient days were relatively stable (0.60–0.56). Since 2014, MRSA BSI rates have gradually increased from 0.66 to 1.05 in 2018. Although healthcare-associated (HA) MRSA BSI has shown a minimal increase (0.40 in 2014 to 0.51 in 2018), community-acquired (CA) MRSA BSI has increased by 150%, from 0.20 in 2014 to 0.50 in 2018 (Fig. 1). Laboratory characterization revealed that the proportion of isolates identified as CMRSA 2 (USA 100) decreased each year, from 39% in 2015 to 28% in 2018, while CMRSA 10 (USA 300) has increased from 41% to 47%. Susceptibility testing shows a decrease in clindamycin resistance from 82% in 2013 to 41% in 2018. Conclusions: Over the last decade, ongoing prospective MRSA BSI surveillance has shown relatively stable HA-MRSA rates, while CA-MRSA BSI rates have risen substantially. The proportion of isolates most commonly associated with HA-MRSA BSI (CMRSA2/USA 100) are decreasing and, given that resistance trends are tied to the prevalence of specific epidemic types, a large decrease in clindamycin resistance has been observed. MRSA BSI surveillance has shown a changing pattern in the epidemiology and laboratory characterization of MRSA BSI. The addition of hospitals in later years that may have had higher rates of CA-MRSA BSI could be a confounding factor. Continued comprehensive national surveillance will provide valuable information to address the challenges of infection prevention and control of MRSA BSI in hospitals.

Funding: None

Disclosures: None

Background: Central-line–associated bloodstream infection (CLABSI) and catheter-associated urinary tract infection (CAUTI) definitions continue to be refined to ensure accuracy. As facilities decrease CLABSI and CAUTI, and as midline catheters become more widely utilized, we sought to understand our non–central-line bloodstream infections (NCLBSI) and non–catheter-associated urinary tract infections (NCAUTI). Total healthcare-associated bloodstream infections (HABSIs) and urinary tract infections (HAUTIs) may provide more objective measures. Methods: The CHOC Children’s Hospital is a 334-bed quaternary-care hospital in Orange, California, with 146 intensive care unit (ICU) beds. We retrospectively reviewed all HABSIs (CLABSIs + NCLBSIs) and HAUTIs (CAUTIs + NCAUTIs) from July 1, 2016, to June 30, 2019, for demographic and microbiologic data. Both HABSI and HAUTI were defined as healthcare-associated infection when the date of event occurs on or after the third calendar day of admission. CLABSI and CAUTI were both defined using CDC-NHSN criteria. Mucosal barrier injury laboratory-confirmed bloodstream infections were excluded. Results: In a 3-year period, there were 100 HABSIs, of which 26 (26%) were NCLBSIs. The mean age for HABSI was 81 months. Enteric gram-negative infections (42%) and Staphylococcus aureus (35%) were the most common etiology for NCLBSI. The most common etiologies for CLABSI were coagulase-negative staphylococci (23%), Staphylococcus aureus (22%), and enteric gram-negatives (22%). Pseudomonas aeruginosa accounted for 16% of CLABSIs, but no NCLBSIs (Fig. 1). There was 1 midline catheter NCLBSI. There were 49 HAUTIs, of which 39 (80%) were NCAUTIs. One asymptomatic bacteremic urinary tract infection was included with the CAUTIs. The mean age for HAUTI was 55 months. The most common etiology of CAUTI was Pseudomonas aeruginosa (50%), whereas for NCAUTI the most common etiology was enteric gram-negative organisms (69%) (Fig. 2). In total, 11 HAUTIs (22%) resulted in secondary sepsis. Most HABSIs and HAUTIs occurred in the ICU setting. There were 6 deaths (6%) among HABSI patients and 3 deaths (8%) among HAUTI patients within 2 weeks of infection (Fig. 3). Conclusions: A preponderance of HABSIs were CLABSIs, but most HAUTIs were NCAUTIs. Although patient demographic and microbiologic differences exist in CLABSIs and NCLBSIs as well as CAUTIs and NCAUTIs, S. aureus and P. aeruginosa are important pathogens, particularly in device-associated infections. Trending total numbers of HABSIs and HAUTIs may be less subjective and may avert the shifting of categories seen with increased use of midline catheters. In addition, non–device-associated infections are potential causes of morbidity and mortality.

Funding: None

Disclosures: None

Background: Carbapenemase-producing Enterobacteriaceae (CPE) are a major public health concern because they typically display multidrug resistance and they cause hard-to-treat infections. Organisms harboring metallo-β-lactamases (MBLs) pose a critical challenge in clinical practice because they confer resistance to nearly all β-lactams, including recently approved β-lactam combination agents. A promising new β-lactam-β-lactamase inhibitor combination for treating infections caused by MBL-producing CPE is aztreonam–avibactam. Although clinical trials using aztreonam–avibactam are ongoing, clinicians can administer this combination using 2 US Food and Drug Administration (FDA)–approved drugs: aztreonam and ceftazidime–avibactam. In 2019, the Centers for Disease Control and Prevention (CDC) initiated a pilot program in the Antibiotic Resistance Laboratory Network (AR Lab Network) to address the lack of commercially available antimicrobial susceptibility tests (ASTs) for aztreonam-avibactam by performing broth microdilution (BMD) for this drug combination. We describe the isolates submitted for aztreonam-avibactam AST during the AR Lab Network pilot in 2019. Methods: The AR Lab Network regional laboratories adopted the HP D300e Digital Dispenser to create customized BMD panels for aztreonam–avibactam ASTs. To qualify for aztreonam–avibactam AST, isolates had to be an Enterobacteriaceae displaying nonsusceptibility to all tested β-lactams (including either ceftazidime-avibactam or meropenem-vaborbactam) or confirmed to harbor at least 1 MBL gene (blaVIM, blaNDM, or blaIMP). Regional laboratories confirmed carbapenemase gene(s) using a molecular method. If an MBL gene was confirmed, aztreonam-–avibactam minimum inhibitory concentrations (MICs) were reported back to submitters within 3 working days of receipt. Findings were reported to CDC using a REDCap database. Results: From March through August 2019, aztreonam–avibactam AST was requested for 32 clinical isolates across 16 states. These isolates included 15 Escherichia coli, 12 Klebsiella pneumoniae, 4 Enterobacter cloacae complex, and 1 Proteus mirabilis. Molecular detection identified 27 blaNDM-positive isolates, 2 blaOXA-48-like-positive isolates, and 3 blaOXA-48/blaNDM-positive isolates. Aztreonam-avibactam results were reported for 30 isolates; 5 displayed elevated aztreonam-avibactam MICs of 8/4 µg/mL (n = 4) or 16/4 µg/mL (n = 1). Results for 2 isolates were not reported because the isolates were MBL negative. Aztreonam-avibactam MICs ranged from 0.06/4 µg/mL to 16/4 µg/mL. The MIC50/MIC90 were 0.5/4 µg/mL and 8/4 µg/mL. Conclusions: In the absence of effective FDA-approved treatments and lack of available AST for novel antibiotic combinations, CDC’s provision of AST for aztreonam-avibactam among MBL-producing CPE, offered through the AR Lab Network, helps fill a critical gap to inform patient treatment decisions. To date, our in vitro data suggest that aztreonam–avibactam could be a promising drug combination for use against infections caused by MBL-producing Enterobacteriaceae.

Funding: None

Disclosures: None

Background: Interventions to reduce unnecessary device use may select a higher-risk population, leading to a paradoxical increase in SIR for some high-performing facilities. The standardized utilization ratio (SUR) adjusts for device use for different units and facilities. We evaluated the performance of a population SIR (pSIR) metric compared to device SIR (dSIR) in the situations of increased, decreased, and no change in SUR for a large system. Methods: We evaluated hospitals that had a reduction, increase, and no substantial change (±5% relative change) in their SUR in FY2019 (July 2018–June 2019) compared to baseline FY2017 (July 2016–June 2017). The dSIR (defined as Σ observed events divided by Σ predicted events based on actual device days) and pSIR (defined as Σ observed events divided by Σ predicted events based on predicted device days). We calculated the cumulative attributable difference (CAD) for catheter-associated urinary tract infections (CAUTIs) for the same facilities based on dSIR and pSIR. Results: Overall, the system SUR dropped from 0.92 in 2017 to 0.85 in 2019 (7.3% decrease). Of the 48 hospitals included, 25 (52%) exhibited a drop, 13 (27%) exhibited an increase, and 10 (21%) had no change in SUR during 2019. For hospitals in which SUR decreased, the dSIR decreased by 15.9% from 0.88 to 0.74, and the pSIR decreased by 32.3% from 0.85 to 0.58 (Table 1). In 2019, the CAD for CAUTI to a target SIR of 1 was 133 for the dSIR compared to 181 for the pSIR, and 36% more events were avoided. Conclusions: The traditional SIR (dSIR) underestimated improvements in infection rates compared to the pSIR because it failed to account for reduced device utilization associated with infection prevention interventions. The pSIR accounts for overall risk of infection associated with device exposure in a population and better reflects the efficacy of prevention efforts compared to dSIR. The pSIR should be considered in situations in which interventions have led to substantial reductions in device use.

Funding: None

Disclosures: None

Background: The Changing Lives by Eradicating Antibiotic Resistance (CLEAR) Trial was a trial of 2,121 recently discharged methicillin-resistant Staphylococcus aureus (MRSA) carriers randomized to MRSA education plus a 5-day decolonization regimen repeated twice monthly for the 6 months following discharge versus MRSA education alone. Decolonization resulted in a 30% reduction in MRSA infection and a 17% reduction in all-cause infection (Huang SS et al, NEJM, 2019) in the year following discharge. We pursued an evaluation of USA300 carriers to determine whether the decolonization benefit differed for this strain type. Methods: A secondary analysis of the CLEAR randomized controlled trial (RCT) was performed, limiting the cohort to participants known to harbor USA300 at or within 30 days of enrollment and who attended all follow-up visits in the year following discharge. Within this subset, we conducted a time-to-event analysis using unadjusted and adjusted Cox proportional-hazard models. Variables in adjusted analyses included demographic data, insurance type, presence of coexisting conditions or medical devices at enrollment, hospitalization or residence in a nursing home in the year before enrollment, receipt of anti-MRSA antibiotics, protocol adherence, and randomization strata. Results: USA300 was identified in 420 of the 783 participants who attended all visits and had strains genetically tested. MRSA infections occurred in 27 of 207 education group participants (0.149 per person year) and in 19 of 213 decolonization group participants (0.099 per-person year). Point estimates from the unadjusted hazard ratios of infection reduction were similar (0.59; 95% CI, 0.32–1.09) to the full trial population (0.61; 95% CI, 0.44–0.85), suggesting nondifferential benefit for the USA300 strain type. Adjusted models were highly similar. Conclusions: The reduction in MRSA infection associated with postdischarge decolonization in the subgroup of participants who harbored the USA300 strain-type was consistent with overall trial findings. Although the original trial was not powered for the evaluation of a USA300 subset, this RCT provides a valuable design for assessing the magnitude of strain-specific responsiveness to decolonization during a time when national rates of MRSA invasive disease have plateaued and USA300 is responsible for an increasing proportion of infections. These data suggest that postdischarge decolonization should be similarly effective in carriers of either USA300 or healthcare-associated MRSA strains.

Funding: None

Disclosure: Gabrielle M. Gussin, Stryker (Sage Products): Conducting studies in which antiseptic product is provided to participating hospitals and nursing homes. Clorox: Conducting studies in which antiseptic product is provided to participating hospitals and nursing homes. Medline: Conducting studies in which antiseptic product is provided to participating hospitals and nursing homes. Xttrium: Conducting studies in which antiseptic product is provided to participating hospitals and nursing homes. Mohamad Sater, Salary-Day Zero Diagnostics.

Background: Antibiotic-resistant organisms (AROs) are associated with greater disease severity and poor outcomes. Previous studies have investigated AROs and healthcare-associated infections (HAIs) within larger urban acute-care settings, but similar data for rural settings are scarce. In this stud, we aimed to fill this gap. Methods: Data on antimicrobial resistance (AMR), additional precautions and HAI were collected from 8 rural Alberta acute-care facilities over a 24-hour period from February 4–28, 2019. Data were gathered as part of the national Canadian, Rural, and Northern Acute Care Point Prevalence (CNAPP) survey. All inpatients on included units were reviewed. CNAPP protocol surveillance definitions were used. Results: In total, 961 patients were surveyed, of whom 94 of 961 (9.8%) were on additional precautions. Contact precautions only were most common (54 of 94, 57.4%) and were predominantly in place for MRSA (30 of 94, 31.9%). Of 961 patients, 100 (~10%) met the surveillance definitions for any infection. The most common infections were skin and soft-tissue infections (29 of 100, 29.0%) and bloodstream infections (28 of 100, 28.0%). An HAI occurred in 30 of 961 patients (3.1%); the most common HAIs were surgical site infections (8 of 30, 26.7%) and urinary tract infections (8 of 30, 26.7%). An antimicrobial was prescribed to 333 of 961 patients (34.6%) at the time of the survey, with ceftriaxone the most commonly prescribed (68 of 333, 20.4%). Most patients receiving an antimicrobial (237 of 333, 71.2%) did not meet the surveillance definition for any infection. The most common reason for any antimicrobial administration was empiric therapy (167 of 333, 50.1%). Conclusions: Investigations into antimicrobial use and the burden of HAIs in rural acute-care settings have been limited. In this study, we (1) established provincial baseline data for burden of disease in these facilities due to HAIs and (2) demonstrated that antimicrobial use is common, though most patients who were prescribed an antimicrobial did not meet study definitions for infection. It will be important to continue this type of surveillance in this understudied population to monitor the burden of HAIs over time, to establish antimicrobial utilization trends, and to continue to identify potential antimicrobial stewardship initiatives.

Funding: None

Disclosures: None

Background: In February 2019, the Orange County Health Care Agency (OCHCA) identified an outbreak of Candida auris, an emerging fungus that spreads rapidly in healthcare facilities. Patients in long-term acute-care hospitals (LTACHs) and skilled nursing facilities that provide ventilator care (vSNFs) are at highest risk for C. auris colonization. With assistance from the California Department of Public Health and the Centers for Disease Control and Prevention, OCHCA instituted enhanced surveillance, communication, and screening processes for patients colonized with or exposed to C. auris. Method: OCHCA implemented enhanced surveillance by conducting point-prevalence surveys (PPSs) at all 3 LTACHs and all 14 vSNFs in the county. Colonized patients were identified through axilla/groin skin swabbing with C. auris detected by PCR and/or culture. In facilities where >1 C. auris colonized patient was found, PPSs were repeated every 2 weeks to identify ongoing transmission. Retrospective case finding was instituted at 2 LTACHs with a high burden of colonized patients; OCHCA contacted patients discharged after January 1, 2019, and offered C. auris screening. OCHCA tracked the admission or discharge of all colonized patients, and facilities with ongoing transmission were required to report transfers of any patient, regardless of colonization status. OCHCA tracked all patients discharged from facilities with ongoing transmission to ensure that accepting facilities conducted admission surveillance testing of exposed patients and implemented appropriate environmental and contact precautions. Result: From February–October 2019, 192 colonized patients were identified. All 3 LTACHs and 6 of 14 VSNFs had at least 1 C. auris–colonized patient identified on initial PPS, and 2 facilities had ongoing transmission identified on serial PPS. OCHCA followed 96 colonized patients transferred a total of 230 times (an average of 2.4 transfers per patient) (Fig. 1) and 677 exposed patients discharged from facilities with ongoing transmission (Fig. 2). Admission screening of 252 exposed patients on transfer identified 13 (5.2%) C. auris–colonized patients. As of November 1, 2019, these 13 patients were admitted 21 times to a total of 6 acute-care hospitals, 2 LTACHs, and 3 vSNFs. Transferring facilities did not consistently communicate the colonized patient’s status and the requirements for isolation and testing of exposed patients. Conclusion: OCHCA oversight of interfacility transfer, though labor-intensive, improved identification of patients colonized with C. auris and implementation of appropriate environmental and contact precautions, reducing the risk of transmission in receiving healthcare facilities.

Funding: None

Disclosures: None

Background:Clostridioides difficile infection (CDI) frequently recurs after initial treatment. Predicting recurrent CDI (rCDI) early in the disease course can assist clinicians in their decision making and improve outcomes. However, predictions based on clinical criteria alone are not accurate and/or do not validate other results. Here, we tested the hypothesis that circulating and stool-derived inflammatory mediators predict rCDI. Methods: Consecutive subjects with available specimens at diagnosis were included if they tested positive for toxigenic C. difficile (+enzyme immunoassay [EIA] for glutamate dehydrogenase and toxins A/B, with reflex to PCR for the tcdB gene for discordants). Stool was thawed on ice, diluted 1:1 in PBS with protease inhibitor, centrifuged, and used immediately. A 17-plex panel of inflammatory mediators was run on a Luminex 200 machine using a custom antibody-linked bead array. Prior to analysis, all measurements were normalized and log-transformed. Stool toxin activity levels were quantified using a custom cell-culture assay. Recurrence was defined as a second episode of CDI within 100 days. Ordination characterized variation in the panel between outcomes, tested with a permutational, multivariate ANOVA. Machine learning via elastic net regression with 100 iterations of 5-fold cross validation selected the optimal model and the area under the receiver operator characteristic curve (AuROC) was computed. Sensitivity analyses excluding those that died and/or lived >100 km away were performed. Results: We included 186 subjects, with 95 women (51.1%) and average age of 55.9 years (±20). More patients were diagnosed by PCR than toxin EIA (170 vs 55, respectively). Death, rCDI, and no rCDI occurred in 32 (17.2%), 36 (19.4%), and 118 (63.4%) subjects, respectively. Ordination revealed that the serum panel was associated with rCDI (P = .007) but the stool panel was not. Serum procalcitonin, IL-8, IL-6, CCL5, and EGF were associated with recurrence. The machine-learning models using the serum panel predicted rCDI with AuROCs between 0.74 and 0.8 (Fig. 1). No stool inflammatory mediators independently predicted rCDI. However, stool IL-8 interacted with toxin activity to predict rCDI (Fig. 2). These results did not change significantly upon sensitivity analysis. Conclusions: A panel of serum inflammatory mediators predicted rCDI with up to 80% accuracy, but the stool panel alone was less successful. Incorporating toxin activity levels alongside inflammatory mediator measurements is a novel, promising approach to studying stool-derived biomarkers of rCDI. This approach revealed that stool IL-8 is a potential biomarker for rCDI. These results need to be confirmed both with a larger dataset and after adjustment for clinical covariates.

Funding: None

Disclosure: Vincent Young is a consultant for Bio-K+ International, Pantheryx, and Vedanta Biosciences.

Background:Clostridioides difficile is a leading cause of healthcare-associated infections, and greater healthcare exposure is a primary risk factor for Clostridioides difficile infection (CDI). Longer hospital stays and greater CDI pressure, both at the hospital level and the level, have been linked to greater risk. In addition, symptoms associated with healthcare-associated CDI often do not present until a patient has been discharged. Our study objective was to estimate the extent to which exposure to different types of healthcare settings (eg, prior hospitalization, emergency department [ED], outpatient or long-term care) increase risk for hospital-onset CDI. Methods: We conducted a case-control study using the Truven Marketscan Commerical Claims and Medicare Supplemental databases from 2001 to 2017. Case patients were selected as all inpatient visits with a secondary diagnosis of CDI and no previous CDI diagnosis in the prior 90 days. Controls were selected from all inpatient admissions without any CDI diagnosis during the current admission or prior 90 days. A logistic regression model was used to estimate risk associated with prior healthcare exposure. Indicators were created for prior exposure to different healthcare settings: separate indicators were used to indicate transfer, exposure to that setting in the prior 1–30 days, 31–60 days and 61–90 days. Separate indicators were created for prior hospitalization, ED, outpatient clinic, nursing home or long-term care facilities (LTCFs), psychiatric or substance-abuse facility or other outpatient facility. We also included an indicator for prior exposure to a family member with CDI and prior outpatient antibiotics. Results: Estimates for selected variables (odds ratios) are presented in Table 1. Prior hospitalization, ED visits, outpatient clinics, nursing home and LTCFs were all associated with increased risk of secondary diagnosed CDI. Prior hospitalization and nursing home/LTCF conveyed the greatest risk. In addition, a ‘dose-–response’ relationship occurred for each of these exposure settings, with exposure nearest the admission date having the largest risk. Prior exposure to psychiatric , substance abuse, or other outpatient facilities were not risk factors for CDI. Having a family member with prior CDI and both low-risk and high-risk outpatient antibiotics were associated with increased risk. These factors also exhibited a ‘dose–response’ pattern. Conclusions: Exposure to various healthcare settings significantly increased risk for secondary CDI. Prior healthcare exposures occurring nearest to the point of admission conveyed the greatest risk. These results suggest that many hospital-associated CDI cases attributed to a current hospital stay may actually be acquired from prior healthcare settings.

Funding: CDC Modeling Infectious Diseases (MInD) in Healthcare Network

Disclosures: None

Background: Transmission of carbapenemase-producing organisms (CPO) threatens patient safety in healthcare facilities. As a result of a 2011 outbreak of blaKPC+ Klebsiella pneumoniae, the NIH Clinical Center (NIHCC) has prioritized early detection and isolation of CPO carriers, using point-prevalence surveys and targeted high-risk ward surveillance since 2011 and admission surveillance since 2013. We describe our experience over 6 years of admission surveillance. Methods: The NIHCC is a 200-bed research hospital that provides care for a highly immunocompromised patient population. From September 2013 to September 2019, perirectal swabs were ordered automatically for all patients on admission to nonbehavioral health wards. Swabs were ordered twice weekly for ICU patients, weekly in other high-risk wards, and monthly for hospital-wide point prevalence (excluding behavioral health). Patients hospitalized in the United States in the previous week or abroad in the previous 6 months were considered high risk for carriage and isolated pending results from 2 swabs. Most swabs (n = 37,526) were cultured onto HardyCHROM CRE. If gram-negative bacilli (GNB) were present, a molecular screen for carbapenemases was performed on a sweep of cultured material (day 1) pending organism isolation. GNB were identified by MALDI-TOF MS. Prior to June 2019, isolates were screened by blaKPC/blaNDM PCR. Starting in June 2019, Enterobacteriaceae and Pseudomonas aeruginosa were screened using the phenotypic modified carbapenem inactivation method (mCIM), reflexing to the GeneXpert CARBA-R molecular assay if positive; other GNB were tested directly with CARBA-R. Selected GNB underwent susceptibility testing (Sensititre). Whole-genome sequencing was used to assess relatedness among CPO isolates. Swabs from high-risk patients were tested directly by blaKPC PCR (n = 699) until August 2019 (most in parallel with culture) and thereafter by CARBA-R (n = 13). Results: Among 54,188 orders for perirectal swabs, 38,238 were collected from 14,497 patients (compliance 71%). Among 33 CPO-colonized patients identified from September 2013 through September 2019, 15 were identified on admission, 6 were identified in point-prevalence surveys, 8 were identified from high-risk ward surveillance, and 4 were identified from clinical cultures. Sequencing demonstrated no relatedness among CPO isolates. Although only 1.4% of patients sampled on admission were colonized with CPO, those meeting high-risk criteria were 21 times as likely to be colonized. Conclusion: Admission surveillance for CPO identified a low rate of colonization, but it detected nearly half of known CPO-colonized NIHCC patients over the past 6 years. Modest compliance with swab collection leaves room for improvement and likely results in missed instances of colonization. Although we cannot determine its effectiveness, we view our strategy as one of several key safety measures for our highly vulnerable patient population.

Funding: None

Disclosures: None

Background: In 2018, the Maryland Department of Health, in collaboration with the University of Maryland and Johns Hopkins University, created the Statewide Prevention and Reduction of Clostridioides difficile (SPARC) collaborative to reduce C. difficile as specified in Healthy People 2020. Methods: The SPARC collaborative recruited hospitals contributing most cases to statewide C. difficile standardized infection ratio (SIR), according to data reported to the National Healthcare Safety Network (NHSN). SPARC developed intervention bundles around 4 domains: infection prevention, environmental cleaning, and diagnostic and antimicrobial stewardship. Each facility completed a self-assessment followed by an on-site, day-long, peer-to-peer (P2P) evaluation with 8–12 SPARC subject matter experts (SMEs) representing each domain. The SMEs met with hospital executive leadership and then led 4 domain-based group discussions with relevant hospital team leaders. To identify policy and practice gaps, SMEs visited hospital inpatient units for informal interviews with frontline staff. In a closing session, SPARC SMEs, hospital executives, and team leaders reconvened to discuss preliminary findings. This included review of covert observation data (hand hygiene, personal protective equipment compliance, environmental cleaning) obtained by SPARC team 1–2 weeks prior. Final SPARC P2P written recommendations guided development of customized interventions at each hospital. SPARC provided continuous support (follow up phone calls, educational webinars, technical support, didactic training for antimicrobial stewardship pharmacists) to enhance facility-specific implementation. For every quarter, we categorized C. difficile NHSN data for each Maryland hospital into “SPARC” or “non-SPARC” based on participation status. Using negative binomial mixed models, we analyzed difference-in-difference of pre- and postincidence rate ratios (IRRs) for SPARC and non-SPARC hospitals, which allowed estimation of change attributable to SPARC participation independent of other time-varying factors. Results: Overall, 13 of 48 (27%) hospitals in Maryland participated in the intervention. The baseline SIR for all Maryland hospitals was 0.92, and the post-SPARC SIR was 0.67. The SPARC hospitals had a greater reduction in hospital-onset C. difficile incidence; 8.6 and 4.3 events per 10,000 patient days for baseline and most recent quarter, respectively. For non-SPARC hospitals, these hospital-onset C. difficile incidences were 5.1 preintervention and 4.3 postintervention. We found a statistically significant difference-in-difference between SPARC and non-SPARC hospital C. difficile reduction rates (ratio of IRR, 0.63; 95% CI, 0.44−0.89; P = .01). Conclusions: The Maryland SPARC collaborative, a public health-academic partnership, was associated with a 25% reduction in the Maryland C. difficile SIR. Hospitals participating in SPARC demonstrated significantly reduced C. difficile incidences to match that of high-performing hospitals in Maryland.

Funding: None

Disclosure: Aaron Milstone, BD – consulting.

Background: The focus on infection prevention in nursing homes is growing, but little is known about the role infections play in transfers from nursing home to hospital. Our goals were (1) to identify rates of infection-related transfers to the hospital and (2) to identify trends in these rates from 2011 to 2014. Methods: Using a nationally representative sample of 2,501 nursing homes (2011–2014), elderly resident data from the Minimum Data Set 3.0 were combined with CMS inpatient data (MedPAR). We classified transfers from nursing home to hospital as caused by infection (1) if infection was the primary diagnosis and present on admission (POA) or (2) if infection was indicated as the MedPAR admitting diagnosis code and POA. We classified all transfers, including those caused by infection, for which infection was POA in any of the 25 diagnosis codes as transfers with infection. Types of infection included respiratory, sepsis, urinary tract infection (UTI), and all (including ‘other’). Results: Table 1 shows the number of all-cause transfers and the percentage caused by infections. From 2011 to 2014, the rate of all-cause transfers declined from 0.479 to 0.396 per patient; infections were primarily responsible for ~1 in 3 transfers each year. The rate of transfers caused by sepsis increased by 37% from 2011 to 2014, and the rate for respiratory infections fell by 18%. More than half of all transfers from nursing home to hospital in each year had an infection POA. Although the percentage of transfers caused by any kind of infection increased by >7% during the period, the number of transfers per patient dropped by 17%. Conclusions: A large number of elderly nursing home residents are transferred to hospitals with infection each year. Many of these transitions may be avoidable with improved infection prevention and surveillance in nursing homes. Reduced infection rates would improve health and quality of life of nursing home residents and reduce infection-related inpatient costs.

Funding: None

Disclosures: None

Background: Due to reliance on hospital discharge data for case identification, the burden of noninvasive and community-acquired S. aureus disease is often underestimated. To determine the full burden of S. aureus infections, we utilized population-based surveillance in a large urban county. Methods: The Georgia Emerging Infections Program (GA EIP) conducted CDC-funded, population-based surveillance by finding cases of S. aureus infections in 8 counties around Atlanta in 2017. Cases were residents with S. aureus isolated from either a normally sterile site in a 30-day period (invasive cases) or another site in a 14-day period (noninvasive cases). Medical records (all invasive and 1:4 sample of noninvasive cases) among Fulton County residents were abstracted for clinical, treatment, and outcome data. Cases treated were mapped to standard therapeutic site codes. Noninvasive specimens were reviewed and attributed to an invasive case if both occurred within 2 weeks. Incidence rates were calculated using 2017 census population and using a weight-adjusted cohort to account for sampling. Results: In total, 1,186 noninvasive (1:4 sample) and 529 invasive cases of S. aureus in Fulton county were reviewed. Only 35 of 1,186 (2.9%) noninvasive cases were temporally linked to invasive cases, resulting in 5,133 cases after extrapolation (529 invasive, 4,604 noninvasive). All invasive cases and 3,776 of 4,604 noninvasive cases (82%) were treated (4,305 total). Treatment was highest in skin (90%) and abscess (97%), lowest in urine (62%) and sputum (60%), and consisted of antibacterial agents alone (65%) or in addition to drainage procedures (35%). Overall, 41% of all cases were hospitalized, 12% required ICU admission, and 2.7% died, almost exclusively with bloodstream and pulmonary infections. Attribution of noninvasive infection was most often outside healthcare settings (87%); only 341 (7.9%) were hospital-onset cases; however, 34% of cases had had healthcare exposure in the preceding year, most often inpatient hospitalization (75%) or recent surgery (35%). Estimated countywide incidence was 414 per 100,000 (130 for MRSA and 284 for MSSA), invasive infection was 50 per 100,000. Among treated cases, 57% were SSTI, and the proportion of cases caused by MRSA was ~33% but varied slightly by therapeutic site (Fig. 1). Conclusions: The incidence of treated S. aureus infection in our large urban county is estimated to be 414 per 100,000 persons, which exceeds previously estimated rates based on hospital discharge data. Only 12% of treated infections were invasive, and <1 in 10 were hospital onset. Also, two-thirds of treated disease cases were MSSA; most were SSTIs.

Funding: Proprietary Organization: Pfizer.

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