Background: Trimethoprim-sulfamethoxazole is commonly used for the treatment of noninvasive methicillin-resistant Staphylococcus aureus (MRSA) infections. Following a report from 2 facilities of increased trimethoprim-sulfamethoxazole resistance among MRSA infections, we assessed changes in resistance nationally and by state. Methods: We reviewed antibiotic susceptibility testing (AST) data for trimethoprim-sulfamethoxazole among S. aureus isolates associated with surgical site infections (SSIs), central-line–associated bloodstream infections (CLABSIs), and catheter-associated urinary tract infections (CAUTIs) from acute-care hospitals reported to the NHSN Device and Procedure Module from 2012 to 2018. We compared the pooled mean percentage of isolates nonsusceptible to trimethoprim-sulfamethoxazole in 2012 and 2018, stratified by MRSA and methicillin-sensitive Staphylococcus aureus (MSSA). Among MRSA isolates, we compared the percentage nonsusceptible to trimethoprim-sulfamethoxazole by healthcare-associated infection (HAI) type and state in 2012 and 2018. States with ≥20 MRSA isolates with AST reported each year were included in the state-level analysis. Results: Overall, 36,587 MRSA isolates and 46,824 MSSA isolates were reported from 2012 to 2018. Moreover, >80% of MRSA and MSSA isolates had trimethoprim-sulfamethoxazole AST reported each year. Nationally, the percentage of trimethoprim-sulfamethoxazole nonsusceptible among MRSA isolates was 3.9% in 2012 compared to 6.5% in 2018 (P < .001), but it was unchanged among MSSA isolates during the same period (1.1% in 2012 vs 1.4% in 2018; P = .08). Among MRSA surgical site infections (SSIs), the proportion of trimethoprim-sulfamethoxazole nonsusceptible isolates was 3.1% in 2012 versus 6.1% in 2018 (P < .001) but did not change significantly for CLABSIs or CAUTIs (Fig. 1). Among the 32 states that met the inclusion criteria, there were no significant decreases, whereas 4 (12.5%) showed significant increases in the percentage of MRSA that were trimethoprim-sulfamethoxazole nonsusceptible in 2018 compared to 2012: New Jersey (2.4% in 2012 vs 19.3% in 2018; P <.001); Florida (9.1% in 2012 vs 22.4% in 2018; P < .001); Maryland (0.0% in 2012 vs 10.9% in 2018; P < .01); and Pennsylvania (1.7% in 2012 vs 6.5% in 2018; P < .001). Conclusions: Nationally, there was a modest but significant increase in the percentage of MRSA HAI isolates nonsusceptible to trimethoprim-sulfamethoxazole in 2018 compared to 2012; however, 3 of 4 states with significant increases in nonsusceptibility had substantial, potentially clinically relevant increases (>10%). Ongoing characterization of MRSA isolates from Florida and New Jersey may provide insight into the underlying cause of these shifting patterns in trimethoprim-sulfamethoxazole resistance among MRSA. Healthcare personnel should select appropriate antibiotic regimens based on local resistance patterns, should monitor patients for treatment failure, and should report changes in resistance to the appropriate public health department.

Funding: None

Disclosures: None

Background: The CDC recently updated recommendations on tuberculosis (TB) screening in healthcare facilities, suggesting the discontinuation of annual TB screening. However, hospitals may opt to continue based on their local TB epidemiology. We assessed TB infection control parameters in our facility to guide the implementation of the new CDC recommendations. Methods:We retrieved data for patients with an International Classification of Disease, Tenth Revision (ICD-10) code for TB treated at the University of Iowa Hospitals and Clinics during 2016–2019. We supplemented our search with microbiology data: culture or PCR for Mycobacterium tuberculosis. Based on manual chart review, we adjudicated each patient as active TB, latent TB, previously treated TB, unclear history, or no TB. We further labeled active TB cases based on their risk of transmission (pulmonary or extrapulmonary cases that underwent an aerosol generating procedure). We then calculated the number of exposure events associated with those patients and tuberculin skin test (TST) conversion rates among the exposed. Results: During 2016–2019, we identified 197 patients based on ICD-10 codes. In total, 10 additional patients were detected by microbiology data review. Of these 207 patients, 48 (23.2%) had active TB: lung, n = 24 (50%); lymph node, n = 9 (19%); bone or spine, n = 5 (10%); eye, n = 3 (6%); disseminated, n = 2 (4%); pleura, n = 2 (4%); skin abscess, n = 2 (4%); and meningitis, n = 1 (2%). Of the 24 pulmonary patients, 6 (25%) had either a positive smear or a cavity on imaging. In total, 159 patients were excluded: no TB, n = 22 (14%); latent TB, n = 27 (17%); old or treated TB, n = 93 (58%); and unclear history, n = 9 (6%). Of the 48 cases with active TB, 31 (65%) were deemed potentially infectious. Also, 10 cases (32%) led to the exposure of 204 healthcare workers (HCWs). Baseline and postexposure TST were available for 179 HCWs (88%); 72 (35%) followed up in the employee health clinic within the 8–12 weeks after exposure. Of 161 HCWs with a negative TST at baseline, no conversions occurred. Of 18 HCWs with positive TST at baseline, no HCW developed symptoms during the observation period. Conclusions: Nearly one-third of infectious TB cases led to HCW exposures in a low-incidence setting. However, no TST conversions or active TB infections were seen. Exposure and conversion rates are useful indicators of TB infection control in healthcare facilities and may help guide implementation of the new CDC TB control recommendations.

Funding: None

Disclosures: None

Background: Central-line–associated bloodstream infections (CLABSIs) are serious complications of modern health care, leading to increased morbidity, mortality, and costs. Since 2012, a multimodal insertion and care bundle for central venous catheters (CVCs) has been implemented in the intensive care unit (ICU) of the Amphia Hospital Breda, The Netherlands. The implementation of this bundle was associated with sustainable low CLABSI rates (1 per 1,000 CVC days). There was no surveillance of CLABSI in the other departments of the hospital. Objectives: We implemented semiautomated surveillance for CLABSI in non-ICU inpatients. Methods: A single-center, retrospective study was conducted in a 1,370-bed teaching hospital in The Netherlands between January 2017 and December 2018. All hospitalized patients (aged ≥18 years) in non-ICU wards, with a CVC inserted, were screened for CLABSI. CLABSIs were diagnosed using the definitions of the national nosocomial surveillance network PREZIES, excluding infections already present on admission and secondary bloodstream infection. CLABSI rates were calculated as cases per 1,000 CVC days with 95% CIs. Results: In 2017, 14 CLABSI were reported during 4,656 CVC days (3.0 per 1,000 CVC days; 95% CI, 1.8–5.1). In 2018, 13 CLABSIs were reported during 4,995 catheter days (2.6 per 1,000 CVC days; 95% CI, 1.5–4.5). The mean duration of CVC days prior to CLABSI in 2017 and 2018 were 20 days (range, 4–28) and 14 days (range, 4–25), respectively. Most CLABSI events occurred in patients admitted to the hematology ward (13 of 27, 48.1%). Of those, 11 of 13 (84,6%) were patients with an acute myeloid leukemia (AML) and severe mucositis due to the intensive chemotherapy at the time of CLABSI. The remaining cases occurred in patients of 4 different surgical departments. Coagulase-negative staphylococci were the most common organisms recovered (25 of 27, 92.6%). Conclusions: To our knowledge, this is the first report of CLABSI-rates in non-ICU wards in the Netherlands. The CLABSI rates were higher in non-ICU wards compared to the ICU of our hospital. This difference was mainly because of the high CLABSI rate in the patients with AML.

Funding: None

Disclosures: None

Background: Methicillin-resistant Staphylococcus aureus (MRSA) colonization of patients and contamination of their immediate environmental surfaces is common in the acute care setting, but there is much to be learned about the dynamics of MRSA transmission over a short period of time. Methods: A prospective, observational time-motion qualitative study was conducted at 2 hospitals: 1 in Michigan (hospital 1) and 1 in Zurich, Switzerland (hospital 2)—between November 2018 and July 2019. Hospitalized patients with a MRSA infection or colonization were enrolled. Microbiologic cultures for MRSA were collected from patient nares, axilla, groin and hands and several high-touch surfaces in their room (bed controls, call button, tray table, etc) at the first visit, and patient hands and high-touch surfaces continued to be swabbed every 90 minutes over the course of 5 hours. Patient hands and environment were disinfected after each swabbing. Clinical data were collected from patient’s medical chart. Results: We recruited 10 MRSA colonized or infected patients for the study with 50 hours of observation and obtained 360 patient and environmental swabs. Most were women (7 of 10); the average age was 52.8 years (Table 1). At the first visit, 8 (80%) patients were MRSA-colonized (at 1 or more body sites) and 5 (50%) rooms were MRSA-contaminated (at 1 or more surfaces). Also, 6 patients (60%) had an active MRSA infection and were actively receiving an anti-MRSA agent (eg, Vancomycin). Among those 6 patients receiving an anti-MRSA agent, 4 patients (67%) and 2 rooms (33%) were contaminated at the first visit. Among those 4 patients not receiving an anti-MRSA agent, all 4 patients (100%) and 3 rooms (75%) were contaminated at the baseline visit. Acquisitions (ie, MRSA recovered from a site it was not previously recovered from) occurred on 3 of 7 patient hands (43%) and on 6 occasions in the room (among 5 patients), most commonly at the toilet seat (2 of 6 times). MRSA prevalence on patient and room surfaces for the 5 patients enrolled at hospital 2 are illustrated in Figure 1, which shows colonization of patient and contamination of environment as well as activities performed by the patient in between culturing. Conclusions: We evaluated transmission of MRSA over brief periods of time; our results show that transmission of MRSA depended on patient activity in the room. Furthermore, degree of patient colonization is reflected by environmental contamination and supports the notion of constant transmission of MRSA from patients to environment.

Funding: None

Disclosures: None

Background: Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for the largest number of invasive infections due to a multidrug-resistant pathogen. Approximately 10% of hospitalized carriers will experience invasive MRSA disease in the year following discharge incurring antibiotic therapy beyond focused treatment of MRSA. Objective: We aimed to quantify the extent of non-MRSA empiric antibiotics incurred by MRSA infections and further assess the risk of Clostridioides difficile Infection (CDI) as a result of treatment of MRSA infection. Methods: The CLEAR Trial was a postdischarge randomized controlled trial of 2,121 MRSA carriers comparing MRSA education alone to education plus repeated decolonization that demonstrated a 30% reduction in MRSA infection and a 17% reduction in all-cause infection attributable to decolonization in the year following hospital discharge (Huang SS, NEJM 2019). We included all hospitalization outcomes due to MRSA infection in the CLEAR Trial with detailed medication administration records to quantify unintended consequences of MRSA infection related to empiric non-MRSA antibiotic use and resultant CDI. Full-text medical records were reviewed with a standardized abstraction form to collect inpatient administered antibiotics and hospital-associated CDI. Results: In total,154 hospitalizations due to MRSA infection with a mean length-of-stay of 10.6 days were identified. During 25 hospitalizations (16.2%), patients received only anti-MRSA antibiotics. During the remaining 129 (83.8%) hospitalizations, patients received a mean of 1.6 distinct non-MRSA antibiotics totaling a mean of 6.6 days of therapy (DOT). Empiric non-MRSA therapy was given for 3.2 DOT before MRSA culture results became available and was continued for an additional 3.4 DOT afterward. Among all 849 non-MRSA DOT, the most common were due to piperacillin-tazobactam (293 DOT, 34.5%), levofloxacin (105 DOT, 12.4%), and metronidazole (93 DOT, 11.0%). Across all 154 hospitalizations, a mean of 5.5 non-MRSA DOT was calculated per MRSA hospitalization, with 6 CDI cases (3.9%) as a direct sequelae of empiric non-MRSA antibiotics provided for MRSA infection. Conclusions: Hospitalization for MRSA infection results in extensive non-MRSA empiric antibiotic therapy both before and after MRSA culture results are known. This antibiotic use is associated with a 3.9% risk of CDI that exceeds the national risk of acquiring CDI (3.2 per 1,000 admissions) by 12-fold during any hospital stay (Barrett ML, AHRQ 2018). The CLEAR Trial findings that postdischarge decolonization reduces MRSA infection and hospitalization by 30% suggests that decolonization may also reduce non-MRSA antibiotic use and CDI in this population.

Funding: None

Disclosures: None

Background: Acute respiratory infections (ARIs) are a key target to improve antibiotic use in the outpatient setting. The Core Elements of Outpatient Antibiotic Stewardship provide a framework for improving antibiotic use, but data on safety and effectiveness of interventions to improve antibiotic use are limited. We report the impact of Core Elements implementation within Veterans’ Healthcare Administration clinics on antibiotic prescribing and patient outcomes. Methods: The intervention targeting treatment of uncomplicated ARIs (sinusitis, pharyngitis, bronchitis, and viral upper respiratory infections [URIs]) in emergency department and primary care settings was initiated within 10 sites between September 2017 and January 2018. The intervention was developed using the Core Elements and included local site champions, audit-and-feedback with peer comparison, and academic detailing. We evaluated the following outcomes: per-visit antibiotic prescribing rates overall and by diagnosis; appropriateness of treatment; 30-day ARI revisits; 30-day infectious complications (eg,, pneumonia,); 30-day adverse medication effects; 90-day Clostridium difficile infection (CDI); and 30-day hospitalizations. Multilevel logistic regression was used to calculate rate ratios (RR) with 95% CI for each outcome in the postintervention period (12 months) compared to the preintervention period (39–42 months). Results: There were 14,020 uncomplicated ARI visits before the intervention and 4,866 uncomplicated ARI visits after the intervention. The proportions of uncomplicated ARI visits with antibiotics prescribed were 59.17% before the intervention versus 44.34% after the intervention. A trend in reduced antibiotic prescribing for ARIs throughout the entire (before and after) observation period was evident (0.92; 95% CI, 0.90–0.94); however, a significant reduction in antibiotic prescribing after the intervention was identified (0.74; 95% CI, 0.59–0.93). Per-visit antibiotic prescribing rates decreased significantly for bronchitis and URI (0.54; 95% CI, 0.44–0.65), pharyngitis (0.76; 95% CI, 0.67–0.86), and sinusitis (0.92; 95% CI, 0.85–1.0). Appropriate therapy for pharyngitis increased (1.43; 95% CI, 1.21–1.68), but appropriate therapy for sinusitis remained unchanged (0.92; 95% CI, 0.85–1.0) after the intervention. Complications associated with antibiotic undertreatment were not different after the intervention: ARI-related revisit rates (1.01; 95% CI, 0.98–1.05) and infectious complications (1.01; 95% CI, 0.79–1.28). A potential benefit of improved antibiotic use included a reduction in visits for adverse medication effects (0.82; 95% CI, 0.72–0.94). Furthermore, 90-day CDI events were too sparse to model: preintervention incidence was 0.08% and postintervention incidence was 0.06%. Additionally, 30-day hospitalizations were significantly lower in the postintervention period (0.79; 95% CI, 0.72–0.87). Conclusions: Implementation of the Core Elements was safe and effective and was associated with reduced antibiotic prescribing rates for uncomplicated ARIs, improvements in diagnosis-specific appropriate therapy, visits for adverse antibiotic effects, and 30-day hospitalization rates. No adverse events were noted in ARI-related revisit rates or infectious complications. CDI rates were low and unchanged.

Funding: None

Disclosures: None

Background: A multinational outbreak of Mycobacterium chimaera endocarditis following cardiac surgery has been attributed to the use of heater-cooler units (HCUs) during cardiopulmonary bypass. It is hypothesized that mycobacteria can be transmitted to the surgical site via the aerosolization of contaminated water from within the unit. In the United Kingdom, M. chimaera infections have been linked to 1 specific make and model of HCU, which was shown to generate microbial aerosols when circulating water. The manufacturer has since modified this HCU and claims that the dispersal of aerosols has now been prevented. M. chimaera is a common contaminant of HCUs, regardless of make, model, and manufacturer. To help inform local decision making, hospitals require evidence that this modified HCU and/or alternative heater-cooler systems can reduce the risk of mycobacterial infection by incorporating design features that prevent the generation of microbial aerosols external to the device. The time required to culture M. chimaera means investigations focusing on naturally or artificially contaminated HCUs are problematic. Instead, specialist aerobiological techniques incorporating a nonpathogenic, aerostable, biological tracer (Bacillus atrophaeus) were used to investigate microbial aerosols generated and released from brand-new and ‘upgraded’ HCUs. Methods: 4 HCUs (A–D), supplied directly by the manufacturers, were filled with filtered tap water, and high numbers of B. atrophaeus (109 CFU/L) were added to the tanks. High-volume cyclone samplers were used to sample the air when each HCU was switched off and during different operational phases. Samplers were operated for 5 minutes and the collecting fluid cultured for B. atrophaeus. The number of colonies was converted to CFU per cubic meter of air. Results: Under controlled experimental conditions, HCU-A released a small but significant level of aerosol during operational phases (eg, cooling) that resulted in increased pressure within the tank. The filler flap was identified as the principal area of aerosol release. The circulation of water within HCU-B and HCU-C was shown to generate an aerosol but, when connected to an ‘aerosol collection set,’ this aerosol was not released. However, it is essential that effective and sufficient vacuum is maintained. There was no aerosol release from HCU-D. Conclusions: A specialist in aerobiology using a biological tracer can determine the level of aerosol released from an HCU and its location. However, transmission of M. chimaera could occur via aerosolization of contaminated water, but it is not the only possible route of infection. The efficacy of recommended decontamination procedures must also be assured.

Funding: None

Disclosures: None

Background: Healthcare-associated group A Streptococcus (GAS) infections can cause severe morbidity and death. Invasive GAS is a reportable condition in the 5-county metropolitan area of Denver, Colorado. Prior to August 2018, methodology to identify long-term care facility (LTCF) residency among reported GAS cases was accomplished by reviewing addresses reported electronically, and identification of postsurgical cases and outbreaks relied on reporting by healthcare facilities. We evaluated whether the use of a health information exchange (HIE) to identify healthcare exposures improved our ability to detect and rapidly respond to these events. Methods: In August 2018, we implemented a review of health records available in the HIE accessible by the Colorado Department of Public Health and Environment for all incoming reports of GAS for selected healthcare exposures: LTCF residency, surgery, delivery, wound care, and other relevant exposures. We defined an LTCF-related case as GAS in a current or recent resident (ie, in the 14 days prior to the positive culture) of an LTCF. Postpartum and postsurgical cases were defined as GAS isolated from a sterile site or wound during the inpatient stay or within 7 days of discharge following a delivery or surgical procedure. Outbreaks in each of these settings were defined as 2 or more cases within a 3-month period. We compared the number of cases and outbreaks identified in each category during a 1-year period before and after implementation of the use of the HIE in the case ascertainment process. Results: During August 2017 through July 2018, prior to implementation of the HIE process, we detected 45 LTCF cases and conducted outbreak investigations in 9 facilities. Moreover, 1 postsurgical case and 1 postpartum outbreak were reported by healthcare facilities; none were detected via surveillance. During August 2018 through July 2019, after the implementation of HIE process, we identified 70 LTCF cases and conducted outbreak investigations in 13 LTCFs. We detected 5 postsurgical cases and 3 postpartum cases, which resulted in 2 outbreak investigations. Conclusions: Enhanced GAS surveillance through use of a HIE resulted in detection of more healthcare-associated GAS infections and outbreaks. Timely identification of healthcare-associated GAS infections can allow for prompt response to outbreaks and promotion of proper infection control practices to prevent further cases. Jurisdictions in which GAS is a reportable condition should consider the use of HIEs as part of routine surveillance to identify GAS outbreaks in high-risk settings. HIEs should be made available to public health agencies for case ascertainment and outbreak identification.

Funding: None

Disclosures: None

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

Funding: None

Disclosures: None

Background: Hospitals struggle nationally to educate healthcare workers on the safe use of N95 respirators as part of their respiratory protection programs. Practical and effective interventions are needed to improve this clinical behavior, which is critical to healthcare worker safety in airborne precautions, hazardous drug administration, and pandemic response. Objective: In this analysis, we specifically investigated 2 just-in-time training interventions that would be practical to implement in a hospital setting. Methods: A simulation approach was used to evaluate 2 interventions for N95 respirator use at a Midwestern Academy Hospital system (n = 62 respirators: 32 control and 30 treatment). Healthcare workers were asked to don and doff an N95 respirator while being video-recorded in an empty hospital corridor and room. After a randomized intervention was applied, they repeated the respirator donning and doffing while being video-recorded. One intervention used an instructional video alone, and the other used the same instructional video but added a video reflection intervention. The video reflection intervention asked the participant to review and score their first performance of N95 donning and doffing using the Critical Safety Behavior Scoring Tool (CSBST). The research team used the same CSBST to score all performances of donning and doffing for comparison and evaluation. Result: The critical safety behaviors at the pretest and posttest for the 2 intervention groups reveal the impact of the 2 types of just-in-time training on demonstrated N95 respirator skills. The video alone and video reflection scores were not significantly different at pretest between the 2 groups. Scores were significantly higher on the posttest for the reflective practice intervention. Findings related to demographic information included years in healthcare, frequency of use, history of needlestick, and fatigue. Conclusions: Video reflection may improve compliance with critical safety behaviors for just-in-time training on N95 respirator use. Further research should examine the video-recorded findings for measurement elements that can be expanded in a scoring tool such as facial hair, hairstyle, and the quality of hand hygiene. Intervention studies should also examine how often the training must be repeated to maintain competency. This intervention may have implications for the training of other critical safety behaviors in infection control and other high-risk procedures.

Funding: None

Disclosures: None

Background: Hand hygiene is essential to prevent healthcare-associated infections, but adherence among clinicians remains low. Objective: We used a human factors framework to understand clinician perceptions of and barriers to achieving high reliability in hand hygiene. Methods: The Systems Engineering Initiative for Patient Safety 2.0 model was used to develop a 24-item electronic survey. Perceived barriers to hand hygiene were classified into several domains: technology and tools, person, organization, tasks, environment, and care processes. After pilot testing, the survey was distributed to a stratified random sample of attending physicians, nurse practitioners, and physician assistants in medical specialties and surgery-anesthesia at a quaternary-care pediatric hospital. Frequencies, percentages, and descriptive statistics were used to summarize responses. Results: Of 200 clinicians, 61 (31%) responded to the survey: 74% were attending physicians, 18% were nurse practitioners, and 7% were physician assistants. Moreover, 51% of respondents represented medical specialties, and 49% came from surgical disciplines or anesthesia. Respondents had served a median 12 years (IQR, 5–19 years) in their current role. Overall, 70% perceived hand hygiene to be “essential” among patient safety issues at the institution, and 84% agreed that leadership openly promotes hand hygiene. Additionally, 97% believed personal hand hygiene efforts were effective in preventing healthcare-associated infections. The availability of alcohol-based hand rub and being a good example for colleagues were perceived as “very effective” in permanently improving hand hygiene reliability by most respondents (87% and 67%, respectively). Furthermore, 77% of clinicians reported alcohol-based hand rub dispensers to be “sometimes” or “often” empty; 52% cited distractions in the workplace as hindrances to hand hygiene; and 21% reported that peers do not openly promote hand hygiene. One-quarter of the respondents indicated that the layout of patient care areas was not conducive to performing hand hygiene. Staffing shortages and the pace and demands of work precluded hand hygiene for 15% and 11% of respondents, respectively. Conclusions: Most clinicians view hand hygiene as essential to patient safety, but aspects of organizational culture, environment, tasks, and tools were identified as barriers to high performance reliability. These data can inform efforts to use human factors engineering principles to optimize systems and organizations to more effectively promote hand hygiene.

Funding: None

Disclosures: None

Background: Central venous catheters (CVCs) are used to provide necessary vascular access. Mechanical issues with the catheters, such as fractures, result in a break in the sterility of the line, increasing the patient’s risk for infection or other adverse events. During a 5-month period in 2018, 15 CVCs (involving 13 patients) were noted to have cracked hubs. Methods: An outbreak should be suspected when a number of adverse events occur above the expected rate. We used a standardized process, Association for Professionals in Infection Control and Epidemiology (APIC) Basic Principles of an Outbreak Investigation, to conduct the epidemiological investigation of the outbreak.Results: All 15 CVCs required replacement, and 1 case of bacteremia was recorded. We suspect that the underlying cause was related to changes in the manufacturing process of hubs along with the product used to prepare the hubs prior to access (Table 1). Conclusions: Following an outbreak investigation process to investigate a noninfectious related outbreak can ensure that a thorough and comprehensive investigation is being completed. Early recognition of an outbreak is essential to recognition of the outbreak and the implementation of mitigation strategies. Inconsistent reporting of adverse events related to mechanical issues with the catheters may have contributed to a delay in recognition.

Funding: None

Disclosures: None

Background: Hospital-acquired infections are commonly spread through the movement of healthcare professionals (HCPs). Computational simulations provide a powerful tool for understanding how HCP behavior contributes to these infections, but how well they reflect the real world rests on a number of critical parameters. Our goal is to provide accurate, fine-grained estimates of real HCP movement and interaction parameters suitable for simulating the potential spread of pathogens over different types of inpatient facilities. Methods: We obtained a commercial data set with 44 million deidentified elements compiled from >27,000 HCPs from >30 job types. The data were collected over 27 months from >20 facilities of varying size using a proprietary electronic sensor system. Each observation recorded an HCP visiting 1 of 12,000 rooms (38% being patient rooms) and consisted of the entry and exit time stamps, hand hygiene behavior, and for many rooms, their (x, y) geometric coordinates within the facility. From these data, we can reconstruct the behavior (including location and hand-hygiene adherence) of each instrumented HCP across multiple shifts. Results: Distributions describing various aspects of HCP behavior (eg, arrival rates and dwell times) were derived using HCP job function, department or unit assignment, type of shift (day vs night), time of day, facility size, and staffing of facility. In a similar fashion, we constructed HCP cross-table transition probabilities using job type, room type, department type, unit type, and facility type. These distributions were used to generate reasonable HCP movement and behavior patterns in a simulation environment. Distributions of dwell time were, for the most part, heavy tailed, but they varied by type of job and facility: dwell times over all facilities, job types, and room types averaged ∼339 seconds (SD, 495 seconds), with a mean of maximums by job type of ∼37,168 seconds. However, these distributions differ within job type but across facilities (ie, nurses in 1 facility averaged 397 seconds, but 277 seconds in another) and within facility but across job type. For example, physicians averaged 292 seconds, whereas nurses averaged 397 seconds and physical therapists averaged 861 seconds. Conclusions: Our results provide a unique resource for disease modelers who wish to build meaningful simulations of the transmission of hospital-acquired infections. The scale and diversity of the data gave us the unique capability to provide, with confidence, distinct parameter sets for different types and sizes of healthcare facilities across a wide range of situations.

Funding: None

Disclosures: None

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

Funding: None

Disclosures: None

Background: As of October 2019, the United States has seen the greatest number of annual measles cases reported since 1992, of which 2 outbreaks originated in Los Angeles County, California. Media reports and public awareness during outbreak events can result in large numbers of worried well patients or patients with outbreak mimics seeking medical attention. In densely populated cities, utilizing alternative approaches to in-person physician appointments can be beneficial to decrease both the overburden of healthcare resources as well as the spread of potential virus. During these measles outbreaks, we employed the use of telemedicine visits to facilitate triage and determination of in-person examination and testing needs. Methods: During the measles outbreak periods, patients who contacted the patient call center at our institution requesting an appointment for fever, rash, or expressing concerns for acute measles infection were instead routed for a telemedicine visit with a physician. All patients were all seen by the same physician, who was trained in internal medicine and pediatrics. During the telemedicine visit, patients were assessed for signs and symptoms consistent with acute measles based on CDC definition. If there was high enough clinical suspicion to warrant testing for measles, infection prevention coordinated logistics with clinic staff, including ensuring the use of appropriate personal protective equipment (PPE), end-of-day appointment scheduling, and appropriate diagnostic testing. Results: During this outbreak timeline, 7 patients were seen through telemedicine visits with ages ranging 13 months to 49 years. Also, 6 patients were scheduled due to a chief complaint of acute rash and 1 was due to a potential exposure to measles. Of 7 patients, 4 had received 1 dose of the MMR vaccine, and the remaining 3 were immune, unvaccinated, or had unknown immunity. The unvaccinated patient was further tested for measles but was IgM negative. Of those with chief complaint of rash, the diagnosis was determined to be some form of nonmeasles viral exanthem, allergic dermatitis/eczema, or hives. The exposed patient was deemed to be asymptomatic. Conclusions: During an outbreak, patients presenting to clinics with suspected measles symptoms can cause tremendous disruption, including concerns about exposure of staff and patients, need for contact tracing, and anxiety. Utilizing telemedicine appointments aided the management of patients during this outbreak by shifting physician evaluation outside the clinic. When evaluating suspect measles cases during an outbreak with patients who do not require further levels of care, telemedicine can prove to be useful in reducing the burden of potential exposure to others in the community and to the healthcare system.

Funding: None

Disclosures: None

Background: Group A Streptococcus (GAS) causes acute upper respiratory tract infections that are frequently treated with antibiotics. GAS vaccines in development may prevent both disease and outpatient antibiotic prescribing. We estimated (1) the incidences of GAS-attributable pharyngitis, sinusitis, and acute otitis media (AOM) infections in the United States; (2) the proportion of these infections resulting in antibiotic prescriptions; and (3) the incidence of infection and antibiotic prescribing potentially preventable by vaccination against GAS. Methods: We estimated annual rates of US outpatient visits and antibiotic prescriptions for pharyngitis, sinusitis, and AOM using physician office and emergency department visit data in the National Ambulatory Care Survey and National Hospital Ambulatory Medical Care Survey from 2012 to 2015. We supplemented this with visits to other outpatient settings (eg, urgent care) from the 2016 IBM MarketScan Commercial Database. We estimated the proportion of episodes attributable to GAS and to GAS emm types targeted by a 30-valent vaccine in development using data from previously conducted etiology studies. We estimated the incidence of disease and antibiotic prescribing preventable by a vaccine meeting the WHO 80% efficacy target for preventing noninvasive GAS disease, with doses administered during infancy and at age 4 years. We estimated the proportion of outpatient antibiotic prescribing preventable by vaccination by dividing estimates by total antibiotic dispensations, estimated from the IQVIA TM dataset. Results: Among individuals aged 0–64 years, GAS causes 27.3 (95% CI, 24.6–30.6) ambulatory care visits and 16.4 (95% CI, 14.5–18.6) outpatient antibiotic prescriptions per 1,000 population annually for pharyngitis, sinusitis, and AOM combined, representing 2.1% (95% CI, 1.8%–2.4%) of all outpatient antibiotic prescriptions. Among children aged 3–9 years, GAS-attributable incidence includes 124.4 (95% CI, 109.0–142.1) visits and 77.1 (95% CI, 65.7–90.6) antibiotic prescriptions per 1,000 population annually, representing 8.6% (95% CI, 7.3%–10.1%) of antibiotic prescriptions in this age group. Individual-level direct protection from a 30-valent vaccine meeting the WHO target could prevent 26.0% (95% CI, 24.0%–28.1%) of pharyngitis visits; 17.3% (95% CI, 15.5%–19.5%) of pharyngitis, sinusitis, and AOM visits; and 5.5% (95% CI, 4.7%–6.4%) of outpatient antibiotic prescriptions among children aged 3–9 years. If vaccination eliminated the need for antibiotic treatment of pharyngitis (for which GAS is the only etiology warranting antibiotic treatment), the total effects of vaccination could include the prevention of up to 17.2% (95% CI, 15.0%–19.6%) and 6.8% (95% CI, 6.3%–7.3%) of antibiotic prescriptions among persons 3–9 years and 0–64 years of age, respectively. Conclusions: In addition to preventing infections and healthcare visits, an efficacious GAS vaccine could prevent a substantial volume of outpatient antibiotic prescribing in the United States.

Funding: This work was supported by the Centers for Disease Control and Prevention. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Disclosures: Laura M. King is a contractor employed by Northrop Grumman Corporation to fulfill research needs at the Centers for Disease Control and Prevention as part of a contract covering many positions and tasks. All other authors declare no conflicts.

Background: From August 2017 to June 2018, 11 hospitals within a large healthcare system switched from multiple different electronic medical records (EMRs) to 1 EMR. At the time of this transition, the NHSN provided guidelines to validate healthcare-associated infection (HAI) denominators when switching from manual denominator collection to electronic denominator collection, but the NHSN did not give guidelines for validation when switching from 1 EMR to another. We aimed to build a validation process to ensure the accuracy of central-line and urinary catheter days reported to the NHSN after switching EMRs. Methods: Our validation process began with a statistical phase followed by a targeted manual validation phase. The statistical phase used 3 prediction methods (linear regression, time series analysis, and statistical process control [SPC] charts) to forecast device days after the EMR switch for units within hospitals. Models were developed using baseline data from the old EMR (January 2015 through the new EMR implementation). Using prespecified criteria for each method to determine discrepancies, we built a decision tree to identify units needing manual validation. Any unit that failed the statistical phase would need to participate in the manual validation phase, using a midnight census and direct visualization of devices. The manual validation process was composed of 14-day blocks. At the end of each block, if manual device days were within ±5% of EMR device days, they were considered validated. Manual validation would be repeated in 14-day blocks until 2 consecutive blocks passed within ±5%. Results: Overall, 157 units were evaluated for urinary catheter days and central-line days. Among them, 143 units passed the statistical validation test for urinary catheter days and 151 passed for central-line days. There was no specific pattern when comparing forecasted versus actual device days. The manual validation process for the 20 failing units (14 urinary catheter and 6 central-line units) is ongoing; preliminary results identified issues with missing nursing documentation in the EMR and with inaccurate manual counting of device days. There were no systematic discrepancies associated with the new EMR. Conclusions: We developed a novel validation process using statistical prediction methods supplemented with a targeted manual process. This process saved resources by identifying the units that need manual validation. Discrepancies were largely related to nursing documentation, which the infection prevention team addressed with additional training.

Funding: None

Disclosures: None

Background: In the Erasmus MC University Medical Center, Rotterdam, the Netherlands, patients considered at risk for carrying highly resistant microorganisms (HRMO) are placed in isolation on admission, until tested negative for HRMO (ie, targeted screening). Patients without risk factors are not routinely screened (ie, nontargeted screening). However, nontargeted screening could identify patients colonized with HRMO missed by targeted screening. To determine the additional value of nontargeted screening, we compared the outcomes of the nontargeted screening approach with all available clinical cultures. Objective: We aim to identify patients colonized with HRMO, but missed by targeted screening, and to determine whether non-targeted screening has additional value. Methods: For the MOVE study, nontargeted admission and discharge cultures (nose and perianal) were obtained from randomly selected patients admitted to specific wards, regardless of HRMO risk factors. This study was part of a research initiative to identify the relation of a contaminated environment with the risk of becoming infected or colonized on a patient level. All bacteriological clinical samples positive for at least 1 HRMO from January 1, 2018, until August 31, 2019, were compared with the nontargeted screening samples. Samples were screened for methicillin-susceptible Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) as well as highly resistant Pseudomonas aeruginosa, Acinetobacter baumannii, Enterococcus faecium, and Enterobacteriales. Broth enrichment was used for all cultures. Results: During the study period, 50,653 patients were admitted. 706 patients (1%) had a clinical sample positive for at least 1 HRMO during their hospital stay. 936 (1.8%) patients were included in the nontargeted screening for the MOVE study, and 40 patients were found to have at least 1 culture positive for HRMO (4.3%). Among these 40 patients, 28 were positive at admission and 12 were positive at discharge. Extended-spectrum β-lactamase (ESBL)–producing Enterobacteriales were most prevalent (n = 36, 90.0%) both at admission and discharge (n = 26 and n = 10, respectively). At admission, 1 patient was identified with MRSA and 1 patient was positive for vancomycin-resistant E. faecium (VRE). At discharge, 1 patient was identified with VRE and 1 had Verona Integron-encoded Metallo-β-lactamase (VIM)–positive P. aeruginosa. Conclusions: Our results show that the current targeted screening does not identify all HRMO carriers. Furthermore, patients who acquire an HRMO during admission are missed. The nontargeted screening identified 40 unknown carriers (4.3%). The limitations of the study are the restricted number of sample sites and the fact that we were unable to culture all patients. Therefore, it is likely that our study shows an underestimation of the true number of patients with HRMO.

Funding: None

Disclosures: None

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

Funding: None

Disclosures: None

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

Funding: None

Disclosures: None