bluuebunny/crossref_metadata_2025 huggingface dataset:
Surgical Site Infections at a Level I Trauma Center in India: Data From an Indigenously Developed, e-SSI Surveillance System
Authors: Lohiya Ayush , Mittal Samarth , Trikha Vivek , Khurana Surbhi , Katyal Sonal , Sagar Sushma , Kumar Subodh , Malhotra Rajesh , Mathur Purva
Published: November 2020

Background: Globally, surgical site infections (SSIs) not only complicate the surgeries but also lead to $5–10 billion excess health expenditures, along with the increased length of hospital stay. SSI rates have become a universal measure of quality in hospital-based surgical practice because they are probably the most preventable of all healthcare-associated infections. Although, many national regulatory bodies have made it mandatory to report SSI rates, the burden of SSI is still likely to be significant underestimated due to truncated SSI surveillance as well as underestimated postdischarge SSIs. A WHO survey found that in low- to middle-income countries, the incidence of SSIs ranged from 1.2 to 23.6 per 100 surgical procedures. This contrasted with rates between 1.2% and 5.2% in high-income countries. Objectives: We aimed to leverage the existing surveillance capacities at our tertiary-care hospital to estimate the incidence of SSIs in a cohort of trauma patients and to develop and validate an indigenously developed, electronic SSI surveillance system. Methods: A prospective cohort study was conducted at a 248-bed apex trauma center for 18 months. This project was a part of an ongoing multicenter study. The demographic details were recorded, and all the patients who underwent surgery (n = 770) were followed up until 90 days after discharge. The associations of occurrence of SSI and various clinico-microbiological variables were studied. Results: In total, 32 (4.2%) patients developed SSI. S. aureus (28.6%) were the predominant pathogen causing SSI, followed by E. coli (14.3%) and K. pneumoniae (14.3%). Among the patients who had SSI, higher SSI rates were associated in patients who were referred from other facilities (P = .03), had wound class-CC (P < .001), were on HBOT (P = .001), were not administered surgical antibiotics (P = .04), were not given antimicrobial coated sutures (P = .03) or advanced dressings (P = .02), had a resurgery (P < .001), had a higher duration of stay in hospital from admission to discharge (P = .002), as well as from procedure to discharge (P = .002). SSI was cured in only 16 patients (50%) by 90 days. SSI data collection, validation, and analyses are essential in developing countries like India. Thus, it is very crucial to implement a surveillance system and a system for reporting SSI rates to surgeons and conduct a robust postdischarge surveillance using trained and committed personnel to generate, apply, and report accurate SSI data.

Funding: None

Disclosures: None
Survey for “iCarePATH”: Improving Caregivers’ Perceptions and Attitudes Towards Hand Washing
Authors: Zahradnik Stephanie , Okeny-Owere James , Tsampalieros Anne , Webster Richard , Bedard Pat , Seidman Gillian , Thampi Nisha
Published: November 2020

Background: Hand hygiene (HH) is the most effective means of preventing healthcare-associated infections (HAI). HH improvement strategies primarily focus on healthcare staff, often overlooking the significant contribution of caregivers to HAI risk. We sought to understand caregivers’ HH knowledge and practices to identify improvement opportunities. Methods: A self-administered survey was developed and distributed to families from June to August 2019; open-ended questions and Likert scales assessed caregivers’ perceptions and practices regarding HH at home and in hospital. HH compliance audits of caregivers entering and exiting inpatient rooms were performed in the same time period. Results: Among 81 caregivers surveyed, median patient age was 4.0 (IQR, 0.9–13.0) years. This was the first admission for 42 patients (53.8%). During this admission, 22 (27.2%) patients had been admitted for ≤1 day and 45 (55.6%) for >3 days. Caregivers reported good knowledge of HH practice, with strongly positive responses to knowledge of HH moments (94%) and proper technique (96%). Caregivers recognized that HH is required of hospital visitors (96%) to protect others (99%) and prevent illness in hospital (93%). Responses were less consistent for performing HH before entering a hospital room (83%), after exiting the room (70%), or after coughing or sneezing (65%). The attitudes of caregivers of children above 2 years were equivocal regarding expectations of their child to wash hands upon entering (40%), or exiting (41%) the hospital room. Multivariable modeling identified higher self-reported HH compliance in caregivers during first admission to hospital, compared to subsequent admissions (OR, 3.15; 95% CI, 1.11–9.65). Reported barriers to HH included hand irritation (27.2%) and perceived HH frequency (18.5%). At the time of survey completion, 62 caregivers (77%) reported not having received HH information during their child’s admission from a healthcare provider or volunteer. Information was most commonly gained from posters (75%) and information in the room (31%). Most caregivers (58.0%) reported that they would prefer to receive HH information in the first 24 hours of admission. Among 200 audits, overall caregiver compliance with HH was 9%; HH before entering the room was 7.2% compared to 11.2% after exiting (P = .33). Conclusions: Reported caregiver knowledge of HH was not reflected in audited practice. Fewer than 1 in 4 had received HH information from healthcare staff. HH education in the hospital environment within the first day of admission provides an opportunity for caregivers to improve compliance as partners in HAI prevention and safer pediatric care.

Funding: None

Disclosures: None
Temporal Change of Risk Factors in Hospital-Acquired Clostridioides difficile Infection Using Time-Trend Analysis
Authors: Song Jiyoun , Cohen Bevin , Zachariah Philip , Liu Jianfang , Larson Elaine
Published: November 2020

Background: In the past few decades, the epidemiology of Clostridioides difficile infection (CDI) has evolved. Given recent changes in the incidence of CDI and prevention efforts, we investigated temporal changes over a period of 8 years (2009–2016) in the incidence of and risk factors for CDI. Methods: Both pediatric and adult inpatients discharged from hospitals in metropolitan New York City were included. Individual and environmental (eg, pharmacological) risk factors were identified through a matched case-control by the length of stay at a ratio of 1:4. A Cochran–Armitage test or Mann-Kendall test was used to investigate trends of incidence and risk factors. Results: During the study period, 6,038 of 694,849 (0.87%) patients had a positive test for C. difficile during their hospitalization. Of these, 2,659 of 6,038 (44.04%) were identified as hospital-acquired CDI (HA-CDI) and just over half (3,379 of 6,038, 55.96%) were identified as community-acquired CDI (CA-CDI). There were no trends in total CDI incidence rates; rather, we detected downward trends in HA-CDI and upward trends in CA-CDI (Ptrend < .05). Younger patients and patients with lower risk of illness had HA-CDI over time (Ptrend < .05). Antibiotics were administered to more patients over time and in longer cumulative days (+3% and +3.1% per year). We detected a reduction in the receipt of high-risk antibiotics in all cohorts (−0.12% per year) and a decrease in cumulative days of high-risk antibiotics in the cohort with HA-CDI (−1.1% per year). When stratified by the type of high-risk antibiotics, the use of carbapenem, cephalosporins, clindamycin, and monobactam increased (+0.53%, +1.8%, +0.5%, and +0.39% per year, respectively), whereas the use of broad-spectrum penicillins and glycylcycline significantly decreased over time in all cohorts (−1.8% and −0.22% per year). Among the cohorts with HA-CDI, only cephalosporins showed a significant upward trend (+ 5.7% per year) and only fluoroquinolones showed a significant downward trend (−2.2% per year). Lastly, a reduction of proton pump inhibitors and an increased use of histamine-2 blockers were detected in all cohorts (−3.8% and +7.3% per year) (all Ptrend < .05). Conclusions: Although the incidence of HA-CDI decreased, more effort to decrease all antibiotics use and cumulative days should be emphasized as part of antibiotic stewardship. The downward trends of high-risk antibiotics might have been associated with the decrease in the trend of HA-CDI; however, the impact of the trends of risk factors on the trend of HA-CDI should be further investigated.

Funding: None

Disclosures: None
The Great Masquerade: Identification of Clinically Relevant Clostridioides difficile Infections
Authors: Sickbert-Bennett Emily , Stancill Lisa , DiBiase Lauren , Alby Kevin , Weber David Jay
Published: November 2020

Background: Despite clear guidance for appropriate testing of symptomatic patients for Clostridioides difficile testing (McDonald et al), the ideal testing methodology remains unresolved. Laboratories currently use different algorithms that incorporate enzyme immunoassay (EIA) testing for toxin, glutamate dehydrogenase (GDH) antigen, and polymerase chain reaction (PCR) testing in combination or as a single test. At UNC Hospitals, a large academic hospital with nearly 1,000 beds in the ninth most populous state in the United States, patients are currently tested by an EIA test for toxin and GDH antigen first, and discordant toxin/GDH results are referred for PCR testing. Previous studies have demonstrated that detection of toxin by EIA is a better predictor of C. difficile infection (CDI) complications (Polage et al). Methods: We investigated all patients who were tested for C. difficile from July 2018 to June 2019. Within each testing methodology and result, we assessed the percentage of patients with at least 3 loose stools documented within a 24-hour period, percentage with a severe episode based on white blood cell (WBC) counts >15,000 cells/mL, or percentage with a serum creatinine level >1.5 mg/dL. Fisher-type confidence intervals were calculated for each proportion. Results: Patients positive for C. difficile by the EIA method had 66.9% appropriate loose stool documentation (95% CI, 57.4%–75.5%), whereas patients with EIA-indeterminate (toxin negative, GDH positive) and positive by only PCR had 49.7% appropriate loose stool documentation (95% CI, 42.7%–56.8%). C. difficile patients that tested negative had 48.1% appropriate loose stool documentation (95% CI, 46.0–50.2%). In addition, patients positive by the EIA method had nearly double the proportion of severe disease by WBC or creatinine criteria compared to patients who were either positive by PCR or who tested negative (Table 1). Conclusions: Patients positive for C. difficile by the EIA method were statistically more likely to meet criteria for loose stool documentation. There was no statistically significant difference between patients that tested positive only by PCR or who tested negative. The percentage of patients with severe episode criteria based on WBC or creatinine was nearly doubled between those who tested positive by EIA and PCR (20% vs 10%), although this finding was not statistically significant. The percentage with severe disease (WBC or creatinine) was nearly identical among patients who were positive by PCR and who tested negative. These findings demonstrate that documentation of loose stool is a more sensitive indicator of toxin detection than either clinical parameter, reinforcing the importance of stool documentation in evaluating patients for C. difficile testing.

Funding: None

Disclosures: None
The ICEL Healthcare-Associated Infection Probability Equation
Authors: Moore Mark
Published: November 2020

Backround: In American hospitals alone, the CDC estimates that hospital acquired infections (HAIs) account for an estimated 1.7 million infections and 99,000 associated deaths each year.1 Although the United states and most industrialized nations have made strides in lowering the overall HAI rate by taking critical steps to reduce HAIs, an overall formula that combines a global risk assessment per patient for HAI acquisition has yet to be established. To address this issue, we developed the ICEL equation. This equation uses a probabilistic argument to estimate the likelihood of HAI acquisition and to promote infection control dialogue among healthcare practitioners from diverse healthcare disciplines. Methods: We defined HAI risk using the ICEL acronym as follows: HAI risk = (I + C + E + L), where I is invasive devices present; C is patient-specific characteristics; E is the average number of pathogenic organisms in the patient environment; and L is the length of stay. A simple scale of 1–10 points is subjectively assigned for each of the following categories:

I = (number of invasive devices / surgeries / % body surface areas open)

C = Patient specific characteristics (immune system integrity / immunomodulators / radiation exposure / chemotherapy, etc)

E = Environmental conditions / cleaning (average number of pathogenic bacteria in room, 100% hand hygiene compliance, patient / staff colonization, etc)

L = Length of stay days risk, where 0–3 days is low risk, 4–7 is moderate risk, and 8–10+ is high risk

Summing the points for each of the 4 categories, the greatest possible total is 40. A total score of 0–10 indicates low risk of HAI; 11–20 indicates low-to-medium risk of HAI; 20–30 indicates a high risk of HAI; and 30–40 indicates a very high risk of HAI. Results:This equation was designed to stimulate thought and encourage multidisciplinary cooperation among providers, nursing, environmental services, and facilities departments rather than provide an exact number for HAI risk. All of these categories are key players in the determining patient risk of acquiring an HAI. If any of the 4 hospital departments mentioned fails in their duties, the patient is at higher risk of HAI. Conclusions: This categorical HAI risk assessment relies on the subjective medical and environmental knowledge of the assessor to assign risk across the continuum of the healthcare environment. Although it is nearly impossible to provide exact numbers regarding total risk in these risk categories, the goal of the scoring system is to encourage clinical dialogue among hospital staff so that they communicate and collaborate within their specialties and with their peers to assure that each category poses as low a risk as possible, thus driving the total risk for HAI lower.

1. https://www.cdc.gov/hai/data/portal/progress-report.html

Funding: None

Disclosures: None
The Role of Routine Practice in Healthcare Worker Strategies when Doffing Unfamiliar Personal Protective Equipment
Authors: Chasco Emily , Silva Jaqueline Pereira da , Dukes Kimberly , Baloh Jure , Ward Melissa , Salehi Hugh , Reisinger Heather , Pennathur Priyadarshini , Abbott Loreen Herwaldt
Published: November 2020

Background: Appropriate doffing of personal protective equipment (PPE) prevents healthcare worker (HCW) self-contamination and spread of pathogens. HCWs may encounter an array of PPE types (eg, gloves, gowns, masks) and designs (eg, masks with elastic ear loops vs ties) during their duties, some of which may be unfamiliar. We know little about how HCWs strategize when doffing unfamiliar PPE. As part of a larger study examining the doffing process and the risk of self-contamination, we used qualitative methods to explore factors influencing HCW PPE doffing strategies. Methods: In total, 70 HCW participants from 2 Midwestern academic hospitals were assigned to 1 of 4 doffing simulation scenarios. In the first 3 scenarios, participants were asked to doff 3 mask designs (n = 10), 2 gown designs (n = 10), or 2 glove designs (n = 10). In the fourth scenario, HCWs with different levels of training (n = 40) participated in 2 doffing simulations randomized per participant: a distraction simulation and a nondistraction simulation (using identical PPE types and designs). In all scenarios, participants were instructed to doff in their usual manner. Doffing performances were video-recorded. Participants then reviewed the recordings and took part in short semistructured interviews about their performance. Interviews were audio-recorded, transcribed, and analyzed using thematic analysis. Results: When faced with unfamiliar PPE during the simulations, participants were required to problem solve. In so doing, participants reported drawing on their day-to-day routine practices with familiar PPE to inform their doffing strategies. Aspects of routine practice identified as influential included PPE types typically worn, PPE donning and doffing order, doffing frequency, familiar PPE design cues, and experience tailoring strategies to specific patient care contexts. Participants frequently reported the desire to avoid self-contamination as driving doffing strategies and problem solving, but they also noted unique patient care demands related to their specific roles when they explained their doffing decisions. At the same time, HCWs identified lack of familiarity, lack of training, and nonintuitive design as barriers to doffing appropriately when encountering unfamiliar PPE. Conclusions: Different PPE designs may not be interchangeable, and proper doffing techniques may not be intuitive. The previous experiences of HCWs informed their strategies when doffing unfamiliar PPE. However, this practice sometimes caused them to use inappropriate doffing techniques and resulted in self-contamination. This finding has important implications for hospital policies and procedures regarding the introduction of new PPE and indicates that HCWs need training when new items are introduced.

Funding: None

Disclosures: None
The Use of Light Sensors in Alcohol Gel Dispensers to Improve Hand Hygiene Compliance of Health Care Workers
Authors: Gonçalves Priscila , Menezes Fernando Gatti de , Santiago Ana Carolina , Kataoka Laura , Martineli Paula Fernanda , Lucinio Neide Marcela , Ferraz Leonardo Jose Rolim , Victor Elivane da Silva , Prado Marcelo , Gagliardi Guilherme Machado , Marra Alexandre
Published: November 2020

Background:
Improving adherence to hand hygiene (HH) of healthcare workers (HCWs) is a challenge for health institutions, and the use of technologies has been considered an important strategy within this process. Methods: To evaluate the impact of the use of alcohol-based hand rub gel (ABHR) dispensers with light sensors on the adherence to HH by HCWs. This is a prospective quasi-experimental study with comparative analysis between two 4-bed adult intensive care units at a private, tertiary-care hospital conducted over 22 weeks. An approach detection module with an LED lamp was attached to the ABHR dispenser. As a healthcare personnel approached it, the sensor was activated, and a red light turned on as a visual stimulus for HH. The color of the light changed to blue when HH was performed. All ABHR dispensers had electronic counters, but light sensors were installed only in the 4-bed dispensers of the intervention unit. Throughout the period, direct observation of adherence to HH was performed by 4 nurses who had previously been rated with an excellent coefficient of agreement (κ test = 0.951 and 0.902). At the end of the study, a perception survey was performed with the HCWs. Results: The median activation of ABHR dispensers per week was higher in the intervention unit with 1,004 (IQR, 706–1,455) versus 432 (IQR, 350–587) in the control group (P < .001). The same occurred when compared to the median activation per 1,000 patient days, with 53,069 (IQR, 47,575–67,275) versus 19,602 (IQR, 15,909–24,500) in the control group (P < .001). However, there was no evidence of difference in adherence to HH during direct observation between the 2 groups: 51.0% HH compliance (359 of 704) in the control group and 53.8% HH compliance (292 of 543) in the intervention group (P = .330). The same result emerged when we evaluated the “My Five Moments for HH” and by professional category. HCWs (N=66) answered the perception survey: 66.6% stated that lighting devices caught their attention regularly or most of the time and 59% agreed that the devices motivated HH. Conclusions: Using light sensors in ABHR dispensers can be an effective technology for improving HH. This finding was evident in the evaluation of the number of uses of the ABHR dispensers and in the HCW perceptions. Although direct observation did not show statistical evidence of difference between the groups, adherence was higher in the intervention group.

Funding: None

Disclosures: None
Treatment Outcomes and Subsequent Healthcare Utilization Among Patients With Injection Drug Use–Associated Endocarditis
Authors: Dhanani Muhammad , Acuna-Villaorduna Carlos , Barlam Tamar
Published: November 2020

Background: Addiction medicine consultation and medication-assisted treatment (MAT) have been promoted as a way to improve outcomes for patients hospitalized with injection drug use–associated endocarditis (IDU-IE). However, IDU-IE outcomes have not been evaluated in settings where these services are commonplace. Objective: In this study, we evaluated IDU-IE outcomes in a setting where involvement of addiction medicine consultants and use of MAT is well integrated into patient care. Methods: Medical records of patients hospitalized with a diagnosis of bacteremia or infective endocarditis (IE) between October 1, 2015, and December 31, 2017, at a safety-net hospital in Boston were screened for evidence of active injection drug use (IDU) within 6 months of hospitalization (as documented by providers or as supported by urine toxicology assays) for suspected or definite IE using modified Duke criteria. Patients without active IDU or IE were excluded, as were those with a diagnosis of IDU-IE over the 6 months prior to the index hospitalization. Demographic parameters, receipt of antibiotics and MAT, other clinical information, and details of rehospitalizations were recorded. Analyses of descriptive statistics were performed. Results: Of 567 subjects screened for inclusion, 47 patients met inclusion criteria. All had opiate use disorder (OUD); 41 patients (87.2%) had polysubstance abuse. Addiction medicine consultation was completed for 41 patients (87.2%). Of the 47 subjects, 23 patients (54.8%) received MAT (methadone or buprenorphine/naloxone) over their entire hospitalization, and 31 patients (73.8%) received MAT for >75% of the index admission. Moreover, 43 patients (91.5%) survived to discharge, of whom 28 (59.6%) completed antibiotic therapy. Relapsed IDU was observed in 33 patients (76.7%). Relapsed IDU trended toward significance among undomiciled patients (OR, 4.07,; 95% CI, 0.93–17.85; P = .06). Also, 24 patients (55.8%) were rehospitalized within 1 year due to infectious complications of IDU; undomiciled patients were readmitted more frequently (OR, 20.45; 95% CI, 1.09–383.99; P = .04). Completion of IDU-IE antibiotic therapy, relapse of IDU, and rehospitalization were not associated with prior AMA discharges, duration or variety of IDU, receipt of MAT during the index admission, or addiction medicine consultation. The rate of readmission due to an infectious complication of IDU within 1 year was unrelated to the proportion of hospital days where MAT was prescribed. Conclusions: In settings with high rates of addiction medicine consultation and in-hospital MAT administration, inpatient interventions targeting OUD may not necessarily be protective against morbidity and rehospitalization. Focusing on housing instability and outpatient continuation of MAT may be beneficial.

Funding: None

Disclosures: None
Two-Year Surveillance of Central-Line–Associated Bloodstream Infections in Non-ICU Wards in a Dutch Teaching Hospital
Authors: Weterings Veronica , Boersma Rinske , Rijen Breda Miranda van , Rijpstra Tom , Kluytmans Jan
Published: November 2020

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
Use of a Biological Tracer to Investigate Microbial Aerosols Generated by Heater-Cooler Units
Authors: Moore Ginny , Parks Simon , Bennett Allan
Published: November 2020

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
Using a Critical Safety Behavior Scoring Tool for N95 Respirator Use to Evaluate Training Interventions
Authors: Beam Elizabeth , Kupzyk Kevin , Herstein Jocelyn , Gibbs Shawn
Published: November 2020

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
Using Data Collected from a Commercial Sensor System to Inform Mathematical Models of Healthcare-Associated Infections
Authors: Liang Jiazhao , Jang Hankyu , Hasan D M Hasibul , Polgreen Philip , Pemmaraju Sriram , Segre Alberto
Published: November 2020

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
Validation Methodology of Healthcare-Associated Infection Device Day Denominators When Switching Electronic Medical Records
Authors: Luong Lan , Simkins Michelle , Snyders Rachael , Gase Kathleen Anne , Leone Carole , Sykora Carol , Hoehner Christine , Babcock Hilary
Published: November 2020

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
VIM-Positive Pseudomonas aeruginosa Sink Colonization Dynamics in Patient Rooms of a Dutch Tertiary-Care Hospital
Authors: Pirzadian Jannette , Klaassen H.W. , Goeij Inge de , Vos Margreet C. , Severin tte A.
Published: November 2020

Background: In hospitals, Verona integron-encoded metallo-β-lactamase (VIM)–positive Pseudomonas aeruginosa (VPPA) frequently colonize sink drains. Sink use has been shown to disperse VPPA to other surfaces surrounding sinks, creating a potential transmission source. Objective: Because VPPA have been isolated from sinks and patients within our hospital, we analyzed colonization dynamics in 2 sinks identified as VPPA hot spots between 2012 and 2018. Methods: One sink was in an intensive care unit (ICU) patient room and the other was in a gastrointestinal surgery (GIS) patient room. ICU patients were screened for VPPA on admission, at discharge, and weekly during hospitalization. GIS patients were screened for VPPA only on clinical indication. In this study, patient and sink isolates were typed at 8 loci using multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA). Results: Overall, 19 sink isolates from the ICU room were included. In 2013, VPPA isolates with identical VNTR genotypes (“clone B,” VNTR nos. 2-4-8-4-4-5-10-[-2]) were found in the wash basin, aerator, drain, and siphon. The drain plug was replaced in August 2013, but B was isolated from the drain 1 month later. Every year between 2014 and 2018, clone B and other closely related genotypes were recovered from this drain. In 2018, clone B was also found on the wash basin and counter. No positive patients were identified in this room until 2016, when a patient acquired clone B 6 days after admission. From the GIS room, 6 sink isolates and 4 patients’ isolates were included. In 2012, clone B was found on the wash basin and sink drain plug. Also, 3 VPPA-positive patients stayed in this room in 2012: at discharge, 1 patient was colonized by “clone A,” VNTR numbers 6-7-8-5-9-8-6-1. Furthermore, 2 other patients screened positive for clone B prior to admission in 2012, so they likely acquired VPPA elsewhere. The drain plug was replaced in 2013, and no VPPA was found again until 2017, when 2 VPPA-positive patients stayed in this room: 1 was already a carrier of clone B, and the other was a carrier of clone B 1 day after admission. No positive sink cultures were found until January 2018, when closely related B isolates were recovered from the wash basin, drain, and drain plug. Conclusions: Between 2013 and 2018, clone B persisted in the ICU room sink. In the GIS room sink, clone B may have disappeared after 2012, but it was reintroduced by known carriers. However, few patients became colonized after being admitted to these rooms, even when VPPA were discovered on surfaces outside the sink drain (ie, the wash basin and counter).

Funding: None

Disclosures: None
What’s in a Handshake? Exploring the Best Form of Greeting to Prevent Hand to Hand Spread of Viruses
Authors: Jones Lucas , Ha Wilson , Cadnum Jennifer , Donskey Curtis
Published: November 2020

Background:
Respiratory and enteric viruses are highly contagious pathogens that can be spread by contaminated hands and surfaces. We hypothesized that alternatives to handshake greetings that reduce the time and surface area of hand contact would be associated with decreased transfer of viral particles. Methods: In a simulation of hand-contact greetings, volunteers (N = 22) used a keyboard contaminated with the benign bacteriophage MS2 and then performed a handshake and fist bump with additional volunteers. To assess viral transfer, hands were cultured for MS2, and plaque-forming units (PFU) were compared for the different types of hand contact. Additional simulations (N = 10) were conducted to compare viral transfer with the fist bump versus a cruise tap greeting (ie, a modified fist bump involving single knuckle contact). Results: The handshake greeting resulted in significantly greater transfer of MS2 than the fist bump (1.31 vs 0.54 log10 PFUs, P < .001) (Fig. 1A), but the frequency of transfer of virus was high for both greetings (91% transfer by handshake vs 59% by fist bump). The cruise-tap greeting did not result in reduced transfer of viral particles in comparison to the fist bump (Fig. 1B), and the frequency of transfer remained high (70%). Conclusions: The fist-bump and cruise-tap greetings could potentially reduce transmission of viruses in comparison to the handshake, but transfer occurred frequently, even with these greeting methods. To eliminate hand-to-hand transmission of respiratory and enteric viruses, alternative greeting methods that do not involve physical contact are needed.

Funding: None

Disclosures: None
Where To From Here? Identifying and Prioritizing Future Directions for Addressing Drug-Resistant Infection in Australia
Authors: Hall Lisa , Merlo Greg , Avent Minyon , Yarwood Trent , Smith Bonnie , Driel Mieke van
Published: November 2020

Background: The Australian Government released a national strategy for antimicrobial resistance in 2015 that calls for a collaborative effort to change practices that have contributed to the development of drug-resistant infection and for the implementation of new initiatives to reduce antibiotic use. Although many achievements have been made in antimicrobial stewardship (AMS), particularly in the acute-care hospital setting, progress more broadly has been slow, and novel solutions are now required to improve clinical practice and community awareness. A facilitated workshop was undertaken at the 2019 National Australian Antimicrobial Resistance Forum to explore the complexity of AMS implementation in Australia and to prioritize future action. Methods: Participants engaged in rotating rounds of discussion using a world café format. The participants sat face-to-face at tables of 7 or fewer. At each table were 2 facilitators: one was a note taker and the other was the discussion leader. Each of the 6 facilitator pairs had a topic for discussion related to implementing antimicrobial stewardship in different contexts, with a focus on experience with strategies that have worked, major implementation barriers, and prioritizing the next steps. The topics for discussion included (1) engaging with hospital staff; (2) implementation in resource-poor settings; (3) implementation in primary care and aged care; (4) engaging and empowering the public; (5) linking data with implementation strategies; and (6) leadership. The facilitators moved between tables at 15-minute intervals to encourage evolving rounds of conversation. Once all tables had discussed all of the themes, the discussion concluded and notes were summarized. A qualitative analysis using an interpretive description approach was conducted using the discussion summaries. The documents were independently openly coded by 2 researchers to identify elements relating to the implementation of antimicrobial stewardship. An iterative approach was used to identify themes and reach a consensus on overarching emergent themes from the workshop. Results: In total, 39 experts (ie, pharmacists, infectious disease physicians, infection prevention nurses, researchers, journalists and consumers) participated in the facilitated discussions. Strategies were discussed relating to engaging with clinicians, consumers, and politicians; adapting to funding, governance, and accreditation limitations; and models for outreach of antimicrobial services. Other themes included the role of clinical champions and mentors as leaders and improving use of audit and feedback through focusing on monitoring appropriateness rather than usage. Conclusions: Recommendations from the workshop will be used to prioritize novel ideas to improve the implementation of AMS initiatives across Australia.

Funding: None

Disclosures: None
Whole-Genome Sequencing for Bacterial Strain Typing Using the iSeq100 Platform
Authors: Vestal Grant , Bruzek Steven , Lasher Amanda , Lima Amorce , Silbert Suzane
Published: November 2020

Background: Hospital-acquired infections pose a significant threat to patient health. Laboratories are starting to consider whole-genome sequencing (WGS) as a molecular method for outbreak detection and epidemiological surveillance. The objective of this study was to assess the use of the iSeq100 platform (Illumina, San Diego, CA) for accurate sequencing and WGS-based outbreak detection using the bioMérieux EPISEQ CS, a novel cloud-based software for sequence assembly and data analysis. Methods: In total, 25 isolates, including 19 MRSA isolates and 6 ATCC strains were evaluated in this study: A. baumannii ATCC 19606, B. cepacia ATCC 25416, E. faecalis ATCC 29212, E. coli ATCC 25922, P. aeruginosa ATCC 27853 and S. aureus ATCC 25923. DNA extraction of all isolates was performed on the QIAcube (Qiagen, Hilden, Germany) using the DNEasy Ultra Clean Microbial kit extraction protocol. DNA libraries were prepared for WGS using the Nextera DNA Flex Library Prep Kit (Illumina) and sequenced at 2×150-bp on the iSeq100 according to the manufacturer’s instructions. The 19 MRSA isolates were previously characterized by the DiversiLab system (bioMérieux, France). Upon validation of the iSeq100 platform, a new outbreak analysis was performed using WGS analysis using EPISEQ CS. ATCC sequences were compared to assembled reference genomes from the NCBI GenBank to assess the accuracy of the iSeq100 platform. The FASTQ files were aligned via BowTie2 version 2.2.6 software, using default parameters, and FreeBayes version 1.1.0.46-0 was used to call homozygous single-nucleotide polymorphisms (SNPs) with a minimum coverage of 5 and an allele frequency of 0.87 using default parameters. ATCC sequences were analyzed using ResFinder version 3.2 and were compared in silico to the reference genome. Results: EPISEQ CS classified 8 MRSA isolates as unrelated and grouped 11 isolates into 2 separate clusters: cluster A (5 isolates) and cluster B (6 isolates) with similarity scores of ≥99.63% and ≥99.50%, respectively. This finding contrasted with the previous characterization by DiversiLab, which identified 3 clusters of 2, 8, and 11 isolates, respectively. The EPISEQ CS resistome data detected the mecA gene in 18 of 19 MRSA isolates. Comparative analysis of the ATCCsequences to the reference genomes showed 99.9986% concordance of SNPs and 100.00% concordance between the resistance genes present. Conclusions: The iSeq100 platform accurately sequenced the bacterial isolates and could be an affordable alternative in conjunction with EPISEQ CS for epidemiological surveillance analysis and infection prevention.

Funding: None

Disclosures: None