Background: Rates of ventilator-associated events (VAEs), including infection-related ventilator-associated complications (IVACs) and probable ventilator-associated pneumonia (PVAPs) have increased nationwide since the onset of the COVID-19 pandemic. In December 2021, our health system adopted a new electronic medical record (EMR), which changed the way surveillance for VAEs is performed. We reviewed surveillance criteria, COVID-19 status, and culturing practices in attempts to understand why VAE rates continue to be elevated. Methods: We collected data on VAE type, culture data, COVID-19 status, and surveillance criteria for all patients meeting NHSN definitions for VAE from 2018 through November 2022. For all patients in 2022 (post-EMR transition), 2 physicians (A.D. and M.D.) manually reviewed documented ventilator settings from flow sheets to validate the automated EMR data, and they evaluated culture data for appropriateness. Cultures were defined as appropriate unless they were included in “pancultures” for leukocytosis without concern for pneumonia documented. Rates were compared using an interrupted time series (ITS) analysis before and after the onset of the COVID-19 pandemic and the EMR transition. Patient level data were compared across periods using the χ2 test. All analyses were performed using SAS version 9.4 software. Results: COVID-19 has been implicated in the increasing number of VAEs since the pandemic began: 6% of patients in 2020, 18% in 2021, and 23% in 2022 (P < .001). The percentage of patients meeting criteria for VAE by positive end-expiratory pressure (PEEP) decreased from 2018 to 2022 (92%, 95%, 93%, 85%, 85%, respectively; P = .0004). Patients meeting criteria for VAE by fraction of inspired oxygen (FiO2) increased from 2018 to 2022 (9%, 6%, 11%, 17%, 19%, respectively; P = .0002). Manual review of 2022 data indicated opportunities for test stewardship in 8 of 65 patients with cultures (12%). ITS analysis revealed that IVAC+ rates were climbing prior to the onset of the COVID-19 pandemic (Fig. 1). We observed a marked increase in rates with the implementation of our new EMR and the changes to our surveillance process (0.32 cases per 100 ventilator days). Manual review of records from 2022 revealed 5 patients in which documentation of ventilator settings to meet VAE diagnosis could not be retrieved from flow sheets. Conclusions: COVID-19 continues to affect VAE despite vaccine availability and may partially account for elevated rates nationwide. However, changes in EMR-automated VAE surveillance may also affect rates. Our findings suggest that automated surveillance captures transient or spurious changes in ventilator machine settings that do not accurately represent clinical status. These data may contribute to spurious increases in VAE. More studies are needed to better understand the impact of both COVID-19 and automated surveillance on VAE.

Disclosures: None

Background: Hand-hygiene technology (HHT) intends to monitor and promote hand washing by healthcare workers, a critical measure of infection control. Healthcare worker noncompliance with HHT is a major limitation to its implementation and utility in clinical settings. We assessed perspectives on HHT in an academic hospital system. Methods: Hand-hygiene team members created an anonymous, 37-question, Likert-scale survey to assess healthcare worker attitudes toward HHT. Surveys targeted nursing staff, advanced practice providers, care partners, and internal medicine physicians. Clinical coordinators from 5 distinct nursing units and 1 physician department emailed surveys to eligible employees. Research coordinators and clinical coordinators also posted a QR code for survey fliers at nursing stations. Results: Overall, 120 surveys were completed. Most surveys were completed by nurses and physicians (66.4% and 14.0%). Most respondents (67.5%) do not find HHT useful. Additionally, 78.3% of respondents believe that HHT does not accurately record hand-washing events. Most (78.3%) do not like using HHT, and 75.8% find it annoying. Only 10.8% believe that patient care suffers because of HHT. Conclusions: Most healthcare workers dislike the HHT badges, primarily due to perceived inaccuracies, lack of utility, burden of use, and pressure to comply. Distrust and effect on patient care do not appear to be substantial factors contributing to negative perceptions of HHT. Weaknesses of the study include overrepresentation of nursing staff and potential bias because respondents may have provided exceptionally negative responses believing it could lead to the removal of HHT.

Disclosures: None

Electronic hand hygiene monitoring systems allow the collection of large volumes of data. However, significant resources are required to validate and maintain these systems. Additionally, data are lacking on the correlation with clinically important outcomes. Direct observation of hand hygiene remains the gold standard for monitoring hand hygiene compliance.

Background: The COVID-19 pandemic has made a significant impact on antimicrobial use patterns across health systems. We have described antibiotic use patterns at an academic medical center in Richmond, Virginia, before and after the onset of COVID-19. We also examined the impact on the proportional consumption of carbapenems (PoCC) metric. PoCC represents meropenem utilization relative to the narrower-spectrum antipseudomonal agents cefepime and piperacillin-tazobactam. Our institution practices antimicrobial restriction for meropenem. All other antibiotics included in the study data can be freely ordered by any provider. Methods: We evaluated antimicrobial use data from September 2018 through August 2021 using days of therapy (DOT) per 1,000 patient days. We included 18 months of data before and after the first recorded COVID-19 admission at our institution in March 2020. Mean comparisons were performed using the Welch 2-sample t test. The Bonferonni correction for multiple comparisons was utilized to determine significance with an initial baseline α of 0.05. All data analyses were performed using R software (R Foundation for Statistical Computing, Vienna, Austria, 2021). Results: Normality was evaluated with QQ-plots and all data demonstrated normality. Bonferroni correction produced an adjusted α value of 0.007. We detected significant increases in the use of cefepime, piperacillin-tazobactam, ceftriaxone, and azithromycin following the onset of the COVID-19 pandemic. We noted a significant decrease in the PoCC metric during this period. No significant change was noted for levofloxacin or meropenem. Conclusions: The COVID-19 pandemic produced significant changes in antimicrobial use patterns at our institution. We noted statistically significant increases in bacterial community-acquired pneumonia-focused antibiotics (ceftriaxone and azithromycin). We observed significant increases for cefepime and piperacillin-tazobactam. Interestingly, relative utilization of carbapenems as measured by the PoCC metric continued to decrease during this time. This trend was primarily driven by increases in cefepime and piperacillin-tazobactam utilization while meropenem utilization remained relatively constant. This study highlights the importance of looking at normalized antibiotic consumption data and not relative-use data alone.

Funding: None

Disclosures: None

Challenges for infection prevention and antimicrobial stewardship programs have arisen with the fourth wave of the coronavirus disease 2019 (COVID-19) pandemic, fueled by the delta variant. These challenges include breakthrough infections in vaccinated individuals, decisions to re-escalate infection prevention measures, critical medication shortages, and provider burnout. Various strategies are needed to meet these challenges.

The use of an electronic hand hygiene monitoring system (EHHMS) decreased due to the coronavirus disease 2019 (COVID-19) pandemic. We analyzed dispenser use, hand hygiene (HH) badge use, and HH compliance to determine the effect of COVID-19 on EHHMS use and HH compliance. HH product shortages and other pandemic-induced challenges influenced EHHMS use.

Background: Colorectal surgery is associated with a high risk of surgical site infections (SSIs), with an incidence ranging from 16.9% to 20%, and SSIs are associated with significant morbidity and mortality, prolonged length of hospitalization, and increased health care costs. Staphylococcal decolonization is an attempt to alter the microbiome to prevent staphylococcal and other skin flora from accessing the surgical site, and This practice effectively reduces SSIs in orthopedic, neurologic, and cardiac surgeries. A staphylococcal decolonization protocol was enacted in colorectal surgeries at our institution beginning in October 2016. We compared patient outcomes between patients who did and did not undergo preoperative staphylococcal decolonization. Methods: All patients undergoing nonemergent NHSN-defined colorectal procedures from July 2015 until June 2019 at a tertiary-care medical center were included in this retrospective study. Staphylococcal decolonization was performed using chlorhexidine 2% body wash solution, mupirocin nasal ointment, and chlorhexidine 0.12% oral rinse all twice daily for 5 days prior to surgery. All SSIs were defined by NSHN criteria. The primary outcome was SSI, and secondary outcomes were superficial wound infection (SIP) and organ-space infection (IAB). Predictive variables included decolonization status (yes or no), age, gender, body mass index, procedure duration, American Society of Anesthesiologists (ASA) score, diabetes, smoking, and surgical oncology service. Surgical antimicrobial prophylaxis with cefazolin and metronidazole OR cefoxitin, and chlorhexidine skin preparation were standard throughout the study period. Univariate analysis was performed using a χ2 or t test. Multivariable logistic regression was performed to control for all clinically important variables above. All statistical analyses were done using SAS version 9.4 software (Cary, NC). Results: In total, 1,139 patients underwent nonemergent colorectal surgery from July 2015 to June 2019. There were 74 SSIs: 42 IABs and 32 SIPs. Decolonization was performed in 332 of 1,139 cases (29%). There was no difference in overall SSIs between those decolonized and not decolonized (P = .50). However, SIPs were reduced in the group receiving decolonization: 1.2% (4 of 332) versus 3.5% (28 of 807) (P = .04. When controlling for known SSI risk factors, those not receiving decolonization remained at increased risk of SIPs (OR, 3.79; 95% CI, 1.14–12.61; P = .03. Conclusions: Staphylococcal decolonization may prevent a subset of SSIs in patients undergoing colorectal surgery.

Funding: None

Disclosures: Michelle Doll reports a research Grant from Molnlycke Healthcare.

Background: Data regarding outpatient antibiotic prescribing for urinary tract infections (UTIs) are limited, and they have never been formally summarized in Virginia. Objective: We describe outpatient antibiotic prescribing trends for UTIs based on gender, age, geographic region, insurance payer and International Classification of Disease, Tenth Revision (ICD-10) codes in Virginia. Methods: We used the Virginia All-Payer Claims Database (APCD), administered by Virginia Health Information (VHI), which holds data for Medicare, Medicaid, and private insurance. The study cohort included Virginia residents who had a primary diagnosis of UTI, had an antibiotic claim 0–3 days after the date of the diagnosis and who were seen in an outpatient facility in Virginia between January 1, 2016, and December 31, 2016. A diagnosis of UTI was categorized as cystitis, urethritis or pyelonephritis and was defined using the following ICD-10 codes: N30.0, N30.00, N30.01, N30.9, N30.90, N30.91, N39.0, N34.1, N34.2, and N10. The following antibiotics were prescribed: aminoglycosides, sulfamethoxazole/trimethoprim (TMP-SMX), cephalosporins, fluoroquinolones, macrolides, penicillins, tetracyclines, or nitrofurantoin. Patients were categorized based on gender, age, location, insurance payer and UTI type. We used χ2 and Cochran-Mantel-Haenszel testing. Analyses were performed in SAS version 9.4 software (SAS Institute, Cary, NC). Results: In total, 15,580 patients were included in this study. Prescriptions for antibiotics by drug class differed significantly by gender (P < .0001), age (P < .0001), geographic region (P < .0001), insurance payer (P < .0001), and UTI type (P < .0001). Cephalosporins were prescribed more often to women (32.48%, 4,173 of 12,846) than to men (26.26%, 718 of 2,734), and fluoroquinolones were prescribed more often to men (53.88%, 1,473 of 2,734) than to women (47.91%, 6,155 of 12,846). Although cephalosporins were prescribed most frequently (42.58%, 557 of 1,308) in northern Virginia, fluoroquinolones were prescribed the most in eastern Virginia (50.76%, 1677 of 3,304). Patients with commercial health insurance, Medicaid, and Medicare were prescribed fluoroquinolones (39.31%, 1,149 of 2,923), cephalosporins (56.33%, 1,326 of 2,354), and fluoroquinolones (57.36%, 5,910 of 10,303) most frequently, respectively. Conclusions: Antibiotic prescribing trends for UTIs varied by gender, age, geographic region, payer status and UTI type in the state of Virginia. These data will inform future statewide antimicrobial stewardship efforts.

Funding: None

Disclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.

Background: Quantification of the magnitude of CRE both within a facility and regionally poses a challenge to healthcare institutions. Periodic point-prevalence surveys are recommended by the CDC CRE tool kit as a facility-level prevention strategy. A 2016 point-prevalence survey of 2 high-risk units at a tertiary-care center in the United States for CRE colonization found that all patients surveyed were negative for CRE. The infection prevention (IP) team repeated the study in 2019 to reassess the prevalence of CRE in the healthcare facility. Methods: A point-prevalence survey was performed in November 2019 on the same 2 high-risk units surveyed in 2016. A perirectal flocked swab was collected from all patients unless a patient refused and/or a contraindication to rectal swab was present. Swabs were inoculated onto HardyChrom TM CRE agar for incubation in ambient air at 35°C for 24 hours. Organism identification was performed using MALDI-TOF mass spectrometry on a MBT Smart by Bruker. Results: None of the patients on either high-risk unit was known to be colonized or infected with CRE at the time of the point-prevalence survey. Of 41 perirectal swabs collected, 4 (9.8%) were positive for CRE. None (0 of 20) were surgical ICU patients and 4 of 21 (19%) were medical ICU patients. All positive swabs revealed different organisms identified as follows: Escherichia coli, Enterobacter cloacae, Enterobacter kobai, and Enterobacter aerogenes. All 4 positive patients had had recent contact with multiple acute-care hospitals. Also, 2 had been transferred for liver transplant evaluation. None of these patients had received a carbapenem during their admission to the facility. Conclusion: CRE are increasingly identified in healthcare centers in the United States. Centers previously classified as low prevalence will need to maintain preventive strategies to limit transmission risks as colonized patients arrive in the facility for care. Adoption of a robust horizontal infection prevention program may be an effective strategy to avoid the spread of CRE.

Funding: None

Disclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.

Background: The relationship between nursing staffing and healthcare-associated infections (HAIs) has been explored previously, with conflicting results. Intensive care units increasingly struggle to maintain trained staff. In May 2019, clinical coordinator (CC) roles changed to include 50% of time in direct patient care rather than supportive roles. In this study, we used shift records to explore the impact of staffing on HAI risk. Methods: Daily staffing records from December 2018 August 2019 for the medical-respiratory unit (MRICU) and the cardiac surgery unit (CSICU) were reviewed. Both units staff a fixed 2:1 patient:nurse ratio (1:1 for specific cardiac surgeries). Staff deficiency was defined as assignments filled by nurses pulled from other units/supplemental/or CC roles. Staff support comprised nursing assistants and unit secretaries. Census, admissions, and complexity score for number of devices were used to estimate care acuity. In CSICU, additional points were added for continuous renal replacement therapy, extracorporeal membrane oxygenation, ventricular assist devices, transplant, operative cases. NHSN definitions were used for central-line–associated bloodstream infections (CLABSIs) and catheter-associated urinary tract infections (CAUTIs). The Spearman correlation coefficient was used to determine relationship between staffing, acuity, and risk window for HAI (days 1–10 preinfection). Linear regression was used to determine whether staffing deficiencies and/or support associate with the risk window prior to HAI. The final model included census and complexity score as control variables. The statistical analysis was performed using SAS version 9.4 software (Cary, NC). Results: Overall, 8 HAIs occurred in the study period: medical-respiratory intensive care unit (MRICU: 3 CAUTIs and 1 CLABSI) and cardiac surgery intensive care unit (CSICU: 1 CAUTI and 3 CLABSIs). Staffing and census fluctuated daily (Table 1). Total number of nurses correlated with complexity scores (r = 0.35; P < .0001) and daily census (r = 0.31; P < .0001) in the CSICU, and the census (r = 0.12; P = .04) in the MRICU. Nursing deficiencies correlated with days 1–10 before infection (r = 0.20; P = .0013) in the CSICU. In the regression model for the CSICU, nursing deficiencies increased in the time prior to HAI (P = .004), and support staff decreased in the time prior to HAI (P = .034) while controlling for census and complexity. These relationships were not significant in the MRICU. Conclusion: The lack of core nurses to support the staffing structure in CSICU correlated with periods prior to CLABSI or CAUTI in this small, unit-based study. Failure to recruit and retain highly skilled core staff may produce HAI risks, particularly for CLABSI in specialized units.

Funding: None

Disclosures: Michelle Doll, Research Grant from Molnlycke Healthcare

Background: Central-line–associated blood stream infections (CLABSIs) are linked with significant morbidity and mortality. A NHSN laboratory-confirmed bloodstream infection (LCBSI) has specific criteria to ascribe an infection to the central line or not. The criteria used to associate the pathogen to another site are restrictive. This objective to better classify CLABSIs using enhanced criteria to gain a comprehensive understanding of the error so that appropriate reduction efforts are utilized. Methods: We conducted a retrospective review of medical records with NHSN-identified CLABSI from July 2017 to December 2018 at 2 geographically proximate hospitals. Trained infectious diseases personnel from tertiary-care academic medical centers, the University of Virginia Health System, a 600-bed medical center in Charlottesville, Virginia, and Virginia Commonwealth University Health System with 865 beds in Richmond, Virginia, reviewed charts. We defined “overcaptured” or O-CLABSI into different categories: O-CLABSI-1 is bacteremia attributable to a primary infectious source; O-CLABSI-2 is bacteremia attributable to neutropenia with gastrointestinal translocation not meeting mucosal barrier injury criteria; O-CLABSI-3 is a positive blood culture attributable to a contaminant; and O-CLABSI-4 is a patient injecting line, though not officially documented. Descriptive analyses were performed using the χ2 and the Fisher exact tests. Results: We found a large number of O-CLABSIs on chart review (79 of 192, 41%). Overall, 56 of 192 (29%) LCBSIs were attributable to a primary infectious source not meeting NHSN definition. O-CLABSI proportions between the 2 hospitals were statistically different; hospital A identified 34 of 59 (58%) of their NHSN-identified CLABSIs as O-CLABSIs, and hospital B identified a 45 of 133 (34%) as O-CLABSIs (P = .0020) (Table 1). When comparing O-CLABSI types, hospital B had a higher percentage of O-CLABSI-1 compared to hospital B: 76% versus 64%. Hospital A had a higher proportion of O-CLABSI-2: 21 versus 7%. Hospitals A and B had similar proportion of O-CLABSI-3: 15% versus 18%. These values were all statistically significant (P < .0001). Discussions: The results of these 2 geographically proximate systems indicate that O-CLABSIs are common. Attribution can vary significantly between institutions, likely depending on differences in incidence of true CLABSI, patient populations, protocols, and protocol compliance. These findings have implications for interfacility comparisons of publicly reported data. Most importantly, erroneous attribution can result in missed opportunity to direct patient safety efforts to the root cause of the bacteremia and could lead to inappropriate treatment.

Funding: None

Disclosures: Michelle Doll, Research Grant from Molnlycke Healthcare