A 54-question survey about System Healthcare Infection Prevention Programs (SHIPPs) was sent out to SHEA Research Network participants in August 2023. Thirty-eight United States-based institutions responded (38/93, 41%), of which 23 have SHIPPs. We found heterogeneity in the structure, staffing, and resources for system infection prevention (IP) programs.

Immediate-use steam sterilization (IUSS) shortens the time of sterilization but may increase the risk of surgical site infection (SSI). Among 23,919 procedures with 416 (1.7%) procedures resulting in SSI, IUSS was associated with a 1.52 (95% CI, 1.10–2.11) times higher risk of SSI. IUSS should be minimized.

Background: Hospitals are increasingly consolidating into networks and integrating infection prevention (IP) into system infection prevention programs (SIPP). Very little has been published about these programs. This survey sheds light on the current state of SIPPs. Methods: We used the survey generator Alchemer.com for setting up the questionnaire, and tested a beta version among peers. The final version was sent out to SHEA Research Network participants in August 2023. Raw data was compiled and analyzed. Results: Forty institutions responded (40/104, 38%), of which 25 (63%) had SIPPs. These SIPPS reported health systems with a median of 4.5 acute care hospitals (range, 1-33); 16 SIPPS reported a median of 2 critical access hospitals (range, 1-8); 4 SIPPs reported 1-3 LTACHs, and 6 SIPPS reported a median of 1.5 nursing homes. All except 3 (88%) contained an academic center; 48% (11/23) of the U.S. based programs operate in multiple states. Four programs have been in place >20 years, four < 2 years, and the remainder a median of 8 years (range, 2-18). Physician directors also have clinical (20/25, 80%), teaching (19/25, 76%), research (15/25, 60%), antimicrobial stewardship (8/25, 32%), quality (8/25, 32%), and/or patient safety (5/25, 20%) roles. Seventeen (68%) report having a written job description. Nineteen (76%) report having an infection preventionist in a system IP director role; only 7/25 (28%) have a dedicated system IP team that operates independent of individual hospitals. Sixteen (64%) report administrative support, 10/25 (40%) have a data manager/analyst, and 4/25 (16%) include IT expert or programmer support. 15/25 (60%) report having done a formal system-wide IP needs assessment. While 16/25 (64%) have some automation in HAI surveillance (predominantly using Bugsy [Epic] or Theradoc [Premier]), while only 5/25 (20%) run fully automated surveillance. 10/25 (40%) have implemented centralized surveillance. 12/25 (48%) have “system IP policies” that are hierarchically above individual site policies. The biggest challenges appear to be gaps in 1) clear governing structure, 2) communication, 3) consistent staffing, 4) data management support, and 5) dedicated, empowered IP expert FTEs. Conclusions: To our knowledge, this is the first U.S. survey to explore present-day system infection prevention. In this sample of hospital networks, we found heterogeneity in the structure, staffing and resources for system IP with significant opportunities for improvement. In this era of healthcare consolidation, our findings highlight the urgent need to more clearly delineate and support system IP needs in order to enhance their functionality.

Background: Detection of outbreaks traditionally relies on passive surveillance, and often misidentify or miss outbreaks. Whole genome sequencing (WGS) surveillance has emerged as a proactive measure, enabling early detection of outbreaks and facilitating rapid intervention strategies. WGS surveillance has not been widely studied due to infrastructure, cost, and evidence barriers regarding its impact on reducing healthcare-associated infections (HAIs). This study represents findings from two years of a real-time WGS surveillance program called the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT). Methods: The study was conducted at UPMC Presbyterian hospital, a 694-bed tertiary care center. Patient isolates of select bacterial pathogens were collected and underwent WGS weekly from November 2021 to November 2023. Potential transmission was defined using single-nucleotide polymorphism thresholds (≤15 for all organisms except Clostridioides difficile). Genetically related clusters were reviewed weekly for epidemiological linkages (unit, personnel, or procedural commonalities) and appropriate interventions were initiated by the infection prevention and control team. We described the frequency of genetic relatedness and nature of epidemiological linkages. Results: Of 7,051 eligible unique patient organism isolates, 4,723 were deemed healthcare-associated and underwent WGS. EDS-HAT identified 478 (12.2%) isolates genetically related to ≥1 other isolate across 173 clusters. Epidemiological links were found in 278 (58.2%) isolates in 114 clusters, with the majority being unit-based (205 isolates, 71.9%); other epidemiological links included equipment or healthcare workers (32 isolates, 11.5%), external facilities (24 isolates, 8.6%), and shared endoscopes (17 isolates, 6.1%); all endoscope outbreaks were effectively contained at two patients. No epidemiological links could be identified for 200 (41.8%) isolates. Infection prevention initiated 134 interventions in 114 clusters, including 74 (55.2%) general staff notification and education, 25 (18.7%) enhanced cleaning efforts, 23 (17.2%) hand hygiene/personal-protective equipment compliance observations, 9 (6.7%) environmental cultures, and 3 (2.2%) enhanced microbiological surveillance. Following the detection of an epidemiological link and intervention, 94/101 (94.1%) outbreaks were effectively halted on the intervened route (Figure). Conclusion: This study demonstrates the feasibility and efficacy of EDS-HAT as an infection prevention tool. Early detection and intervention of outbreaks significantly enhance the capability of healthcare facilities to control and prevent the spread of HAIs. Investment in infrastructure and implementation costs will result in reducing pathogen transmission and improving patient safety in acute care settings.

Disclosure: Alexander Sundermann: Honoraria - Opgen

Background: Immediate use steam sterilization (IUSS) shortens the time from sterilization to the aseptic transfer onto the surgical sterile field. Published data incompletely defines the extent to which IUSS increases risk of surgical site infection (SSI), compared to standard sterile reprocessing methods. We aimed to measure the association between IUSS use for surgical instrument reprocessing and SSI risk in a facility where IUSS use increased due to staffing constraints and case volumes. Methods: In this retrospective observational study at a tertiary care hospital with a diverse mix of surgery types, we used sterile reprocessing logs and SSI outcomes defined using National Health and Safety Network definitions to compare SSI rates among surgeries using surgical devices sterilized using IUSS compared to standard terminal sterilization methods. We calculated a risk ratio (RR) and 95% confidence interval (95%CI), including stratification by eleven high-volume service lines. Results: Among 23,919 surgical procedures, 416 (1.74%) developed SSIs. IUSS was used to sterilize instruments prior to 1,524 (6.37%) surgical procedures, and of these procedures 39 (2.56%) developed an SSI, compared to 1.68% of non-IUSS procedures (377 SSI in 22,395 procedures; risk ratio [RR] 1.52, 95% confidence interval [95%CI] 1.10-2.11). Two surgical services had statistically significant RRs for SSI development after IUSS: transplant surgery (RR 2.47, 95%CI 1.32-4.60] and plastic surgery (RR 3.64, 95%CI 1.13-11.74; Figure). Conclusion: IUSS is associated with a significant increase in SSIs, including among varied surgery types. IUSS utilization should be minimized.

Background: Contact precautions (CP) to prevent transmission of multidrug-resistant gram-negative (MDRGN) Enterobacteriaceae are recommended, although studies of discontinuation of CP (DcCP) have found no change in healthcare associated infections (HAI) due to extended-spectrum beta-lactamase (ESBL) producing Enterobacteriaceae. Limited data exists on DcCP for MDRGN in a large health system. Methods: We performed a retrospective observational study analyzing the relationship between use of CP and HAI due to two definitions of MDRGN Enterobacteriaceae: ESBL, and non-susceptibility to ≥3 drug classes (3DC-GNR), with carbapenem resistant Enterobacteriaceae (CRE) serving as control. The study included all inpatient admissions from 2/2017 through 9/2022 at 21 acute care hospitals. Hospitals had latitude to determine CP practices based on local risk assessment, but in 2/2018, system-wide transmission-based precautions guidance was updated to recommend DcCP for MDRGN Enterobacteriaceae and in 12/2019 was updated to clarify DcCP specifically for ESBL and 3DC-GNR while continuing CP for carbapenem-resistant organism carriage. We interviewed infection preventionists to define when CP were used for CRE, ESBL, and 3DC-GNR Enterobacteriaceae. HAI were defined using National Healthcare Safety Network criteria including all HAI categories. We compared the incidence rate of HAI attributable to the two MDRGN types in hospital months with and without use of CP, with HAI due to CRE as a comparison group since all hospitals used CP for CRE throughout the study period. Results: The periods of CP use, by hospital, are shown in Figure 1. Throughout the study period, there were 987 HAI attributed to ESBL Enterobacteriaceae, 579 due to 3DC-GNR Enterobacteriaceae, and 329 due to CRE. Figure 2 shows the unadjusted aggregate rate of HAI for each of the three MRGN types, including among hospitals with and without CP in each month, for ESBL and 3DC-GNR. In months with and without CP, the rate of HAI was 1.482/10,000 and 1.093/10,000 patient days (incidence rate ratio [IRR], 1.356 [95% confidence interval, 1.195-1.540]) for ESBL Enterobacteriaceae. In months with and without CP, the rate of HAI was 1.071/10,000 and 0.493/10,000 patient days (IRR,2.173[95% confidence interval, 1.838-2.569]) for 3DC-GNR Enterobacteriaceae. Conclusion: DcCP was not associated with an increase in HAI due to ESBL and 3DC-GNR Enterobacteriaceae in aggregated facilities that self-selected for DcCP. Facilities that used CP were associated with significantly higher rates of ESBL and 3DC-GNR Enterobacteriaceae, a relationship that did not change as hospitals DcCP for these MDRGN. Further analyses are necessary to assess for a causal relationship.

Background: Clinically non-indicated asymptomatic bacteriuria (ASB) identification precipitates higher reported catheter-associated urinary tract infection (CAUTI) rates and urinary tract infection (UTI)-directed antimicrobial overuse. Published diagnostic stewardship interventions to reduce ASB were mostly tested individually and heterogeneously; hence the optimal bundle approach is yet to be defined. Methods: We performed a single-center sequential quasi-experimental study involving hospitalized, emergency, and long-term care patients at a VA healthcare facility, retrospectively comparing standard of care (period 1: 1/1/2022-6/30/2022) to adding dedicated provider education on facility-approved urine-culturing indications (period 2: 7/1/2022-1/19/2023), then adding an electronic clinical decision support (CDS) tool (Figure 1) mandating urine-culturing indications selections (period 3: 1/20/2023-6/30/2023), then prospectively adding real-time case-based physician-generated audit/feedback emails on ordering appropriateness (period 4: 7/1/2023-12/31/2023). We randomly sampled approximately 500 orders from each period and measured the impact on the rate of urine reflex/culture orders, the percentage of non-indicated orders and ASB, UTI-directed antimicrobial usage, and facility-wide CAUTI rates. Results: We analyzed 2140 urine reflex/culture orders (Table 1 and Figure 2). The mean monthly orders per 1000 bed-days and percentage of non-indicated orders decreased with each intervention to one-fourth of the initial values by period 4 (p=0.0002). The ASB rate among positive cultures was unchanged from periods 1 to 2 but started to decrease in period 3 with the biggest impact in period 4 (p=0.01). Non-indicated and ASB-directed antimicrobial courses both followed the previous pattern, dropping from 28% and 26% baseline to 6% and 4% by the study conclusion (p=0.015 and 0.008), respectively. Estimated UTI-directed antimicrobials decreased by 34% (363/551) with antimicrobial-days saved from 4093 to 2846 per 6-month period. CAUTI rate relatively declined with each intervention, along with a reduction in ASB-attributed CAUTI’s from 45% (5/11) initially to 20% (1/5) in period 4. Conclusion: A stepwise urine-culturing diagnostic stewardship approach of clinical education, electronic CDS tool, plus real-time audit/feedback decreased overall urine reflex/cultures, non-indicated ordering, ASB identification, unnecessary antimicrobials, and CAUTI rates, with the greatest impact after bundling all interventions including order appropriateness audit/feedback.

Background: Nontuberculous mycobacteria (NTM) are ubiquitous potential pathogens implicated in healthcare-associated outbreaks. There is a paucity of studies describing transmission risk in the healthcare setting. To estimate the potential healthcare-associated transmission of NTM, we characterized the frequency of NTM clinical isolates across our multi-facility healthcare system. Method: We performed a retrospective review of all clinical NTM isolates at 21 healthcare facilities in a large health system between January 2019 through June 2023 (inclusion criteria: all first unique species). We analyzed the quarterly frequency of isolates for each species, by facility. We identified higher-than-expected species frequencies, which was defined as a quarterly frequency ≥50% higher than the average quarterly frequency for that facility, for the entire study period (analysis omitted for any hospital with an average quarterly frequency 10 unique patient isolates in any 12-month period or >2 in a single month except for M. abscessus at Hospital A. The quarterly frequency of the three most common species among hospitals with ≥2 unique isolates per 12-month period are displayed in figure 2. An increase of 50% from the average quarterly infection count occurred 34 times for M. avium complex across 10 hospitals, 14 times for M. gordonae across 2 hospitals and 14 times for M. lentiflavum across 2 hospitals (Figure 3). Conclusion: A diverse group of NTM were isolated across our healthcare system over the study period, most commonly M. avium complex, M. gordonae, and M. lentiflavum, each with hospital-specific temporal frequencies that suggest the potential for undetected outbreaks, while frequencies of less commonly isolated species were rarely suggestive of potential undetected outbreaks. Further epidemiologic investigation of in-hospital transmission routes, with whole genome sequencing to determine genetic relatedness, is necessary to identify undetected outbreaks.

“All or none” approaches to the use of contact precautions for methicillin-resistant Staphylococcus aureus (MRSA) both fail to recognize that transmission risk varies. This qualitative study assessed healthcare personnel perspectives regarding the feasibility of a risk-tailored approach to use contact precautions for MRSA more strategically in the acute care setting.

We estimated the extent of respiratory virus transmission over three pre-COVID-19 seasons. Of 16,273 assays, 22.9% (3,726) detected ≥1 respiratory virus. The frequency of putatively hospital-acquired infection ranged from 6.9% (influenza A/B) to 24.7% (adenovirus). The 176 clusters were most commonly associated with rhinovirus/enterovirus (70) and influenza A/B (62).

A hospital-onset bacteremia and fungemia (HOB) metric will expand hospital surveillance of bloodstream infections beyond current state and provide an opportunity to re-evaluate infection prevention strategies. Here we consider the added value and potential pitfalls of HOB surveillance and present a framework for the standardized assessment of HOB events.

Background: Current guidelines recommend contact precautions to prevent transmission of methicillin-resistant Staphylococcus aureus (MRSA) in acute-care hospitals. Prior literature demonstrates that discontinuation of contact precautions for MRSA has not been associated with an increase in carriage rates including surveillance-defined healthcare-associated infection (HAI) while horizontal infection prevention strategies are implemented. Objective: To analyze the impact of discontinuation of contact precautions on the rate of MRSA infections, including surveillance-defined HAI and transmission events identified through whole-genome sequencing (WGS) surveillance. Methods: In this single tertiary-care center, retrospective, observational, quality improvement analysis, we measured 2 MRSA HAI outcomes before and after discontinuation of contact precautions (ie, gown and gloves no longer required for care of patients with prior or current MRSA infections or colonization, effective December 2, 2020). First, we conducted a time-series analysis using linear regression modelling of NHSN reported MRSA HAI rates (January 2019–November 2022). We also calculated the frequency of WGS-confirmed MRSA transmission events before in the discontinuation of contact precautions (January 2019–August 2019) and after the discontinuation of contact precautions (January 2022–November 2022) periods. Surveillance HAI events were determined using NHSN definitions; MRSA transmission events were defined as an isolate identified ≥3 days after hospitalization or within 30 days of a healthcare exposure, genetically related by ≤15 single-nucleotide polymorphisms compared to ≥1 previously sequenced MRSA isolate. Results: We identified 171 MRSA HAIs in the 23 months before discontinuation of contact precautions, corresponding to 4.24 HAI per 10,000 patient days, and 129 HAIs in the 24 months after discontinuation of contact precautions, corresponding to 3.01 HAI per 10,000 patient days (Fig.). We detected a nonsignificant change in the trend in HAI rate before and after discontinuation of contact precautions (P = .22) as well as a significant immediate decrease in the MRSA HAI rate (P < 0 .001) at the time of discontinuation of contact precautions. In the WGS analysis 8 months before discontinuation of contact precautions, 11 MRSA transmission events were confirmed, comprising 4 clusters (0.75 per 10,000 patient days). In the WGS for the 11-month analysis period after discontinuation of contact precautions, there were 23 confirmed MRSA transmission events comprising 10 clusters (1.22 per 10,000 patient days; incidence rate ratio, 1.61; 95% CI, 0.75–3.66; P = .19). Conclusions: After discontinuation of contact precautions, there was no significant increase in MRSA HAI or transmission events. Further evaluation of the individual WGS transmission clusters will be helpful to determine whether discontinuation of contact precautions led to MRSA transmission in this facility in the period after discontinuation of contact precautions.

Disclosure: None

Background: Detecting healthcare-associated transmission and outbreaks often relies on reactive whole-genome sequencing (WGS), which occurs after the suspected transmission has occurred. Additionally, reactive WGS frequently misidentifies transmission and misses transmission when it has occurred. We initiated weekly real-time WGS to detect bacterial transmission and direct infection prevention interventions. We describe our experience after 1 year of real-time WGS surveillance at the University of Pittsburgh Medical Center–Presbyterian Hospital, a large, tertiary-care facility. Methods: Weekly WGS surveillance was performed from November 1, 2021, to October 31, 2022. Cultured isolates of select bacterial pathogens from patients who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30 days were collected and sequenced. Isolates that were ≤15 single-nucleotide polymorphisms (SNPs) were considered genetically related clusters except for Clostridioides difficile (≤2 SNPs). Genetically related clusters were investigated for epidemiological links and interventions to interrupt transmission were implemented at the discretion of the infection prevention team. We analyzed subsequent infections that occurred within an outbreak after an intervention was in place. Results: In total, 1,909 isolates were sequenced. Of 1,633 unique patient isolates clustered by sequence type, 74 clusters were identified comprising 210 (12.9%) patient isolates (Table 1). The median time from culture date to sequencing was 14 days (IQR, 5.25). The median cluster size was 2 (IQR, 1) (Table 2). Overall, 118 patient isolates (56.2%) had an epidemiological link to a prior isolate, indicating potential transmission. Of 74 clusters, 66 (89.2%) received infection prevention interventions after notification based upon epidemiological data. The infection prevention team performed 69 total interventions, which included unit education (n = 28), hand hygiene observations (n = 16), enhanced cleaning (n = 16), environmental cultures or removal of endoscope (n = 7), and enhanced microbiology surveillance (n = 2). The 59 subsequent infections after infection prevention notification included 17 (28.8%) with no clear epidemiological link, and 41 (69.5%) with an epidemiological link either to a new transmission route (n = 37) or the same route prior to infection prevention intervention (n = 4). Only 1 (1.7%) subsequent infection within a cluster occurred after an infection prevention intervention from the same potential route, which was a suspected unit-based transmission of vancomycin-resistant Enterococcus faecium. Conclusions: Real-time WGS was effective at detecting genetically related clusters, finding potential sources, and halting further transmission after interventions by the infection prevention team. Quick turnaround times from patient culture to sequencing and analysis were vital for successful WGS surveillance. Real-time WGS surveillance has the potential to substantially shift the infection prevention paradigm for outbreak detection.

Disclosure: None

Background: Identifying and interrupting transmission of severe acute respiratory syndrome coronavirus 2 and resulting disease (COVID-19) in acute-care settings can be challenging due to incubation period, asymptomatic infection, and prevalent community disease. To elucidate routes of infection and interrupt COVID-19 outbreaks with uncertain epidemiological chains of transmission, UPMC utilized reactive whole-genome sequencing (WGS) of viral specimens. Methods: UPMC infection prevention teams identified healthcare-associated COVID-19 clusters with uncertain transmission pathways among patients and/or healthcare personnel (HCP) in acute-care hospitals. Nasopharyngeal samples preserved in viral transport media were obtained for genetic analyses. Nucleic acids were extracted and WGS libraries were prepared by targeted enrichment or multiplex PCR methodologies. Resulting sequencing reads were aligned to the Wuhan-1 reference genome, followed by identification of single-nucleotide polymorphisms (SNPs) among the genomes and construction of a phylogenetic tree. Specimens were considered genetically similar if there were ≤2 SNP differences between viral genomes within a cluster. Results: Between May 2020 until August 2022, infection prevention teams requested WGS for 17 healthcare-associated clusters of COVID-19 involving 182 individuals across 8 UPMC facilities (median outbreak size, 9 individuals; range, 2–26). Of the 182 individuals, 36 lacked clinical specimens and 30 did not pass WGS quality-control criteria of ≥95% of the reference genome with a minimum of 10× coverage. Of the 116 sequenced genomes, 94 (81%) had virus genetically similar to ≥1 other specimen, including 87 (83.6%) of 104 patient viruses and 7 (58.3%) of 12 HCP viruses, comprising 22 clusters (Fig. 1). The remaining 22 (20.6%) specimens were genetically unrelated. In total, 16 (94.1%) of the 17 epidemiologically identified clusters had 2 or more individuals with a genetically similar virus. Also, 7 (41.1%) of these clusters had genetically similar viral genomes for every individual within each cluster. Also, 9 (52.9%) clusters contained both genetically related and unrelated specimens: 5 of these had more complex genomic profiles (including 4 clusters containing 2 distinct subclusters of ≥2 genetically related viruses) and 1 cluster contained 3 subclusters of ≥2 genetically related viruses. In the outbreak with 3 clusters, 3 SNPs separated specimens from 2 temporally proximal clusters, suggesting possible propagation between clusters (cluster B-3 in Fig. 1). Conclusions: WGS can complement traditional epidemiological investigations of healthcare-associated COVID-19 outbreaks, revealing complex transmission dynamics. Future investigations will characterize the impact of WGS on determining specific transmission pathways in acute-care facilities.

Disclosures: None