The California Department of Public Health (CDPH) reviewed 109 cases of healthcare personnel (HCP) with laboratory-confirmed mpox to understand transmission risk in healthcare settings. Overall, 90% of HCP with mpox had nonoccupational exposure risk factors. One occupationally acquired case was associated with sharps injury while unroofing a patient’s lesion for diagnostic testing.

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) are bacteria that cause healthcare-associated infections and outbreaks. Most produce carbapenemases like New Delhi metallo-β-lactamase (NDM), which are more commonly found in carbapenem-resistant Enterobacterales but rarely in CRAB. In 2018, selected laboratories began participating in a public health sentinel surveillance program by routinely submitting CRAB and other antimicrobial-resistant isolates to the AR Laboratory Network for specialized testing. In May 2020, the Antimicrobial Resistance Laboratory Network detected the first NDM-CRAB case in California, triggering an investigation. Initial whole-genome sequencing of subsequent isolates indicated high relatedness. Methods: We defined confirmed cases as patients with NDM detected in CRAB isolates and probable cases as NDM detected in a screening swab from a patient epidemiologically linked to a known case(s) with specimens collected during May 2020–September 2022. We defined outbreak facilities as having (1) 1 or more newly identified cases during a point-prevalence survey in response to a known case or (2) at least 2 cases identified within 4 weeks of each other that were epidemiologically linked. We analyzed demographic and specimen characteristics, as well as healthcare exposure history using R Studio version 1.3.959 software. Results: Of 230 total patients, 176 (77%) were confirmed and 54 (23%) were probable cases; 150 (65%) were identified through colonization screening. Among 176 NDM-CRAB isolates, the most common specimen sources were respiratory (n = 29), wound (n = 28), and urine (n = 24), and 87 (49%) of 176 isolates were nonsusceptible to all antimicrobials tested. Among patients, median age was 65 years (range, 24–97), 127 (55%) were male, 37 (15%) were Hispanic or Latino, and 100 (43%) were White. We identified 37 outbreak facilities across 13 counties, including 25 acute-care hospitals (ACHs), 6 skilled nursing facilities (SNFs), 5 ventilator-equipped SNFs (vSNFs), and 1 long-term ACH. We identified 125 cases (54%) in SNFs and vSNFs and 93 cases (40%) in ACHs; among ACH patients, 43 (46%) had been SNF or vSNF residents within the prior year. No patients reported international exposure. Conclusions: The first known case of NDM-CRAB in California was detected by sentinel surveillance. In this extensive regional outbreak, most cases were identified by screening at public health and clinical laboratories. Transmission occurred across healthcare settings connected by patient sharing, underscoring the importance of communication, active surveillance, and implementation of infection prevention and control practices to mitigate spread within and between facilities. Expanding these efforts, with support and resources from public health departments, is key to detecting, characterizing, and containing future outbreaks of antimicrobial-resistant pathogens.

Disclosure: None

Objectives: Few reports have been published about the transmission of mpox in healthcare settings. During the 2022 multinational outbreak, the California Department of Public Health (CDPH) conducted a systematic review of healthcare personnel (HCP) with mpox, including their community and occupational exposures, to understand the transmission risk in healthcare settings. We also sought to inform return-to-work protocols by describing the frequency of HCP working while symptomatic for mpox and identifying occurrences of secondary transmission from infected HCP to patients. Methods: We analyzed surveillance data for laboratory-confirmed mpox cases in California with symptom onset from May 17 to September 30, 2022, collected by investigators at local health departments and reported to the CDPH. The reported data were supplemented by review of free-text variables, interview notes, and other files uploaded to state and county disease surveillance data registries. We identified HCP as all persons working in healthcare settings with potential for direct or indirect exposure to patients or infectious materials, including clinical and nonclinical staff but excluding remote workers. Results: The CDPH received reports of 3,176 mpox cases during the study period: 109 were HCP. Of the 109 HCP identified from 19 counties, 78 (72%) were aged 30–49 years, 102 (94%) were male, and 43 (39%) were Hispanic or Latino. Also, 29 HCP (27%) had received at least 1 dose of the JYNNEOS vaccine. Occupations requiring frequent physical interactions with patients were reported for 66 individuals (61%). During interviews with local health department investigators, nearly all HCP (n = 98, 90%) reported potential or confirmed sources of community exposure; 1 had confirmed occupational exposure with symptom onset 9 days after a sharps injury acquired during collection of an mpox specimen for testing. Of the 60 HCP who provided information about the days they worked, 35 (58%) worked while symptomatic, for a mean of 3.14 days (median, 2; IQR, 3). Also, 2 HCP worked for 12 days after symptom onset. No secondary cases of mpox were associated with HCP reported to the CDPH. Conclusions: This analysis suggests that HCP are more likely to be exposed to mpox in community settings than healthcare settings. The findings support recommendations against sharps use for mpox specimen collection. Although transmission between symptomatic HCP and patients was not reported, HCP can decrease opportunities for mpox transmission by closely monitoring themselves for symptoms after potential exposures and staying home from work if symptoms develop.

Disclosures: None

Background: Burkholderia multivorans are gram-negative bacteria typically found in water and soil. B. multivorans outbreaks among patients without cystic fibrosis have been associated with exposure to contaminated medical devices or nonsterile aqueous products. Acquisition can also occur from exposure to environmental reservoirs like sinks or other hospital water sources. We describe an outbreak of B. multivorans among hospitalized patients without cystic fibrosis at 2 hospitals within the same healthcare system in California (hospitals A and B) between August 2021 and July 2022. Methods: We defined confirmed case patients as patients without cystic fibrosis hospitalized at hospital A or hospital B between January 2020 to July 2022 with B. multivorans isolated from any body site matching the outbreak strain. We reviewed medical records to describe case patients and to identify common exposures. We evaluated infection control practices and interviewed staff to detect exposures to nonsterile water. Select samples from water, ice, drains, and sink splash zone surfaces were collected and cultured for B. multivorans in March 2022 and July 2022 from both hospitals. Common aqueous products used among case patients were tested for B. multivorans. Genetic relatedness between clinical and environmental samples was determined using random amplified polymorphic DNA (RAPD) and repetitive extragenic palindromic polymerase chain reaction (Rep-PCR). Results: We identified 23 confirmed case patients; 20 (87%) of these were identified at an intensive care unit (ICU) in hospital A. B. multivorans was isolated from respiratory sources in 18 cases (78%). We observed medication preparation items, gloves, and patient care items stored within sink splash zones in ICU medication preparation rooms and patient rooms. Nonsterile water and ice were used for bed baths, swallow evaluations, and ice packs. B. multivorans was cultured from ice and water dispensed from an 11-year-old ice machine in the ICU at hospital A in March 2022 but no other water sources. Additional testing in July 2022 yielded B. multivorans from ice and a drain pan from a new ice machine in the same ICU location at hospital A. All products were negative. Clinical and environmental isolates were the same strain by RAPD and Rep-PCR. Conclusions: The use of nonsterile water and ice from a contaminated ice machine contributed to this outbreak. Water-related fixtures can serve as reservoirs for Burkholderia, posing infection risk to hospitalized and immunocompromised patients. During outbreaks of water-related organisms, such as B. multivorans , nonsterile water and ice use should be investigated as potential sources of transmission and other options should be considered, especially for critically ill patients.

Disclosures: None

We examined markers of completeness in healthcare-associated infection (HAI) data reported by California hospitals to the National Healthcare Safety Network for each half of 2020 compared with 2019. There were indications of decreased data completeness for both halves of 2020. California 2020 HAI data should be interpreted with caution.

We describe a large outbreak of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) involving an acute-care hospital emergency department during December 2020 and January 2021, in which 27 healthcare personnel worked while infectious, resulting in multiple opportunities for SARS-CoV-2 transmission to patients and other healthcare personnel. We provide recommendations for improving infection prevention and control.

Background: In 2021, the California Department of Public Health Healthcare-Associated Infections Program developed new infection prevention and control (IPC) training for skilled nursing facility (SNF) certified nursing assistants (CNAs), as part of the CDC Project Firstline. CNAs comprise approximately one-third of SNF healthcare personnel (HCP) nationwide; ~50,000 CNAs are employed in California SNFs. Despite making up a large proportion of direct care HCP, CNAs can frequently lack understanding of fundamental IPC practices, including hand hygiene and appropriate personal protective equipment use. We conducted a learning needs assessment for SNF can and leadership to understand and design our program to mecanCNA IPC training needs and preferences. Methods: We distributed the learning needs assessment via SurveyMonkey in English and Spanish with questions regarding current IPC practices and challenges, as well as preferred training delivery methods and posttraining support. We leveraged partnershipscanth CNA-affiliated organizations to engage CNAs throughout California. Results: Of 193 respondents, 80 (41%) were CNAs and 113 (59%) were leadership staff, representing 97 SNFs in 41 local health jurisdictions. Among CNAs, 34 (43%) believed that they had to do workarounds in their IPC practice and 18 (23%) stated that they would benefit from one-on-one question-and-answer sessions with an infection prevention expert. Also, 50 (63%) selected visual learning, 34 selected (43%) in-person learning, and 30 (38%) selected live or online trainings as their preferred learning style and training method. Most CNAs stated that they were most comfortable listening and speaking (73%) and reading (76%) in English only, followed by listening and speaking (16%) and reading (13%) in English and Spanish. For posttraining support, CNAs preferred access to online training materials (75%), digital materials (68%), virtual office hours with IPC educators (53%), and regular webinars (49%). Conclusions: The results of our learning needs assessment confirm the need for accessible IPC training and materials and continued engagement with posttraining support for CNAs. We will continue to provide online training and resources, access to IPC experts including an ‘AskBox’ for CNAs to e-mail IPC questions or request one-on-one support, and monthly office hours. Even though most CNAs are comfortable with training in English only, we will translate curricula into Spanish to support our bilingual Spanish-canaking CNA population. We are developing a tool kit to support SNFs and local health jurisdictions interested in providing their own training using our materials, and we will offer icanerson CNA training. We will use our experience from this process in future learning needs assessments to inform other frontline HCP training, including for SNF environmental services staff.

Funding: None

Disclosures: None

Background: Accurate and complete hospital healthcare-associated infection (HAI) data are essential to inform facility-level HAI prevention efforts and to ensure the validity and reliability of annual public reports. We implemented a validation attestation survey to assess and improve the HAI data reported by California hospitals via NHSN. Methods: The California Department of Public Health (CDPH) HAI Program invited all 401 general acute-care hospitals in California to participate in an annual HAI validation attestation survey in 2021. The survey was designed to be completed by the person with primary responsibility for HAI surveillance and reporting consistent with NHSN protocols and California laws. Survey questions addressed HAI reporting knowledge and practices and surgical procedures performed, and they included 3 hypothetical scenarios evaluating hospital application of HAI surveillance, decision making, and reporting methods. Results: We received responses from 345 hospitals (86%). For the 3 hypothetical scenarios, 171 hospitals (49.6%) correctly answered all 3 questions, 110 hospitals (31.9%) answered 2 questions correctly, 52 (15.1%) hospitals answered 1 question correctly, and 12 hospitals (3.5%) answered zero questions correctly. We did not detect a statistically significant association between facility type (ie, acute-care hospital, critical access hospital, long-term acute-care hospital, or rehabilitation hospital or unit) and the probability of getting all questions correct (Fisher exact P = .42). Of the 303 hospitals (88.0%) that perform at least 1 of the 28 surgical procedures reportable in California, 269 (88.8%) apply CDPH-recommended postoperative ICD-10 diagnosis flag codes to identify records that might indicate a possible surgical site infection (SSI). Moreover, ~289 (84.0%) hospitals confirmed that someone at their facility reviews CDPH quality assurance–quality control reports to verify the accuracy and completeness of their hospital’s reported HAI data. In 321 hospitals (93.0%) decisions about which infections are reported to NHSN are made solely by the infection preventionists or hospital epidemiologists, who are thoroughly familiar and follow NHSN protocol, definitions, and criteria. Conclusions: Most hospitals reported following best practices for evaluating records for SSIs; however, only half responded correctly to all 3 hypothetical scenarios. Our results highlight the need for ongoing education on HAI surveillance, decision making and reporting methods, and external HAI data validation in hospitals. This survey could serve as a model for other states that work with hospitals to improve HAI surveillance data and to ensure the integrity of public reports. Future research will link the results of this survey to NHSN validation audits.

Funding: None

Disclosures: None

Background: Antimicrobials are among the most commonly prescribed medications in US hospitals; an estimated 50% of hospitalized patients receive an antimicrobial. Research has shown that antimicrobial prescriptions to vary by patient- and hospital-level factors; however, disparities by patient neighborhood characteristics have not been examined. We evaluated associations between hospital and neighborhood indicators of socioeconomic status (SES) and antimicrobial use (AU) for gram-positive bacterial infections (GPBs), and broad-spectrum use for community-acquired infections (BSCAs) and hospital-onset infections (BSHOs). Methods: This analysis was conducted among 86 acute-care hospitals in California that submitted AU data via the NHSN in 2019. Hospital-level AU was measured as standardized antimicrobial administration ratios (SAARs) calculated by dividing observed antimicrobial use by risk-adjusted predicted antimicrobial use for GPB, BSCA, and BSHO antimicrobial groupings and categorized as binary (>1 or <1); SAARs >1 indicate potential inappropriate prescribing. California Office of Statewide Health Planning and Development 2018 data were used to obtain hospital characteristics and patient age, race or ethnicity, insurance, and comorbidities (defined by Charlson comorbidity index) for hospitalizations where AU may have been indicated, based on International Classification of Diseases Tenth Revision (ICD-10) diagnosis codes. The California Healthy Places Index (HPI) was used to obtain composite neighborhood SES indicators for each patient at the ZIP code level, measured as tertiles. Covariates were aggregated to the hospital level. Poisson regressions were used to evaluate the association between hospital and neighborhood SES indicators and SAAR scores, controlling for potential hospital-level confounders. Results: Among 86 hospitals included in the analysis, the mean patient age for hospitalizations where AU may have been indicated was 66 years, the proportion of white patients was 55%, and the mean proportion of Medi-Cal users was 19%. After adjusting for confounders including age, race or ethnicity, insurance status, comorbidities, and number of hospital beds; higher median values of patient SES had a protective effect against hospitals having GP SAAR scores > 1 (relative risk [RR], 0.68; 95% CI, 0.50–0.93) but was not significantly associated with hospitals having BSCA SAAR scores >1 (RR, 0.79; 95% CI, 0.62–1.02) or BSHO SAAR scores >1 (RR, 0.80; 95% CI, 0.61–1.04). Conclusions: Considering SES in addition to summary antimicrobial use scores such as SAARs may help identify populations potentially at risk for inappropriate AU; however, patient-level information is still necessary to evaluate appropriateness of antimicrobial prescribing.

Funding: No

Disclosures: None

Background: Diversion of resources from infection prevention activities, personal protective equipment supply shortages, conservation (extended use and reuse) or overuse with multiple gown and glove layers, and antimicrobial prescribing changes during the COVID-19 pandemic might increase healthcare-associated infection (HAI) incidence and antimicrobial resistance. We compared the incidences of Clostridioides difficile infection (CDI), methicillin-resistant Staphyloccocus aureus bloodstream infection (MRSA BSI), and vancomycin-resistant enterococci bloodstream infection (VRE BSI) reported by California hospitals during the COVID-19 pandemic with incidence data collected prior to the pandemic. Methods: Using data reported by hospitals to the California Department of Health via the NHSN, we compared incidences in the second and third quarters of 2020 (pandemic) to the second and third quarters of 2019 (before the pandemic). For CDI and MRSA BSI, we compared the standardized infection ratios (SIRs, based on the 2015 national baseline), and we calculated the P values. No adjustment model is available for VRE BSI; thus, we measured incidence via crude incidence rates (infections per 100,000 patient days). We calculated incidence rate ratio (IRR) with 95% CI for VRE BSI. To examine the possible effect of missing data during the pandemic, we performed a sensitivity analysis by excluding all facilities that had incomplete data reporting at any time during either analysis period. Results: Incidence measures and numbers of facilities contributing data in prepandemic and pandemic periods are shown in Table 1. There were no statistically significant changes in SIRs at P = .05 for either MRSA BSI or CDI between the prepandemic and pandemic periods (MRSA BSI P = .17; CDI P = .08). Crude VRE BSI incidence increased during the pandemic compared to the prepandemic period (IRR, 1.40; 95% CI, 1.16–1.70). Excluding facilities with incomplete data had minimal effect. Conclusions: We found insufficient evidence that MRSA BSI or CDI incidence changed in California hospitals during the pandemic relative to the prepandemic period; however, there was a significant increase in the crude incidence of VRE BSI. Next, we will include interrupted time series analyses to assess departure from long-term trends, including a risk-adjusted model for VRE BSI. Additionally, we will evaluate for changes in central-line–associated bloodstream infection incidence and antimicrobial resistance among HAI pathogens.

Funding: No

Disclosures: None

Table 1.

Background: The novel coronavirus (COVID-19) pandemic has caused significant morbidity and mortality in California: 2,218,000 cases and 24,598 deaths had occurred by December 31, 2020. Deaths at skilled nursing facilities (SNFs) and assisted living facilities (ALFs) comprise 26.2% of deaths in California; the fatality rate (299 per 10,000 SNF and ALF residents) in such facilities is nearly 50 times the statewide COVID-19 mortality rate (6.4 per 10,000 California residents). For healthcare facility (SNF, ALF, acute-care hospitals) and correctional facility outbreak management, the California Department of Public Health (CDPH) Healthcare-Associated Infections (HAI) Program deployed trained infection preventionists (IPs) to perform on-site infection prevention and control (IPC) assessments and to provide recommendations to staff and local health departments (LHDs). We describe the number and distribution of visits across the state and common IPC challenges identified. Methods: From February 1, 2020, to December 31, 2020, CDPH IP visits were requested directly by facilities, coordinated through LHDs and other state agencies, or prompted by a facility’s increasing case count on twice weekly review of the daily California healthcare facility data survey (Survey 123). Deployed IPs evaluated facility COVID-19 IPC protocols, assessed facility staff adherence using a standardized assessment tool, and provided verbal feedback followed by written summary reports and recommendations. We categorized visits geographically into 5 California Health Officer Association regions and by month, and we reviewed visit reports for common findings. Results: In total, 623 visits were performed for 489 outbreaks at 465 distinct facilities across 46 LHDs; 71 facilities received ≥2 visits. Southern California facilities received 292 visits (46.9%), San Joaquin region facilities received 138 visits (22.2%), Bay Area facilities received 131 visits (21%), Greater Sacramento facilities received 54 visits (8.7%), and Rural North facilities received 8 visits (1.3%) (Figure 1). The highest number of visits per month occurred in December (n = 143, 22.9%), followed by July (n = 87, 13.9%), and April (n = 83, 13.3%). Common IPC challenges included inappropriate resident cohorting practices, improper use of personal protective equipment, and lapses in physical distancing, and source control in breakrooms. Conclusions: On-site visits by CDPH IPs during the COVID-19 pandemic in California, though resource-intensive, provided substantial technical support for healthcare facilities during outbreaks and identified key areas for IPC improvement. Ongoing CDPH HAI guidance and training materials for facility-based IP staff are now being informed by these IPC challenges.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: Antimicrobial stewardship has been demonstrated to improve patient outcomes and reduce unwanted consequences, such as antimicrobial resistance and Clostridioides difficile infection. The California Department of Public Health (CDPH) Healthcare-Associated Infection (HAI) Program developed an honor roll to recognize facilities with the goal of promoting antimicrobial stewardship programs and encouraging collaboration and research. Methods: The first open enrollment period in California was from August 1 to September 1, 2020, and was only open to acute-care hospitals (ACHs). Enrollment occurs every 6 months. Applicants completed an application and provided supporting documentation for bronze, silver, or gold designations. The criteria for the bronze designation were at least 1 item from each of CDC’s 7 core elements for ACHs. The criteria for silver were bronze criteria plus 9 HAI program prioritized items (based on published literature) from the CDC Core Elements and demonstration of outcomes from an intervention. The criteria for gold designation were silver criteria plus community engagement (ie, local work or collaboration with healthcare partners). Applications were evaluated in 3 phases: (1) CDPH reviewed core elements and documentation, (2) CDPH and external blinded antimicrobial stewardship experts reviewed outcomes as scientific abstracts, and (3) CDPH reviewed each program for overall effectiveness in antimicrobial stewardship and final designation determination. Designations expire after 2 years. Results: In total, 119 applications were submitted (30% of all ACHs in California), of which 100 were complete and thus were included for review. Moverover, 33 facilities were from northern California and 67 were from southern California. Also, 85 facilities were part of a health system or network, 14 were freestanding, and 1 was a district facility. Facility types included 68 community hospitals, 17 long-term acute-care (LTAC) facilities, 17 academic or teaching hospitals, 4 critical-access hospitals, and 4 pediatric hospitals. There was an even distribution of hospital bed size: 35 facilities had <250 beds. The final designations included 19 gold, 35 silver and 43 bronze designations. There was 44% incongruency in applicants not receiving the designation for which they applied. Community hospitals were 63%–74% of all designations, and no LTACs received a gold designation. Moreover, 63% of hospitals with gold designations had >250 beds, and 47% of hospitals with bronze designations had <1 25 beds. Conclusions: The number of applicants was higher than expected because the open enrollment period occurred during the COVID-19 pandemic. This finding demonstrates the high importance placed on antimicrobial stewardship among ACHs. It also provides insight into how facilities are performing and collaborating and how CDPH can support facilities to improve their ASP.

Funding: No

Disclosures: None

Background: NDM/OXA-23 carbapenemase-producing Acinetobacter baumannii isolates have been reported worldwide, but rarely in the United States. A California acute-care hospital (ACH) A identified 3 patients with pan-nonsusceptible A. baumannii during May–June 2020, prompting a public health investigation to prevent further transmission among the regional healthcare network. Methods: A clinical isolate was defined as NDM/OXA-23–producing A. baumannii from a patient at ACH A or B, or an epidemiologically linked patient identified through colonization screening during May 2020–January 2021. ACHs A and B are sentinel sites for carbapenem-resistant A. baumannii surveillance through the Antibiotic Resistance Laboratory Network (AR Lab Network), where isolates are tested for carbapenemase genes. The California Department of Public Health with 3 local health departments conducted an epidemiological investigation, contact tracing, colonization screening, and whole-genome sequencing (WGS). Results: In total, 11 cases were identified during May 2020–January 2021, including 3 cases at ACH A during May–June 2020, and 8 additional cases during November 2020–January 2021: 5 at ACH A, 1 at ACH B, and 2 at skilled nursing facility (SNF) A. Isolates from ACHs A and B were identified through testing at the AR Lab Network. Of the 11 patients (including the index patient), 4 had exposure at SNF A, where 2 cases were identified through colonization screening. Screening conducted at ACH A and 5 other long-term care facilities (LTCFs) identified no additional cases. WGS results for the first 8 cases identified showed 2–13 single-nucleotide polymorphism differences. Antibiotic resistance genes for all isolates sequenced included NDM-1 and OXA-23. On-site assessments related to a COVID-19 outbreak conducted at ACH A identified infection control gaps. Conclusions: Hospital participation in public health laboratory surveillance allows early detection of novel multidrug-resistant organisms (MDROs), which enabled outbreak identification and public health response. A high COVID-19 burden and related changes in infection control practices have been associated with MDRO transmission elsewhere in California. This factor might have contributed to spread at ACH A and hampered earlier screening efforts at SNF A, likely leading to undetected transmission. Extensive movement of positive patients among a regional healthcare network including at least 6 ACHs and 7 LTCFs likely contributed to the prolonged duration of this outbreak. This investigation highlights the importance of enhanced novel MDRO surveillance strategies coupled with strong infection prevention and control practices as important factors in identifying outbreaks and preventing further transmission in regional networks.

Funding: No

Disclosures: None

Background: Antimicrobial resistance (AR), including Clostridioides difficile infection (CDI), can spread across the healthcare continuum when patients move between facilities. In 2015, the CDC recommended that healthcare facilities (HCFs) and local public health departments (LPH) coordinate their efforts to prevent the spread of AR and CDI. Accordingly, the California Department of Public Health (CDPH) Healthcare-Associated Infections (HAI) Program developed a model for implementing regionally based AR/CDI prevention collaboratives within HCF networks. Methods: The CDPH HAI Program began identifying regions in California with high AR/CDI incidence or risk for AR/CDI emergence using NHSN data. During 2015–2019, we organized AR/CDI prevention collaboratives in these regions. We recruited HCFs for participation by presenting at local professional organization meetings and engaging skilled nursing facility corporate leadership. HAI Program infection preventionists conducted onsite infection prevention assessments at each participating HCF. HAI Program and LPH staff convened quarterly in-person learning and discussion sessions focused on infection prevention and antimicrobial stewardship best practices. Participating HCFs committed to facility-tailored process improvement plans and conducted self-assessments to evaluate infection prevention practice changes at the conclusion of the collaborative. For CDI-focused collaboratives, we used data reported to CDPH via NHSN to assess changes in hospital- and community-onset CDI incidence among participating hospitals before and after the collaboratives. Results: Since 2015, 205 HCFs in 15 LPH jurisdictions have participated in 6 regional AR/CDI prevention collaboratives. Participating HCFs reported improved implementation of AR/CDI prevention strategies. For CDI-focused collaboratives, hospital-onset CDI incidence decreased by ~3% per month among participating hospitals. The collaboratives created forums for communication and relationship building, which previously did not exist among LPH and the HCF networks. We used our experience and feedback from partners to develop an HAI Program AR Prevention Collaborative Tool Kit to help LPHs and healthcare organizations develop and implement regional AR/CDI prevention collaboratives in other at-risk or high AR/CDI prevalence areas in California. The tool kit includes materials developed for each of our collaboratives, which may be adapted to meet local needs. Conclusions: Regionally coordinated AR/CDI prevention initiatives among LPHs and HCFs can contribute to increased AR awareness, improved AR prevention practices, and decreased AR/CDI incidence. The effectiveness of regional AR/CDI prevention collaboratives may be the result of concurrent efforts to improve AR prevention practices both within individual HCFs and across patient sharing networks.

Funding: None

Disclosures: None

Background: Pneumonia (PNA) is an important cause of morbidity and mortality among nursing home residents. The McGeer surveillance definitions were revised in 2012 to help NHs better monitor infections for quality improvement purposes. However, the concordance between surveillance definitions and clinically diagnosed PNA has not been well studied. Our objectives were to identify nursing home residents who met the revised McGeer PNA definition, to compare them with residents with clinician documented PNA, and determine whether modifications to the surveillance criteria could increase concordance. Methods: We analyzed respiratory tract infection (RTI) data from 161 nursing homes in 10 states that participated in a 1-day healthcare-associated infection point-prevalence survey in 2017. Trained surveillance officers from the CDC Emerging Infections Program collected data on residents with clinician documentation, signs, symptoms, and diagnostic testing potentially indicating an RTI. Clinician-documented pneumonia was defined as any resident with a diagnosis of pneumonia identified in the medical chart. We identified the proportion of residents with clinician documented PNA who met the revised McGeer PNA definition. We evaluated the criteria reported to develop 3 modified PNA surveillance definitions (Box), and we compared them to residents with clinician documented PNA.

Results: Among the 15,296 NH residents surveyed, 353 (2%) had >1 signs and/or symptoms potentially indicating RTI. Among the 353 residents, the average age was 76 years, 105 (30%) were admitted to postacute care or rehabilitation, and 108 (31%) had clinician-documented PNA. Among those with PNA, 28 (26%) met the Revised McGeer definition. Among 81 residents who did not meet the definition, 39 (48%) were missing the chest x-ray requirement, and among the remaining 42, only 3 (7%) met the constitutional criteria requirement (Fig. 1). Modification of the constitutional criteria requirement increased the detection of clinically documented PNA from 28 (26%) to 36 (33%) using modified definition 1; to 51 (47%) for modified definition 2; and to 55 (51%) for modified definition 3. Conclusions: Tracking PNA among nursing home residents using a standard definition is essential to improving detection and, therefore, informing prevention efforts. Modifying the PNA criteria increased the identification of clinically diagnosed PNA. Better concordance with clinically diagnosed PNA may improve provider acceptance and adoption of the surveillance definition, but additional research is needed to test its validity.

Funding: None

Disclosures: None

Background: With the emergence of antibiotic resistant threats and the need for appropriate antibiotic use, laboratory microbiology information is important to guide clinical decision making in nursing homes, where access to such data can be limited. Susceptibility data are necessary to inform antibiotic selection and to monitor changes in resistance patterns over time. To contribute to existing data that describe antibiotic resistance among nursing home residents, we summarized antibiotic susceptibility data from organisms commonly isolated from urine cultures collected as part of the CDC multistate, Emerging Infections Program (EIP) nursing home prevalence survey. Methods: In 2017, urine culture and antibiotic susceptibility data for selected organisms were retrospectively collected from nursing home residents’ medical records by trained EIP staff. Urine culture results reported as negative (no growth) or contaminated were excluded. Susceptibility results were recorded as susceptible, non-susceptible (resistant or intermediate), or not tested. The pooled mean percentage tested and percentage non-susceptible were calculated for selected antibiotic agents and classes using available data. Susceptibility data were analyzed for organisms with ≥20 isolates. The definition for multidrug-resistance (MDR) was based on the CDC and European Centre for Disease Prevention and Control’s interim standard definitions. Data were analyzed using SAS v 9.4 software. Results: Among 161 participating nursing homes and 15,276 residents, 300 residents (2.0%) had documentation of a urine culture at the time of the survey, and 229 (76.3%) were positive. Escherichia coli, Proteus mirabilis, Klebsiella spp, and Enterococcus spp represented 73.0% of all urine isolates (N = 278). There were 215 (77.3%) isolates with reported susceptibility data (Fig. 1). Of these, data were analyzed for 187 (87.0%) (Fig. 2). All isolates tested for carbapenems were susceptible. Fluoroquinolone non-susceptibility was most prevalent among E. coli (42.9%) and P. mirabilis (55.9%). Among Klebsiella spp, the highest percentages of non-susceptibility were observed for extended-spectrum cephalosporins and folate pathway inhibitors (25.0% each). Glycopeptide non-susceptibility was 10.0% for Enterococcus spp. The percentage of isolates classified as MDR ranged from 10.1% for E. coli to 14.7% for P. mirabilis. Conclusions: Substantial levels of non-susceptibility were observed for nursing home residents’ urine isolates, with 10% to 56% reported as non-susceptible to the antibiotics assessed. Non-susceptibility was highest for fluoroquinolones, an antibiotic class commonly used in nursing homes, and ≥ 10% of selected isolates were MDR. Our findings reinforce the importance of nursing homes using susceptibility data from laboratory service providers to guide antibiotic prescribing and to monitor levels of resistance.

Disclosures: None

Funding: None

Background: Automated testing instruments (ATIs) are commonly used by clinical microbiology laboratories to perform antimicrobial susceptibility testing (AST), whereas public health laboratories may use established reference methods such as broth microdilution (BMD). We investigated discrepancies in carbapenem minimum inhibitory concentrations (MICs) among Enterobacteriaceae tested by clinical laboratory ATIs and by reference BMD at the CDC. Methods: During 2016–2018, we conducted laboratory- and population-based surveillance for carbapenem-resistant Enterobacteriaceae (CRE) through the CDC Emerging Infections Program (EIP) sites (10 sites by 2018). We defined an incident case as the first isolation of Enterobacter spp (E. cloacae complex or E. aerogenes), Escherichia coli, Klebsiella pneumoniae, K. oxytoca, or K. variicola resistant to doripenem, ertapenem, imipenem, or meropenem from normally sterile sites or urine identified from a resident of the EIP catchment area in a 30-day period. Cases had isolates that were determined to be carbapenem-resistant by clinical laboratory ATI MICs (MicroScan, BD Phoenix, or VITEK 2) or by other methods, using current Clinical and Laboratory Standards Institute (CLSI) criteria. A convenience sample of these isolates was tested by reference BMD at the CDC according to CLSI guidelines. Results: Overall, 1,787 isolates from 112 clinical laboratories were tested by BMD at the CDC. Of these, clinical laboratory ATI MIC results were available for 1,638 (91.7%); 855 (52.2%) from 71 clinical laboratories did not confirm as CRE at the CDC. Nonconfirming isolates were tested on either a MicroScan (235 of 462; 50.9%), BD Phoenix (249 of 411; 60.6%), or VITEK 2 (371 of 765; 48.5%). Lack of confirmation was most common among E. coli (62.2% of E. coli isolates tested) and Enterobacter spp (61.4% of Enterobacter isolates tested) (Fig. 1A), and among isolates testing resistant to ertapenem by the clinical laboratory ATI (52.1%, Fig. 1B). Of the 1,388 isolates resistant to ertapenem in the clinical laboratory, 1,006 (72.5%) were resistant only to ertapenem. Of the 855 nonconfirming isolates, 638 (74.6%) were resistant only to ertapenem based on clinical laboratory ATI MICs. Conclusions: Nonconfirming isolates were widespread across laboratories and ATIs. Lack of confirmation was most common among E. coli and Enterobacter spp. Among nonconfirming isolates, most were resistant only to ertapenem. These findings may suggest that ATIs overcall resistance to ertapenem or that isolate transport and storage conditions affect ertapenem resistance. Further investigation into this lack of confirmation is needed, and CRE case identification in public health surveillance may need to account for this phenomenon.

Funding: None

Disclosures: None

Background: With an aging population, increasingly complex care, and frequent re-admissions, prevention of healthcare-associated infections (HAIs) in nursing homes (NHs) is a federal priority. However, few contemporary sources of HAI data exist to inform surveillance, prevention, and policy. Prevalence surveys (PSs) are an efficient approach to generating data to measure the burden and describe the types of HAI. In 2017, the Centers for Disease Control and Prevention (CDC) performed its first large-scale HAI PS through the Emerging Infections Program (EIP) to measure the prevalence and describe the epidemiology of HAI in NH residents. Methods: NHs from several states (CA, CO, CT, GA, MD, MN, NM, NY, OR, & TN) were randomly selected and asked to participate in a 1-day HAI PS between April and October 2017; participation was voluntary. EIP staff reviewed available medical records for NH residents present on the survey date to collect demographic and basic clinical information and infection signs and symptoms. HAIs with onset on or after NH day 3 were identified using revised McGeer infection definitions applied to data collected by EIP staff and were reported to the CDC through a web-based system. Data were reviewed by CDC staff for potential errors and to validate HAI classifications prior to analysis. HAI prevalence, number of residents with >1 HAI per number of surveyed residents ×100, and 95% CIs were calculated overall (pooled mean) and for selected resident characteristics. Data were analyzed using SAS v9.4 software. Results: Among 15,296 residents in 161 NHs, 358 residents with 375 HAIs were identified. The most common HAI sites were skin (32%), respiratory tract (29%), and urinary tract (20%). Cellulitis, soft-tissue or wound infection, symptomatic UTI, and cold or pharyngitis were the most common individual HAIs (Fig. 1). Overall HAI prevalence was 2.3 per 100 residents (95% CI, 2.1–2.6); at the NH level, the median HAI prevalence was 1.8 and ranged from 0 to 14.3 (interquartile range, 0–3.1). At the resident level (Fig. 2), HAI prevalence was significantly higher in persons admitted for postacute care with diabetes, with a pressure ulcer, receiving wound care, or with a device. Conclusions: In this large-scale survey, 1 in 43 NH residents had an HAI on a given day. Three HAI types comprised >80% of infections. In addition to identifying characteristics that place residents at higher risk for HAIs, these findings provide important data on HAI epidemiology in NHs that can be used to expand HAI surveillance and inform prevention policies and practices.

Funding: None

Disclosures: None