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The incidence of infections from extended-spectrum β-lactamase (ESBL)–producing Enterobacterales (ESBL-E) is increasing in the United States. We describe the epidemiology of ESBL-E at 5 Emerging Infections Program (EIP) sites.
During October–December 2017, we piloted active laboratory- and population-based (New York, New Mexico, Tennessee) or sentinel (Colorado, Georgia) ESBL-E surveillance. An incident case was the first isolation from normally sterile body sites or urine of Escherichia coli or Klebsiella pneumoniae/oxytoca resistant to ≥1 extended-spectrum cephalosporin and nonresistant to all carbapenems tested at a clinical laboratory from a surveillance area resident in a 30-day period. Demographic and clinical data were obtained from medical records. The Centers for Disease Control and Prevention (CDC) performed reference antimicrobial susceptibility testing and whole-genome sequencing on a convenience sample of case isolates.
We identified 884 incident cases. The estimated annual incidence in sites conducting population-based surveillance was 199.7 per 100,000 population. Overall, 800 isolates (96%) were from urine, and 790 (89%) were E. coli. Also, 393 cases (47%) were community-associated. Among 136 isolates (15%) tested at the CDC, 122 (90%) met the surveillance definition phenotype; 114 (93%) of 122 were shown to be ESBL producers by clavulanate testing. In total, 111 (97%) of confirmed ESBL producers harbored a blaCTX-M gene. Among ESBL-producing E. coli isolates, 52 (54%) were ST131; 44% of these cases were community associated.
The burden of ESBL-E was high across surveillance sites, with nearly half of cases acquired in the community. EIP has implemented ongoing ESBL-E surveillance to inform prevention efforts, particularly in the community and to watch for the emergence of new ESBL-E strains.
The National Healthcare Safety Network (NHSN) Antibiotic Resistance (AR) Option is a valuable tool that can be used by acute-care hospitals to track and report antibiotic resistance rate data. Selective and cascading reporting results in suppressed antibiotic susceptibility results and has the potential to adversely affect what data are submitted into the NHSN AR Option. We describe the effects of antibiotic suppression on NHSN AR Option data.
NHSN AR Option data were collected from 14 hospitals reporting into an existing NHSN user group from January 1, 2017, to December 31, 2018, and linked to commercial automated antimicrobial susceptibility testing instruments (cASTI) that were submitted as part of unrelated Tennessee Emerging Infections Program surveillance projects. A susceptibility result was defined as suppressed if the result was not found in the NHSN AR Option data but was reported in the cASTI data. Susceptibility results found in both data sets were described as released. Proportions of suppressed and released results were compared using the Pearson χ2 and Fisher exact tests.
In total, 852 matched isolates with 3,859 unique susceptibilities were available for analysis. At least 1 suppressed antibiotic susceptibility result was available for 726 (85.2%) of the isolates. Of the 3,859 susceptibility results, 1,936 (50.2%) suppressed antibiotic susceptibility results were not reported into the NHSN AR option when compared to the cASTI data.
The effect of antibiotic suppression described in this article has significant implications for the ability of the NHSN AR Option to accurately reflect antibiotic resistance rates.
To study the airflow, transmission, and clearance of aerosols in the clinical spaces of a hospital ward that had been used to care for patients with coronavirus disease 2019 (COVID-19) and to examine the impact of portable air cleaners on aerosol clearance.
A single ward of a tertiary-care public hospital in Melbourne, Australia.
Glycerin-based aerosol was used as a surrogate for respiratory aerosols. The transmission of aerosols from a single patient room into corridors and a nurses’ station in the ward was measured. The rate of clearance of aerosols was measured over time from the patient room, nurses’ station and ward corridors with and without air cleaners [ie, portable high-efficiency particulate air (HEPA) filters].
Aerosols rapidly travelled from the patient room into other parts of the ward. Air cleaners were effective in increasing the clearance of aerosols from the air in clinical spaces and reducing their spread to other areas. With 2 small domestic air cleaners in a single patient room of a hospital ward, 99% of aerosols could be cleared within 5.5 minutes.
Air cleaners may be useful in clinical spaces to help reduce the risk of acquisition of respiratory viruses that are transmitted via aerosols. They are easy to deploy and are likely to be cost-effective in a variety of healthcare settings.
We aimed to identify a threshold number of Clostridioides difficile infections (CDI) for acute-care hospitals (ACHs) to notify public health agencies of outbreaks and we aimed to determine whether thresholds can be used with existing surveillance strategies to further infection reduction goals.
Descriptive analysis of laboratory-identified CDI reported to the National Healthcare Safety Network by Colorado and Tennessee ACH inpatient units in 2018.
Threshold levels of ≥2, ≥3, and ≥4 CDI events per calendar month per unit (unit month) were assessed to identify units that would trigger facility reporting to public health. Values meeting thresholds were defined as alerts. Recurrent alerts were defined as alerts from units meeting the threshold ≥2 times within 12 months. The presence of alerts was compared to the number of excess infections to identify high-burden facilities.
At an alert threshold of ≥2 CDI events per unit month, 204 alerts occurred among 43 Colorado ACHs and 290 among 78 Tennessee ACHs. At a threshold of ≥3, there were 59 and 61 alerts, and at a threshold of ≥4, there were 17 and 10 alerts in Colorado and Tennessee, respectively. In both Colorado and Tennessee, at a threshold of ≥3 nearly 50% of alerts were recurrent, and facilities with at least one alert in 2018 accounted for ∼85% of the statewide excess infections.
An alert threshold of ≥3 CDI events per unit month is feasible for rapid identification of outbreaks in ACHs. This threshold can facilitate earlier assessments and interventions in high-burden facilities.
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.
Background: Carbapenemase-producing organisms (CPOs) are a growing antibiotic resistance threat. Colonization screening can be used to identify asymptomatically colonized individuals for implementation of transmission-based precautions. Identifying high-risk patients and settings to prioritize screening recommendations can preserve facility resources. To inform screening recommendations, we analyzed CPO admission screens and screening conducted on point-prevalence surveys (PPSs) performed through the Antibiotic Resistance Laboratory Network’s Southeast Regional Laboratory (SE AR Lab Network). Methods: During 2017–2019, the SE AR Lab Network collected data via a REDCap survey for a subset of CPO screens on a limited set of easily determined patient risk factors. Rectal swabs were collected and tested with the Cepheid Carba-R. Specimens collected within 2 days of admission were classified as admission screening and the remainder were classified as PPS. Index cases were excluded from analyses. Odd ratios (ORs) and 95% confidence intervals were calculated, and a value of 0.1 was used for cells with a value of zero. Results: In total, 520 screens were conducted, which included 366 admission screens at 2 facilities and 154 screens from 27 PPSs at 8 facilities. CPOs were detected in 14 (2.7%) screens, including in 10 (2.7%) admission screens and in 4 (2.6%) contacts during PPSs; carbapenemases detected were Klebsiella pneumoniae carbapenemase (KPC) (n = 12), New Delhi Metallo-β-lactamase (NDM) (n = 1) and Verona Integron-Encoded Metallo-β-lactamase (VIM) (n = 1). One long-term acute care hospital (LTACH) performed universal admission screening, which accounted for 96% of admission screens and all 10 CPOs detected by admission screening. Mechanical ventilation (OR, 5.0; 95% CI, 1.4–18.0) and the presence of a tracheostomy (OR, 5.4; 95% CI, 1.5–19.4) were associated with a positive admission screen. Moreover, 8 facilities conducted PPSs: 4 acute care hospitals, 2 long-term acute care hospitals, and 2 nursing homes. CPO prevalence in long-term acute care hospitals was 4.8% (2 of 42), 2.4% (1 of 41) in acute care hospitals, and 1.5% (1 of 69) in nursing homes. Requiring assistance with bathing (OR, 4.8; 95% CI, 1.6–8.0) and stool incontinence (OR, 16.6; 95% CI, 13.4–19.8) were associated with a positive screen on PPSs. All 7 roommates of known cases tested negative for CPO colonization. Conclusions: Findings suggest that patients with certain easily assessed characteristics, such as mechanical ventilation, tracheostomy, or stool incontinence or who require bathing assistance, may be associated with CPO positivity during screening. Further data collection and analysis of such risk factors may provide insight for the development of more targeted admission and contact screening strategies.
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.
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.
Background: Detection of unusual carbapenemase-producing organisms (CPOs) in a healthcare facility may signify broader regional spread. During investigation of a VIM-producing Pseudomonas aeruginosa (VIM-CRPA) outbreak in a long-term acute-care hospital in central Florida, enhanced surveillance identified VIM-CRPA from multiple facilities, denoting potential regional emergence. We evaluated infection control and performed screening for CPOs in skilled nursing facilities (SNFs) across the region to identify potential CPO reservoirs and improve practices. Methods: All SNFs in 2 central Florida counties were offered a facility-wide point-prevalence survey (PPS) for CPOs and a nonregulatory infection control consultation. PPSs were conducted using a PCR-based screening method; specimens with a carbapenemase gene detected were cultured to identify the organisms. Infection control assessments focused on direct observations of hand hygiene (HH), environmental cleaning, and the sink splash zone. Thoroughness of environmental cleaning was evaluated using fluorescent markers applied to 6 standardized high-touch surfaces in at least 2 rooms per facility. Results: Overall, 21 (48%) SNFs in the 2-county region participated; 18 conducted PPS. Bed size ranged from 40 to 391, 5 (24%) facilities were ventilator-capable SNFs (vSNFs), and 12 had short-stay inpatient rehabilitation units. Of 1,338 residents approached, 649 agreed to rectal screening, and 14 (2.2%) carried CPOs. CPO-colonized residents were from the ventilator-capable units of 3 vSNFs (KPC-CRE=7; KPC-CRPA=1) and from short-stay units of 2 additional facilities (VIM-CRPA, n = 5; KPC-CRE, n = 1). Among the 5 facilities where CPO colonization was identified, the prevalence ranged from 1.1% in a short-stay unit to 16.1% in a ventilator unit. All facilities had access to soap and water in resident bathrooms; 14 (67%) had alcohol-based hand rubs accessible. Overall, mean facility HH adherence was 52% (range, 37%–66%; mean observations per facility = 106) (Fig. 1). We observed the use of non–EPA-registered disinfectants and cross contamination from dirty to clean areas during environmental cleaning; the overall surface cleaning rate was 46% (n = 178 rooms); only 1 room had all 6 markers removed. Resident supplies were frequently stored in the sink splash zone. Conclusions: A regional assessment conducted in response to emergence of VIM-CRPA identified a relatively low CPO prevalence at participating SNFs; CPOs were primarily identified in vSNFs and among short-stay residents. Across facilities, we observed low adherence to core infection control practices that could facilitate spread of CPOs and other resistant organisms. In this region, targeting ventilator and short-stay units of SNFs for surveillance and infection control efforts may have the greatest prevention impact.
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.
Background:Clostridioides difficile remains a pervasive issue throughout healthcare facilities in the United States. Currently, no national guidelines exist for healthcare facilities to notify public health about suspected C. difficile transmission. Identification of a threshold for public health notification is needed to improve efforts to target prevention in facilities and to contain the spread of C. difficile.Methods: We analyzed C. difficile data reported by acute-care hospitals (ACHs) during October 2017–September 2018 via the CDC NHSN in Colorado and Tennessee. Threshold levels of ≥2, ≥3, and ≥4 C. difficile infections per calendar month per unit were assessed to identify ACH units that would trigger facility reporting to public health. Values meeting thresholds were defined as “alerts.” Facilities were further stratified by size and medical teaching status. Recurrent alerts were defined as meeting the threshold at least twice within 12 months. Presence and recurrence of facility alerts were compared to facility-specific standardized infection ratios (SIRs) and cumulative attributable differences (CADs). Results: Of 105 ACHs in Tennessee and 50 in Colorado, 46 in Tennessee (44%) and 28 in Colorado (56%) had alerts with a threshold of ≥2 cases per calendar month per unit; 20 in Tennessee (19%) and 19 in Colorado (38%) had ≥3 cases per calendar month per unit; and 7 in Tennessee (7%) and 10 in Colorado (20%) had ≥4 cases per calendar month per unit. Most alerts with each threshold were in facilities with ≥400 beds and in major teaching hospitals. Using a threshold of ≥2, 64% of Tennessee and 79% of Colorado alerts were associated with recurrent alerting units. Using an alert threshold of ≥3, 85% of Tennessee facilities (17 of 20) and 75% of Colorado facilities (15 of 20) with the highest CAD values had at least 1 alert. Using state-based CAD values, 79% of the CAD value for Tennessee (356 of 449) and 91% of the CAD value for Colorado (309 of 340) were attributable to facilities with at least 1 alert. Facilities above a threshold of ≥3 had a pooled SIR of 0.92 in Tennessee (range, 0.46–7.94) and 1.07 in Colorado (range, 0.74–1.74). Conclusions: Using alert threshold levels identified ACHs with higher levels of C. difficile. Recurrent alerts account for a substantial proportion of the total alerts in ACHs, even as thresholds increased. Alerts were strongly correlated with high CAD values. Because NHSN C. difficile data are not available to public health departments until several months after cases are identified, public health departments should consider working with ACHs to implement a threshold model for public health notification, enabling earlier intervention than those prompted by SIR and CAD calculations.
Background: Certain nursing home (NH) resident care tasks have a higher risk for multidrug-resistant organisms (MDRO) transfer to healthcare personnel (HCP), which can result in transmission to residents if HCPs fail to perform recommended infection prevention practices. However, data on HCP-resident interactions are limited and do not account for intrafacility practice variation. Understanding differences in interactions, by HCP role and unit, is important for informing MDRO prevention strategies in NHs. Methods: In 2019, we conducted serial intercept interviews; each HCP was interviewed 6–7 times for the duration of a unit’s dayshift at 20 NHs in 7 states. The next day, staff on a second unit within the facility were interviewed during the dayshift. HCP on 38 units were interviewed to identify healthcare personnel (HCP)–resident care patterns. All unit staff were eligible for interviews, including certified nursing assistants (CNAs), nurses, physical or occupational therapists, physicians, midlevel practitioners, and respiratory therapists. HCP were asked to list which residents they had cared for (within resident rooms or common areas) since the prior interview. Respondents selected from 14 care tasks. We classified units into 1 of 4 types: long-term, mixed, short stay or rehabilitation, or ventilator or skilled nursing. Interactions were classified based on the risk of HCP contamination after task performance. We compared proportions of interactions associated with each HCP role and performed clustered linear regression to determine the effect of unit type and HCP role on the number of unique task types performed per interaction. Results: Intercept-interviews described 7,050 interactions and 13,843 care tasks. Except in ventilator or skilled nursing units, CNAs have the greatest proportion of care interactions (interfacility range, 50%–60%) (Fig. 1). In ventilator and skilled nursing units, interactions are evenly shared between CNAs and nurses (43% and 47%, respectively). On average, CNAs in ventilator and skilled nursing units perform the most unique task types (2.5 task types per interaction, Fig. 2) compared to other unit types (P < .05). Compared to CNAs, most other HCP types had significantly fewer task types (0.6–1.4 task types per interaction, P < .001). Across all facilities, 45.6% of interactions included tasks that were higher-risk for HCP contamination (eg, transferring, wound and device care, Fig. 3). Conclusions: Focusing infection prevention education efforts on CNAs may be most efficient for preventing MDRO transmission within NH because CNAs have the most HCP–resident interactions and complete more tasks per visit. Studies of HCP-resident interactions are critical to improving understanding of transmission mechanisms as well as target MDRO prevention interventions.
Funding: Centers for Disease Control and Prevention (grant no. U01CK000555-01-00)
Disclosures: Scott Fridkin, consulting fee, vaccine industry (spouse)
Background: In 2017, a new antimicrobial stewardship standard was established by the Joint Commission that requires long-term care facilities (LTCFs) to have an antimicrobial stewardship program (ASP) based on current scientific literature. The Tennessee Department of Health (TDH) team sought to ascertain the current state of ASPs across Tennessee and to assist programs with implementation strategies. Utilizing a Centers for Medicaid and Medicare Services’ Civil Monetary Penalties grant, the TDH purchased copies of the National Quality Partners Playbook for Antibiotic Stewardship in Post-Acute and Long-Term Care to provide to LTCFs as incentive to complete a survey that would evaluate their current adoption of core elements. Methods: A self-administered questionnaire on ASP practices was developed and distributed to LCTFs. This survey expanded upon questions from the NHSN 2018 LTCF annual survey. These questions pertained to actionable items facilities are taking to achieve core elements. Achievement of the CDC’s 7 core elements of ASPs was determined based upon a combination of 1 or more responses to the survey questions. The percentage of LTCFs achieving each ASP core element at the regional and statewide level was determined. We also calculated the percentage of LTCFs that achieved all 7 elements versus 5 or more core elements. The analyses and visualizations were performed using SAS 9.4 and Tableau software. Results: Currently, 88 of 316 licensed LTCF facilities in Tennessee have participated in the survey. All regions were represented by EMS region. Based on the results of our survey, 100% of participating facilities have achieved at least 5 core elements, and 78% of participating facilities have achieved all 7 core elements. The core element with the lowest achievement was Accountability at 89%, and reporting and action had the highest achievement (100%). Conclusions: Early results suggest that LTCFs across Tennessee have active ASPs with strong core element achievement. However, we received responses from only 27% of licensed LTCFs. Minimal data are available regarding the current state of LTCF ASPs in Tennessee, and data will continue to be collected and analyzed. Participation may be limited to those already actively engaged in public health efforts, including antimicrobial stewardship. LTCFs that have participated in the initial evaluation will be surveyed at 6 months and 12 months after receipt of playbooks to evaluate their ASP progression and NQP Playbook utilization.
Background: Antibiotics are among the most commonly prescribed drugs in nursing homes; urinary tract infections (UTIs) are a frequent indication. Although there is no gold standard for the diagnosis of UTIs, various criteria have been developed to inform and standardize nursing home prescribing decisions, with the goal of reducing unnecessary antibiotic prescribing. Using different published criteria designed to guide decisions on initiating treatment of UTIs (ie, symptomatic, catheter-associated, and uncomplicated cystitis), our objective was to assess the appropriateness of antibiotic prescribing among NH residents. Methods: In 2017, the CDC Emerging Infections Program (EIP) performed a prevalence survey of healthcare-associated infections and antibiotic use in 161 nursing homes from 10 states: California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee. EIP staff reviewed resident medical records to collect demographic and clinical information, infection signs, symptoms, and diagnostic testing documented on the day an antibiotic was initiated and 6 days prior. We applied 4 criteria to determine whether initiation of treatment for UTI was supported: (1) the Loeb minimum clinical criteria (Loeb); (2) the Suspected UTI Situation, Background, Assessment, and Recommendation tool (UTI SBAR tool); (3) adaptation of Infectious Diseases Society of America UTI treatment guidelines for nursing home residents (Crnich & Drinka); and (4) diagnostic criteria for uncomplicated cystitis (cystitis consensus) (Fig. 1). We calculated the percentage of residents for whom initiating UTI treatment was appropriate by these criteria. Results: Of 248 residents for whom UTI treatment was initiated in the nursing home, the median age was 79 years [IQR, 19], 63% were female, and 35% were admitted for postacute care. There was substantial variability in the percentage of residents with antibiotic initiation classified as appropriate by each of the criteria, ranging from 8% for the cystitis consensus, to 27% for Loeb, to 33% for the UTI SBAR tool, to 51% for Crnich and Drinka (Fig. 2). Conclusions: Appropriate initiation of UTI treatment among nursing home residents remained low regardless of criteria used. At best only half of antibiotic treatment met published prescribing criteria. Although insufficient documentation of infection signs, symptoms and testing may have contributed to the low percentages observed, adequate documentation in the medical record to support prescribing should be standard practice, as outlined in the CDC Core Elements of Antibiotic Stewardship for nursing homes. Standardized UTI prescribing criteria should be incorporated into nursing home stewardship activities to improve the assessment and documentation of symptomatic UTI and to reduce inappropriate antibiotic use.
Outbreaks of infections in healthcare negatively impact patient outcomes and experience. Transparency is critical to engendering trust and optimizing health. Consistent guidance is not available regarding when to report a possible outbreak of healthcare-associated infections (HAIs) to public health and when to notify a limited population or to publicly disclose the occurrence of HAI. Recent analyses of state public health policies revealed that most states address reporting of outbreaks using terms such as clusters, unusual occurrences, or incidences over baseline. Specific wording about healthcare outbreaks or guidance for notifying patients or public is often absent. Thus, HAI outbreak notification and disclosure guidance and practices vary significantly around the country. A best-practice guidance document will provide clarity for when such reporting should occur. Methods: The Council for Outbreak Response: HAI and Antimicrobial-Resistant Pathogens (CORHA) has undertaken the task of developing this guidance by forming a multidiscipline policy work group with representation from its partner organizations. This work group has been tasked with creating a general framework that will guide notification and disclosure in the context of a possible HAI outbreak. The draft guidance document has been developed over several months of telephone and in-person conferences among work group members. Results: The standardized actions stemming from the guiding principles and recommended practices for conducting step 1 (immediate notification, initial and critical communications that occur when an outbreak is first suspected), were arranged in a table format with rows representing stakeholders and constituents to be notified and columns demonstrating the actions to be taken (Fig. 1). As an investigation progresses, notification should be revisited, especially if an investigation’s scope expands. The principles and practices for step 2 (expanded notification) have also been drafted in a table format. Next, the draft guidance addresses step 3 (public disclosure), outlining indications, practical guidance, and considerations in an outline and/or summary format. Real-world examples demonstrating application of the framework are being developed as supplementary resources to the framework. Current work group activities include engaging bioethicists, media reporters and patient advocates to review and comment on the guidance to ensure that it is clear, consistent and practical. Discussion: The draft guidance provides a framework for standardized actions for HAI outbreak notification and disclosure in a stepwise fashion, modeling public health practices and grounded in bioethical principles. The final product will provide valuable, practical advice for effectively sharing information with affected or potentially affected individuals and their caregivers in a timely manner.
Dawn Terashita reports that her spouse has received honoraria rom the speaker’s bureaus of Novo Nordisk and Abbott.
Background: Antibiotic stewardship is an area of great concern in long-term care facilities nationwide. The CDC promotes 7 core elements of antimicrobial stewardship. Based on information obtained from the Infection Control Assessment and Response (ICAR) Program, the 2 core elements most infrequently achieved by LTCFs are tracking and reporting. Currently, minimal data are available on antibiotic use (AU) in LTCFs in Tennessee. To address both issues, the Tennessee Department of Health (TDH) developed a monthly antibiotic use (AU) point-prevalence (PP) survey to provide LTCFs with a free tool to both track and report their AU and to gather data on how LTCFs are using antibiotics. Methods: We used REDCap to create a questionnaire to collect information on selected antibiotics administered in Tennessee LTCFs. This self-administered survey was promoted through the TDH monthly antimicrobial stewardship and infection control (ASIC) call as well as at various conferences and speaking engagements across the state. Antimicrobial stewardship leads for each facility were targeted. Antibiotics were grouped into 4 classes according to their indications: C. difficile infections, urinary tract infections, skin and soft-tissue infections (SSTIs) and respiratory infections. We determined AU percentage by dividing the number of days of therapy for a drug by a facility’s average census. Individualized reports are provided to each participating facility on a quarterly basis. Results: Currently, 16 facilities have participated in the survey. Overall, 40.7% of antibiotics prescribed were in the common for SSTI category and 39.3% were common for respiratory infections. The top 33 most commonly prescribed antibiotics were amoxicillin (156 days of therapy [DOT]), nitrofurantoin (92 DOT), and levofloxacin (88 DOT). The average percentage of residents on antimicrobials on the day of survey was 12.3%; within this group, 57% of antibiotics were initiated in the LTCF, whereas 43% were present upon admission. Conclusions: Early results from the TDH AU PP survey revealed that drugs commonly used for SSTIs and respiratory infection were the most common antibiotic prescriptions and a potential area of focus for TDH’s antimicrobial stewardship efforts. None of the 3 most frequently prescribed antibiotics, however, fall under the SSTI indication, despite SSTI being the most commonly prescribed indication based on the survey’s evaluation metrics. This finding could be related to the larger number of antibiotics that fall under the SSTI indication. Preliminary data are being used to guide the direction of TDH’s future ASIC calls to better suit disease states, which have room for improvement.
Background: Carbapenem-resistant Enterobacteriaceae (CRE) are an urgent public health threat associated with poor patient outcomes. CRE that produce carbapenemase (CP-CRE) are of particular concern because the mechanism-conferring genes in plasmids can be transferred to other bacteria. CRE are reportable in Tennessee (TN); isolate submission is required for CP production and resistance mechanism testing. We aimed to compare patient characteristics and outcomes between CP-CRE and non–CP-CRE patients to guide potential public health interventions. Methods: A retrospective cohort study to compare 30-day mortality, and clinical characteristics of CP-CRE to non–CP-CRE patients was conducted. Laboratory data were gathered from CRE isolates of Tennessee residents from July 1, 2015, to June 30, 2018. The most recent Council of State and Territorial Epidemiologists CRE and CP-CRE case definition was used to confirm and classify cases. Healthcare exposures within 1 year prior to onset, demographic characteristics, and clinical characteristics were obtained by linking surveillance data with the inpatient and outpatient Tennessee hospital discharge data. Cases were also matched with Tennessee vital statistics data to determine all-cause 30-day mortality from the event date. We evaluated risk ratios of 30-day mortality with a multivariable regression model. Results: Among 1,034 CRE cases that had at least 1 isolate submitted to public health, 445 (43.0%) were CP-CRE and 589 (57.0%) were non–CP-CRE. Among CP-CRE isolates, the blaKPC gene was found in 434 (98.9%). CP-CRE cases were more likely to have isolates from normally sterile sites, to have an organism with elevated resistance to meropenem (minimum inhibitory concentration, >16 µg/mL), to have prior admission to a long-term acute-care hospital, and to live in a nursing home (all P < .001). Also, 77 CP-CRE cases (17.3%) and 56 non–CP-CRE cases (9.6%) died within 30 days of infection onset. The risk of 30-day mortality was 57% higher for CP-CRE (adjusted risk ratio, 1.57; 95% CI:, 1.10–2.23) compared to non–CP-CRE patients after adjusting for comorbidities, nursing home residence, and prior healthcare exposures. Conclusions: CP-CRE cases had poorer outcomes than non–CP-CRE cases. This may be related in part to a higher proportion of sterile site infections among CP-CRE cases; our study was underpowered to analyze this subpopulation of sterile site cases. We plan to continue monitoring and performing analyses as mortality and hospital discharge data from more recent years become available and as more cases accumulate.
Background: Chlorhexidine bathing reduces bacterial skin colonization and prevents infections in specific patient populations. As chlorhexidine use becomes more widespread, concerns about bacterial tolerance to chlorhexidine have increased; however, testing for chlorhexidine minimum inhibitory concentrations (MICs) is challenging. We adapted a broth microdilution (BMD) method to determine whether chlorhexidine MICs changed over time among 4 important healthcare-associated pathogens. Methods: Antibiotic-resistant bacterial isolates (Staphylococcus aureus from 2005 to 2019 and Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae complex from 2011 to 2019) were collected through Emerging Infections Program surveillance in 2 sites (Georgia and Tennessee) or through public health reporting in 1 site (Orange County, California). A convenience sample of isolates were collected from facilities with varying amounts of chlorhexidine use. We performed BMD testing using laboratory-developed panels with chlorhexidine digluconate concentrations ranging from 0.125 to 64 μg/mL. After successfully establishing reproducibility with quality control organisms, 3 laboratories performed MIC testing. For each organism, epidemiological cutoff values (ECVs) were established using ECOFFinder. Results: Among 538 isolates tested (129 S. aureus, 158 E. coli, 142 K. pneumoniae, and 109 E. cloacae complex), S. aureus, E. coli, K. pneumoniae, and E. cloacae complex ECVs were 8, 4, 64, and 64 µg/mL, respectively (Table 1). Moreover, 14 isolates had an MIC above the ECV (12 E. coli and 2 E. cloacae complex). The MIC50 of each species is reported over time (Table 2). Conclusions: Using an adapted BMD method, we found that chlorhexidine MICs did not increase over time among a limited sample of S. aureus, E. coli, K. pneumoniae, and E. cloacae complex isolates. Although these results are reassuring, continued surveillance for elevated chlorhexidine MICs in isolates from patients with well-characterized chlorhexidine exposure is needed as chlorhexidine use increases.
Background: The National Healthcare Safety Network’s (NHSN) Antibiotic Resistance (AR) Option offers hospitals a way to report antibiotic resistance data from their facility’s laboratory information system and create facility-specific antibiograms. Suppression of select antibiotic susceptibility results may be used by antibiotic stewardship teams to prevent unnecessary use of broad-spectrum therapies by not making those susceptibilities available to providers. To be of use, antibiograms should offer a complete picture of antibiotic resistance. We wanted to understand the impact of data suppression. Methods: A retrospective cross-sectional study was conducted including data from 2017 and 2018. The clinical susceptibility data for cefotaxime, ceftriaxone, ceftazidime, ertapenem, imipenem, and meropenem against carbapenem-resistant Enterobacteriaceae (CRE), Pseudomonas aeruginosa (CRPA), Acinetobacter baumannii (CRAB), and extended-spectrum β-lactamase–producing Enterobacteriaceae (ESBL) were collected from commercial antimicrobial susceptibility testing instruments (cASTI) in 3 Tennessee healthcare networks that also report to the NHSN AR Option. These data were linked to the NHSN data using 4 keys: date of birth, isolate collection date, pathogen, and specimen source. An isolate was defined as suppressed when susceptibility results were observed from the cASTI but not in NHSN. The proportions of suppressed results were calculated and stratified by genus, facility, and antibiotic. Results: Overall, 1,009 isolates were matched between the NHSN AR data and the laboratory test results. Of these, 4.1% were CRAB, 23.3% were CRPA, and 72.6% were Enterobacteriaceae. In total, 4,948 susceptibility results were available from cASTIs. Suppressed results in NHSN data were observed in 918 isolates (91.0%) and accounted for 2,797 results (56.6%). Of the 817 isolates tested against imipenem, 18.7% were found to be suppressed. Moreover, 100%, 57.9%, and 8.6% of imipenem tests against CRAB, CRPA, and Enterobacteriaceae, respectively, were suppressed. Of the suppressed results, 38.3%, 3.6%, and 58.1% were susceptible, intermediate, and resistant respectively. Of the 363 isolates tested against meropenem, 48.2% were found to be suppressed. In addition, 12.2%, 53.0%, and 52.2% of meropenem tests against CRAB, CRPA, and Enterobacteriaceae, respectively, were suppressed. Of the suppressed results, 47.4%, 11.4%, and 41.1% were susceptible, intermediate, and resistant, respectively. Conclusions: A large proportion of isolates had at least 1 analyzed antibiotic suppressed within the NHSN AR Option. It will be important to develop and implement strategies to ensure that nonsuppressed data are available to be reported to the NHSN AR module.
Background: Extended-spectrum β-lactamase–producing (ESBL) Escherichia coli infection incidence is increasing in the United States. This increase may be due to the rapid expansion of ST131, which is now the predominant ESBL strain globally, often multidrug resistant, and has been shown to establish longer-term human colonization than other E. coli strains. We assessed potential risk factors that distinguish ST131 from other ESBL E. coli. Methods: From October 1 through December 31, 2017, 5 CDC Emerging Infections Program (EIP) sites pilot tested active, laboratory-based surveillance in selected counties in Colorado, Georgia, New Mexico, New York, and Tennessee. An E. coli case was defined as the first isolation from a normally sterile body site or urine in a surveillance area resident in a 30-day period resistant to 1 extended-spectrum cephalosporin antibiotic and susceptible or intermediate to all carbapenem antibiotics tested. Epidemiologic data were collected from case patients’ medical records. A convenience sample of 117 E. coli isolates from case patients was collected. All isolates underwent whole-genome sequencing to determine sequence type and the presence of ESBL genes. We compared ST131 E. coli epidemiology to other ESBL E. coli. Results: Among 117 E. coli isolates, 97 (83%) were ESBL producers. Of the 97 ESBL E. coli, 52 (54%) were ST131 (range, for 4 EIP sites submitting >10 isolates: 25%–88%; P < .001). Other common STs were ST38 (12%) and ST10 (5%). ST131 infections were more likely to be healthcare-associated than non-ST131 (56% vs 36%; P = .05) (Table 1). Among specific prior healthcare exposures, only residence in long-term care facilities (LTCFs) in the year before culture was more common among ST131 case patients (29% vs 11%; P = .03). Notably, 85% of ESBL E. coli collected from LTCF residents were ST131. ST131 E. coli were more common among patients with underlying medical conditions (81% vs 60%; P = .02). No statistically significant difference by sex, race, age, culture source, location of culture collection, and frequency of antibiotic use in the prior 30 days was observed. Conclusions:The prevalence of ST131 E. coli varies regionally. The association between ST131 and LTCFs suggests that these may be particularly important settings for ST131 acquisition. Improving infection control measures that limit ESBL transmission in these settings and preventing dissemination in facilities receiving patients from LTCFs may be necessary to contain ST131 spread.