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Objective: We evaluated the impact of test-order frequency per diarrheal episodes on Clostridioides difficile infection (CDI) incidence estimates in a sample of hospitals at 2 CDC Emerging Infections Program (EIP) sites. Design: Observational survey. Setting: Inpatients at 5 acute-care hospitals in Rochester, New York, and Atlanta, Georgia, during two 10-workday periods in 2020 and 2021. Outcomes: We calculated diarrhea incidence, testing frequency, and CDI positivity (defined as any positive NAAT test) across strata. Predictors of CDI testing and positivity were assessed using modified Poisson regression. Population estimates of incidence using modified Emerging Infections Program methodology were compared between sites using the Mantel-Hanzel summary rate ratio. Results: Surveillance of 38,365 patient days identified 860 diarrhea cases from 107 patient-care units mapped to 26 unique NHSN defined location types. Incidence of diarrhea was 22.4 of 1,000 patient days (medians, 25.8 for Rochester and 16.2 for Atlanta; P < .01). Similar proportions of diarrhea cases were hospital onset (66%) at both sites. Overall, 35% of patients with diarrhea were tested for CDI, but this differed by site: 21% in Rochester and 49% in Atlanta (P < .01). Regression models identified location type (ie, oncology or critical care) and laxative use predictive of CDI test ordering. Adjusting for these factors, CDI testing was 49% less likely in Rochester than Atlanta (adjusted rate ratio, 0.51; 95% confidence interval [CI], 0.40–0.63). Population estimates in Rochester had a 38% lower incidence of CDI than Atlanta (summary rate ratio, 0.62; 95% CI, 0.54–0.71). Conclusion: Accounting for patient-specific factors that influence CDI test ordering, differences in testing practices between sites remain and likely contribute to regional differences in surveillance estimates.

Objectives:To determine the incidence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare personnel (HCP) and to assess occupational risks for SARS-CoV-2 infection.Design:Prospective cohort of healthcare personnel (HCP) followed for 6 months from May through December 2020.Setting:Large academic healthcare system including 4 hospitals and affiliated clinics in Atlanta, Georgia.Participants:HCP, including those with and without direct patient-care activities, working during the coronavirus disease 2019 (COVID-19) pandemic.Methods:Incident SARS-CoV-2 infections were determined through serologic testing for SARS-CoV-2 IgG at enrollment, at 3 months, and at 6 months. HCP completed monthly surveys regarding occupational activities. Multivariable logistic regression was used to identify occupational factors that increased the risk of SARS-CoV-2 infection.Results:Of the 304 evaluable HCP that were seronegative at enrollment, 26 (9%) seroconverted for SARS-CoV-2 IgG by 6 months. Overall, 219 participants (73%) self-identified as White race, 119 (40%) were nurses, and 121 (40%) worked on inpatient medical-surgical floors. In a multivariable analysis, HCP who identified as Black race were more likely to seroconvert than HCP who identified as White (odds ratio, 4.5; 95% confidence interval, 1.3–14.2). Increased risk for SARS-CoV-2 infection was not identified for any occupational activity, including spending >50% of a typical shift at a patient’s bedside, working in a COVID-19 unit, or performing or being present for aerosol-generating procedures (AGPs).Conclusions:In our study cohort of HCP working in an academic healthcare system

We evaluated the impact of test-order frequency per diarrheal episodes onObservational survey.Inpatients at 5 acute-care hospitals in Rochester, New York, and Atlanta, Georgia, during two 10-workday periods in 2020 and 2021.We calculated diarrhea incidence, testing frequency, and CDI positivity (defined as any positive NAAT test) across strata. Predictors of CDI testing and positivity were assessed using modified Poisson regression. Population estimates of incidence using modified Emerging Infections Program methodology were compared between sites using the Mantel-Hanzel summary rate ratio.Surveillance of 38,365 patient days identified 860 diarrhea cases from 107 patient-care units mapped to 26 unique NHSN defined location types. Incidence of diarrhea was 22.4 of 1,000 patient days (medians, 25.8 for Rochester and 16.2 for Atlanta;Accounting for patient-specific factors that influence CDI test ordering, differences in testing practices between sites remain and likely contribute to regional differences in surveillance estimates.

In total, 13 facilities changed C. difficile testing to reflexive testing by enzyme immunoassay (EIA) only after a positive nucleic acid-amplification test (NAAT); the standardized infection ratio (SIR) decreased by 46% (range, −12% to −71% per hospital). Changing testing practice greatly influenced a performance metric without changing C. difficile infection prevention practice.

Among persons with an initial Clostridioides difficile infection (CDI) across 10 US sites in 2018 compared with 2013, 18.3% versus 21.1% had ≥1 recurrent CDI (rCDI) within 180 days. We observed a 16% lower adjusted risk of rCDI in 2018 versus 2013 (P

Background:Fluoroquinolones (FQs) and extended-spectrum cephalosporins (ESCs) are associated with higher risk of Clostridioides difficile infection (CDI). Decreasing the unnecessary use of FQs and ESCs is a goal of antimicrobial stewardship. Understanding how prescribers perceive the risks and benefits of FQs and ESCs is needed.Methods:We conducted interviews with clinicians from 4 hospitals. Interviews elicited respondent perceptions about the risk of ESCs, FQs, and CDI. Interviews were audio recorded, transcribed, and analyzed using a flexible coding approach.Results:Interviews were conducted with 64 respondents (38 physicians, 7 nurses, 6 advance practice providers, and 13 pharmacists). ESCs and FQs were perceived to have many benefits, including infrequent dosing, breadth of coverage, and greater patient adherence after hospital discharge. Prescribers stated that it was easy to make decisions about these drugs, so they were especially appealing to use in the context of time pressures. They described having difficulty discontinuing these drugs when prescribed by others due to inertia and fear. Prescribers were skeptical about targeting specific drugs as a stewardship approach and felt that the risk of a negative outcome from under treatment of a suspected bacterial infection was a higher priority than the prevention of CDI.Conclusions:Prescribers in this study perceived many advantages to using ESCs and FQs, especially under conditions of time pressure and uncertainty. In making decisions about these drugs, prescribers balance risk and benefit, and they believed that the risk of CDI was acceptable in compared with the risk of undertreatment.

Sepsis is a major physiologic response to infection that if not managed properly can lead to multiorgan failure and death. The US Centers for MedicareMedicaid Services (CMS) requires that hospitals collect data on core sepsis measure Severe Sepsis and Septic Shock Management Bundle (SEP-1) in an effort to promote the early recognition and treatment of sepsis. Despite implementation of the SEP-1 measure, sepsis-related mortality continues to challenge acute care hospitals nationwide.To determine if registered nurse workload was associated with mortality in Medicare beneficiaries admitted to an acute care hospital with sepsis.This cross-sectional study used 2018 data from the American Hospital Association Annual Survey, CMS Hospital Compare, and Medicare claims on Medicare beneficiaries age 65 to 99 years with a primary diagnosis of sepsis that was present on admission to 1 of 1958 nonfederal, general acute care hospitals that had data on CMS SEP-1 scores and registered nurse workload (indicated by registered nurse hours per patient day [HPPD]). Patients with sepsis were identified based on 29SEP-1 score and registered nurse staffing.The patient outcome of interest was mortality within 60 days of admission. Hospital characteristics included number of beds, ownership, teaching status, technology status, rurality, and region. Patient characteristics included age, sex, transfer status, intensive care unit admission, palliative care, do-not-resuscitate order, and a series of 29 comorbid diseases based on the Elixhauser Comorbidity Index.In total, 702 140 Medicare beneficiaries (mean [SD] age, 78.2 [8.7] years; 360 804 women [51%]) had a diagnosis of sepsis. The mean SEP-1 score was 56.1, and registered nurse HPPD was 6.2. In a multivariable regression model, each additional registered nurse HPPD was associated with a 3% decrease in the odds of 60-day mortality (odds ratio, 0.97; 95% CI 0.96-0.99) controlling for SEP-1 score and hospital and patient characteristics.The results of this cross-sectional study suggest that hospitals that provide more registered nurse hours of care could likely improve SEP-1 bundle compliance and decrease the likelihood of mortality in Medicare beneficiaries with sepsis.

Estimate incidence of and risks for SARS-CoV-2 infection among nursing home staff in the state of Georgia during the 2020-2021 Winter COVID-19 Surge in the United States.Serial survey and serologic testing at 2 time points with 3-month interval exposure assessment.Fourteen nursing homes in the state of Georgia; 203 contracted or employed staff members from those 14 participating nursing homes who were seronegative at the first time point and provided a serology specimen at second time point, at which time they reported no COVID-19 vaccination or only very recent vaccination (≤4 weeks).Interval infection was defined as seroconversion to antibody presence for both nucleocapsid protein and spike protein. We estimated adjusted odds ratios (aORs) and 95% CIs by job type, using multivariable logistic regression, accounting for community-based risks including interval community incidence and interval change in resident infections per bed.Among 203 eligible staff, 72 (35.5%) had evidence of interval infection. In multivariable analysis among unvaccinated staff, staff SARS-CoV-2 infection-induced seroconversion was significantly higher among nurses and certified nursing assistants accounting for race and interval infection incidence in both the community and facility (aOR 5.3, 95% CI 1.0-28.4). This risk persisted but was attenuated when using the full study cohort including those with very recent vaccination.Midway through the first year of the pandemic, job type continues to be associated with increased risk for infection despite enhanced infection prevention efforts including routine screening of staff. These results suggest that mitigation strategies prior to vaccination did not eliminate occupational risk for infection and emphasize critical need to maximize vaccine utilization to eliminate excess risk among front-line providers.

Background The prioritization of U.S. health care personnel for early receipt of messenger RNA (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19), allowed for the evaluation of the effectiveness of these new vaccines in a real-world setting. Methods We conducted a test-negative case–control study involving health care personnel across 25 U.S. states. Cases were defined on the basis of a positive polymerase-chain-reaction (PCR) or antigen-based test for SARS-CoV-2 and at least one Covid-19–like symptom. Controls were defined on the basis of a negative PCR test for SARS-CoV-2, regardless of symptoms, and were matched to cases according to the week of the test date and site. Using conditional logistic regression with adjustment for age, race and ethnic group, underlying conditions, and exposures to persons with Covid-19, we estimated vaccine effectiveness for partial vaccination (assessed 14 days after receipt of the first dose through 6 days after receipt of the second dose) and complete vaccination (assessed ≥7 days after receipt of the second dose). Results The study included 1482 case participants and 3449 control participants. Vaccine effectiveness for partial vaccination was 77.6% (95% confidence interval [CI], 70.9 to 82.7) with the BNT162b2 vaccine (Pfizer–BioNTech) and 88.9% (95% CI, 78.7 to 94.2) with the mRNA-1273 vaccine (Moderna); for complete vaccination, vaccine effectiveness was 88.8% (95% CI, 84.6 to 91.8) and 96.3% (95% CI, 91.3 to 98.4), respectively. Vaccine effectiveness was similar in subgroups defined according to age (

In total, 13 facilities changed

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: Epidemiological studies have utilized administrative discharge diagnosis codes to identify methicillin-resistant and methicillin-sensitive Staphylococcus aureus (MRSA and MSSA) infections and trends, despite debate regarding the accuracy of utilizing codes for this purpose. We assessed the sensitivity and positive predictive value (PPV) of MRSA- and MSSA-specific diagnosis codes, trends, characteristics, and outcomes of S. aureus hospitalizations by method of identification. Methods: Clinical micro biology results and discharge data from geographically diverse US hospitals participating in the Premier Healthcare Database from 2012–2017 were used to identify monthly rates of MRSA and MSSA. Positive MRSA or MSSA clinical cultures and/or a MRSA- or MSSA-specific International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification (ICD-9/10 CM) diagnosis codes from adult inpatients (aged ≥18 years) were included as S. aureus hospitalizations. Septicemia was defined as a positive blood culture or a MRSA or MSSA septicemia code. Sensitivity and PPV for codes were calculated for hospitalizations where admission status was not listed as transfer; true infection was considered a positive clinical culture. Negative binominal regression models measured trends in rates of MRSA and MSSA per 1,000 hospital discharges. Results: We identified 168,634 MRSA and 148,776 MSSA hospitalizations in 256 hospitals; 17% of MRSA and 21% of MSSA were septicemia. Less than half of all S. aureus hospitalizations (49% MRSA, 46% MSSA) and S. aureus septicemia hospitalizations (37% MRSA, 38% MSSA) had both a positive culture and diagnosis code (Fig. 1). Sensitivity of MRSA codes in identifying positive cultures was 61% overall and 56% for septicemia, PPV was 62% overall and 53% for septicemia. MSSA codes had a sensitivity of 49% in identifying MSSA cultures and 52% for MSSA septicemia; PPV was 69% overall and 62% for septicemia. Despite low sensitivity, MRSA trends are similar for cultures and codes, and MSSA trends are divergent (Fig. 2). For hospitalizations with septicemia, mortality was highest among those with a blood culture only (31.3%) compared to hospitalizations with both a septicemia code and blood culture (16.6%), and septicemia code only (14.7%). Conclusions: ICD diagnosis code sensitivity and PPV for identifying infections were consistently poor in recent years. Less than half of hospitalizations have concordant microbiology laboratory results and diagnosis codes. Rates and trend estimates for MSSA differ by method of identification. Using diagnosis codes to identify S. aureus infections may not be appropriate for descriptive epidemiology or assessing trends due to significant misclassification.Funding: NoneDisclosures: Scott Fridkin reports that his spouse receives consulting fees from the vaccine industry.

Updated Clostridioides difficile infection (CDI) guidelines published in 2018 recommend vancomycin as first-line treatment. Of 833 community-onset CDI cases in metropolitan Atlanta, Georgia in 2018, over half did not receive first-line treatment, although guideline adherence increased over the year. Second-line treatment was more common in patients treated in ambulatory settings.

Key Points Question What risk factors are associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among health care personnel (HCP) inside and outside the workplace? Findings In this cross-sectional study of 24 749 HCP in 3 US states, contact with an individual with known coronavirus disease 2019 (COVID-19) exposure outside the workplace was the strongest risk factor associated with SARS-CoV-2 seropositivity, along with living in a zip code with higher COVID-19 incidence. None of the assessed workplace factors were associated with seropositivity. Meaning In this study, most risk factors associated with SARS-CoV-2 infection among HCP were outside the workplace, suggesting that current infection prevention strategies in health care are effective in preventing patient-to-HCP transmission in the workplace., This cross-sectional study evaluates the risk factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among health care personnel., Importance Risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care personnel (HCP) are unclear. Objective To evaluate the risk factors associated with SARS-CoV-2 seropositivity among HCP with the a priori hypothesis that community exposure but not health care exposure was associated with seropositivity. Design, Setting, and Participants This cross-sectional study was conducted among volunteer HCP at 4 large health care systems in 3 US states. Sites shared deidentified data sets, including previously collected serology results, questionnaire results on community and workplace exposures at the time of serology, and 3-digit residential zip code prefix of HCP. Site-specific responses were mapped to a common metadata set. Residential weekly coronavirus disease 2019 (COVID-19) cumulative incidence was calculated from state-based COVID-19 case and census data. Exposures Model variables included demographic (age, race, sex, ethnicity), community (known COVID-19 contact, COVID-19 cumulative incidence by 3-digit zip code prefix), and health care (workplace, job role, COVID-19 patient contact) factors. Main Outcome and Measures The main outcome was SARS-CoV-2 seropositivity. Risk factors for seropositivity were estimated using a mixed-effects logistic regression model with a random intercept to account for clustering by site. Results Among 24 749 HCP, most were younger than 50 years (17 233 [69.6%]), were women (19 361 [78.2%]), were White individuals (15 157 [61.2%]), and reported workplace contact with patients with COVID-19 (12 413 [50.2%]). Many HCP worked in the inpatient setting (8893 [35.9%]) and were nurses (7830 [31.6%]). Cumulative incidence of COVID-19 per 10 000 in the community up to 1 week prior to serology testing ranged from 8.2 to 275.6; 20 072 HCP (81.1%) reported no COVID-19 contact in the community. Seropositivity was 4.4% (95% CI, 4.1%-4.6%; 1080 HCP) overall. In multivariable analysis, community COVID-19 contact and community COVID-19 cumulative incidence were associated with seropositivity (community contact: adjusted odds ratio [aOR], 3.5; 95% CI, 2.9-4.1; community cumulative incidence: aOR, 1.8; 95% CI, 1.3-2.6). No assessed workplace factors were associated with seropositivity, including nurse job role (aOR, 1.1; 95% CI, 0.9-1.3), working in the emergency department (aOR, 1.0; 95% CI, 0.8-1.3), or workplace contact with patients with COVID-19 (aOR, 1.1; 95% CI, 0.9-1.3). Conclusions and Relevance In this cross-sectional study of US HCP in 3 states, community exposures were associated with seropositivity to SARS-CoV-2, but workplace factors, including workplace role, environment, or contact with patients with known COVID-19, were not. These findings provide reassurance that current infection prevention practices in diverse health care settings are effective in preventing transmission of SARS-CoV-2 from patients to HCP.

Among 353 healthcare personnel in a longitudinal cohort in 4 hospitals in Atlanta, Georgia (May–June 2020), 23 (6.5%) had severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies. Spending >50% of a typical shift at the bedside (OR, 3.4; 95% CI, 1.2–10.5) and black race (OR, 8.4; 95% CI, 2.7–27.4) were associated with SARS-CoV-2 seropositivity.

Background Identifying occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care workers (HCWs) can improve HCW and patient safety. Objective To quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among HCWs in a large health care system. Design A logistic regression model was fitted to data from a cross-sectional survey conducted in April to June 2020, linking risk factors for occupational and community exposure to coronavirus disease 2019 (COVID-19) with SARS-CoV-2 seropositivity. Setting A large academic health care system in the Atlanta, Georgia, metropolitan area. Participants Employees and medical staff members elected to participate in SARS-CoV-2 serology testing offered to all HCWs as part of a quality initiative and completed a survey on exposure to COVID-19 and use of personal protective equipment. Measurements Demographic risk factors for COVID-19, residential ZIP code incidence of COVID-19, occupational exposure to HCWs or patients who tested positive on polymerase chain reaction test, and use of personal protective equipment as potential risk factors for infection. The outcome was SARS-CoV-2 seropositivity. Results Adjusted SARS-CoV-2 seropositivity was estimated to be 3.8% (95% CI, 3.4%-4.3%) (positive, n = 582) among the 10 275 HCWs (35% of the Emory Healthcare workforce) who participated in the survey. Community contact with a person known or suspected to have COVID-19 (adjusted odds ratio [aOR], 1.9 [CI, 1.4 to 2.6]; 77 positive persons [10.3%]) and community COVID-19 incidence (aOR, 1.5 [CI, 1.0 to 2.2]) increased the odds of infection. Black individuals were at high risk (aOR, 2.1 [CI, 1.7 to 2.6]; 238 positive persons [8.3%]). Limitations Participation rates were modest and key workplace exposures, including job and infection prevention practices, changed rapidly in the early phases of the pandemic. Conclusion Demographic and community risk factors, including contact with a COVID-19-positive person and Black race, are more strongly associated with SARS-CoV-2 seropositivity among HCWs than is exposure in the workplace. Primary funding source Emory COVID-19 Response Collaborative.

Objective: To determine the impact of an inpatient stewardship intervention targeting fluoroquinolone use on inpatient and postdischarge Clostridioides difficile infection (CDI). Design: We used an interrupted time series study design to evaluate the rate of hospital-onset CDI (HO-CDI), postdischarge CDI (PD-CDI) within 12 weeks, and inpatient fluoroquinolone use from 2 years prior to 1 year after a stewardship intervention. Setting: An academic healthcare system with 4 hospitals. Patients: All inpatients hospitalized between January 2017 and September 2020, excluding those discharged from locations caring for oncology, bone marrow transplant, or solid-organ transplant patients. Intervention: Introduction of electronic order sets designed to reduce inpatient fluoroquinolone prescribing. Results: Among 163,117 admissions, there were 683 cases of HO-CDI and 1,104 cases of PD-CDI. In the context of a 2% month-to-month decline starting in the preintervention period (P < .01), we observed a reduction in fluoroquinolone days of therapy per 1,000 patient days of 21% after the intervention (level change, P < .05). HO-CDI rates were stable throughout the study period. In contrast, we also detected a change in the trend of PD-CDI rates from a stable monthly rate in the preintervention period to a monthly decrease of 2.5% in the postintervention period (P < .01). Conclusions: Our systemwide intervention reduced inpatient fluoroquinolone use immediately, but not HO-CDI. However, a downward trend in PD-CDI occurred. Relying on outcome measures limited to the inpatient setting may not reflect the full impact of inpatient stewardship efforts.

Objectives: To estimate prior severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among skilled nursing facility (SNF) staff in the state of Georgia and to identify risk factors for seropositivity as of fall 2020. Design: Baseline survey and seroprevalence of the ongoing longitudinal Coronavirus 2019 (COVID-19) Prevention in Nursing Homes study. Setting: The study included 14 SNFs in the state of Georgia. Participants: In total, 792 SNF staff employed or contracted with participating SNFs were included in this study. The analysis included 749 participants with SARS-CoV-2 serostatus results who provided age, sex, and complete survey information. Methods: We estimated unadjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for potential risk factors and SARS-CoV-2 serostatus. We estimated adjusted ORs using a logistic regression model including age, sex, community case rate, SNF resident infection rate, working at other facilities, and job role. Results: Staff working in high-infection SNFs were twice as likely (unadjusted OR, 2.08; 95% CI, 1.45–3.00) to be seropositive as those in low-infection SNFs. Certified nursing assistants and nurses were 3 times more likely to be seropositive than administrative, pharmacy, or nonresident care staff: unadjusted OR, 2.93 (95% CI, 1.58–5.78) and unadjusted OR, 3.08 (95% CI, 1.66–6.07). Logistic regression yielded similar adjusted ORs. Conclusions: Working at high-infection SNFs was a risk factor for SARS-CoV-2 seropositivity. Even after accounting for resident infections, certified nursing assistants and nurses had a 3-fold higher risk of SARS-CoV-2 seropositivity than nonclinical staff. This knowledge can guide prioritized implementation of safer ways for caregivers to provide necessary care to SNF residents.

It is critical to determine how best to prevent SARS-CoV-2 infection in health care workers. Early in the pandemic, a voluntary survey of such workers coupled with serologic testing were used to assess the relative contribution of specific demographic, occupational, residential, and community-level risk factors for SARS-CoV-2 positivity., Background: Identifying occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care workers (HCWs) can improve HCW and patient safety. Objective: To quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among HCWs in a large health care system. Design: A logistic regression model was fitted to data from a cross-sectional survey conducted in April to June 2020, linking risk factors for occupational and community exposure to coronavirus disease 2019 (COVID-19) with SARS-CoV-2 seropositivity. Setting: A large academic health care system in the Atlanta, Georgia, metropolitan area. Participants: Employees and medical staff members elected to participate in SARS-CoV-2 serology testing offered to all HCWs as part of a quality initiative and completed a survey on exposure to COVID-19 and use of personal protective equipment. Measurements: Demographic risk factors for COVID-19, residential ZIP code incidence of COVID-19, occupational exposure to HCWs or patients who tested positive on polymerase chain reaction test, and use of personal protective equipment as potential risk factors for infection. The outcome was SARS-CoV-2 seropositivity. Results: Adjusted SARS-CoV-2 seropositivity was estimated to be 3.8% (95% CI, 3.4%-4.3%) (positive, n = 582) among the 10 275 HCWs (35% of the Emory Healthcare workforce) who participated in the survey. Community contact with a person known or suspected to have COVID-19 (adjusted odds ratio [aOR], 1.9 [CI, 1.4 to 2.6]; 77 positive persons [10.3%]) and community COVID-19 incidence (aOR, 1.5 [CI, 1.0 to 2.2]) increased the odds of infection. Black individuals were at high risk (aOR, 2.1 [CI, 1.7 to 2.6]; 238 positive persons [8.3%]). Limitations: Participation rates were modest and key workplace exposures, including job and infection prevention practices, changed rapidly in the early phases of the pandemic. Conclusion: Demographic and community risk factors, including contact with a COVID-19–positive person and Black race, are more strongly associated with SARS-CoV-2 seropositivity among HCWs than is exposure in the workplace. Primary Funding Source: Emory COVID-19 Response Collaborative.

We evaluated the association between socioeconomic status (SES) and community-associated Clostridioides difficile infection (CA-CDI) incidence across 2474 census tracts in 10 states. Highly correlated community-level SES variables were transformed into distinct factors using factor analysis. We found low SES communities were associated with higher CA-CDI incidence.

Fluoroquinolones (FQs) and extended-spectrum cephalosporins (ESCs) are associated with higher risk of Clostridioides difficile infection (CDI). Decreasing the unnecessary use of FQs and ESCs is a goal of antimicrobial stewardship. Understanding how prescribers perceive the risks and benefits of FQs and ESCs is needed.We conducted interviews with clinicians from 4 hospitals. Interviews elicited respondent perceptions about the risk of ESCs, FQs, and CDI. Interviews were audio recorded, transcribed, and analyzed using a flexible coding approach.Interviews were conducted with 64 respondents (38 physicians, 7 nurses, 6 advance practice providers, and 13 pharmacists). ESCs and FQs were perceived to have many benefits, including infrequent dosing, breadth of coverage, and greater patient adherence after hospital discharge. Prescribers stated that it was easy to make decisions about these drugs, so they were especially appealing to use in the context of time pressures. They described having difficulty discontinuing these drugs when prescribed by others due to inertia and fear. Prescribers were skeptical about targeting specific drugs as a stewardship approach and felt that the risk of a negative outcome from under treatment of a suspected bacterial infection was a higher priority than the prevention of CDI.Prescribers in this study perceived many advantages to using ESCs and FQs, especially under conditions of time pressure and uncertainty. In making decisions about these drugs, prescribers balance risk and benefit, and they believed that the risk of CDI was acceptable in compared with the risk of undertreatment.

Objective:To determine the effect of an electronic medical record (EMR) nudge at reducing total and inappropriate orders testing for hospital-onset Clostridioides difficile infection (HO-CDI).Design:An interrupted time series analysis of HO-CDI orders 2 years before and 2 years after the implementation of an EMR intervention designed to reduce inappropriate HO-CDI testing. Orders for C. difficile testing were considered inappropriate if the patient had received a laxative or stool softener in the previous 24 hours.Setting:Four hospitals in an academic healthcare network.Patients:All patients with a C. difficile order after hospital day 3.Intervention:Orders for C. difficile testing in patients administered a laxative or stool softener in Results:Of the 17,694 HO-CDI orders, 7% were inappropriate (8% prentervention vs 6% postintervention; P < .001). Monthly HO-CDI orders decreased by 21% postintervention (level-change rate ratio [RR], 0.79; 95% confidence interval [CI], 0.73–0.86), and the rate continued to decrease (postintervention trend change RR, 0.99; 95% CI, 0.98–1.00). The intervention was not associated with a level change in inappropriate HO-CDI orders (RR, 0.80; 95% CI, 0.61–1.05), but the postintervention inappropriate order rate decreased over time (RR, 0.95; 95% CI, 0.93–0.97).Conclusion:An EMR nudge to minimize inappropriate ordering for C. difficile was effective at reducing HO-CDI orders, and likely contributed to decreasing the inappropriate HO-CDI order rate after the intervention.

Background Interventions to reduce community-onset (CO) Clostridioides difficile Infection (CDI) are not usually hospital-based due to the perception that they are often acquired outside the hospital. We determined the proportion of admitted CO CDI that might be associated with previous hospitalization. Methods The CDC’s Emerging Infections Program conducts population-based CDI surveillance in 10 US sites. We defined an incident case as a C. difficile-positive stool collected in 2017 from a person aged ≥ 1 year admitted to a hospital with no positive tests in the prior 8 weeks. Cases were defined as CO if stool was collected within 3 days of hospitalization. CO cases were classified into four categories: long-term care facility (LTCF)-onset if patient was admitted from an LTCF; long-term acute care hospital (LTACH)-onset if patient was admitted from an LTACH; CO-healthcare-facility associated (CO-HCFA) if patient was admitted from a private residence but had a prior healthcare-facility admission in the past 12 weeks; or community-associated (CA) if there was no admission to a healthcare facility in the prior 12 weeks. We excluded hospitals with < 10 cases among admitted catchment-area residents. Results Of 4724 cases in 86 hospitals, 2984 (63.2%) were CO (median per hospital: 65.8%; interquartile range [IQR]: 58.3%-70.7%). Among the CO cases, 1424 (47.7%) were CA (median per hospital: 48.1%; IQR: 40.3%-57.7%), 1201 (40.3%) were CO-HCFA (median per hospital: 41.0%; IQR: 32.9%-47.8%), 350 (11.7%) were LTCF-onset (median per hospital: 10.0%; IQR: 0.6%-14.4%), and 9 (0.3%) were LTACH-onset. Of 1201 CO-HCFA cases, 1174 (97.8%) had a prior hospitalization; among these, 978 (83.3%) (median per hospital: 83.3%; IQR: 69.2%-90.6%), which consists of 32.8% of all hospitalized CO cases, had been discharged from the same hospital (Figure), and 84.4% of the 978 cases (median per hospital: 88.2%: IQR: 76.5%-100.0%) had received antibiotics sometime in the prior 12 weeks. Figure. Frequency of Cases Discharged in the 12 Weeks Prior to Readmission with Clostridioides difficile Infection (N=1138*) Conclusion A third of hospitalized CO CDI had been recently discharged from the same hospital, and most had received antibiotics during or soon after the last admission. Hospital-based and post-discharge antibiotic stewardship interventions could help reduce subsequent CDI hospitalizations. Disclosures Ghinwa Dumyati, MD, Roche Diagnostics (Consultant)

Background: Effective inpatient stewardship initiatives can improve antibiotic prescribing, but impact on outcomes like Clostridioides difficile infections (CDIs) is less apparent. However, the effect of inpatient stewardship efforts may extend to the postdischarge setting. We evaluated whether an intervention targeting inpatient fluoroquinolone (FQ) use in a large healthcare system reduced incidence of postdischarge CDI. Methods: In August 2019, 4 acute-care hospitals in a large healthcare system replaced standalone FQ orders with order sets containing decision support. Order sets redirected prescribers to syndrome order sets that prioritize alternative antibiotics. Monthly patient days (PDs) and antibiotic days of therapy (DOT) administered for FQs and NHSN-defined broad-spectrum hospital-onset (BS-HO) antibiotics were calculated using patient encounter data for the 23 months before and 13 months after the intervention (COVID-19 admissions in the previous 7 months). We evaluated hospital-onset CDI (HO-CDI) per 1,000 PD (defined as any positive test after hospital day 3) and 12-week postdischarge (PDC- CDI) per 100 discharges (any positive test within healthcare system Results: Among 163,117 admissions, there were 683 HO-CDIs and 1,009 PDC-CDIs. Overall, FQ DOT per 1,000 PD decreased by 21% immediately after the intervention (level change; P < .05) and decreased at a consistent rate throughout the entire study period (−2% per month; P < .01) (Fig. 1). There was a nonsignificant 5% increase in BS-HO antibiotic use immediately after intervention and a continued increase in use after the intervention (0.3% per month; P = .37). HO-CDI rates were stable throughout the study period, with a nonsignificant level change decrease of 10% after the intervention. In contrast, there was a reversal in the trend in PDC-CDI rates from a 0.4% per month increase in the preintervention period to a 3% per month decrease in the postintervention period (P < .01). Sensitivity analysis with adjustment for facility-specific CMI produced similar results but with wider confidence intervals, as did an analysis with a distinct COVID-19 time point. Conclusion: Our systemwide intervention using order sets with decision support reduced inpatient FQ use by 21%. The intervention did not significantly reduce HO-CDI but significantly decreased the incidence of CDI within 12 weeks after discharge. Relying on outcome measures limited to inpatient setting may not reflect the full impact of inpatient stewardship efforts and incorporating postdischarge outcomes, such as CDI, should increasingly be considered.Funding: NoDisclosures: None

In 2016, Zika virus disease developed in a man (patient A) who had no known risk factors beyond caring for a relative who died of this disease (index patient). We investigated the source of infection for patient A by surveying other family contacts, healthcare personnel, and community members, and testing samples for Zika virus. We identified 19 family contacts who had similar exposures to the index patient; 86 healthcare personnel had contact with the index patient, including 57 (66%) who had contact with body fluids. Of 218 community members interviewed, 28 (13%) reported signs/symptoms and 132 (61%) provided a sample. Except for patient A, no other persons tested had laboratory evidence of recent Zika virus infection. Of 5,875 mosquitoes collected, none were known vectors of Zika virus and all were negative for Zika virus. The mechanism of transmission to patient A remains unknown but was likely person-to-person contact with the index patient.

Background: The NHSN methods for central-line–associated bloodstream infection (CLABSI) surveillance do not account for additive CLABSI risk of concurrent central lines. Past studies were small and modestly risk adjusted but quantified the risk to be ~2-fold. If the attributable risk is this high, facilities that serve high-acuity patients with medically indicated concurrent central-line use may disproportionally incur CMS payment penalties for having high CLABSI rates. We aimed to build evidence through analysis using improved risk adjustment of a multihospital CLABSI experience to influence NHSN CLABSI protocols to account for risks attributed to concurrent central lines. Methods: In a retrospective cohort of adult patients at 4 hospitals (range, 110–733 beds) from 2012 to 2017, we linked central-line data to patient encounter data (age, comorbidities, total parenteral nutrition, chemotherapy, CLABSI). Analysis was limited to patients with >2 central-line days, with either a single central line or concurrence of no more than 2 central lines where insertion and removal dates overlapped by >1 day. Propensity-score matching for likelihood of concurrence and conditional logistic regression modeling estimated the risk of CLABSI attributed to concurrence of >1 day. To evaluate in Cox proportional hazards regression of time to CLABSIs, we also analyzed patients as unique central-line episodes: low risk (ie, ports, dialysis central lines, or PICC) or high risk (ie, temporary or nontunneled) and single versus concurrent. Results: In total, 64,575 central lines were used in 50,254 encounters. Among these patients, 517 developed a CLABSI; 438 (85%) with a single central line and 74 (15%) with concurrence. Moreover, 4,657 (9%) patients had concurrence (range, 6%–14% by hospital); of these, 74 (2%) had CLABSI, compared to 71 of 7,864 propensity-matched controls (1%). Concurrence patients had a median of 17 NHSN central-line days and 21 total central-line days. In multivariate modeling, patients with more concurrence (>2 of 3 of concurrent central-line days) had an higher risk for CLABSI (adjusted risk ratio, 1.62; 95% CI, 1.1–2.3) compared to controls. In survival analysis, 14,610 concurrent central-line episodes were compared to 31,126 single low-risk central-line episodes; adjusting for comorbidity, total parenteral nutrition, and chemotherapy, the daily excess risk of CLABSI attributable to the concurrent central line was ~80% (hazard ratio 1.78 for 2 high-risk or 2 low-risk central lines; hazard ratio 1.80 for a mix of high- and low-risk central lines) (Fig. 1). Notably, the hazard ratio attributed to a single high-risk line compared to a low-risk line was 1.44 (95% CI, 1.13–1.84). Conclusions: Since a concurrent central line nearly doubles the risk for CLABSI compared to a single low-risk line, the CDC should modify NHSN methodology to better account for this risk.Funding: NoneDisclosures: Scott Fridkin reports that his spouse receives consulting fees from the vaccine industry.

Background Peer comparison reduces unnecessary outpatient antibiotic prescribing, but no prescribing metric has been validated for inpatient comparison. We aimed to evaluate if an electronically derived antibiotic prescribing metric correlated with indicated antibiotic days in hospitalized patients. Methods We previously created a hospitalist-specific adjusted antibiotic use metric (observed:expected [O:E]) for National Healthcare Safety Network-defined broad-spectrum antibiotics. From May-Oct 2019 at four Emory Healthcare hospitals, we identified outlier hospitalists prescribing in the top (high O:E) and bottom (low O:E) 15th percentile. We randomly selected 10 days of antibiotic administration from each outlier and reviewed days with > 2 days of consecutive days of antibiotics. For pneumonia, chronic obstructive pulmonary disease (COPD), or urinary tract infection (UTI) we determined if each day of antibiotics was indicated, assuming the diagnosis was accurate. We compared high vs. low O:E providers and used regression modeling to determine if the metric predicted indicated days of antibiotics. Results Among 997 days, 510 (51%) were from high and 487 (49%) from low O:E providers. High O:E providers had a greater proportion of days with > 2 prior days of antibiotics (60%) compared to low O:E providers (54%, p = 0.03). In the subset of days with > 2 prior days of antibiotics (n = 569), high O:E providers had more patient-days with longer hospital stays, diabetes and Charlson comorbidity index (CCI) >3, and fewer days supervising (resident/advanced practice provider, Table 1). The primary diagnosis was pneumonia, COPD exacerbation or UTI in 260 (25%) days; 91% were indicated based on duration with no difference between high and low O:E providers (88% vs. 94%, p = 0.1). After controlling for days of hospitalization, CCI, immunocompromised status, and supervisory role, a high O:E was not associated with indicated antibiotic use (OR 0.5, 95% CI 0.2 – 1.3). Description of days with a patient on greater than two days of antibiotics, comparing high- versus low-metric providers Conclusion A high hospitalist antibiotic prescribing metric correlated with patients receiving > 2 consecutive days of antibiotics on any given day but did not predict unindicated antibiotic use for a subset of diagnoses. Evaluating indicated use by validating diagnoses may improve metric performance. Disclosures Jessica Howard-Anderson, MD, Antibacterial Resistance Leadership Group (ARLG) (Other Financial or Material Support, The ARLG fellowship provides salary support for ID fellowship and mentored research training)

Background: Historically, metronidazole was first-line therapy for Clostridioides difficile infection (CDI). In February 2018, the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) updated clinical practice guidelines for CDI. The new guidelines recommend oral vancomycin or fidaxomicin for treatment of initial episode of CDI in adults. We examined the changes in treatment of CDI during 2018 across all types of healthcare settings in metropolitan Atlanta. Methods: Cases were identified through the Georgia Emerging Infections program (funded by the Centers for Disease Control and Prevention), which conducts active population-based surveillance in an 8-county area including Atlanta, Georgia (population, 4,126,399). An incident case was a resident of the catchment area with a positive C. difficile toxin test and no additional positive test in the previous 8 weeks. Recurrent CDI was defined as >1 incident CDI episode in 1 year. Clinical and treatment data were abstracted on a random 33% sample of adult (>17 years) cases. Definitive treatment categories were defined as the single antibiotic agent, metronidazole or vancomycin, used to complete a course. We examined the effect of time of infection, location of treatment, and number of CDI episodes on the use of metronidazole only. Results: We analyzed treatment information for 831 adult sampled cases. Overall, cases were treated at 29 hospitals (568 cases), 4 nursing homes (6 cases), and 101 outpatient providers (257 cases). The mean age was 60 (IQR, 34–86), and 111 (13.4%) had recurrent infection. Moreover, ∼28% of first-incident CDI episodes, 8% of second episodes, and 6% of third episodes were treated with metronidazole only. Compared to facility-based providers, outpatient providers were more likely to treat initial CDI episodes with metronidazole only (44% vs 21%; relative risk [RR], 2.1; 95% CI, 1.7–2.7). Treatment changed over time from 56% metronidazole only in January to 10% in December (Fig. 1). First-incident cases in the first quarter of 2018 were more likely to be treated with metronidazole only compared to those in the fourth quarter (RR, 2.76; 95% CI, 1.91–3.97). Conclusions: Preferential use of vancomycin for initial CDI episodes increased throughout 2018 but remained Funding: NoneDisclosures: Scott Fridkin reports that his spouse receives a consulting fee from the vaccine industry.

Background: Nursing home (NH) residents are at high risk for Clostridioides difficile infection (CDI) due to older age, frequent antibiotic exposure, and previous healthcare exposure. Incidence of CDI attributed to NHs is not well established, but it is hypothesized to be related to the magnitude of transfers. We evaluated the relationship between NH CDI incidence and facility characteristics to explain variability in rates in Atlanta, Georgia. Methods: Incident C. difficile cases from 2016 to 2018 were identified through the Georgia Emerging Infections Program (funded by the Centers for Disease Control and Prevention), which conducts active population-based surveillance in the 8-county metro Atlanta area. An incident case was defined as an NH resident with a toxin-positive stool specimen (without a positive test within 8 weeks). Sampled (1 to 3 on age and gender) incident cases were attributed to a NH if a patient was an NH resident within 4 days of specimen collection. Facility characteristics (beds, resident days, admissions, and average length of stay [ALOS]) were obtained from NH cost reports, and facility-specific connectivity metrics were calculated (indegree and betweenness) from 2016 Medicare claims data. Case counts were aggregated to estimate yearly incidence and correlated with facility characteristics and location within the healthcare network using the Spearman correlation. A negative binomial model was used to assess residual variability in NH CDI incidence. Results: In total, 386 incident CDI cases were attributed to 64 NHs (range, 0–27). Approximately half (54.7%) resided in the NH at the time of specimen collection; however, 33.7% were in inpatient units (≤4 days of admission), and 10.9% were in an emergency room (ER). The frequency of NH CDI cases correlated strongly with admissions (r = .70; P < .01), inversely with ALOS (r = −0.53; P < .01), and moderately with resident days (r = .38; P < .01). After accounting for admissions, incidence (per 1,000 admissions) still varied (Fig. 1) (median 14; range, 0–34). The inverse association with ALOS decreased and incidence no longer correlated with the remaining facility characteristics or location within the healthcare transfer network (P > .05, all comparisons). However, there was residual correlation with connectivity metrics (indegree r = 0.26; P = .04). Conclusions: Our data suggest that attributing CDI to NHs requires the inclusion of hospital and ER-based specimen collection. NH CDI incidence appears highest among facilities with a low ALOS and a high number of admissions; incidence rates calculated per 1,000 admissions may best account for infection risk inherent early in a resident’s stay. Residual variability attributed to connectivity to the healthcare network was of borderline significance and should be further explored in the NH setting.Funding: NoneDisclosures: Scott Fridkin, consulting fee, vaccine industry (spouse)

Background: Hospitalists play a critical role in antimicrobial stewardship as the primary antibiotic prescriber for many inpatients. We sought to describe antibiotic prescribing variation among hospitalists within a healthcare system. Methods: We created a novel metric of hospitalist-specific antibiotic prescribing by linking hospitalist billing data to hospital medication administration records in 4 hospitals (two 500-bed academic (AMC1 and AMC2), one 400-bed community (CH1), and one 100-bed community (CH2)) from January 2016 to December 2018. We attributed dates that a hospitalist electronically billed for a given patient as billed patient days (bPD) and mapped an antibiotic day of therapy (DOT) to a bPD. Each DOT was classified according to National Healthcare Safety Network antibiotic categories: broad-spectrum hospital-onset (BS-HO), broad-spectrum community-onset (BS-CO), anti-MRSA, and highest risk for Clostridioides difficile infection (CDI). DOT and bPD were pooled to calculate hospitalist-specific DOT per 1,000 bPD. Best subsets regression was performed to assess model fit and generate hospital and antibiotic category-specific models adjusting for patient-level factors (eg, age ≥65, ICD-10 codes for comorbidities and infections). The models were used to calculate predicted hospitalist-specific DOT and observed-to-expected ratios (O:E) for each antibiotic category. Kruskal-Wallis tests and pairwise Wilcoxon rank-sum tests were used to determine significant differences between median DOT per 1,000 bPD and O:E between hospitals for each antibiotic category. Results: During the study period, 116 hospitalists across 4 hospitals contributed a total of 437,303 bPD. Median DOT per 1,000 bPD varied between hospitals (BS-HO range, 46.7–84.2; BS-CO range, 63.3–100; anti-MRSA range, 48.4–65.4; CDI range, 82.0–129.4). CH2 had a significantly higher median DOT per 1,000 bPD compared to the academic hospitals (all antibiotic categories P < .001) and CH1 (BS-HO, P = .01; anti-MRSA, P = .02) (Fig. 1A). The 4 antibiotic groups at 4 hospitals resulted in 16 models, with good model fit for CH2 (R2 > 0.55 for all models), modest model fit for AMC2 (R2 = 0.46–0.55), fair model fit for CH1 (R2 = 0.19–0.35), and poor model fit for AMC1 (R2 < 0.12 for all models). Variation in hospitalist-specific O:E was moderate (IQR, 0.9–1.1). AMC1 showed greater variation than other hospitals, but we detected no significant differences in median O:E between hospitals (all antibiotic categories P > .10) (Fig. 1B). Conclusions: Adjusting for patient-level factors significantly reduced much of the variation in hospitalist-specific DOT per 1,000 bPD in some but not all hospitals, suggesting that unmeasured factors may drive antibiotic prescribing. This metric may represent a target for stewardship intervention, such as hospitalist-specific feedback of antibiotic prescribing practices.Funding: NoneDisclosures: Scott Fridkin, consulting fee - vaccine industry (various) (spouse)