41. Assessing Past vs Present COVID-19 Infection: A Survey of Criteria for Discontinuing Precautions in Asymptomatic Patients

Abstract Background COVID-19 patients can remain positive by PCR-testing for several months. Pre-admission or pre-procedure testing can identify recovered asymptomatic patients who may no longer be contagious but would require precautions according to current CDC recommendations (10 days). This can result in unintended consequences, including procedure delays or transfer to appropriate care (e.g., psychiatric or post-trauma patients requiring admission to COVID-19 units instead of psychiatric or rehabilitation facilities, respectively). Methods We conducted a structured survey of healthcare epidemiologists and infection prevention experts from the SHEA Research Network between March-April, 2021. The 14-question survey, presented a series of COVID-19 PCR+ asymptomatic patient case scenarios and asked respondents if (1) they would consider the case recovered and not infectious, (2) if they have cleared precautions in such cases, and if so, (3) how many transmission events occurred after discontinuing precautions. The survey used one or a combination of 5 criteria: history of COVID-19 symptoms, history of exposure to a household member with COVID-19, COVID-19 PCR cycle threshold (CT), and IgG serology. Percentages were calculated among respondents for each question. Results Among 60 respondents, 56 (93%) were physicians, 51 (86%) were hospital epidemiologists, and 46 (77%) had >10y infection prevention experience. They represented facilities that cumulatively cared for >29,000 COVID-19 cases; 46 (77%) were academic, and 42 (69%) were large ( >400 beds). One-third to one-half would consider an incidentally found PCR+ case as recovered based on solo criteria, particularly those with two consecutive high CTs or COVID IgG positivity recovered (53-55%) (Table 1). When combining two criteria, half to four-fifths of respondents deemed PCR+ cases to be recovered (Table 2). Half of those had used those criteria to clear precautions (45-64%) and few to none experienced a subsequent transmission event resulting from clearance. Conclusion The majority of healthcare epidemiologists consider a combination of clinical and diagnostic criteria as recovered and many have used these to clear precautions without high numbers of transmission. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Deborah S. Yokoe, MD, MPH, Nothing to disclose Stuart H. Cohen, MD, Seres (Research Grant or Support) Jonathan Grein, MD, Gilead (Other Financial or Material Support, Speakers fees) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products

Assessing past versus present severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection: A survey of criteria for discontinuing precautions in asymptomatic patients testing positive on admission.

Infection prevention program leaders report frequent use of criteria to distinguish recently recovered coronavirus disease 2019 (COVID-19) cases from actively infectious cases when incidentally positive asymptomatic patients were identified on routine severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing. Guidance on appropriate interpretation of high-sensitivity molecular tests can prevent harm from unnecessary precautions that delay admission and impede medical care

41. Assessing Past vs Present COVID-19 Infection: A Survey of Criteria for Discontinuing Precautions in Asymptomatic Patients

Abstract Background COVID-19 patients can remain positive by PCR-testing for several months. Pre-admission or pre-procedure testing can identify recovered asymptomatic patients who may no longer be contagious but would require precautions according to current CDC recommendations (10 days). This can result in unintended consequences, including procedure delays or transfer to appropriate care (e.g., psychiatric or post-trauma patients requiring admission to COVID-19 units instead of psychiatric or rehabilitation facilities, respectively). Methods We conducted a structured survey of healthcare epidemiologists and infection prevention experts from the SHEA Research Network between March-April, 2021. The 14-question survey, presented a series of COVID-19 PCR+ asymptomatic patient case scenarios and asked respondents if (1) they would consider the case recovered and not infectious, (2) if they have cleared precautions in such cases, and if so, (3) how many transmission events occurred after discontinuing precautions. The survey used one or a combination of 5 criteria: history of COVID-19 symptoms, history of exposure to a household member with COVID-19, COVID-19 PCR cycle threshold (CT), and IgG serology. Percentages were calculated among respondents for each question. Results Among 60 respondents, 56 (93%) were physicians, 51 (86%) were hospital epidemiologists, and 46 (77%) had >10y infection prevention experience. They represented facilities that cumulatively cared for >29,000 COVID-19 cases; 46 (77%) were academic, and 42 (69%) were large ( >400 beds). One-third to one-half would consider an incidentally found PCR+ case as recovered based on solo criteria, particularly those with two consecutive high CTs or COVID IgG positivity recovered (53-55%) (Table 1). When combining two criteria, half to four-fifths of respondents deemed PCR+ cases to be recovered (Table 2). Half of those had used those criteria to clear precautions (45-64%) and few to none experienced a subsequent transmission event resulting from clearance. Conclusion The majority of healthcare epidemiologists consider a combination of clinical and diagnostic criteria as recovered and many have used these to clear precautions without high numbers of transmission. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Deborah S. Yokoe, MD, MPH, Nothing to disclose Stuart H. Cohen, MD, Seres (Research Grant or Support) Jonathan Grein, MD, Gilead (Other Financial or Material Support, Speakers fees) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products

84. Evaluation of the NHSN Standardized Infection Ratio (SIR) Risk Adjustment for HO-CDI in Oncology and ICU Patients in General Acute Care Hospitals

Abstract Background The NHSN healthcare-facility onset Clostridioides difficile infection (CDI) standardized infection ratio (SIR) is used to compare hospital quality and set hospital reimbursement but inadequate risk adjustment could penalize hospitals unnecessarily. We hypothesized that general hospitals with large oncology and/or ICU populations were not fully adjusted in the 2015 NHSN acute care hospital CDI Laboratory-Identified (LabID) event prediction model and SIRs would be affected. Methods We validated a negative binomial regression HO-CDI event prediction model identical to the 2015 published model and used FY2016 data from eight general hospitals in California to test our hypothesis. We compared HO-CDI events and SIR values, with and without oncology/hematopoietic stem cell transplant or ICU unit events, patient-days, admissions, bed counts, and adjustment parameters included. Results Seven major teaching and one nonteaching general acute care hospitals were included (see Table). Eight had oncology/hematopoietic stem cell transplant units; seven had ≥43 ICU beds (median: 134; interquartile range [IQR]: 84–161). The median facility unmodified FacWideIn SIR was 1.23 [IQR: 1.15, 1.29]. Removal of oncology unit data resulted in a 15% median facility decrease in HO-CDI events (IQR: 14%, 21%) and −8% median facility decrease in SIR (IQR: −2%, −14%). Removal of ICU unit data resulted in a 22% median facility decrease in HO-CDI events (IQR: 16%, 26%) and 97% median facility increase in SIR at each facility (IQR: 78%, 105%). Conclusion The ICU bed adjustment in the 2015 NHSN SIR is a powerful correction that fully adjusted for ICU HO-CDI events at all hospitals in the study. However, the lack of risk adjustment for oncology/hematopoietic stem cell transplant unit HO-CDI events suggests that the current model unfairly penalizes general acute facilities, many of which also provide specialized oncologic care. Thus, the model needs to be re-adjusted to account for this important specialty care population in general acute care facilities. Disclosures All Authors: No reported Disclosures

84. Evaluation of the NHSN Standardized Infection Ratio (SIR) Risk Adjustment for HO-CDI in Oncology and ICU Patients in General Acute Care Hospitals

Abstract Background The NHSN healthcare-facility onset Clostridioides difficile infection (CDI) standardized infection ratio (SIR) is used to compare hospital quality and set hospital reimbursement but inadequate risk adjustment could penalize hospitals unnecessarily. We hypothesized that general hospitals with large oncology and/or ICU populations were not fully adjusted in the 2015 NHSN acute care hospital CDI Laboratory-Identified (LabID) event prediction model and SIRs would be affected. Methods We validated a negative binomial regression HO-CDI event prediction model identical to the 2015 published model and used FY2016 data from eight general hospitals in California to test our hypothesis. We compared HO-CDI events and SIR values, with and without oncology/hematopoietic stem cell transplant or ICU unit events, patient-days, admissions, bed counts, and adjustment parameters included. Results Seven major teaching and one nonteaching general acute care hospitals were included (see Table). Eight had oncology/hematopoietic stem cell transplant units; seven had ≥43 ICU beds (median: 134; interquartile range [IQR]: 84–161). The median facility unmodified FacWideIn SIR was 1.23 [IQR: 1.15, 1.29]. Removal of oncology unit data resulted in a 15% median facility decrease in HO-CDI events (IQR: 14%, 21%) and −8% median facility decrease in SIR (IQR: −2%, −14%). Removal of ICU unit data resulted in a 22% median facility decrease in HO-CDI events (IQR: 16%, 26%) and 97% median facility increase in SIR at each facility (IQR: 78%, 105%). Conclusion The ICU bed adjustment in the 2015 NHSN SIR is a powerful correction that fully adjusted for ICU HO-CDI events at all hospitals in the study. However, the lack of risk adjustment for oncology/hematopoietic stem cell transplant unit HO-CDI events suggests that the current model unfairly penalizes general acute facilities, many of which also provide specialized oncologic care. Thus, the model needs to be re-adjusted to account for this important specialty care population in general acute care facilities. Disclosures All Authors: No reported Disclosures

Evaluation of the National Healthcare Safety Network standardized infection ratio risk adjustment for healthcare-facility-onset Clostridioides difficile infection in intensive care, oncology, and hematopoietic cell transplant units in general acute-care hospitals.

ObjectiveTo evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.DesignRetrospective cohort study.SettingEight tertiary-care referral general hospitals in California.MethodsWe used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.ResultsFor these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15-1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, -25%; IQR, -20% to -29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%-105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, -15%; IQR, -14% to -21%) and decreased the SIR at all hospitals (median, -8%; IQR, -4% to -11%).ConclusionsFor tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR

84. Evaluation of the NHSN Standardized Infection Ratio (SIR) Risk Adjustment for HO-CDI in Oncology and ICU Patients in General Acute Care Hospitals

Abstract Background The NHSN healthcare-facility onset Clostridioides difficile infection (CDI) standardized infection ratio (SIR) is used to compare hospital quality and set hospital reimbursement but inadequate risk adjustment could penalize hospitals unnecessarily. We hypothesized that general hospitals with large oncology and/or ICU populations were not fully adjusted in the 2015 NHSN acute care hospital CDI Laboratory-Identified (LabID) event prediction model and SIRs would be affected. Methods We validated a negative binomial regression HO-CDI event prediction model identical to the 2015 published model and used FY2016 data from eight general hospitals in California to test our hypothesis. We compared HO-CDI events and SIR values, with and without oncology/hematopoietic stem cell transplant or ICU unit events, patient-days, admissions, bed counts, and adjustment parameters included. Results Seven major teaching and one nonteaching general acute care hospitals were included (see Table). Eight had oncology/hematopoietic stem cell transplant units; seven had ≥43 ICU beds (median: 134; interquartile range [IQR]: 84–161). The median facility unmodified FacWideIn SIR was 1.23 [IQR: 1.15, 1.29]. Removal of oncology unit data resulted in a 15% median facility decrease in HO-CDI events (IQR: 14%, 21%) and −8% median facility decrease in SIR (IQR: −2%, −14%). Removal of ICU unit data resulted in a 22% median facility decrease in HO-CDI events (IQR: 16%, 26%) and 97% median facility increase in SIR at each facility (IQR: 78%, 105%). Conclusion The ICU bed adjustment in the 2015 NHSN SIR is a powerful correction that fully adjusted for ICU HO-CDI events at all hospitals in the study. However, the lack of risk adjustment for oncology/hematopoietic stem cell transplant unit HO-CDI events suggests that the current model unfairly penalizes general acute facilities, many of which also provide specialized oncologic care. Thus, the model needs to be re-adjusted to account for this important specialty care population in general acute care facilities. Disclosures All Authors: No reported Disclosures

Evaluation of the National Healthcare Safety Network standardized infection ratio risk adjustment for healthcare-facility-onset Clostridioides difficile infection in intensive care, oncology, and hematopoietic cell transplant units in general acute-care hospitals.

ObjectiveTo evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.DesignRetrospective cohort study.SettingEight tertiary-care referral general hospitals in California.MethodsWe used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.ResultsFor these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15-1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, -25%; IQR, -20% to -29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%-105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, -15%; IQR, -14% to -21%) and decreased the SIR at all hospitals (median, -8%; IQR, -4% to -11%).ConclusionsFor tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR

426. COVID-19 Infection Prevention Practices That Exceed CDC Guidance: Balancing Extra Caution Against Impediments to Care

Abstract Background At the outset of the COVID-19 pandemic, healthcare workers (HCWs) raised concerns about personal risks of acquiring infection during patient care. This led to more stringent infection prevention practices than CDC guidelines during a time of uncertainty about transmission and limited U.S. testing capacity. Hospitals were challenged to protect against true COVID-19 exposure risks, while avoiding use of unproven measures that could interfere with timely, high quality care. We evaluated hospital experiences with HCW COVID-19 exposure concerns impacting clinical workflow/management. Methods We conducted a 32-question structured survey of hospital infection prevention leaders (one per hospital) from CDC Prevention Epicenters, University of California (CA) Health system, HCA Healthcare, and the Southern CA Metrics Committee between May–Dec, 2020. We assessed facility characteristics and COVID-19 exposure concerns causing changes in respiratory care, procedure delays/modifications, requests to change infection prevention processes, disruptions in routine medical care, and health impacts of PPE overuse. Percentages were calculated among respondents for each question. Results Respondents represented 53 hospitals: 22 (42%) were small (< 200 beds), 14 (26%) medium (200-400 beds), and 17 (32%) large ( >400 beds) facilities. Of these, 11 (21%) provided Level 1 trauma care, and 22 (41%) provided highly immunocompromised patient care; 75% had cared for a substantial number of COVID-19 cases before survey completion. Majority reported changes in respiratory care delivery (71%-87%), procedural delays (75%-87%), requests to change infection prevention controls/protocols (58%-96%), and occupational health impacts of PPE overuse including skin irritation (98%) and carbon dioxide narcosis symptoms (55%) (Table). Conclusion HCW concerns over work-related COVID-19 exposure contributed to practice changes, many of which are unsupported by CDC guidance and resulted in healthcare delivery delays and alterations in clinical care. Pandemic planning and response must include the ability to rapidly develop evidence to guide infection prevention practice. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Deborah S. Yokoe, MD, MPH, Nothing to disclose Jonathan Grein, MD, Gilead (Other Financial or Material Support, Speakers fees) Stuart H. Cohen, MD, Seres (Research Grant or Support) Kimberly N. Smith, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Brandon Carver, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products

839. Effect of Clostridioides difficile (C. difficile) Toxin Test Reporting on Clinical Treatment and Outcomes of Toxin-Negative PCR-Positive Patients at Five California Hospitals

Abstract Background Guidelines support the use of toxin tests after C. difficile antigen detection or nucleic acid amplification tests (e.g., PCR) to help clinicians distinguish colonization from infection and reduce overdiagnosis but the safety of toxin-based diagnostic approaches remains controversial. Methods Five California hospitals monitored hospitalized adults with C. difficile testing before and after operational changes to reduce test-related overdiagnosis (2016–2018). Four added a toxin test to an existing GDH antigen/PCR-based approach and/or changed reporting to encourage the use of toxin results for clinical decision-making (i.e.,“toxin-dominant reporting”). One used the same test (toxin only) and reporting strategy throughout. All used a standardized tool to document clinical outcomes and treatment four days after testing (i.e., Day 5). Results In total, 1,034 patients had a Day 5 assessment with PCR-dominant reporting (pre-operational changes); 2,511 patients had a Day 5 assessment with toxin-dominant reporting (post-operational changes and single facility with no test change). Fewer Toxin-negative/PCR-positive (Toxin−/PCR+) patients received treatment with toxin-dominant reporting (median change: −52.1% [interquartile range (IQR): −35.1%, −69.1%]; aggregate P < 0.001). Day 5 outcomes were similar or better with toxin-dominant reporting despite less treatment. Patient discharge rates and in hospital diarrheal recovery was greater in the subset of Toxin−/PCR+ patients during the toxin-dominant reporting period: median discharge rate change = 8.8% [IQR: 1.5%, 11.9%] (aggregate P = 0.04); median diarrheal recovery rate change = 11.8% [IQR: 8.8%, 18.2%] (aggregate P = 0.018). Conclusion In a 5-center study, toxin-dominant test result reporting decreased anti-C. difficile treatment and improved discharge rates and diarrheal recovery in Toxin−/PCR+ patients. More work is needed to determine the rate of C. difficile-related adverse events in Toxin−/PCR+ patients. Disclosures All Authors: No reported Disclosures