Jessica Howard-Anderson, Radhika Prakash Asrani, Chris Bower, Chad Robichaux, Rishi Kamaleswaran, Jesse Jacob, Scott Fridkin
Background: Prompt identification of patients colonized or infected with carbapenem-resistant Enterobacterales (CRE) upon admission can help ensure rapid initiation of infection prevention measures and may reduce intrafacility transmission of CRE. The Chicago CDC Prevention Epicenters Program previously created a CRE prediction model using state-wide public health data (doi: 10.1093/ofid/ofz483). We evaluated how well a similar model performed using data from a single academic healthcare system in Atlanta, Georgia, and we sought to determine whether including additional variables improved performance. Methods: We performed a case–control study using electronic medical record data. We defined cases as adult encounters to acute-care hospitals in a 4-hospital academic healthcare system from January 1, 2014, to December 31, 2021, with CRE identified from a clinical culture within the first 3 hospital days. Only the first qualifying encounter per patient was included. We frequency matched cases to control admissions (no CRE identified) from the same hospital and year. Using multivariable logistic regression, we compared 2 models. The “public health model” included 4 variables from the Chicago Epicenters model (age, number of hospitalizations in the prior 365 days, mean length of stay in hospitalizations in the prior 365 days, and hospital admission with an infection diagnosis in the prior 365 days). The “healthcare system model” added 4 additional variables (admission to the ICU in the prior 365 days, malignancy diagnosis, Elixhauser score and inpatient antibiotic days of therapy in the prior 365 days) to the public health model. We used billing codes to determine Elixhauser score, malignancy status, and recent infection diagnoses. We compared model performance using the area under the receiver operating curve (AUC). Results: We identified 105 cases and 441,460 controls (Table 1). CRE was most frequently identified in urine cultures (46%). All 4 variables included in the public health model and the 4 additional variables in the healthcare system model were all significantly associated with being a case in unadjusted analyses (Table 1). The AUC for the public health model was 0.76, and the AUC for the healthcare system model was 0.79 (Table 2; Fig. 1). In both models, a prior admission with an infection diagnosis was the most significant risk factor. Conclusions: A modified CRE prediction model developed using public health data and focused on prior healthcare exposures performed reasonably well when applied to a different academic healthcare system. The addition of variables accessible in large healthcare networks did not meaningfully improve model discrimination. Disclosures: None
{"title":"Identifying patients at high risk for carbapenem-resistant Enterobacterales carriage upon admission to acute-care hospitals","authors":"Jessica Howard-Anderson, Radhika Prakash Asrani, Chris Bower, Chad Robichaux, Rishi Kamaleswaran, Jesse Jacob, Scott Fridkin","doi":"10.1017/ash.2023.339","DOIUrl":"https://doi.org/10.1017/ash.2023.339","url":null,"abstract":"Background: Prompt identification of patients colonized or infected with carbapenem-resistant Enterobacterales (CRE) upon admission can help ensure rapid initiation of infection prevention measures and may reduce intrafacility transmission of CRE. The Chicago CDC Prevention Epicenters Program previously created a CRE prediction model using state-wide public health data (doi: 10.1093/ofid/ofz483). We evaluated how well a similar model performed using data from a single academic healthcare system in Atlanta, Georgia, and we sought to determine whether including additional variables improved performance. Methods: We performed a case–control study using electronic medical record data. We defined cases as adult encounters to acute-care hospitals in a 4-hospital academic healthcare system from January 1, 2014, to December 31, 2021, with CRE identified from a clinical culture within the first 3 hospital days. Only the first qualifying encounter per patient was included. We frequency matched cases to control admissions (no CRE identified) from the same hospital and year. Using multivariable logistic regression, we compared 2 models. The “public health model” included 4 variables from the Chicago Epicenters model (age, number of hospitalizations in the prior 365 days, mean length of stay in hospitalizations in the prior 365 days, and hospital admission with an infection diagnosis in the prior 365 days). The “healthcare system model” added 4 additional variables (admission to the ICU in the prior 365 days, malignancy diagnosis, Elixhauser score and inpatient antibiotic days of therapy in the prior 365 days) to the public health model. We used billing codes to determine Elixhauser score, malignancy status, and recent infection diagnoses. We compared model performance using the area under the receiver operating curve (AUC). Results: We identified 105 cases and 441,460 controls (Table 1). CRE was most frequently identified in urine cultures (46%). All 4 variables included in the public health model and the 4 additional variables in the healthcare system model were all significantly associated with being a case in unadjusted analyses (Table 1). The AUC for the public health model was 0.76, and the AUC for the healthcare system model was 0.79 (Table 2; Fig. 1). In both models, a prior admission with an infection diagnosis was the most significant risk factor. Conclusions: A modified CRE prediction model developed using public health data and focused on prior healthcare exposures performed reasonably well when applied to a different academic healthcare system. The addition of variables accessible in large healthcare networks did not meaningfully improve model discrimination. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kathryn Willebrand, Jacqueline Fredrick, Lauren Pischel, Kavin Patel, Scott Roberts, Thomas Murray, Richard Martinello
Background: Recent evidence has shown that the updated COVID-19 bivalent booster is effective in preventing COVID-19 compared with no previous vaccination and prior monovalent vaccination. Despite its effectiveness, uptake has been poor, and a minority of eligible recipients have received the booster. Understanding healthcare worker (HCW) attitudes for and against voluntary uptake of the bivalent booster dose against COVID-19 can help guide communication strategy to maximize uptake. In this survey study, we investigated attitudes toward updated and/or bivalent booster uptake in a behavioral health hospital shortly after a COVID-19 outbreak. Methods: A survey tool was developed and sent to all HCWs at the Yale New Haven Psychiatric Hospital in December 2022. The survey queried demographic data, job category, history of COVID-19, prior COVID-19 vaccinations, perception of COVID-19 exposure, and updated and/or bivalent booster doses. The survey was administered several weeks after a COVID-19 outbreak on multiple inpatient behavioral health units. Receipt of the COVID-19 primary vaccination series and the first booster dose were mandated for HCWs; however, receipt of the bivalent booster was voluntary. Results: The survey was sent to 664 HCWs with primary assignments in behavioral health settings. In total, 182 (27.4%) provided complete responses to the survey and are included in these data. Moreover, 91 HCWs (50.0%) reported previously having COVID-19 at least once. Overall, 100 HCWs (55.0%) received the bivalent booster. The most identified reasons for receiving the bivalent booster were wanting to protect family and friends (n = 113), importance of staying healthy (n = 112), and protecting colleagues and patients (n = 103). The most identified reasons for not wanting to receive the bivalent booster dose were not thinking it provides additional protection (n = 33), “too many” shots already received (n = 31), and concern about side effects (n = 30). Discussion: Bivalent booster dose uptake in HCWs on behavioral health units shortly after a COVID-19 outbreak was greater than the general population. HCWs reported varying reasons for and against receipt of the bivalent booster dose, with the most common being protection of family and friends and perceptions of no additional protection, respectively. A limitation of this study was voluntary response bias, in which results are biased toward individuals more likely to receive a bivalent booster vaccine. It is unclear whether reasons for declining the vaccine are representative of HCWs who did not complete the survey. Assessing attitudes for the bivalent booster dose can assist in guiding communication and outreach strategies to increase vaccine uptake by HCWs. Disclosures: None
{"title":"Characterizing healthcare worker attitudes toward the bivalent COVID-19 booster","authors":"Kathryn Willebrand, Jacqueline Fredrick, Lauren Pischel, Kavin Patel, Scott Roberts, Thomas Murray, Richard Martinello","doi":"10.1017/ash.2023.300","DOIUrl":"https://doi.org/10.1017/ash.2023.300","url":null,"abstract":"Background: Recent evidence has shown that the updated COVID-19 bivalent booster is effective in preventing COVID-19 compared with no previous vaccination and prior monovalent vaccination. Despite its effectiveness, uptake has been poor, and a minority of eligible recipients have received the booster. Understanding healthcare worker (HCW) attitudes for and against voluntary uptake of the bivalent booster dose against COVID-19 can help guide communication strategy to maximize uptake. In this survey study, we investigated attitudes toward updated and/or bivalent booster uptake in a behavioral health hospital shortly after a COVID-19 outbreak. Methods: A survey tool was developed and sent to all HCWs at the Yale New Haven Psychiatric Hospital in December 2022. The survey queried demographic data, job category, history of COVID-19, prior COVID-19 vaccinations, perception of COVID-19 exposure, and updated and/or bivalent booster doses. The survey was administered several weeks after a COVID-19 outbreak on multiple inpatient behavioral health units. Receipt of the COVID-19 primary vaccination series and the first booster dose were mandated for HCWs; however, receipt of the bivalent booster was voluntary. Results: The survey was sent to 664 HCWs with primary assignments in behavioral health settings. In total, 182 (27.4%) provided complete responses to the survey and are included in these data. Moreover, 91 HCWs (50.0%) reported previously having COVID-19 at least once. Overall, 100 HCWs (55.0%) received the bivalent booster. The most identified reasons for receiving the bivalent booster were wanting to protect family and friends (n = 113), importance of staying healthy (n = 112), and protecting colleagues and patients (n = 103). The most identified reasons for not wanting to receive the bivalent booster dose were not thinking it provides additional protection (n = 33), “too many” shots already received (n = 31), and concern about side effects (n = 30). Discussion: Bivalent booster dose uptake in HCWs on behavioral health units shortly after a COVID-19 outbreak was greater than the general population. HCWs reported varying reasons for and against receipt of the bivalent booster dose, with the most common being protection of family and friends and perceptions of no additional protection, respectively. A limitation of this study was voluntary response bias, in which results are biased toward individuals more likely to receive a bivalent booster vaccine. It is unclear whether reasons for declining the vaccine are representative of HCWs who did not complete the survey. Assessing attitudes for the bivalent booster dose can assist in guiding communication and outreach strategies to increase vaccine uptake by HCWs. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anthony Abustan, Unarose Hogan, Julie Winn, Paul Pagaran, Joan Littlefield, Ted Miles
Background: Globally, the 30-day cumulative incidence of surgical-site infections (SSI) was 11% (95% CI, 10%–13%) based on the systematic review and meta-analysis derived from 57 studies. SSIs are poorly studied in the Philippines. Americares and its hospital partner, Camarines Norte Provincial Hospital, Philippines, sought to reduce SSIs through (1) establishing SSI surveillance in the hospitals’ surgical departments, (2) implementing quality improvement processes, and (3) developing and implementing an SSI prevention care bundle. Methods: A quality improvement methodology was used to introduce SSI surveillance and care-bundle checklist in partnership with Americares. Using paired t tests, pre- and posttest scores of the SSI care bundle training were analyzed. SSI surveillance was established based on the adapted CDC criteria. All clean surgeries were monitored except orthopedic surgeries. The number of surgeries performed, monitored, and SSIs identified were documented using the surveillance forms and plotted using Microsoft Excel software. A care bundle based on WHO evidence-based interventions for SSI prevention was designed and implemented. Compliance with the SSI care bundle was documented using Microsoft Excel. The relationship between the use of a care bundle and SSIs was analyzed using the Pearson correlation coefficient. Results: An online SSI care bundle training session was conducted. Overall, 150 participants had a mean pretraining test score of +6.46. After the training was conducted, the same participants had a mean posttraining test score of + 1.76). a statistically significant increase of 5.29 (95% CI). Thereby, the mean score difference after training showed that knowledge increased overall. These findings show an average of 90.43% compliance with the SSI care-bundle checklist over the 18-month window from May 2021 to November 2022. From a baseline of 0%, compliance increased from 80% upon its introduction in May 2021. Lastly, the SSI incidence rate from May 2021to November 2022 averaged 1.89%. The days between reported SSIs averaged 16.85. No baseline was available for comparison prior to the introduction of the surveillance and care bundle. A Pearson r data analysis (n = 1,850) was used to determine the relationship between the use of the care bundle and SSIs. The data illustrated a moderate negative correlation ( r = −.31). Therefore, higher care-bundle compliance yielded fewer SSI cases. Conclusions: The use of an evidence-based care bundle paired with a local quality improvement process significantly improved SSI prevention and surveillance. Future studies are needed that include clean-contaminated, contaminated, and dirty surgical cases to test the degree of SSI reduction possible. Disclosures: None
{"title":"Quality improvement approach for surgical-site infection prevention in a Philippine provincial hospital","authors":"Anthony Abustan, Unarose Hogan, Julie Winn, Paul Pagaran, Joan Littlefield, Ted Miles","doi":"10.1017/ash.2023.368","DOIUrl":"https://doi.org/10.1017/ash.2023.368","url":null,"abstract":"Background: Globally, the 30-day cumulative incidence of surgical-site infections (SSI) was 11% (95% CI, 10%–13%) based on the systematic review and meta-analysis derived from 57 studies. SSIs are poorly studied in the Philippines. Americares and its hospital partner, Camarines Norte Provincial Hospital, Philippines, sought to reduce SSIs through (1) establishing SSI surveillance in the hospitals’ surgical departments, (2) implementing quality improvement processes, and (3) developing and implementing an SSI prevention care bundle. Methods: A quality improvement methodology was used to introduce SSI surveillance and care-bundle checklist in partnership with Americares. Using paired t tests, pre- and posttest scores of the SSI care bundle training were analyzed. SSI surveillance was established based on the adapted CDC criteria. All clean surgeries were monitored except orthopedic surgeries. The number of surgeries performed, monitored, and SSIs identified were documented using the surveillance forms and plotted using Microsoft Excel software. A care bundle based on WHO evidence-based interventions for SSI prevention was designed and implemented. Compliance with the SSI care bundle was documented using Microsoft Excel. The relationship between the use of a care bundle and SSIs was analyzed using the Pearson correlation coefficient. Results: An online SSI care bundle training session was conducted. Overall, 150 participants had a mean pretraining test score of +6.46. After the training was conducted, the same participants had a mean posttraining test score of + 1.76). a statistically significant increase of 5.29 (95% CI). Thereby, the mean score difference after training showed that knowledge increased overall. These findings show an average of 90.43% compliance with the SSI care-bundle checklist over the 18-month window from May 2021 to November 2022. From a baseline of 0%, compliance increased from 80% upon its introduction in May 2021. Lastly, the SSI incidence rate from May 2021to November 2022 averaged 1.89%. The days between reported SSIs averaged 16.85. No baseline was available for comparison prior to the introduction of the surveillance and care bundle. A Pearson r data analysis (n = 1,850) was used to determine the relationship between the use of the care bundle and SSIs. The data illustrated a moderate negative correlation ( r = −.31). Therefore, higher care-bundle compliance yielded fewer SSI cases. Conclusions: The use of an evidence-based care bundle paired with a local quality improvement process significantly improved SSI prevention and surveillance. Future studies are needed that include clean-contaminated, contaminated, and dirty surgical cases to test the degree of SSI reduction possible. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alex Zimmet, David Ha, Emily Mui, Mary Smith, William Alegria, Marisa Holubar
Background: International Classification of Diseases, Tenth Edition (ICD-10) data help track outpatient antibiotic prescribing but lack validation in immunocompromised populations or subspecialty clinics for this purpose. Asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) are important stewardship targets in renal transplant (RT) patients, but they may require alternative metrics to best monitor prescribing patterns. We describe ICD-10 utilization for RT clinic encounters in which antibiotics were prescribed. We developed a metric classifying “acute urinary antibiotics” (AUA) to track antibiotic use for ASB and UTI, and we validated systematic identification of AUA to enable practical implementation. Methods: We examined RT clinic visit and telemedicine encounters from 2018 to 2021 conducted 1 month after transplant. This project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research. Results: The analytic cohort included 420 antibacterial prescriptions from 408 encounters (Fig. 1). Of 238 patients, 136 (57%) were male and 112 (47%) were Hispanic or Latino. The most common primary ICD-10 code was Z94.0 (kidney transplant status) (N = 302 of 408 encounters, 75%); 26 encounters (6%) were coded for UTI (eg, N39.0, urinary tract infection, site not specified); and 214 encounters (53%) had multiple ICD-10 codes. The R82.71 code (bacteriuria) was never used. However, 215 prescriptions (51%) were classified as AUA (Fig. 2). The validation cohort included 130 prescriptions; 59 (45%) were classified as AUA and 51 (39%) had documented intent to treat ASB or UTI (positive percent agreement, 83%; negative percent agreement, 97%) (Table 1). For patients >1 month after transplant, the positive percent agreement was 95% and the negative percent agreement was 98%. Of 51 patients receiving AUA, 32 (63%) were asymptomatic despite frequently having a code for UTI (Fig. 3). Conclusions: ICD-10 coding may not be helpful in monitoring antibiotic prescribing in RT patients. The AUA metric offers a practical alternative to track antibiotic prescribing for urinary syndromes and reliably correlates with physician intent. Monitoring AUA prescribing rates could help identify opportunities to optimize antibiotic use in this complex outpatient setting. Disclosures: None
{"title":"“Acute urinary antibiotics”—A simple metric to identify outpatient antibiotic stewardship opportunities in renal transplant","authors":"Alex Zimmet, David Ha, Emily Mui, Mary Smith, William Alegria, Marisa Holubar","doi":"10.1017/ash.2023.330","DOIUrl":"https://doi.org/10.1017/ash.2023.330","url":null,"abstract":"Background: International Classification of Diseases, Tenth Edition (ICD-10) data help track outpatient antibiotic prescribing but lack validation in immunocompromised populations or subspecialty clinics for this purpose. Asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) are important stewardship targets in renal transplant (RT) patients, but they may require alternative metrics to best monitor prescribing patterns. We describe ICD-10 utilization for RT clinic encounters in which antibiotics were prescribed. We developed a metric classifying “acute urinary antibiotics” (AUA) to track antibiotic use for ASB and UTI, and we validated systematic identification of AUA to enable practical implementation. Methods: We examined RT clinic visit and telemedicine encounters from 2018 to 2021 conducted 1 month after transplant. This project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research. Results: The analytic cohort included 420 antibacterial prescriptions from 408 encounters (Fig. 1). Of 238 patients, 136 (57%) were male and 112 (47%) were Hispanic or Latino. The most common primary ICD-10 code was Z94.0 (kidney transplant status) (N = 302 of 408 encounters, 75%); 26 encounters (6%) were coded for UTI (eg, N39.0, urinary tract infection, site not specified); and 214 encounters (53%) had multiple ICD-10 codes. The R82.71 code (bacteriuria) was never used. However, 215 prescriptions (51%) were classified as AUA (Fig. 2). The validation cohort included 130 prescriptions; 59 (45%) were classified as AUA and 51 (39%) had documented intent to treat ASB or UTI (positive percent agreement, 83%; negative percent agreement, 97%) (Table 1). For patients >1 month after transplant, the positive percent agreement was 95% and the negative percent agreement was 98%. Of 51 patients receiving AUA, 32 (63%) were asymptomatic despite frequently having a code for UTI (Fig. 3). Conclusions: ICD-10 coding may not be helpful in monitoring antibiotic prescribing in RT patients. The AUA metric offers a practical alternative to track antibiotic prescribing for urinary syndromes and reliably correlates with physician intent. Monitoring AUA prescribing rates could help identify opportunities to optimize antibiotic use in this complex outpatient setting. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Miranda Monk, Sarah Turbett, Christine Yang, Ramy Elshaboury
Background: Multidrug-resistant bacteria are of high concern, and empiric antimicrobial choice for infections caused by these pathogens, while awaiting susceptibilities, is increasingly encountered. We describe the susceptibility patterns of ceftazidime-avibactam (CZA), imipenem-rel-ebactam (I-R), meropenem-vaborbactam (MVB), cefiderocol (FDC), ceftolozone-tazobactam (C/T), minocycline (MIN), and tigecycline (TGC) for carbapenem-resistant Enterobacterales at an academic medical center. Methods: We performed a single-center analysis of Enterobacterales isolates from 110 hospitalized adult patients who had CZA, I-R, MVB, FDC, MIN, or TGC susceptibility testing performed between October 2020 and September 2022. The study included 1 isolate per patient per infection site per year. Isolates were divided into carbapenem susceptible and non susceptible categories. For carbapenem nonsusceptible isolates, phenotypic confirmatory testing of carbapenem nonsusceptibility was performed using disk diffusion, gradient diffusion, and/or broth microdilution. Interpretive categories were applied using CLSI- or FDA-approved break-points where applicable. Carbapenemase testing was also performed using the modified carbapenem inactivation method (mCIM) and, where applicable, this testing was confirmed at the Massachusetts State Public Health Laboratory using genotypic methods. Results: In total, 125 unique isolates were reviewed: 34 meropenem-susceptible and 91 meropenem-intermediate or resistant isolates. CZA, I-R, MVB, and FDC were active against all tested meropenem-susceptible isolates; however, 50% of tested isolates were susceptible to C/T. MIN and TGC, when tested, were active against 2 of 11 isolates (18%) and 14 of 16 isolates (86%), respectively. Of 91 meropenem-nonsusceptible isolates, most tested isolates were susceptible to MVB (59 of 72, 82%), followed by CZA (63 of 82, 77%), I-R (8 of 11, 73%), FDC (9 of 16, 56%), and C/T (1 of 12, 8%). TGC retained activity against 78 of 81 (96%) tested isolates. In contrast, MIN retained activity against 8 of 45 isolates (18%). Additionally, all (28 of 28, 100%) isolates that were nonsusceptible to at least 1 novel agent (CZA, I-R, MVB, FDC, or C/T) remained susceptible to TGC. State laboratory confirmatory testing was available for 75 isolates. Of 43 mCIM-positive isolates, all 28 KPC-producing isolates were susceptible to CZA, I-R, MVB, FDC and TGC. Conclusions: Among Enterobacterales, CZA, MVB, and I-R retained activity against most non-NDM CRE isolates in this local analysis, with comparable susceptibilities. TGC demonstrated excellent susceptibility for CRE and meropenem-susceptible isolates, offering an alternative for nonbloodstream infections. Choice of empiric agent with a newβ-lactam, β-lactam–β-lactamase inhibitors, or TGC appear to be reasonable empiric therapeutic options at our institution. CT and MIN warrant confirmatory testing prior to use due to low susceptibility rates among meropenem nonsusceptibl
{"title":"Carbapenem-resistant Enterobacterales susceptibility patterns to new antimicrobials: A single-center analysis","authors":"Miranda Monk, Sarah Turbett, Christine Yang, Ramy Elshaboury","doi":"10.1017/ash.2023.337","DOIUrl":"https://doi.org/10.1017/ash.2023.337","url":null,"abstract":"Background: Multidrug-resistant bacteria are of high concern, and empiric antimicrobial choice for infections caused by these pathogens, while awaiting susceptibilities, is increasingly encountered. We describe the susceptibility patterns of ceftazidime-avibactam (CZA), imipenem-rel-ebactam (I-R), meropenem-vaborbactam (MVB), cefiderocol (FDC), ceftolozone-tazobactam (C/T), minocycline (MIN), and tigecycline (TGC) for carbapenem-resistant Enterobacterales at an academic medical center. Methods: We performed a single-center analysis of Enterobacterales isolates from 110 hospitalized adult patients who had CZA, I-R, MVB, FDC, MIN, or TGC susceptibility testing performed between October 2020 and September 2022. The study included 1 isolate per patient per infection site per year. Isolates were divided into carbapenem susceptible and non susceptible categories. For carbapenem nonsusceptible isolates, phenotypic confirmatory testing of carbapenem nonsusceptibility was performed using disk diffusion, gradient diffusion, and/or broth microdilution. Interpretive categories were applied using CLSI- or FDA-approved break-points where applicable. Carbapenemase testing was also performed using the modified carbapenem inactivation method (mCIM) and, where applicable, this testing was confirmed at the Massachusetts State Public Health Laboratory using genotypic methods. Results: In total, 125 unique isolates were reviewed: 34 meropenem-susceptible and 91 meropenem-intermediate or resistant isolates. CZA, I-R, MVB, and FDC were active against all tested meropenem-susceptible isolates; however, 50% of tested isolates were susceptible to C/T. MIN and TGC, when tested, were active against 2 of 11 isolates (18%) and 14 of 16 isolates (86%), respectively. Of 91 meropenem-nonsusceptible isolates, most tested isolates were susceptible to MVB (59 of 72, 82%), followed by CZA (63 of 82, 77%), I-R (8 of 11, 73%), FDC (9 of 16, 56%), and C/T (1 of 12, 8%). TGC retained activity against 78 of 81 (96%) tested isolates. In contrast, MIN retained activity against 8 of 45 isolates (18%). Additionally, all (28 of 28, 100%) isolates that were nonsusceptible to at least 1 novel agent (CZA, I-R, MVB, FDC, or C/T) remained susceptible to TGC. State laboratory confirmatory testing was available for 75 isolates. Of 43 mCIM-positive isolates, all 28 KPC-producing isolates were susceptible to CZA, I-R, MVB, FDC and TGC. Conclusions: Among Enterobacterales, CZA, MVB, and I-R retained activity against most non-NDM CRE isolates in this local analysis, with comparable susceptibilities. TGC demonstrated excellent susceptibility for CRE and meropenem-susceptible isolates, offering an alternative for nonbloodstream infections. Choice of empiric agent with a newβ-lactam, β-lactam–β-lactamase inhibitors, or TGC appear to be reasonable empiric therapeutic options at our institution. CT and MIN warrant confirmatory testing prior to use due to low susceptibility rates among meropenem nonsusceptibl","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: The CDC’s new Public Health Strategies to Prevent the Spread of Novel and Targeted Multidrug-Resistant Organisms (MDROs) were informed by mathematical models that assessed the impact of implementing preventive strategies directed at a subset of healthcare facilities characterized as influential or highly connected based on their predicted role in the regional spread of MDROs. We developed an interactive tool to communicate mathematical modeling results and visualize the regional patient transfer network for public health departments and healthcare facilities to assist in planning and implementing prevention strategies. Methods: An interactive RShiny application is currently hosted in the CDC network and is accessible to external partners through the Secure Access Management Services (SAMS). Patient transfer volumes (direct and indirect, that is, with up to 30 days in the community between admissions) were estimated from the CMS fee-for-service claims data from 2019. The spread of a carbapenem-resistant Enterobacterales (CRE)–like MDROs within a US state was simulated using a deterministic model with susceptible and infectious compartments in the community and healthcare facilities interconnected through patient transfers. Individuals determined to be infectious through admission screening, point-prevalence surveys (PPSs), or notified from interfacility communication were assigned lower transmissibility if enhanced infection prevention and control practices were in place at a facility. Results: The application consists of 4 interactive tabs. Users can visualize the statewide patient-sharing network for any US state and select territories in the first tab (Fig. 1). A feature allows users to highlight a facility of interest and display downstream or upstream facilities that received or sent transfers from the facility of interest, respectively. A second tab lists influential facilities to aid in prioritizing screening and prevention activities. A third tab lists all facilities in the state in descending order of their dispersal rate (ie, the rate at which patients are shared downstream to other facilities), which can help identify highly connected facilities. In the fourth tab, an interactive graph displays the predicted reduction of MDRO prevalence given a range of intervention scenarios (Fig. 2). Conclusions: Our RShiny application, which can be accessed by public health partners, can assist healthcare facilities and public health departments in planning and tailoring MDRO prevention activity bundles. Disclosures: None
{"title":"An interactive patient transfer network and model visualization tool for multidrug-resistant organism prevention strategies","authors":"Rany Octaria, Samuel Cincotta, Jessica Healy, Camden Gowler, Prabasaj Paul, Maroya Walters, Rachel Slayton","doi":"10.1017/ash.2023.403","DOIUrl":"https://doi.org/10.1017/ash.2023.403","url":null,"abstract":"Background: The CDC’s new Public Health Strategies to Prevent the Spread of Novel and Targeted Multidrug-Resistant Organisms (MDROs) were informed by mathematical models that assessed the impact of implementing preventive strategies directed at a subset of healthcare facilities characterized as influential or highly connected based on their predicted role in the regional spread of MDROs. We developed an interactive tool to communicate mathematical modeling results and visualize the regional patient transfer network for public health departments and healthcare facilities to assist in planning and implementing prevention strategies. Methods: An interactive RShiny application is currently hosted in the CDC network and is accessible to external partners through the Secure Access Management Services (SAMS). Patient transfer volumes (direct and indirect, that is, with up to 30 days in the community between admissions) were estimated from the CMS fee-for-service claims data from 2019. The spread of a carbapenem-resistant Enterobacterales (CRE)–like MDROs within a US state was simulated using a deterministic model with susceptible and infectious compartments in the community and healthcare facilities interconnected through patient transfers. Individuals determined to be infectious through admission screening, point-prevalence surveys (PPSs), or notified from interfacility communication were assigned lower transmissibility if enhanced infection prevention and control practices were in place at a facility. Results: The application consists of 4 interactive tabs. Users can visualize the statewide patient-sharing network for any US state and select territories in the first tab (Fig. 1). A feature allows users to highlight a facility of interest and display downstream or upstream facilities that received or sent transfers from the facility of interest, respectively. A second tab lists influential facilities to aid in prioritizing screening and prevention activities. A third tab lists all facilities in the state in descending order of their dispersal rate (ie, the rate at which patients are shared downstream to other facilities), which can help identify highly connected facilities. In the fourth tab, an interactive graph displays the predicted reduction of MDRO prevalence given a range of intervention scenarios (Fig. 2). Conclusions: Our RShiny application, which can be accessed by public health partners, can assist healthcare facilities and public health departments in planning and tailoring MDRO prevention activity bundles. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hannah Wolford, Brandon Attell, James Baggs, Sujan Reddy, Sarah Kabbani, Melinda Neuhauser, Lauri Hicks
Background: Community-acquired pneumonia (CAP) is a common indication for antibiotic prescribing in hospitalized patients. Professional societies’ clinical guidelines recommend specific antibiotics for empiric treatment of CAP based on clinical factors. Manual assessments of appropriateness are time-consuming and are often conducted on a smaller scale. We evaluated empiric antibiotic selection among a large cohort of adults hospitalized with CAP using electronic health records. Methods: In this study, we used the PINC-AI healthcare database to define a cohort of adults hospitalized with CAP from 2013 to 2020. CAP was identified by International Classification of Diseases (ICD) diagnosis codes. Exclusions were applied to identify uncomplicated CAP (Fig. 1). Treatment was only evaluated if a chest radiograph or computerized tomography (CT) scan was charged during the first 2 days of hospitalization, otherwise it was considered an inadequate CAP evaluation. Administrative billing data were used to identify antibiotics charged within the first 2 days of hospitalization. Empiric guideline-recommended treatment was determined based on 2019 CAP guidelines and more recent studies. Patients who received nonrecommended treatment were evaluated for antibiotic allergies in the current hospitalization or methicillin-resistant Staphylococcus aureus (MRSA) colonization or infection in the year prior or on admission using International Classification of Disease, Tenth Revision (ICD-10) diagnosis codes. Results: We identified 4.47 million adult hospitalizations with CAP from 2013 to 2020; 32% (1.43 million) were included in this analysis (Fig. 1). Among discharges with adequate CAP evaluation (1.37 million), 59.7% received recommended antibiotics in the first 2 days of hospitalization, ranging from 62.6% in 2013 to 57.5% in 2019. Overall, 34.8% of our study population received a nonrecommended antibiotic without documentation of an antibiotic allergy or MRSA colonization (2013: 32.5%; 2018: 36.7%) (Fig. 2). Most patients in our study population received >1 antibiotic (92.3%) in the first 2 days of hospitalization. The most common antibiotics among patients receiving recommended treatment were ceftriaxone (74.2% of patients receiving recommended treatment), azithromycin (67.2%), and levofloxacin (31.8%) (Fig. 3a). The most common nonrecommended antibiotics were vancomycin (57.2% of patients receiving nonrecommended treatment), piperacillin-tazobactam (48.1%), and cefepime (25.7%) (Fig. 3b). From 2013 to 2020, cefepime charges consistently increased among CAP patients treated with nonrecommended antibiotics, whereas levofloxacin charges consistently decreased among CAP patients treated with only recommended antibiotics. Conclusions: Approximately one-third of patients with uncomplicated CAP received nonrecommended empiric antibiotics, and from 2013 to 2020 that proportion increased by 9%. Additional strategies are needed to help identify opportunities to optimiz
{"title":"Empiric antibiotic selection for community-acquired pneumonia in US hospitals, 2013–2020","authors":"Hannah Wolford, Brandon Attell, James Baggs, Sujan Reddy, Sarah Kabbani, Melinda Neuhauser, Lauri Hicks","doi":"10.1017/ash.2023.249","DOIUrl":"https://doi.org/10.1017/ash.2023.249","url":null,"abstract":"Background: Community-acquired pneumonia (CAP) is a common indication for antibiotic prescribing in hospitalized patients. Professional societies’ clinical guidelines recommend specific antibiotics for empiric treatment of CAP based on clinical factors. Manual assessments of appropriateness are time-consuming and are often conducted on a smaller scale. We evaluated empiric antibiotic selection among a large cohort of adults hospitalized with CAP using electronic health records. Methods: In this study, we used the PINC-AI healthcare database to define a cohort of adults hospitalized with CAP from 2013 to 2020. CAP was identified by International Classification of Diseases (ICD) diagnosis codes. Exclusions were applied to identify uncomplicated CAP (Fig. 1). Treatment was only evaluated if a chest radiograph or computerized tomography (CT) scan was charged during the first 2 days of hospitalization, otherwise it was considered an inadequate CAP evaluation. Administrative billing data were used to identify antibiotics charged within the first 2 days of hospitalization. Empiric guideline-recommended treatment was determined based on 2019 CAP guidelines and more recent studies. Patients who received nonrecommended treatment were evaluated for antibiotic allergies in the current hospitalization or methicillin-resistant Staphylococcus aureus (MRSA) colonization or infection in the year prior or on admission using International Classification of Disease, Tenth Revision (ICD-10) diagnosis codes. Results: We identified 4.47 million adult hospitalizations with CAP from 2013 to 2020; 32% (1.43 million) were included in this analysis (Fig. 1). Among discharges with adequate CAP evaluation (1.37 million), 59.7% received recommended antibiotics in the first 2 days of hospitalization, ranging from 62.6% in 2013 to 57.5% in 2019. Overall, 34.8% of our study population received a nonrecommended antibiotic without documentation of an antibiotic allergy or MRSA colonization (2013: 32.5%; 2018: 36.7%) (Fig. 2). Most patients in our study population received >1 antibiotic (92.3%) in the first 2 days of hospitalization. The most common antibiotics among patients receiving recommended treatment were ceftriaxone (74.2% of patients receiving recommended treatment), azithromycin (67.2%), and levofloxacin (31.8%) (Fig. 3a). The most common nonrecommended antibiotics were vancomycin (57.2% of patients receiving nonrecommended treatment), piperacillin-tazobactam (48.1%), and cefepime (25.7%) (Fig. 3b). From 2013 to 2020, cefepime charges consistently increased among CAP patients treated with nonrecommended antibiotics, whereas levofloxacin charges consistently decreased among CAP patients treated with only recommended antibiotics. Conclusions: Approximately one-third of patients with uncomplicated CAP received nonrecommended empiric antibiotics, and from 2013 to 2020 that proportion increased by 9%. Additional strategies are needed to help identify opportunities to optimiz","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jennifer Sanguinet, Gerard Marshall, Julia Moody, Kenneth Sands
Background: Candida auris is an emerging pathogen that exhibits broad antimicrobial resistance and causes highly morbid infections. Prolonged survival on surfaces has been demonstrated, and standard disinfectants may not achieve adequate disinfection. Persistent patient colonization and constant environmental recontamination poses an infection risk that may be mitigated by no touch disinfection systems. We evaluated the efficacy of continuous dry hydrogen peroxide (DHP) exposure on C. auris environmental contamination. Methods: The study was conducted in a large tertiary-care center where multiple patients were identified as either infected or colonized with C. auris . DHP-emitting systems were installed in the ventilation systems dedicated to the adult burn intensive care and children’s cardiac intensive care units. Composite surface samples were collected in a sample of patient rooms and shared clinical workspaces among units with current C. auris patients, before and after installation of the DHP system, and from areas with and without exposure to DHP. The samples included “high touch” surfaces near the patient, the general area of the patient room, shared medical equipment for the unit, shared staff work areas, and equipment dedicated to individual staff members (Table 1). Presence of C. auris was determined by polymerase chain reaction (PCR). Association between DHP exposure and C. auris contamination was determined using the Fisher exact test. Results: In the presence of C. auris patients, 5 baseline samples per unit were taken before DHP was installed, and then 5 samples per unit were taken on days 7, 14, and 28 after installation. Prior to initiation of DHP, 7 (70%) of 10 samples were PCR positive for C. auris . After DHP installation, a statistically significant decrease to 5 (16.7%) of 30 samples ( P <.05) was observed. In total, 20 samples (5 before installation and 15 after installation) were collected from units without DHP on the same days. At baseline, 2 (40%) of 5 samples were PCR positive for C. auris . During subsequent periods, 4 (27%) 15 samples were positive ( P = .66). No adverse effects were reported by patients, visitors, or personnel in association with the operation of the DHP systems. Conclusions: These findings suggest that DHP is effective in reducing surface C. auris contamination in a variety of patient and healthcare worker surfaces. Disclosures: None
{"title":"Effect of dry hydrogen peroxide on <i>Candida auris</i> environmental contamination","authors":"Jennifer Sanguinet, Gerard Marshall, Julia Moody, Kenneth Sands","doi":"10.1017/ash.2023.316","DOIUrl":"https://doi.org/10.1017/ash.2023.316","url":null,"abstract":"Background: Candida auris is an emerging pathogen that exhibits broad antimicrobial resistance and causes highly morbid infections. Prolonged survival on surfaces has been demonstrated, and standard disinfectants may not achieve adequate disinfection. Persistent patient colonization and constant environmental recontamination poses an infection risk that may be mitigated by no touch disinfection systems. We evaluated the efficacy of continuous dry hydrogen peroxide (DHP) exposure on C. auris environmental contamination. Methods: The study was conducted in a large tertiary-care center where multiple patients were identified as either infected or colonized with C. auris . DHP-emitting systems were installed in the ventilation systems dedicated to the adult burn intensive care and children’s cardiac intensive care units. Composite surface samples were collected in a sample of patient rooms and shared clinical workspaces among units with current C. auris patients, before and after installation of the DHP system, and from areas with and without exposure to DHP. The samples included “high touch” surfaces near the patient, the general area of the patient room, shared medical equipment for the unit, shared staff work areas, and equipment dedicated to individual staff members (Table 1). Presence of C. auris was determined by polymerase chain reaction (PCR). Association between DHP exposure and C. auris contamination was determined using the Fisher exact test. Results: In the presence of C. auris patients, 5 baseline samples per unit were taken before DHP was installed, and then 5 samples per unit were taken on days 7, 14, and 28 after installation. Prior to initiation of DHP, 7 (70%) of 10 samples were PCR positive for C. auris . After DHP installation, a statistically significant decrease to 5 (16.7%) of 30 samples ( P <.05) was observed. In total, 20 samples (5 before installation and 15 after installation) were collected from units without DHP on the same days. At baseline, 2 (40%) of 5 samples were PCR positive for C. auris . During subsequent periods, 4 (27%) 15 samples were positive ( P = .66). No adverse effects were reported by patients, visitors, or personnel in association with the operation of the DHP systems. Conclusions: These findings suggest that DHP is effective in reducing surface C. auris contamination in a variety of patient and healthcare worker surfaces. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ian Hennessee, Kaitlin Forsberg, Susan E. Beekmann, Philip Polgreen, Jeremy Gold, Meghan Lyman
Background: Candida auris , an emerging fungal pathogen, is frequently drug resistant and spreads rapidly in healthcare facilities. Screening to identify patients colonized with C. auris can prevent further spread by prompting aggressive infection prevention and control measures. The CDC recommends C. auris screening based on local epidemiological conditions, patient characteristics, and facility-level risk factors; such screening might help facilities in higher burden areas to mitigate transmission and those in lower-burden areas to detect new introductions before spread begins. To describe US screening practices and challenges, we surveyed a network of infection disease practitioners, comparing responses by local C. auris case burdens. Methods: In August 2022, we emailed a survey about C. auris screening practices to ~3,000 members of the IDSA Emerging Infection Network. We describe survey results, stratifying findings by whether the healthcare facility was in a region where C. auris is frequently identified (tier 3 facility) or not frequently identified (tier 2 facility), based on CDC assessment using existing multidrug-resistant organism containment guidance (https://www.cdc.gov/hai/containment/guidelines.html). Results: We received 253 responses (tier 3 facilities: 119, tier 2 facilities: 134); overall, 37% performed screening. Tier 3 facilities more frequently performed screening than tier 2 facilities (59% vs 17%). Among facilities that performed screening, tier 3 facilities, compared with tier 2 facilities, more frequently screened patients on admission (84% vs 55%) and used an in-house laboratory for testing (68% vs 29%), most often with culture-based methods. Tier 2 facilities more frequently screened patients already admitted in the facility (eg, in response to cases or as part of point-prevalence surveys) compared with tier 3 facilities (59% vs 49%). Among facilities performing screening, 72% had identified ≥1 case in the previous year (tier 3 facilities, 85%; tier 2 facilities, 33%). Barriers to screening included limited laboratory capacity, long testing turnaround times, and the perception that screening was not useful. Conclusions: Most facilities surveyed did not perform C. auris screening. However, most facilities that performed screening, including those in regions of higher and lower C. auris burden, detected cases during the previous year. Admission screening, which might help detect new introductions before spread begins, was uncommon in facilities in lower-burden areas. Improving ease of C. auris screening through access to in-house laboratory testing with rapid turnaround times might increase the adoption of C. auris screening by facilities, thereby increasing detection and preventing spread. Disclosures: None
{"title":"<i>Candida auris</i> screening practices at healthcare facilities in the United States: A survey of the Emerging Infections Network","authors":"Ian Hennessee, Kaitlin Forsberg, Susan E. Beekmann, Philip Polgreen, Jeremy Gold, Meghan Lyman","doi":"10.1017/ash.2023.371","DOIUrl":"https://doi.org/10.1017/ash.2023.371","url":null,"abstract":"Background: Candida auris , an emerging fungal pathogen, is frequently drug resistant and spreads rapidly in healthcare facilities. Screening to identify patients colonized with C. auris can prevent further spread by prompting aggressive infection prevention and control measures. The CDC recommends C. auris screening based on local epidemiological conditions, patient characteristics, and facility-level risk factors; such screening might help facilities in higher burden areas to mitigate transmission and those in lower-burden areas to detect new introductions before spread begins. To describe US screening practices and challenges, we surveyed a network of infection disease practitioners, comparing responses by local C. auris case burdens. Methods: In August 2022, we emailed a survey about C. auris screening practices to ~3,000 members of the IDSA Emerging Infection Network. We describe survey results, stratifying findings by whether the healthcare facility was in a region where C. auris is frequently identified (tier 3 facility) or not frequently identified (tier 2 facility), based on CDC assessment using existing multidrug-resistant organism containment guidance (https://www.cdc.gov/hai/containment/guidelines.html). Results: We received 253 responses (tier 3 facilities: 119, tier 2 facilities: 134); overall, 37% performed screening. Tier 3 facilities more frequently performed screening than tier 2 facilities (59% vs 17%). Among facilities that performed screening, tier 3 facilities, compared with tier 2 facilities, more frequently screened patients on admission (84% vs 55%) and used an in-house laboratory for testing (68% vs 29%), most often with culture-based methods. Tier 2 facilities more frequently screened patients already admitted in the facility (eg, in response to cases or as part of point-prevalence surveys) compared with tier 3 facilities (59% vs 49%). Among facilities performing screening, 72% had identified ≥1 case in the previous year (tier 3 facilities, 85%; tier 2 facilities, 33%). Barriers to screening included limited laboratory capacity, long testing turnaround times, and the perception that screening was not useful. Conclusions: Most facilities surveyed did not perform C. auris screening. However, most facilities that performed screening, including those in regions of higher and lower C. auris burden, detected cases during the previous year. Admission screening, which might help detect new introductions before spread begins, was uncommon in facilities in lower-burden areas. Improving ease of C. auris screening through access to in-house laboratory testing with rapid turnaround times might increase the adoption of C. auris screening by facilities, thereby increasing detection and preventing spread. Disclosures: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: A sustainable, continuous supply of alcohol-based hand rub (ABHR) is essential for healthcare workers in health facilities. The WHO provides guidance for production in individual health facilities. In Uganda, using this guidance, an innovative approach was implemented at the district local government level to produce and subsequently distribute ABHR to primary-care health facilities that have limited capacity for local facility-level production. This project was supported by the CDC in collaboration with the Infectious Diseases Institute (IDI) and targeted governmental or district engagement with local partners to ensure sustainability. Methods: District stakeholders were engaged to obtain buy-in and define roles and responsibilities. Overall, 4 staff members in each of 6 supported districts were nominated by District Health Officers for training: 2 staff members were trained to produce ABHR and conduct internal quality control and 2 were trained on external quality control. Districts provided ABHR production-unit facilities and facilitated integration within the government essential supplies delivery system, National Medical Stores in Uganda, which supports last-mile delivery to facilities. An implementing partner purchased initial raw materials necessary for production. The cost of materials for local production was compared to the price of commercial ABHR available in Uganda. Results: Between January and August 2021, 23 staff members were trained, and 380 batches of quality-assured ABHR (17,820 L) were produced and distributed to 278 health facilities. Consumption of ABHR in the first distribution was used to benchmark predicted ABHR consumption per targeted facility in subsequent months. Increased demand for ABHR due to the COVID-19 pandemic and the Ebola virus disease outbreak in central Uganda (September 2022) was addressed through emergency requests on a case-by-case basis. ABHR local production costs $3 per liter for materials, less than half of commercial ABHR ($8 per liter). Conclusions: Early results suggest that this approach is potentially sustainable but requires national advocacy as well. Leveraging existing distribution systems while building local capacity for ABHR production and distribution may improve longevity of such innovations in similar resource-limited settings. Disclosure: None
{"title":"Approach for sustainable district-led production and distribution of alcohol-based hand rub in Uganda","authors":"Maureen Kesande","doi":"10.1017/ash.2023.224","DOIUrl":"https://doi.org/10.1017/ash.2023.224","url":null,"abstract":"Background: A sustainable, continuous supply of alcohol-based hand rub (ABHR) is essential for healthcare workers in health facilities. The WHO provides guidance for production in individual health facilities. In Uganda, using this guidance, an innovative approach was implemented at the district local government level to produce and subsequently distribute ABHR to primary-care health facilities that have limited capacity for local facility-level production. This project was supported by the CDC in collaboration with the Infectious Diseases Institute (IDI) and targeted governmental or district engagement with local partners to ensure sustainability. Methods: District stakeholders were engaged to obtain buy-in and define roles and responsibilities. Overall, 4 staff members in each of 6 supported districts were nominated by District Health Officers for training: 2 staff members were trained to produce ABHR and conduct internal quality control and 2 were trained on external quality control. Districts provided ABHR production-unit facilities and facilitated integration within the government essential supplies delivery system, National Medical Stores in Uganda, which supports last-mile delivery to facilities. An implementing partner purchased initial raw materials necessary for production. The cost of materials for local production was compared to the price of commercial ABHR available in Uganda. Results: Between January and August 2021, 23 staff members were trained, and 380 batches of quality-assured ABHR (17,820 L) were produced and distributed to 278 health facilities. Consumption of ABHR in the first distribution was used to benchmark predicted ABHR consumption per targeted facility in subsequent months. Increased demand for ABHR due to the COVID-19 pandemic and the Ebola virus disease outbreak in central Uganda (September 2022) was addressed through emergency requests on a case-by-case basis. ABHR local production costs $3 per liter for materials, less than half of commercial ABHR ($8 per liter). Conclusions: Early results suggest that this approach is potentially sustainable but requires national advocacy as well. Leveraging existing distribution systems while building local capacity for ABHR production and distribution may improve longevity of such innovations in similar resource-limited settings. Disclosure: None","PeriodicalId":7953,"journal":{"name":"Antimicrobial Stewardship & Healthcare Epidemiology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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