scholarly journals 1019. Defining electronic patient phenotypes to inform risk-adjustment strategies in hospital antimicrobial use comparisons

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S359-S359
Author(s):  
Rebekah W Moehring ◽  
Matthew Phelan ◽  
Eric Lofgren ◽  
Alicia Nelson ◽  
Melinda M Neuhauser ◽  
...  
Keyword(s):  
Risk Adjustment ◽  
Diagnosis Related Groups ◽  
Patient Characteristics ◽  
Antibiotic Use ◽  
Low Risk ◽  
Antimicrobial Use ◽  
Cell Transplant ◽  
Lengths Of Stay ◽  
Days Of Therapy ◽  
Adjustment Factors

Abstract Background Comparison of antimicrobial use (AU) rates among hospitals can identify areas to intervene for antimicrobial stewardship. Hospital AU interpretation is difficult without risk-adjustment for patient mix. Identifying high- or low-risk patient characteristics, or “electronic phenotypes,” for receipt of antimicrobials using data from electronic health records (EHR) could help define risk-adjustment factors AU comparisons. Methods We performed a retrospective study of EHR-derived data from adult and pediatric inpatients within the Duke University Health System from October 2015 to September 2017. Encounters were included if the patient spent time in an inpatient location. The analysis aimed to identify subpopulations that were high- or low-risk for antimicrobial exposure based on EHR data summarized on the encounter level. Antimicrobial days of therapy (DOT) and days present, representing the length of stay (LOS), were defined as in the 2018 NHSN AU Option. Location exposures were defined in binary variables if patients were housed at least 1 day on a hospital unit type. We compared antimicrobial-exposed to unexposed patients as well as DOT among various factors including demographics, location, nonantimicrobial medications, labs, ICD-10 codes, and diagnosis-related groups (DRG). Results The EHR-derived dataset included 170,294 encounters and 204 variables in one academic and two community hospitals; 80,192 (47%) received at least one antimicrobial. Distributions of both LOS and DOT were zero-inflated and skewed by long outliers (figure). Encounters with >=7 DOT made up 63% of total DOT, but only 9% of inpatient encounters. Electronic phenotypes with highest DOT included those with long lengths of stay, older age, exposures to stem cell transplant, pulmonary, and critical care units, and DRG that included transplant, respiratory, or infectious diagnoses. Zero DOT phenotypes included those with short lengths of stay, exposure to labor and delivery wards, medical wards, and DRG that included birth and pregnancy. Conclusion Future work in defining risk-adjustment factors for hospital AU data comparisons should determine if factors associated with low- or high-risk electronic phenotypes assist in prediction of antibiotic use. Disclosures All authors: No reported disclosures.

scholarly journals 139. association of Physician Orders for Life-sustaining Treatment (POLST) with Antimicrobial Use at End of Life in Cancer Patients: An Antimicrobial Stewardship Opportunity

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S199-S200
Author(s):  
Olivia Kates ◽  
Elizabeth M Krantz ◽  
Juhye Lee ◽  
John Klaassen ◽  
Jessica Morris ◽  
...  
Keyword(s):  
End Of Life ◽  
Cancer Patients ◽  
Symptom Management ◽  
Research Study ◽  
Antibiotic Use ◽  
Antimicrobial Use ◽  
Study Investigator ◽  
Days Of Therapy ◽  
Life Sustaining Treatment ◽  
Rate Ratios

Abstract Background IDSA/SHEA guidelines recommend that antimicrobial stewardship programs support providers in antibiotic decisions for end of life care. Washington State Physician Orders for Life-Sustaining Treatment (POLST) forms allow patients to indicate antimicrobial use preferences. We sought to characterize antimicrobial use in the last 30 days of life for cancer patients by presence of a POLST and antimicrobial use preferences. Methods We performed a single-center, retrospective cohort study of cancer patient deaths from January 1, 2016 - June 30, 3018. Patient demographics, clinical characteristics, POLST, and antimicrobial use within 30 days before death were extracted from electronic records. To test for an association between POLST completed at least 30 days before death and inpatient antimicrobial days of therapy (DOT) in the 30 days before death, we used negative binomial models adjusted for age, sex, race, and service line (hematologic versus solid malignancy); model estimates are presented as incidence rate ratios (IRR) with 95% confidence intervals (CI) Results Of 1796 patients, 406 (23%) had a POLST. 177/406 (44%) were completed less than 30 days before death, and 58/177 (32.8%) specified limited antibiotic use; 40/177 (23%) did not specify any antimicrobial use preference (Fig 1). Of 1295 patients with at least 1 inpatient day in the 30 days before death, 1070 (83%) received at least 1 inpatient antimicrobial with median DOT of 1077 per 1000 inpatient days (Tab 1). There was no difference in DOT among patients with and without a POLST > /= 30 days before death (IRR 0.92, CI 0.77, 1.10). Patients with a POLST specifying limited antibiotic use had significantly lower inpatient IV antimicrobial DOT compared to those without a POLST (IRR 0.64, CI 0.42–0.97) (Fig 2). Figure 1. Classification of Patients by Presence of POLST, Timing, and Antimicrobial Preference Content of POLST. Numbers shown represent the number of patients (percentage). Full antibiotic use refers to the selection “Use antibiotics for prolongation of life.” Limited antibiotic use refers to the selection “Do not use antibiotics except when needed for symptom management.” Table 1: Antimicrobial use for all patients and by advance directive group Figure 2. Forest plot of model estimates, represented as incidence rate ratios (IRR) with 95% confidence intervals (CI), for associations between POLST antimicrobial specifications completed at least 30 days before death and inpatient antibiotic days of therapy (DOT) in the 30 days before death. Estimates represent comparisons between each POLST category and no POLST completed at least 30 days before death. Dots represent the IRR and brackets extend to the lower and upper limit of the 95% CI. Blue estimates are for the inpatient antibiotic DOT outcome and red estimates are for the inpatient IV antibiotic DOT outcome. Conclusion POLST completion is rare > /= 30 days before death, with few POLSTs specifying antimicrobial use. Compared to those with no POLST in this time frame, patients who indicated that antibiotics should be used only for symptom management received significantly fewer inpatient IV antimicrobials. Early discussion of advance directives including POLST with specification of antimicrobial use preferences may promote more thoughtful use of antimicrobials near the end of life in a compassionate, patient-centered way. Disclosures Steven A. Pergam, MD, MPH, Chimerix, Inc (Scientific Research Study Investigator)Global Life Technologies, Inc. (Research Grant or Support)Merck & Co. (Scientific Research Study Investigator)Sanofi-Aventis (Other Financial or Material Support, Participate in clinical trial sponsored by NIAID (U01-AI132004); vaccines for this trial are provided by Sanofi-Aventis)

scholarly journals Prospective Audit for Antimicrobial Use and Stewardship Practices in Intensive Care Unit at a Tertiary-Care Center in India

2021 ◽  
Vol 1 (S1) ◽  
pp. s40-s40
Author(s):  
Parul Singh ◽  
Purva Mathur ◽  
Kamini Walia ◽  
Anjan Trikha
Keyword(s):  
Care Center ◽  
Tertiary Care ◽  
Empirical Therapy ◽  
Antibiotic Use ◽  
Audit And Feedback ◽  
Antimicrobial Use ◽  
Defined Daily Dose ◽  
Survey Form ◽  
Specimen Collection ◽  
Days Of Therapy

Background: Antimicrobial decision making in the ICU is challenging. Injudicious use of antimicrobials contributes to the development of resistant pathogens and drug-related adverse events. However, inadequate antimicrobial therapy is associated with mortality in critically ill patients. Antimicrobial stewardship programs are increasingly being implemented to improve prescribing. Methods: This prospective study was conducted over 11 months, during which the pharmacist used a standardized survey form to collect data on antibiotic use. Evaluation of antimicrobial use and stewardship practices in a 12-bed polytrauma ICU and a 20-bed neurosurgery ICU of the 248-bed AIIMS Trauma Center in Delhi, India. Antimicrobial consumption was measured using WHO-recommended defined daily dose (DDD) of given antimicrobials and days of therapy (DOT). Results: Antibiotics were ranked by frequency of use over the 11-month period based on empirical therapy and culture-based therapy. The 11-month DDD and DOT averages when empiric antibiotics were used were 532 of 1,000 patient days and 484 per 1,000 patient days, respectively (Figure 1). When cultures were available, DDD was 486 per 1,000 patient days and DOT was 442 per 1,000 patient days (Figure). Conclusions: The quantity and frequency of antibiotics used in the ICUs allowed the AMSP to identify areas to optimize antibiotic use such as educational initiatives, early specimen collection, and audit and feedback opportunities.Funding: NoDisclosures: None

scholarly journals 181. Antimicrobial Use in the Time of COVID-19 – Data from 84 VA Facilities

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S219-S220
Author(s):  
Matthew B Goetz ◽  
Christopher J Graber ◽  
Makoto M Jones ◽  
Vanessa W Stevens ◽  
Peter A Glassman ◽  
...  
Keyword(s):  
Antimicrobial Stewardship ◽  
Lower Respiratory Tract ◽  
Drug Class ◽  
Training Programs ◽  
Antibiotic Use ◽  
Seasonal Effects ◽  
Antimicrobial Use ◽  
Drug Classes ◽  
Stewardship Program ◽  
Days Of Therapy

Abstract Background The VA initiated an antimicrobial stewardship program in 2011, which includes participation in the Center for Disease Control (CDC) Antimicrobial Use Option, educational webinars, training programs for antimicrobial stewards, required staffing & reporting, and quality improvement initiatives, that has led to ongoing decreases in antimicrobial therapy nationwide. With the onset of the COVID-19 pandemic, however, there are several factors that may contribute increases in antimicrobial use (increased presentations of lower respiratory tract infection, concern for bacterial co-infection with SARS-CoV-2, etc.). We sought to compare patterns of antibacterial use in the VA from January – May 2020 with corresponding time periods in prior years. Methods Data on antibacterial use from 2015 – 2020 were extracted from the VA Corporate Data Warehouse for acute inpatient care units in 84 VA facilities (facilities which provide limited acute inpatient services were excluded). To control for seasonal effects, only data from January to May for each year were included in the analysis. Days of therapy (DOT) per 1000 days-present (DP) were calculated and stratified by CDC-defined antibiotic classes. Results From 2015 – 2019, total antibiotic use from January to May decreased by a mean of 9.1 DOT/1000 DP per year. In contrast, from 2019 to 2020, antibiotic use over the same months increased by 26.4 DOT/1000 DP (Table). Increases were observed in all drug classes except for a decrease in narrow spectrum ß-lactam antibiotics. Total antibiotic DOT in 2020 increased by 27.9 and 7.3 DOT/1000 DP in facilities in the highest and lowest terciles of use in 2019 (Figure). Table – Trends in Yearly Antibiotic Use by CDC Drug Class, 2015 to 2019 versus 2019 to 2020 Figure – Facility Specific Total Antibiotic Use in 2019 and Change in Use from 2019 to 2020 Conclusion We observed a broad increase in antibacterial use during the initial surge of COVID-19 cases in VA facilities that abruptly reversed steady reductions in use over the prior 4 years. The degree to which this increase reflects potentially appropriate use in the setting of increased patient vulnerability and provider uncertainty, inappropriately decreased provider thresholds for initiating or continuing therapy, or stresses on the structure and staffing of antimicrobial stewardship programs requires further study. Disclosures All Authors: No reported disclosures

Does Severity Explain Differences in Hospital Length of Stay for Pneumonia Patients?

1996 ◽  
Vol 1 (2) ◽  
pp. 65-76 ◽  
Author(s):  
Lisa I. Iezzoni ◽  
Michael Shwartz ◽  
Arlene S. Ash ◽  
Yevgenia D. Mackiernan
Keyword(s):  
Diagnosis Related Groups ◽  
Patient Characteristics ◽  
Hospital Length ◽  
Clinical Findings ◽  
Hospital Length Of Stay ◽  
Data Set ◽  
Average Hospital ◽  
Lengths Of Stay ◽  
Complete Study ◽  
The Usa

Objectives: In the USA, the role of patient severity in determining hospital resource use has been questioned since Medicare adopted prospective hospital payment based on diagnosis-related groups (DRGs). Exactly how to measure severity, however, remains unclear. We examined whether assessments of severity-adjusted hospital lengths of stay (LOS) varied when different measures were used for severity adjustment Methods: The complete study sample included 18 016 patients receiving medical treatment for pneumonia at 105 acute care hospitals. We studied 11 severity measures, nine based on patient demographic and diagnosis and procedure code information and two derived from clinical findings from the medical record. For each severity measure, LOS was regressed on patient age, sex, DRG, and severity score. Analyses were performed on trimmed and untrimmed data. Trimming eliminated cases with LOS more than three standard deviations from the mean on a log scale. Results: The trimmed data set contained 17 976 admissions with a mean (S.D.) LOS of 8.9 (6.1) days. Average LOS ranged from 5.0–11.8 days among the 105 hospitals. Using trimmed data, the 11 severity measures produced Rsquared values ranging from 0.098–0.169 for explaining LOS for individual patients. Across all severity measures, predicted average hospital LOS varied much less than the observed LOS, with predicted mean hospital LOS ranging from about 8.4–9.8 days. Discussion: No severity measure explained the two-fold differences among hospitals in average LOS. Other patient characteristics, practice patterns, or institutional factors may cause the wide differences across hospitals in LOS.

scholarly journals 1348. Indirect Standardization to Improve Comparison of Children’s Hospitals’ Antimicrobial Use

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S685-S685
Author(s):  
Rachel Wattier ◽  
Cary Thurm ◽  
Ritu Banerjee ◽  
Ritu Banerjee ◽  
Adam Hersh
Keyword(s):  
Antimicrobial Agents ◽  
Diagnosis Related Groups ◽  
Case Mix ◽  
Antimicrobial Use ◽  
Children's Hospitals ◽  
Ratio Distribution ◽  
Children’S Hospitals ◽  
Days Of Therapy ◽  
Indirect Standardization ◽  
High Outlier

Abstract Background Antimicrobial use (AU) measured by days of therapy per 1000 patient-days (DOT/1000pd), the most established metric, varies widely between children’s hospitals despite robust adoption of antimicrobial stewardship. Differences in diagnoses and procedures (case mix) between hospitals are a source of AU variation not included in adjustment methods such as the Standardized Antimicrobial Administration Ratio. In this study, we evaluated an indirect standardization method to adjust children’s hospital AU for case mix. Methods This multicenter retrospective cohort study included 51 children’s hospitals participating in the Pediatric Health Information System database from 2016-2018. All inpatient, observation, and neonatal admissions were included, with a total of 2,558,948 discharges. Hospitalizations were grouped into 83 strata defined based on All Patients Refined Diagnosis Related Groups (APR-DRGs). Observed to expected (O:E) ratios were calculated by indirect standardization of mean antibiotic DOT per case, with expected values from 2016-2018 and observed values from 2018, and compared to DOT/1000pd. Outlier hospitals were defined by O:E z-scores corresponding to below 10th percentile (low outlier) and above 90th percentile (high outlier). Results Antibacterial DOT/1000pd ranged from 345 to 776 (2.2-fold variation from lowest to highest), whereas O:E ratios ranged from 0.8 to 1.14 (1.4-fold variation from lowest to highest) (Figure 1). O:E ratios were moderately correlated with DOT/1000pd (correlation estimate 0.45; 95% CI 0.19-0.64; p=0.0008). Three high outlier hospitals and 6 low outlier hospitals were identified. Examining hospitals with comparably high DOT/1000pd but discordant O:E ratios, differences could be explained by variation in both case mix and condition-specific AU within strata defined by APR-DRGs. Figure 1. Individual hospitals labeled on the X-axis, ordered by level of antibacterial DOT/1000pd (left axis), represented by bars. Diamonds represent O:E ratios derived by indirect standardization (right axis). Outlier hospitals (low and high) are highlighted in yellow. Dashed horizontal lines represent 10th percentile (lower) and 90th percentile (upper) limits of the O:E ratio distribution. Conclusion The observed variation in DOT/1000pd between hospitals is reduced when indirect standardization is applied to account for case mix differences. This approach can be adapted for more specific uses including clinical conditions, patient populations, or antimicrobial agents. Indirect standardization may enhance stewardship efforts by providing adjusted comparisons that incorporate case mix differences between hospitals. Disclosures All Authors: No reported disclosures

scholarly journals Postprescription Review With Threat of Infectious Disease Consultation and Sustained Reduction in Meropenem Use Over Four Years

2020 ◽  
Author(s):  
Nandita S Mani ◽  
Kristine F Lan ◽  
Rupali Jain ◽  
Chloe Bryson-Cahn ◽  
John B Lynch ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Medical Center ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Percentage Change ◽  
Antimicrobial Use ◽  
Sustained Reduction ◽  
Days Of Therapy ◽  
The University ◽  
The Impact

Abstract Background Following a meropenem shortage, we implemented a postprescription review with feedback (PPRF) in November 2015 with mandatory infectious disease (ID) consultation for all meropenem and imipenem courses > 72 hours. Providers were made aware of the policy via an electronic alert at the time of ordering. Methods A retrospective study was conducted at the University of Washington Medical Center (UWMC) and Harborview Medical Center (HMC) to evaluate the impact of the policy on antimicrobial consumption and clinical outcomes pre- and postintervention during a 6-year period. Antimicrobial use was tracked using days of therapy (DOT) per 1000 patient-days, and data were analyzed by an interrupted time series. Results There were 4066 and 2552 patients in the pre- and postintervention periods, respectively. Meropenem and imipenem use remained steady until the intervention, when a marked reduction in DOT/1000 patient-days occurred at both hospitals (UWMC: percentage change −72.1% (95% confidence interval [CI] −76.6, −66.9), P < .001; HMC: percentage change −43.6% (95% CI −59.9, −20.7), P = .001). Notably, although the intervention did not address antibiotic use until 72 hours after initiation, there was a significant decline in meropenem and imipenem initiation (“first starts”) in the postintervention period, with a 64.9% reduction (95% CI 58.7, 70.2; P < .001) at UWMC and 44.7% reduction (95% CI 28.1, 57.4; P < .001) at HMC. Conclusions PPRF and mandatory ID consultation for meropenem and imipenem use beyond 72 hours resulted in a significant and sustained reduction in the use of these antibiotics and notably impacted their up-front usage.

scholarly journals 1018. Using prediction modeling to inform risk-adjustment strategy for hospital antimicrobial use: Can we predict who gets an inpatient antimicrobial?

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S358-S359
Author(s):  
Rebekah W Moehring ◽  
Matthew Phelan ◽  
Eric Lofgren ◽  
Alicia Nelson ◽  
Melinda M Neuhauser ◽  
...  
Keyword(s):  
Antimicrobial Stewardship ◽  
Risk Adjustment ◽  
Model Performance ◽  
Area Under The Curve ◽  
Absolute Error ◽  
Antimicrobial Use ◽  
Antimicrobial Stewardship Program ◽  
Stewardship Program ◽  
Days Of Therapy ◽  
Tier 1

Abstract Background Hospital antimicrobial stewardship program (ASP) assessments based on comparisons of antimicrobial use (AU) among multiple hospitals are difficult to interpret without risk-adjustment for patient case-mix. We aimed to determine whether variables of varying complexity, derived retrospectively from the electronic health record (EHR), were predictive of inpatient antimicrobial exposures. Methods We performed a retrospective study of EHR-derived data from adult and pediatric inpatients within the Duke University Health System from October 2015 to September 2017. We used Random Forests machine learning models on two antimicrobial exposure outcomes at the encounter level: binary (ever/never) exposure and days of therapy (DOT). Antimicrobial groups were defined by the NHSN AU Option 2017 baseline. Analyses were stratified by pediatric/adult, location type (ICU/ward), and antimicrobial group. Candidate variables were categorized into four tiers based on feasibility of measurement from the EHR. Tier 1 (easy) included demographics, season, location, while Tier 4 (hard) included all variables from Tier 1–3 and laboratory results, vital signs, and culture data. Data were split into 80/20 training and testing sets to measure model performance using area under the curve (AUC) for the binary outcomes and absolute error for DOT. Results The analysis dataset included 170,294 encounters and 204 candidate variables from three hospitals. A total of 80,190 (47%) encounters had antimicrobial exposure; 64,998 (38%) had 1–6 DOT, and 15,192 (9%) had 7 or greater DOT. Models strongly predicted the binary outcome, with AUCs ranging from 0.70 to 0.95 depending on the stratum (Figure A, B). The addition of more complex variables increased accuracy (Figure Model Tiers 1–4). Model performance varied based on location and antimicrobial group. Models for infrequently used groups performed better (Figure C, D). Models underestimated DOTs of encounters with extremely long lengths of stay. Conclusion Models utilizing EHR-derived variables strongly predicted antimicrobial exposure. Risk-adjustment strategies incorporating measures of patient mix may provide more informative benchmark comparisons for use in Antimicrobial Stewardship Program assessments. Disclosures All authors: No reported disclosures.

scholarly journals Changes in antimicrobial utilization during the coronavirus disease 2019 (COVID-19) pandemic after implementation of a multispecialty clinical guidance team

2020 ◽  
pp. 1-7
Author(s):  
Milner B. Staub ◽  
Ronald M. Beaulieu ◽  
John Graves ◽  
George E. Nelson
Keyword(s):  
Internal Medicine ◽  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Patient Characteristics ◽  
Patient Specific ◽  
Antimicrobial Use ◽  
Specific Patient ◽  
Clinical Guidance ◽  
Days Of Therapy

Abstract Objective: Evaluate changes in antimicrobial use during COVID-19 and after implementation of a multispecialty COVID-19 clinical guidance team compared to pre–COVID-19 antimicrobial use. Design: Retrospective observational study. Setting: Tertiary-care academic medical center. Participants: Internal medicine and medical intensive care unit (MICU) provider teams and hospitalized COVID-19 patients. Methods: Difference-in-differences analyses of antibiotic days of therapy per 1,000 patient days present (DOT) for internal medicine and MICU teams treating COVID-19 patients versus teams that did not were performed for 3 periods: before COVID-19, initial COVID-19 period, and after implementation of a multispecialty COVID-19 clinical guidance team which included daily, patient-specific antimicrobial stewardship recommendations. Patient characteristics associated with antibiotic DOT were evaluated using multivariable Poisson regression. Results: In the initial COVID-19 period, compared to the pre–COVID-19 period, internal medicine and MICU teams increased weekly antimicrobial use by 145.3 DOT (95% CI, 35.1–255.5) and 204.0 DOT (95% CI, −16.9 to 424.8), respectively, compared to non–COVID-19 teams. In the intervention period, internal medicine and MICU COVID-19 teams both had significant weekly decreases of 362.3 DOT (95% CI, −443.3 to −281.2) and 226.3 DOT (95% CI, −381.2 to –71.3). Of 131 patients hospitalized with COVID-19, 86 (65.6%) received antibiotics; no specific patient factors were significantly associated with an expected change in antibiotic days. Conclusions: Antimicrobial use initially increased for COVID-19 patient care teams compared to pre–COVID-19 levels but significantly decreased after implementation of a multispecialty clinical guidance team, which may be an effective strategy to reduce unnecessary antimicrobial use.

scholarly journals Variability in Antimicrobial Use Among Hospitals Participating in the Canadian Nosocomial Infection Surveillance Program

2020 ◽  
Vol 41 (S1) ◽  
pp. s509-s509
Author(s):  
Wallis Rudnick ◽  
Linda Pelude ◽  
Michelle Science ◽  
Daniel J.G. Thirion ◽  
Jeannette Comeau ◽  
...  
Keyword(s):  
Nosocomial Infection ◽  
Anatomical Therapeutic Chemical ◽  
Health Agency ◽  
Antibiotic Use ◽  
Teaching Hospitals ◽  
Surveillance Program ◽  
Antimicrobial Use ◽  
Defined Daily Doses ◽  
Infection Surveillance ◽  
Days Of Therapy

Background: The association between antimicrobial use (AMU) and emergence of antimicrobial resistance is well documented. The Canadian Nosocomial Infection Surveillance Program (CNISP) has conducted sentinel surveillance of AMU at participating Canadian hospitals since 2009 resulting in the largest pan-Canadian hospital database of dispensed antimicrobials. Objectives: Describe interhospital variability of AMU across Canada. Methods: Hospitals submit annual AMU data based on patient days (PD). Antimicrobials were measured in defined daily doses (DDD) for adults using the WHO Anatomical Therapeutic Chemical (ATC) system. The AMU data among pediatric patients have been available since 2017 using days of therapy (DOT). Surveillance includes systemic antibacterial agents (J01 ATC codes), oral metronidazole, and oral vancomycin. AMU was assessed using quintiles, interquartile ranges (IQR), and relative IQRs (upper- and lower-quartile values divided by the median). Results: Between 2009 and 2018, 20–26 hospitals participated in adult surveillance each year (35 teaching hospitals and 3 nonteaching hospitals participated in ≥1 year). Over this period, overall AMU decreased by 13% at participating adult hospitals from 645 to 560 DDD per 1,000 PD. AMU varied substantially between hospitals, but this variability decreased over time (Fig. 1). In 2009, the IQRs for overall AMU spanned 309 DDD per 1,000 PD, and in 2018 it spanned only 103 DDD per 1,000 PD. This decrease in variability was due to large decreases in use among hospitals with high use in 2009–2010. Among hospitals in the highest use quintile in 2009–2010, AMU decreased, on average, 44 DDD per 1,000 PD each year. Among hospitals in the lowest use quintile in 2009–2010, AMU increased, on average, 6 DDD per 1,000 PD each year. In 2018, antibiotics with the largest absolute IQR variability were cefazolin (61–113 DDD per 1,000 PD), piperacillin-tazobactam (32–64 DDD per 1,000 PD), and vancomycin (24–49 DDD per 1,000 PD). Among antibiotics with ≥1 DDD per 1,000 PD, antibiotics with the largest relative IQR variability were tobramycin (0.3–6 DDD per 1,000 PD), cefadroxil (0.08–9 DDD per 1,000 PD), and linezolid (0.2–3 DDD per 1,000 PD). In 2018, the IQR for overall pediatric AMU (n = 7 teaching hospitals) was 426–581 DOT per 1,000 PD. Antibiotics with the largest IQRs were vancomycin (0.6–58 DOT per 1,000 PD), cefazolin (33–88 DOT per 1,000 PD), and tobramycin (3–57 DOT per 1,000 PD). Among antibiotics with ≥1 DOT per 1,000 PD in 2018, antibiotics with the largest relative IQRs were tobramycin (3–57 DOT per 1,000 PD), cefuroxime (1–6 DOT per 1,000 PD), and amoxicillin (8–42 DOT per 1,000 PD). Conclusions: There is wide variation in overall antibiotic use across hospitals. Variation between AMU at adult hospitals has decreased between 2009 and 2018; in 2018, antibiotics with the largest IQRs were cefazolin and piperacillin-tazobactam. Benchmarking AMU is crucial for informing antimicrobial stewardship efforts.Funding: CNISP is funded by the Public Health Agency of Canada.Disclosures: Allison McGeer reports funds to her institution from Pfizer and Merck for projects for which she is the principal investigator. She also reports consulting fees from Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara.

scholarly journals Reported β-Lactam and Other Antibiotic Allergies in Solid Organ and Hematopoietic Cell Transplant Recipients

2019 ◽  
Vol 71 (7) ◽  
pp. 1587-1594 ◽  
Author(s):  
Hannah Imlay ◽  
Elizabeth M Krantz ◽  
Erica J Stohs ◽  
Kristine F Lan ◽  
Jacqlynn Zier ◽  
...  
Keyword(s):  
Antibiotic Use ◽  
Hematopoietic Cell ◽  
Solid Organ ◽  
Cell Transplant ◽  
Antibiotic Exposure ◽  
Transplant Recipients ◽  
Hematopoietic Cell Transplant ◽  
Antibiotic Allergy ◽  
Days Of Therapy ◽  
Lactam Antibiotic

Abstract Background Patients with reported β-lactam antibiotic allergies (BLAs) are more likely to receive broad-spectrum antibiotics and experience adverse outcomes. Data describing antibiotic allergies among solid organ transplant (SOT) and hematopoietic cell transplant (HCT) recipients are limited. Methods We reviewed records of adult SOT or allogeneic HCT recipients from 1 January 2013 to 31 December 2017 to characterize reported antibiotic allergies at time of transplantation. Inpatient antibiotic use was examined for 100 days posttransplant. Incidence rate ratios (IRRs) comparing antibiotic use in BLA and non-BLA groups were calculated using multivariable negative binomial models for 2 metrics: days of therapy (DOT) per 1000 inpatient days and percentage of antibiotic exposure-days. Results Among 2153 SOT (65%) and HCT (35%) recipients, 634 (29%) reported any antibiotic allergy and 347 (16%) reported BLAs. Inpatient antibiotics were administered to 2020 (94%) patients during the first 100 days posttransplantation; average antibiotic exposure was 41% of inpatient-days (interquartile range, 16.7%–62.5%). BLA patients had significantly higher DOT for vancomycin (IRR, 1.4 [95% confidence interval {CI}, 1.2–1.7]; P < .001), clindamycin (IRR, 7.6 [95% CI, 2.2–32.4]; P = .001), and aztreonam in HCT (IRR, 9.7 [95% CI, 3.3–35.0]; P < .001), and fluoroquinolones in SOT (IRR, 2.9 [95% CI, 2.1–4.0]; P < .001); these findings were consistent when using percentage of antibiotic exposure-days. Conclusions Transplant recipients are frequently exposed to antibiotics and have a high prevalence of reported antibiotic allergies. Reported BLA was associated with greater use of β-lactam antibiotic alternatives. Pretransplant antibiotic allergy evaluation may optimize antibiotic use in this population.

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