scholarly journals 307. Predictors of Respiratory Bacterial Co-Infection in Hospitalized COVID-19 Patients

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S260-S260
Author(s):  
Erica E Reed ◽  
Austin Bolker ◽  
Kelci E Coe ◽  
Jessica M Smith ◽  
Kurt Stevenson ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Antibiotic Use ◽  
Hospitalized Patients ◽  
Mortality Data ◽  
Chi Square ◽  
Academic Medical ◽  
Cumulative Duration ◽  
To Receive ◽  
Mlr Model

Abstract Background COVID-19 pneumonia can be indistinguishable from other infectious respiratory etiologies, so providers are challenged with deciding whether empiric antibiotics should be prescribed to hospitalized patients with SARS-CoV-2. This study aimed to evaluate predictors of respiratory bacterial co-infections (RBCI) in hospitalized patients with COVID-19. Methods Retrospective study evaluating COVID-19 inpatients from Feb 1, 2020 to Sept 30, 2020 at a tertiary academic medical center. Patients with RBCI were matched with three COVID-19 inpatients lacking RBCI admitted within 7 days of each other. The primary objectives of this study were to determine the prevalence of and identify variables associated with RBCI in COVID-19 inpatients. Secondary outcomes included length of stay and mortality. Data collected included demographics; inflammatory markers; bacterial culture/antigen results; antibiotic exposure; and COVID-19 severity. Wilcoxon rank sum, Chi Square tests, or Fisher’s exact tests were utilized as appropriate. A multivariable logistic regression (MLR) model was conducted to identify covariates associated with RBCI. Results Seven hundred thirty-five patients were hospitalized with COVID-19 during the study period. Of these, 82 (11.2%) had RBCI. Fifty-seven of these patients met inclusion criteria and were matched to three patients lacking RBCI (N = 228 patients). Patients with RBCI were more likely to receive antibiotics [57 (100%) vs. 130 (76%), p < 0.0001] and for a longer cumulative duration [19 (13-33) vs. 8 (4-13) days, p < 0.0001] compared to patients lacking RBCI. The MLR model revealed risk factors of RBCI to be admission from SNF/LTAC/NH (AOR 6.8, 95% CI 2.6-18.2), severe COVID-19 (AOR 3.03, 95% CI 0.78-11.9), and leukocytosis (AOR 3.03, 95% CI 0.99-1.16). Conclusion Although RBCI is rare in COVID-19 inpatients, antibiotic use is common. COVID-19 inpatients may be more likely to have RBCI if they are admitted from a SNF/LTAC/NH, have severe COVID-19, or present with leukocytosis. Early and prompt recognition of RBCI predictors in COVID-19 inpatients may facilitate timely antimicrobial therapy while improving antimicrobial stewardship among patients at low risk for co-infection. Disclosures All Authors: No reported disclosures

scholarly journals Clinical Team Distribution and Antibiotic Use Patterns at a Tertiary-Care Academic Medical Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s168-s169
Author(s):  
Rebecca Choudhury ◽  
Ronald Beaulieu ◽  
Thomas Talbot ◽  
George Nelson
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Antibiotic Use ◽  
Care Hospital ◽  
Hospital Units ◽  
Antibiotic Utilization ◽  
Academic Medical ◽  
Level Data ◽  
Utilization Data

Background: As more US hospitals report antibiotic utilization to the CDC, standardized antimicrobial administration ratios (SAARs) derived from patient care unit-based antibiotic utilization data will increasingly be used to guide local antibiotic stewardship interventions. Location-based antibiotic utilization surveillance data are often utilized given the relative ease of ascertainment. However, aggregating antibiotic use data on a unit basis may have variable effects depending on the number of clinical teams providing care. In this study, we examined antibiotic utilization from units at a tertiary-care hospital to illustrate the potential challenges of using unit-based antibiotic utilization to change individual prescribing. Methods: We used inpatient pharmacy antibiotic use administration records at an adult tertiary-care academic medical center over a 6-month period from January 2019 through June 2019 to describe the geographic footprints and AU of medical, surgical, and critical care teams. All teams accounting for at least 1 patient day present on each unit during the study period were included in the analysis, as were all teams prescribing at least 1 antibiotic day of therapy (DOT). Results: The study population consisted of 24 units: 6 ICUs (25%) and 18 non-ICUs (75%). Over the study period, the average numbers of teams caring for patients in ICU and non-ICU wards were 10.2 (range, 3.2–16.9) and 13.7 (range, 10.4–18.9), respectively. Units were divided into 3 categories by the number of teams, accounting for ≥70% of total patient days present (Fig. 1): “homogenous” (≤3), “pauciteam” (4–7 teams), and “heterogeneous” (>7 teams). In total, 12 (50%) units were “pauciteam”; 7 (29%) were “homogeneous”; and 5 (21%) were “heterogeneous.” Units could also be classified as “homogenous,” “pauciteam,” or “heterogeneous” based on team-level antibiotic utilization or DOT for specific antibiotics. Different patterns emerged based on antibiotic restriction status. Classifying units based on vancomycin DOT (unrestricted) exhibited fewer “heterogeneous” units, whereas using meropenem DOT (restricted) revealed no “heterogeneous” units. Furthermore, the average number of units where individual clinical teams prescribed an antibiotic varied widely (range, 1.4–12.3 units per team). Conclusions: Unit-based antibiotic utilization data may encounter limitations in affecting prescriber behavior, particularly on units where a large number of clinical teams contribute to antibiotic utilization. Additionally, some services prescribing antibiotics across many hospital units may be minimally influenced by unit-level data. Team-based antibiotic utilization may allow for a more targeted metric to drive individual team prescribing.Funding: NoneDisclosures: None

scholarly journals 154. Antibiotic Use During Three Separate Waves of the COVID-19 Pandemic at a Large Academic Medical Center in Detroit, MI

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S188-S189
Author(s):  
Deepika Sivakumar ◽  
Shelbye R Herbin ◽  
Raymond Yost ◽  
Marco R Scipione
Keyword(s):  
Retrospective Review ◽  
Bacterial Pneumonia ◽  
Medical Center ◽  
Academic Medical Center ◽  
Antibiotic Use ◽  
Percent Change ◽  
Academic Medical ◽  
Days Of Therapy ◽  
Time Periods ◽  
The Impact

Abstract Background Inpatient antibiotic use early on in the COVID-19 pandemic may have increased due to the inability to distinguish between bacterial and COVID-19 pneumonia. The purpose of this study was to determine the impact of COVID-19 on antimicrobial usage during three separate waves of the COVID-19 pandemic. Methods We conducted a retrospective review of patients admitted to Detroit Medical Center between 3/10/19 to 4/24/21. Median days of therapy per 1000 adjusted patient days (DOT/1000 pt days) was evaluated for all administered antibiotics included in our pneumonia guidelines during 4 separate time periods: pre-COVID (3/3/19-4/27/19); 1st wave (3/8/20-5/2/20); 2nd wave (12/6/21-1/30/21); and 3rd wave (3/7/21-4/24/21). Antibiotics included in our pneumonia guidelines include: amoxicillin, azithromycin, aztreonam, ceftriaxone, cefepime, ciprofloxacin, doxycycline, linezolid, meropenem, moxifloxacin, piperacillin-tazobactam, tobramycin, and vancomycin. The percent change in antibiotic use between the separate time periods was also evaluated. Results An increase in antibiotics was seen during the 1st wave compared to the pre-COVID period (2639 [IQR 2339-3439] DOT/1000 pt days vs. 2432 [IQR 2291-2499] DOT/1000 pt days, p=0.08). This corresponded to an increase of 8.5% during the 1st wave. This increase did not persist during the 2nd and 3rd waves of the pandemic, and the use decreased by 8% and 16%, respectively, compared to the pre-COVID period. There was an increased use of ceftriaxone (+6.5%, p=0.23), doxycycline (+46%, p=0.13), linezolid (+61%, p=0.014), cefepime (+50%, p=0.001), and meropenem (+29%, p=0.25) during the 1st wave compared to the pre-COVID period. Linezolid (+39%, p=0.013), cefepime (+47%, p=0.08) and tobramycin (+47%, p=0.05) use remained high during the 3rd wave compared to the pre-COVID period, but the use was lower when compared to the 1st and 2nd waves. Figure 1. Antibiotic Use 01/2019 to 04/2019 Conclusion Antibiotics used to treat bacterial pneumonia during the 1st wave of the pandemic increased and there was a shift to broader spectrum agents during that period. The increased use was not sustained during the 2nd and 3rd waves of the pandemic, possibly due to the increased awareness of the differences between patients who present with COVID-19 pneumonia and bacterial pneumonia. Disclosures All Authors: No reported disclosures

Screening for expired medications in automated dispensing cabinets

2020 ◽  
Vol 77 (24) ◽  
pp. 2107-2111
Author(s):  
Alexis N Nanni ◽  
Trusha S Rana ◽  
Daniel H Schenkat
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Experimental Period ◽  
Experimental Phase ◽  
Monthly Basis ◽  
Main Campus ◽  
Dose Rates ◽  
Additional Intervention ◽  
Academic Medical ◽  
To Receive

Abstract Purpose Results of a study to quantify rates of identification of expired medications in automated dispensing cabinets (ADCs) are reported. Methods A pre-post analysis was conducted to determine the effect of various types of ADC audits on rates of finding expired medications in ADCs. For the experimental phase of the study, 4 ADCs at the main campus of an academic medical center were randomly assigned to receive one of 4 interventions: (1) monthly audits of all ADC pockets, (2) monthly audits of matrix (open pocket) drawers only, (3) monthly audits of unassigned pockets only, and (4) no additional intervention. Results At baseline, rates of finding expired medication doses in the 4 ADCs ranged from 0.4% to 0.7%. During the 3-month experimental period, rates of finding expired medication doses ranged from 0.1% to 0.3%. During a final audit 1 month later, the ADC targeted for monthly audits of all pockets was found to contain no expired doses, with an overall improvement in expired-dose rates for all audited ADCs observed over the course of the 4-month study. The average time to perform a full audit for an ADC with about 340 pockets was 1 hour, or 15 seconds per pocket. The average time to perform matrix drawer–only audits averaged around 45 minutes, or 11 seconds per pocket. The average time to perform audits of unassigned matrix drawers averaged 30 minutes, or 10 seconds per pocket. Conclusion Auditing of all ADC pockets on a monthly basis appears to be an effective method of reducing the rate of identification of expired medications in ADC pockets.

Implementation of computerized add-on testing for hospitalized patients in a large academic medical center

2011 ◽  
Vol 49 (5) ◽  
Author(s):  
Ji Yeon Kim ◽  
Irina K. Kamis ◽  
Balaji Singh ◽  
Shalini Batra ◽  
Roberta H. Dixon ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Hospitalized Patients ◽  
Academic Medical

scholarly journals 2101. Impact of “Code Sepsis” on Antimicrobial Utilization at an Academic Medical Center

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S710-S710
Author(s):  
Minji Kang ◽  
Francesca J Torriani ◽  
Rebecca Sell ◽  
Shira Abeles
Keyword(s):  
Organ Dysfunction ◽  
Early Recognition ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospitalized Patients ◽  
Antibiotic Administration ◽  
Academic Medical ◽  
Sepsis Bundle ◽  
The Impact ◽  
Infectious Source

Abstract Background Balancing antimicrobial stewardship with sepsis management is a challenge. At our academic medical center, a “Code Sepsis” was implemented as a nursing driven initiative to improve early recognition and management of sepsis. Per protocol, Code Sepsis is activated in patients who meet two or more systemic inflammatory response syndrome (SIRS) criteria due to a suspected infection to allow for early implementation of the sepsis bundle, which includes laboratory testing, fluid resuscitation, and antibiotic administration (Figure 1). We analyzed the impact that Code Sepsis had on antimicrobial use among hospitalized patients over a six month period. Methods We reviewed the electronic medical records of hospitalized patients with Code Sepsis activation between January 1, 2018 and June 30, 2018 to determine whether antibiotics were “escalated” or “not escalated.” Among patients who had antibiotic escalation, escalation was classified as “indicated” or “not indicated” (Figure 2). A logistic regression model was used to identify characteristics, SIRS or organ dysfunction criteria predictive of indicated antimicrobial escalation. Results Code Sepsis was activated in 529 patients with antibiotics escalated in 247 (47%) and not escalated in 282 (53%) (Table 1). Among patients whose antibiotics were escalated, 64% (152) had an indication. In 36% (89), escalation was not indicated as Code Sepsis was due to a suspected noninfectious source, known infectious source already on appropriate antimicrobials, or a suspected infectious source in which diagnostic results had already shown the absence of the infection (Figure 2). Odds of indicated antibiotic escalation increased with the number of SIRS and organ dysfunction criteria (Table 2). Conclusion In our efforts to improve sepsis outcomes, we focused on early recognition (Code Sepsis) and intervention (sepsis bundle). However, our Code Sepsis inadvertently led to antibiotic overutilization. By refocusing Code Sepsis on early recognition of severe sepsis and septic shock, we hope to optimize resource utilization and improve patient outcomes. Disclosures All authors: No reported disclosures.

Relationship between dental loss and health outcomes among hospitalized patients with and without diabetes

2018 ◽  
Vol 67 (3) ◽  
pp. 669-673
Author(s):  
Kenneth Izuora ◽  
Ammar Yousif ◽  
Gayle Allenback ◽  
Civon Gewelber ◽  
Michael Neubauer
Keyword(s):  
Diabetes Mellitus ◽  
Heart Disease ◽  
Health Outcomes ◽  
Medical Center ◽  
Dental Health ◽  
Academic Medical Center ◽  
Hospitalized Patients ◽  
Academic Medical ◽  
Patients With Diabetes ◽  
The Impact

There is mixed evidence regarding the impact of poor dental health on cardiovascular disease and other health outcomes. Our objective was to determine the outcomes associated with poor dental health among hospitalized patients with and without diabetes mellitus (DM) at our institution. We enrolled a consecutive sample of adult patients admitted to an academic medical center. We gathered demographic, health and dental information, reviewed their medical records and then examined their teeth. We analyzed data using SPSS V.24. There was a high prevalence of dental loss among all hospitalized patients. Older age (p<0.001), smoking (p=0.034), having DM (p=0.001) and lower frequency of teeth brushing (p<0.001) were predictors of having a lower number of healthy teeth. Among DM and non-DM patients, fewer remaining healthy teeth was associated with presence of heart disease (p=0.025 and 0.003, respectively). Patients with diabetes mellitus (DM) had a higher prevalence of stroke (p=0.006) while patients without DM had a higher number of discharge medications (p=0.001) associated with having fewer number of healthy teeth. There was no correlation between number of healthy teeth and the length or frequency of hospitalization. Patients with DM are more likely to have fewer number of healthy teeth compared with non-DM patients. Fewer number of healthy teeth was associated with higher prevalence of heart disease in both DM and non-DM patients and with more discharge medications in non-DM patients.

Barriers in communicating medication changes at hospital discharge: Informing CancelRx design requirements

2021 ◽  
pp. 251604352110059
Author(s):  
Yushi Yang ◽  
Samantha I Pitts ◽  
Allen R Chen
Keyword(s):  
Hospital Discharge ◽  
Medical Center ◽  
Academic Medical Center ◽  
Structured Interviews ◽  
Medication Discontinuation ◽  
Academic Medical ◽  
Receive System ◽  
Design Requirements ◽  
To Receive ◽  
Medication Changes

Objectives This operational study aims to investigate the barriers in communicating medication changes at hospital discharge, and to inform design requirements of the CancelRx functionality to better support the communication. Methods We conducted seven semi-structured interviews with inpatient prescribers at an urban academic medical center. The interview protocol was framed from a human factors perspective, specifically the work system design approach. We took notes of the interviews and identified the initial themes of system barriers that may impact patient safety. Results Medication changes need to be communicated to multiple stakeholders. We identified two initial themes of the system barriers: the lack of an information flow that connects all the involved stakeholders, and the difficulties to communicate key pieces of information. We identified three key pieces of information that are difficult to communicate: the discontinuation reasons, the notification urgency, and the duration of changes. Conclusions While the CancelRx functionality can facilitate the communication (e.g. prescribers no longer need to call pharmacists when a medication is discontinued), enhancements are needed to address the system barriers. We proposed enhanced design requirements of the CancelRx functionality, e.g., to allow users to specify a reason for a medication discontinuation and transmit the reasons to other stakeholders, to indicate the urgency of notification, to specify the duration of a change, and to receive system status feedback .

scholarly journals Evaluation of Antibiotic Prophylaxis and Postsurgery Antibiotics for Urological Surgeries at an Academic Medical Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s227-s227
Author(s):  
Emily Drwiega ◽  
Saira Rab ◽  
Sheetal Kandiah ◽  
Jane Kriengkauykiat ◽  
Jordan Wong
Keyword(s):  
Clostridium Difficile ◽  
Antibiotic Prophylaxis ◽  
Primary Outcome ◽  
Medical Center ◽  
Academic Medical Center ◽  
Antibiotic Use ◽  
Composite Outcome ◽  
Academic Medical ◽  
Perioperative Antibiotics ◽  
Urological Procedures

Objective: The purpose of this study was to evaluate antibiotic use in patients undergoing urological procedures. Methodology: This single-center, IRB-approved, retrospective, observational study was conducted at Grady Health System. Patients were included if they underwent their first inpatient urologic procedure between April 1, 2016, and April 1, 2018. Patients were excluded if they were <18 years old, pregnant, or a prisoner. The primary outcome was percentage of overall adherence to our institutional guidelines for surgical prophylaxis as a composite of antibiotic selection, dose, preoperative timing, and postoperative duration. Secondary outcomes include individual components of the composite outcome, nephrotoxicity, Clostridium difficile infection, and discharge antibiotic prescriptions. Descriptive statistics were used. Results: Of the 100 patients evaluated, 11% achieved adherence with the primary outcome. Of the 89 patients who did not achieve composite outcome, only 8 selected the appropriate perioperative antibiotic. Overall, 30% were dosed appropriately, 47% were administered at the appropriate time with respect to time of incision, and 46% received perioperative antibiotics for no more than 24 hours. Also, 19 patients did not receive perioperative antibiotics. Overall, 14 different perioperative antibiotic regimens were utilized, despite institutional guidelines recommending 1 of 3 options. All 9 patients who developed nephrotoxicity received noncompliant perioperative prophylaxis. No patient developed Clostridium difficile infection within 30 days of surgery. Moreover, 58 patients were discharged with a prescription for at least 1 antibiotic. Conclusions: Most perioperative antibiotic prophylaxes for genitourinary surgeries are not compliant with institution guideline recommendations. Despite having institutional guidelines, there was a large variety in the antibiotic regimens that patients received. All of the patients identified as having an evaluated antibiotic-related adverse effect did not receive appropriate perioperative antibiotic prophylaxis. More than half of the patients received a prescription at discharge for at least 1 antibiotic.Funding: NoneDisclosures: None

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