Draper, Evan

Abstract Background Outpatient antibiotic stewardship programs (ASP) are recommended by the CDC and Joint Commission. We analyzed the impact of annual, focused syndrome-specific ASP interventions on trends in long-duration antibiotic prescribing (LDAP). Methods This was a retrospective, observational, multicenter cohort study from November 2020 through June 2025. All ambulatory encounters generating systemic antibiotic prescriptions within the healthcare enterprise were screened. Hospitalizations, emergency department visits, and infectious diseases encounters were excluded. Encounters generating ≥1 systemic antibiotic with >7 days duration were categorized as long-duration. Targeted departments (primary and urgent care) received direct intervention (eg, education, peer-comparison reporting, data tracking). LDAP was modeled over time by month and compared by diagnosis group (ASP-priority diagnoses vs nonpriority) and provider specialty department (ASP-targeted vs nontargeted) using linear regression models. Results Of 642 579 encounters included, 42.2% were long duration. LDAP in ASP-targeted departments dropped from 46.8% to 34.8% (difference −12 percentage points [pp]), whereas nontargeted departments dropped from 45.5% to 39.1% (difference −6.4 pp). The estimated annual LDAP decrease was 3.4 pp in targeted versus 2.4 pp in nontargeted departments (difference 1.0 pp, P = .009). Within targeted departments, significant LDAP decreases were seen both in priority and nonpriority diagnoses, whereas nontargeted departments showed no change in LDAP in priority diagnoses. In a sensitivity analysis of nonpriority diagnoses, ASP-targeted departments had a larger estimated annual decrease in LDAP versus nontargeted (difference 1.4 pp, P < .001). Conclusions Annual syndrome-specific ASP interventions correlated with improvements in LDAP, including outside of priority syndromes in targeted departments. LDAP is a viable metric for evaluating ambulatory ASPs.

Abstract Use of Direct oral anticoagulants (DOAC) has increased exponentially since their introduction in 2010. Over the years they have been used without any systematic oversight, there have been ongoing concerns related to inappropriate or incorrect dosing, incorrect duration, and non-adherence to the drugs leading to adverse patient outcomes. Several factors have been attributed to DOAC non-adherence such as presence or fear of adverse effects, affordability, lack of perceived benefit, or concerns for reversibility. These barriers impact both primary (first time prescription) and secondary adherence (longer term prescription). Poor adherence can lead to adverse outcomes such as stroke, death, and higher medical resource utilization hence increased cost to the patient and payors. This study was conducted as a quality improvement (QI) initiative to improve the adherence to the prescription DOACS. We included patients 18 years old, a diagnosis of Atrial fibrillation and flutter who had a primary care provider writing the prescription for chronic DOAC therapy. Patients with venous thrombosis, pregnancy or who were institutionalized were excluded. The charts were reviewed for primary and secondary adherence using Surescripts functionality which can provide baseline information about prescription fills from the participating pharmacies. In the preimplementation phase we identified 1030 patients meeting inclusion criteria associated with the pilot sites within Mayo Clinic practice in preceding 6 months. For this population, Surescripts data found that the rates of primary and secondary adherence to be 84% and 86% respectively. We then implemented a 6-month pilot where we created workflow for a pharmacy led DOAC management unit. Herein, once a DOAC prescription was made for patients meeting inclusion criteria, they would enter a registry where the pharmacy team would review the charts for primary adherence by utilizing Surescripts data. If adherent these patients would be marked for follow up in the secondary adherence phase. However, if non adherent, the team would initiate intervention including engagement with patient online services which was further escalated to phone calls by the pharmacy team. Once the barriers were identified several remediation approaches were incorporated in the process, these included education about DOACS, medicare education, social work assistance to even switching to warfarin if necessary. The same process was followed for secondary adherence management. In the intervention cohort, we had 411 patients during the pilot, for primary adherence 87.1% of patients were adherent at baseline and an additional 3.4% became adherent with interventions, while 9.5% remain nonadherent. The primary causes of nonadherence, amongst 9.5%, were cost (86%) while 1% were concerned about side effects and 3% were concerned about lack of perceived benefit. The inverntions lead to impoved adherence in most patients and very few patients were transitioned to warfarin. For secondary adherence 92% of the patients were adherent without any intervention, an additional 4% of patients benefited with the interventions of the DOAC management unit with approaches to address cost considerations, while another 4% remained nonadherent where cost remained the primary reason for nonadherence, other reasons being lack of perceived benefit and side effect concerns. In summary, with active intervention, in our patient population we were able to improve the primary adherence from 84% to 91% and secondary adherence from 86% to 96% . Cost remained the biggest barrier for adherence followed by concern for side effects and lack of perceived benefit. Our engaged team of pharmacy staff was able to manage those concerns with the education and cost mitigation strategies leading to improved adherence. Based on previously published literature even a 5% difference in adherence to DOACS can make a huge difference in population-based outcomes. Our work was able to demonstrate a positive impact of the intervention, highlighting the need for a well-managed DOAC unit especially for complex care populations.

Background The vitamin K antagonist, warfarin, is the preferred anticoagulant in patients with antiphospholipid syndrome (APS). Direct oral anticoagulant (DOAC) use in APS is associated with inferior outcomes, including significantly increased odds of arterial thrombotic events, particularly cerebrovascular accidents (CVA). Despite growing evidence supporting warfarin as the preferred first-line agent, DOACs continue to be utilized by providers in the management of APS. The primary aim of this analysis was to scrutinize the patients with a diagnosis of APS and their anticoagulant choices, to identify quality gaps such as unconfirmed diagnosis (with the need for further testing), lack of awareness of the evidence by the prescribing provider or inadequate documentation of risk benefit conversation, versus patient preference and then systematically intervene to reduce the utilization of DOACS in this patient population. Methods We retrospectively reviewed 100 patients with an ICD code diagnosis of APS documented in the electronic health record (EHR) who were recently prescribed a DOAC within Mayo Clinic enterprise. These cases were assessed for appropriateness of the diagnosis (defined as having at least one clinical manifestation of APS, including venous/arterial thrombosis and/or adverse pregnancy outcome in the setting of persistent antiphospholipid antibody (aPL) positivity by Sapporo criteria). aPL positivity was defined as having positive tests on two occasions with a minimum of 12 weeks apart. Antiphospholipid antibody testing included anticardiolipin (aCL) antibodies (IgG and IgM), anti-beta2 glycoprotein I antibodies (IgG and IgM) and lupus anticoagulant (LA). If the patient met diagnostic criteria, they were then risk stratified to identify high-risk cases. High-risk profile was defined as persistently positive levels of all three aPL (triple-positive). Following review for the appropriate diagnosis, intervention gaps were identified, including the need for additional diagnostic testing, provider education, documenting risk-benefits discussion, and removal of APS from the patient's problem list in the EHR. Clinical intervention was done by sending an EHR message to the prescribing provider which included reason for communication, intervention and recommendation. Reminders were sent every 2 weeks to providers who did not respond, with maximum of 3 messages per provider. Results Of the 100 patients, 60/100 (60%) did not meet criteria for APS, as either initial or repeat aPL testing was negative, and therefore were excluded from this project. Within the remaining 40 patients, 17/100 (17%) had thrombotic APS and 23/100 (23%) had unconfirmed diagnosis Reasons for no intervention (20/40) included not meeting criteria for APS, no longer on a DOAC, and risk versus benefits discussion documented. After adjudication only 20 patients qualified for intervention, 10/20 (50%) patients required additional testing due to lack of repeat testing or referral to a specialist, 7/20 (35%) required removal of APS from problem list, and 3/20 (15%) needed provider. Only 12/20 (65%) of providers accepted the recommendation, 7/20 (35%) did not, and 1/20 (5%) did not respond. Conclusions Despite syndrome-defining criteria, APS remains a commonly misdiagnosed condition. Our QI analysis found that more than half of patients in our cohort with HER documented diagnosis of APS did not meet the Sapporo diagnostic criteria. The tested intervention was time-intensive and prospective, which may have contributed to limited provider acceptance. We propose a robust system-based intervention to remedy this quality issue, which will leverage the EHR to create smart tools in the form of order sets and a passive Our Best Practice Advisory alert to highlight incomplete testing or suggest follow up lab testing at 12 weeks. We will also integrate just in time provider education resources and material embedded in the orders. Our future goal is to assess the impact of this intervention with a similarly sampled cohort.

ABSTRACT The use of ceftriaxone, a highly protein-bound drug, in the setting of hypoalbuminemia may result in suboptimal drug exposure. Patients with obesity also exhibit higher absolute drug clearance. We aimed to evaluate the impact of hypoalbuminemia on clinical success among hospitalized adults with obesity who were treated with ceftriaxone. This retrospective review included adult inpatients with weight >100 kg or body mass index >40 kg/m 2 who received ceftriaxone 2 g intravenously every 12 hours for at least 72 hours. The primary outcome was clinical success, a composite of clinical cure and microbiologic cure. Secondary outcomes included clinical cure, microbiologic cure, length of stay, ICU length of stay, mortality, 30-day readmission, and adverse events. In all, 137 patients were included, 34 of whom had a serum albumin of ≤2.5 g/dL. In a propensity-score-weighted analysis, clinical success was significantly more common among those without hypoalbuminemia (91.2%) as compared to those with hypoalbuminemia (77.8%) ( P = 0.038). Death within 30 days (13.7% vs 0%, P < 0.001) and 30-day readmission (31.6% vs 12.0%, P = 0.008) were more common in the hypoalbuminemia group. In a univariate analysis, serum albumin and indication for ceftriaxone use were found to be predictors of clinical success. Hypoalbuminemia was associated with a lower rate of clinical success among patients with obesity who were treated with ceftriaxone 2 g every 12 hours.

Abstract Objectives Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists’ review. Materials and methods A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared. Results Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes. Discussion This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms. Conclusion Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems.

Introduction: Warfarin is a commonly prescribed anticoagulant for treating atrial fibrillation, mechanical valves, and venous thromboembolism. Warfarin dose management remains challenging due to dosing variability between patients and warfarin’s narrow therapeutic window. Time in therapeutic range (TTR) is critical to warfarin’s safety and efficacy, but TTR typically remains low (40-50%) in community practices. Specialized anticoagulation clinics and protocolized approaches can increase TTR but have great administrative burdens and health care costs. Aim: To develop standardized optimal warfarin dose decision support using a machine learning model based on time series anticoagulation data and patient demographic characteristics Methods: The dataset included 12,497 warfarin patients monitored in the anticoagulation tracker of electronic medical records across the Mayo Clinic Enterprise. The dataset contained time series anticoagulation data (warfarin dose, INR, INR target range) and patient demographic characteristics. We implemented an offline deep reinforcement learning model (DRL) to predict the cumulative warfarin dose for the days until the next INR test based on a patient’s historical anticoagulation data. Prior approaches utilized traditional supervised learning methods such as regression or Long Short Term Memory (LSTM) neural networks to approximate a function mimicking the behavior of the training data. On the other hand, DRL learned an optimal dosing policy through continuous interaction and feedback from the training data. The key advantage of DRL is the model can learn to behave differently (and potentially better) for suboptimal clinical states in the data such as overdosing or underdosing. To evaluate the DRL model we compared the predicted warfarin doses with the physician-prescribed doses Results: DRL model’s prediction accuracy was 96.96%, outperforming our implementation of a baseline LSTM model with a prediction accuracy of 70.58%. Further evaluation of the DRL model indicated that the model correctly adjusted the warfarin dose at time steps when patients had out-of-range INRs. Conclusions: Offline deep reinforcement learning demonstrates potential in supporting warfarin dose management to maximize TTR.

Abstract Background Remdesivir is FDA-approved for the treatment of hospitalized patients with severe COVID-19. Many patients improve clinically to allow for hospital dismissal before completing the 5-day course. In prior work, those who continued remdesivir in an outpatient setting had better outcomes. Here, we assessed patients’ perspectives and the economic impact of this outpatient practice. Methods During a one-year period, 3,029 patients received remdesivir for COVID-19 in the hospital; of them, 542 were dismissed to continue remdesivir in the outpatient setting and were surveyed. The cost of care was compared between those who remained in the hospital vs. those who were dismissed. Results 470 of 542 patients were surveyed, and 93 (19.8%) responded. Responders were older than non-responders (median, 63 vs. 58 years). The majority (70.5%) had symptoms resolved by the time of the survey. Ten patients (11.4%) had persistent symptoms attributed to long COVID-19, including fatigue (30.1%), brain fog (23.7%), and insomnia (18.3%). 73.8% were excited to learn about the outpatient remdesivir program. The majority (81.0%) felt that receiving therapy at home was the right decision; 79.5% had support and felt the benefits of completing treatment at home. The majority were satisfied with communication before (75.6%) and during (80.5%) the outpatient appointment, information on benefits (80.3%) and risks (58.5%), time spent at the infusion center (88.6%), quality of care (82.3%) and overall experience (76.0%). The benefits of treatment were high-value (82.6%), while the infusions' cost, inconvenience, and discomfort were unimportant for most responders. After adjusting for gender, comorbidity score, and WHO scale, the predicted costs for the groups were $16,544 (inpatient) and $9,097 (outpatient) per patient (difference of $7,447; p&lt; .01). During this study, we estimated a total of 1,077 hospital room-days were made available to other patients. Conclusion An outpatient remdesivir program that allowed for early dismissal was perceived favorably by patients hospitalized for COVID-19. The program resulted in significant cost and resource savings, the latter in terms of the availability of hospital rooms for other patients needing critical services. Disclosures Christina G. Rivera (O'Connor), Pharm.D, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Board Member|Gilead Sciences: Grant/Research Support|Gilead Sciences: Honoraria Bijan J. Borah, Ph.D., Boehringer Ingelheim: Advisor/Consultant|Exact Sciences: Advisor/Consultant Ravindra Ganesh, M.B.B.S., M.D., Alpaca Health: Advisor/Consultant Raymund R. Razonable, MD, Allovir: Endpoint Adjudication Committee|American Society of Transplantation: Board Member|Gilead: Grant/Research Support|Novartis: DSMB|Regeneron: Grant/Research Support|Roche: Grant/Research Support

Abstract Background Due to extensive protein binding, use of ceftriaxone in the setting of hypoalbuminemia may result in suboptimal drug exposure via higher concentrations of unbound drug resulting in increased volume of distribution and increased drug clearance. We aimed to evaluate the impact of hypoalbuminemia on clinical success among hospitalized adults with obesity who were treated with ceftriaxone for a bacterial infection. Methods This retrospective review included adult inpatients with weight &gt; 100 kg or body mass index (BMI) &gt; 40 who received ceftriaxone 2 grams intravenously every 12 hours for at least 72 hours for one of the following indications: bloodstream infection, pneumonia, urinary tract infection, non-enterococcal endocarditis, skin and soft tissue infection, or bone and joint infection. The primary outcome was clinical success, a composite of clinical cure and microbiologic cure. Clinical cure was defined as resolution of signs and symptoms compatible with active infection without need to change or extend antibiotic therapy due to inadequate effect of ceftriaxone. Microbiologic cure was defined as negative repeat sterile site cultures, if applicable. Secondary outcomes included length of stay, mortality, and 30-day readmission. Outcomes were analyzed with Mann-Whitney U tests, Pearson’s chi-squared tests, and Fisher’s exact tests (α level = 0.05). Results 137 patients were included, 34 of whom had a serum albumin ≤ 2.5 g/dL. Patients were predominantly white (94.2%) and male (69.3%) with a median BMI of 48.6 (Table 1). Clinical success, a composite of clinical and microbiologic cure, was achieved in 76.5% and 92.2% (p = 0.013) of those with and without hypoalbuminemia, respectively. Clinical cure was significantly more common among those without hypoalbuminemia (93.2%) as compared to those with hypoalbuminemia (76.5%) (p = 0.007). Death during hospitalization was more common (14.7% vs. 0%, p &lt; 0.001) and median length of stay was longer (14 vs. 9 days, p = 0.009) in the hypoalbuminemia group. No difference was seen in 30-day readmission (23.5% vs. 11.7%, p = 0.089). Conclusion Hypoalbuminemia was associated with a lower rate of clinical success among patients with obesity who were treated with ceftriaxone 2 grams every 12 hours. Disclosures Christina G. Rivera (O'Connor), Pharm.D, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Board Member|Gilead Sciences: Grant/Research Support|Gilead Sciences: Honoraria

Abstract Background The aim of this study was to evaluate the frequency of unnecessary antibiotic prescribing for Tier 3 upper respiratory infection (URI) syndromes across the Mayo Clinic Enterprise before and after a multifaceted antimicrobial stewardship intervention, and to determine ongoing factors associated with antibiotic prescribing and repeat respiratory healthcare contact in the postintervention period. Methods This was a quasi-experimental, pre/post, retrospective cohort study from 1 January 2019 through 31 December 2022, with 12-month washout during implementation from 1 July 2020 through 30 June 2021. All outpatient encounters, adult and pediatric, from primary care, urgent care, and emergency medicine specialties with a Tier 3 URI diagnosis were included. The intervention was a multifaceted outpatient antibiotic stewardship bundle. The primary outcome was the rate of antibiotic prescribing in Tier 3 encounters. Secondary outcomes included 14-day repeat healthcare contact for respiratory indications and factors associated with persistent unnecessary prescribing. Results A total of 165 658 Tier 3 encounters, 96 125 in the preintervention and 69 533 in the postintervention period, were included. Following intervention, the prescribing rate for Tier 3 encounters decreased from 21.7% to 11.2% (P &lt; .001). Repeat 14-day respiratory healthcare contact in the no antibiotic group was lower postintervention (9.9.% vs 9.4%; P = .004). Multivariable models indicated that increasing patient age, Charlson comorbidity index, and primary diagnosis selected were the most important factors associated with persistent unnecessary antibiotic prescribing. Conclusions Outpatient antibiotic stewardship initiatives can reduce unnecessary antibiotic prescribing for Tier 3 URIs without increasing repeat respiratory healthcare contact. Advancing age and number of comorbidities remain risk factors for persistent unnecessary antibiotic prescribing.