Clostridioides difficile infection (CDI) accounts for 450,000 cases and $6.3 billion in healthcare costs annually in the US. The June 2021 IDSA/SHEA guideline update recommended fidaxomicin over vancomycin for initial and recurrent CDI and adjuvant bezlotoxumab for high-risk patients. We evaluated the impact of this update on CDI management, outcomes, and healthcare utilization. We conducted a retrospective study using Epic Cosmos (Epic EHR data, US only, 2018-2024), including all adult inpatient/outpatient encounters with a CDI diagnosis. An interrupted time series analysis evaluated trends in monthly utilization of enteral fidaxomicin, vancomycin, metronidazole, and IV bezlotoxumab; 30-day CDI recurrence (logistic regression); mean length of stay (LOS) (linear regression); and total monthly CDI-related costs (linear regression; including antibiotics, LOS, and recurrence-related readmissions) before (Jun 2018-May 2021) and after (July 2021-Dec 2024) the guideline update. We identified 1,204,726 CDI encounters. Following the guideline update, fidaxomicin, vancomycin, and bezlotoxumab use increased (3.1% to 9.6%; 26.4% to 30.1%, and 0.1% to 0.5%, respectively), while metronidazole use decreased (6.6% to 3.5%, Figures 1-2). The guideline update was associated with an immediate 4% reduction in the odds of 30-day recurrence (OR 0.96, 95% CI 0.94-0.97, p< 0.001) followed by a flattening in recurrence trend post-intervention (interaction OR 0.98, p< 0.001, Figures 3-4). Mean LOS increased immediately (β=0.12 log-days, 95% CI 0.07-0.16, p< 0.001), but declined significantly over time (interaction β=–0.10, p< 0.001). Total monthly cost increased sharply post-intervention (β=$19.5 million, 95% CI: $10.6M–28.4M, p< 0.001); but slopes changes were not significant (interaction β=$2.85M, p=0.2). Adoption of the updated CDI guidelines was associated with reduced recurrence and declining LOS. Although monthly costs increased substantially following the intervention, there was no significant ongoing upward trend. These findings highlight the clinical benefits of guideline implementation, while emphasizing the need to balance improved outcomes against higher sustained treatment costs. All Authors: No reported disclosures

Data regarding cardiogenic shock (CS) from safety-net hospitals serving socioeconomically-disadvantaged patients are limited. In addition, little is known regarding long-term outcomes and management of heart failure-related CS (HF-CS), a population potentially especially vulnerable to adverse social determinants of health (SDOH). A single-center retrospective cohort study of patients with Stage C, D, or E CS at a public safety-net hospital between 2017 and 2023 was performed. Management and outcomes were compared between patients with HF-CS and myocardial infarction-CS (AMI-CS). The primary outcome was survival through 2 years. The cohort included 378 patients (median age 57y, 44% Black race, 35% Hispanic ethnicity, 81% HF-CS, 19% AMI-CS); 23% received mechanical circulatory support. Thirty-day mortality was lower among patients with HF-CS than AMI-CS (16% vs 28%; HR 0.50 [95% CI 0.30 to 0.84], p = 0.01]). In contrast, mortality from 31 days through 2 years was higher after HF-CS (45% vs 22%, HR 1.94 [1.11 to 3.38], p = 0.02). At long-term follow-up, 53% of survivors were on beta blockers and 32% on no guideline-directed medical therapies. Eighteen patients (5%) received transplant or left ventricular assist device, all of whom had HF-CS and survived through available follow up (median 2.3y [0.9 to 4.0]). In conclusion, in a large safety-net hospital serving a diverse population with adverse SDOH, HF-CS was much more common than AMI-CS, with lower short-term but higher long-term mortality in HF-CS. Use of advanced therapies was low, with favorable survival among patients who received these. These results highlight the importance of expanding access to specialized heart failure care for socially vulnerable patients with CS.

BACKGROUND:Familial hypercholesterolemia (FH) is an inherited cholesterol disorder that is markedly underdiagnosed. OBJECTIVE:This study evaluated the real-world performance of the Find, Identify, Network, Deliver-FH (FIND-FH) score, a novel machine learning algorithm, in identifying individuals with high likelihood of FH. METHODS:The FIND-FH model was applied to electronic health record (EHR) data from UT Southwestern Medical Center. Manual chart review was performed on those deemed high probability of FH (score >0.35) to assess accuracy of FH diagnosis by modified Simon-Broome and Dutch Lipid Clinic Network (DLCN) criteria. Individual characteristics were compared across quintiles of the FIND-FH score. Individuals deemed suitable for FH outreach were identified using predetermined clinical criteria denoting adequate clinical probability of FH. RESULTS:Of the 93,418 individuals in the EHR dataset, the FIND-FH algorithm identified 340 with high probability of FH. These 340 individuals had a mean age of 49.8 years, were 59% male, and had a highest low-density lipoprotein cholesterol (LDL-C) of 168.4 mg/dL (±51.9). A total of 20-32% met modified Simon-Broome or DLCN criteria for at least possible FH based on available EHR data. Several variables differed significantly by FIND-FH score quintile, including Simone-Broome and DLCN probability. In the reviewed cohort, 191 (56%) had enough clinical suspicion for FH to warrant outreach. Among these, 101 (53%) had highest LDL-C <190 mg/dL and would be missed by LDL-C-based FH screening strategies. CONCLUSION:In a large healthcare system EHR cohort, most individuals identified as higher risk for FH by the FIND-FH algorithm were deemed appropriate for further evaluation, despite the majority not meeting FH diagnostic criteria using available EHR data.

As health care embraces learning health systems, data-oriented approaches provide a path for genetic counselors to actively contribute to improving clinical care through evidence-driven insights. The informatics-driven querying of electronic health record (EHR) data in genetic counseling has the potential to advance clinical practice, quality improvement, and research. This paper examines the opportunities and challenges associated with leveraging EHR data in genetic counseling, with a focus on practical, collaborative, and future-oriented applications. Quality improvement initiatives focused on identifying eligible patients for genetic services, assessing access and uptake patterns, and evaluating genetic testing outcomes serve as a natural gateway to research. Here, we demonstrate how genetic counseling professionals can use EHR data to conduct research that drives impactful changes in patient care and service delivery. By highlighting key applications and identifying areas for future exploration, this paper argues that EHR-based research represents not only a practical solution to current challenges but also the future of genetic counseling inquiry. This approach promises to unlock new opportunities to measure and enhance the effectiveness, equity, and accessibility of genetic counseling services.

Introduction: Traditionally, access to HIPAA-compliant nationally representative data has been difficult. Cosmos by Epic aims to simplify access to big data for epidemiological research. We used Cosmos to evaluate the population impact of upcoming revised cholesterol guidelines. The upcoming guidelines might lower the LDL-C goal to 55 mg/dL from the current 70 mg/dL goal set by the 2018 ACC/AHA cholesterol guidelines. Hypothesis: We hypothesized that a democratized business analytic tool like Cosmos can be leveraged to estimate the population-level impact of guideline and policy changes. Methods: Cosmos was queried using the patient data model to identify adult patients (≥ 18 years) with clinical ASCVD, defined using a combination of ICD-10 codes and SNOMED CT custom groupers. Patients were included if they had at least 1 LDL-C value recorded between September 2022 and September 2024, and only the most recent value was used in our analysis. The population was sliced using the Lab Component à LDL and Medication filters to assess LDL-C levels and lipid lowering therapy (LLT) utilization. Results: We identified 6,657,563 patients with clinical ASCVD (mean age 69, 53.8% male, 81.7% White). Most of the patients (60.0%) had LDL-C above 70 mg/dL, 19.4% had an LDL-C between 55-70 mg/dL, and 20.8% had an LDL-C below 55 mg/dL ( Figure ). Among the 1,290,111 patients with an LDL-C between 55-70 mg/dL, 79.8% were on statin monotherapy, 47.3% were on a high intensity or maximally tolerated statin, 11.3% were receiving non-statin LLT, and 8.9% had no record of any LLT ( Table ). Conclusions: Our analysis highlights the potential of Epic Cosmos as a powerful tool for answering epidemiological questions using real-world data. In this cohort of 6.7 million patients with ASCVD, about 1.3 million (19.4%) individuals with an LDL-C between 55-70 mg/dL would be considered to have uncontrolled cholesterol if the LDL-C target is lowered to <55 mg/dL in the future ACC/AHA cholesterol guidelines. Less than half of these patients were on high-intensity or maximally tolerated statins, about 1 in 10 were on non-statin LLTs, and around 9% were not receiving any LLT at all. This presents a substantial opportunity for treatment escalation or initiation to help these individuals achieve lower LDL-C targets.

Introduction: Contemporary trial data and professional guidelines support a rhythm control strategy with catheter ablation for patients with comorbid atrial fibrillation (AF) and heart failure (HF). However, the penetrance of these specialized and expensive interventions by race, ethnicity, and socioeconomic status has not been well described. Research Question: We sought to examine how race/ethnicity may be associated with rates of catheter ablation among patients with AF and HF. Methods: Using the Epic Cosmos database, which provides nationally-representative data by combining electronic health record data from over 1,500 electronic health record systems, we examined trends in catheter ablation over time stratified by race and ethnicity. Patients were identified if they had at least two encounters between 2015 and 2024 with ICD-10 codes for each of AF and HF. We used social vulnerability index (SVI), a geographically defined measure in which higher SVI indicates more social vulnerability, as a proxy for socioeconomic status. The primary outcome of interest was catheter ablation for atrial fibrillation, identified by CPT code. Patients were followed until the outcome of interest or 12/31/2024, whichever was earlier. Results: Among 2,646,219 patients with comorbid AF and HF, 137,260 (5.2%) underwent catheter ablation during the study period. Ablation rate was greater among non-Hispanic White (NHW) patients (5.5%) than Hispanic (4.7%, p < 0.05) or non-Hispanic Black (NHB) patients (3.5%, p < 0.05). Ablation rates were higher among each race/ethnicity group as social vulnerability decreased (p < 0.05 for trend) (Figure 1). The ablation rate for the most vulnerable NHW patients (5.0%) was numerically higher than that of the least vulnerable NHB patients (4.3%), although this comparison was not statistically significant. The annualized rate of catheter ablation per 100 new AF diagnoses increased faster among NHW patients (1.2% per year) compared to Hispanic (0.8% per year, p < 0.05) or NHB patients (0.7% per year, p < 0.05) (Figure 2). Conclusion: Our findings suggest a disparity in care utilization by race/ethnicity that is not explained by differences in social vulnerability and appears to be increasing over time. More equitable use of catheter ablation is important to improving outcomes for patients with comorbid AF and HF.

The University of Texas Southwestern Medical Center (UTSW) and Texas Health Resources (THR) implemented an Observational Medical Outcomes Partnership (OMOP) common data model (CDM) that utilizes the Epic electronic health record's (EHR) extract, transform, and load (ETL) system to enable collaborative research with other health institutions within the OHDSI network. We mapped EHR data from core Epic reporting tables to 25 OMOP CDM tables and transferred the data to a shared OMOP database housed within the Caboodle infrastructure using Epic's pre-existing ETL system, minimizing the need for customization. ETL processes occur weekly at THR and daily at UTSW. OMOP CDM mapping resulted in data quality assessment values of 97% and 98% for THR and UTSW respectively. Our study established a reproduceable, collaborative pipeline using the OMOP CDM with Epic's native ETL framework, expanding the OHDSI research network resulting in better quality and more generalizable data sets available for future research.

Introduction: Clinical trial data and professional guidelines support rhythm control strategies over rate control in patients with comorbid atrial fibrillation (AF) and heart failure (HF). Studies have also shown that males and females experience differences in symptom burden, comorbidities, management strategies, and outcomes. Catheter ablation utilization between sex has not been well described. Research Questions: We sought to analyze rates of catheter ablation for comorbid AF and HF by patient-reported sex. Methods: Using the Epic Cosmos database, which provides nationally-representative data by combining electronic health record data from over 1,500 electronic health record systems, we examined trends in catheter ablation rates over time, stratified by sex. Patients were identified if they had at least two encounters between 2015 and 2024 with ICD-10 codes for each of AF and HF. The primary outcome was catheter ablation for AF. Patients were followed until the outcome of interest or 12/31/2024, whichever was earlier. Results: A total of 2,646,219 patient records with comorbid AF and HF were identified, of which 44.3% were women. There were 137,260 catheter ablations (5.2%). Overall, 5.9% of men and 4.2% of women underwent catheter ablation. Women were 29% less likely to receive catheter ablation (RR = 0.713; 95% CI = 0.705 - 0.721). The catheter ablation rate per 100 new AF diagnoses per year increased by 1.3% among men and 0.9% among women from 2015 to 2024 (p = 0.045) (Figure 1). Under the age of 65, men are significantly more likely to undergo ablation than are women of similar age (p < 0.05) (Figure 2). Above the age of 65, the overall ablation rate decreases, and there is no apparent difference by sex (Figure 2). Conclusion: Men undergo catheter ablation more frequently than women. Moreover, the difference in ablation rates persists over time despite increasing use of AF ablation overall. Ablation rates are attenuated > 65 years of age, partially masking marked sex-based differences in ablation rates among younger patients, especially those <55 years.

Objective: Familial Hypercholesterolemia (FH) is underdiagnosed and undertreated. Several electronic health record (EHR) algorithms have been developed to improve identification of patients with FH. The approach to improving downstream processes of care and implementation of appropriate treatment after identification of these individuals is unclear. Methods: Individuals at UT Southwestern Medical Center with an LDL-C >= 190mg/dL (n = 8368) ever recorded in the EHR were included in an FH registry. As part of a QI program, random individuals from the registry deemed to possibly have FH were contacted via (1) MyChart message, (2) phone call, (3) letter, and/or (4) InBasket message to their PCP to notify them of the potential FH diagnosis, higher risk of ASCVD events, and offering referral to an FH specialist. Participants were contacted 1-4 times by one of these modalities. Chart extraction of contacted patients was performed to determine the type and frequency of contact and downstream visits and interventions. The composite primary outcome of the study included changes to lipid-lowering medications, family screening for FH, and new chart diagnosis of FH. Results: A total of 242 patients from the FH registry were reviewed of which 108 (mean age 55, 69 % women, highest mean LDL-C 267 +/- 47 mg/dL) met the inclusion criteria. A total of 180 patient contact attempts were made (mean 1.7 per patient) with most being by MyChart (48 %) and telephone (41 %). Of those contacted, 35 % had a follow-up visit with a PCP and/or a lipid specialist, and 22 % saw any composite change. Patients whose PCP was contacted were more likely to have adjustments made to their lipid lowering medication(s) (p = 0.016), be diagnosed with FH (p = 0.025), and have a follow-up visit (p = 0.033). A greater number of contacts (2.17 vs 1.52, p < 0.001) was also associated with any composite change in outcome. Conclusions: Approximately 1 in 5 individuals in a large healthcare system who were contacted for a recorded LDL-C > 190 mg/dL had a meaningful improvement in the management of severe hypercholesterolemia and diagnosis of FH. Various process factors were associated with a greater change in clinical care. These data highlight the importance of systematic evaluation to enhance interventions to improve the care of individuals with possible FH.

Background: Familial Hypercholesterolemia (FH) is a genetic predisposition to high LDL-C levels and premature atherosclerotic cardiovascular disease (ASCVD) that remains underdiagnosed and undertreated. We developed a patient registry within the EPIC (Epic Systems Corp., Verona, WI) electronic health record (EHR) system to identify patients who have severe hypercholesterolemia or FH. We illustrate how our platform reveals gaps in treatment and outcomes for these patients across a large academic medical center. Methods: We extracted health information for all living, adult patients from UT Southwestern Medical Center who have ever had an LDL-C >= 190 mg/dL or an FH diagnosis (ICD-10 E78.01) from our FH patient registry. Patients with only laboratory data and no other meaningful encounter or treatment data were omitted from the cohort. We characterized LDL-C levels across the patient cohort and determined the proportion who had seen cardiology or endocrinology, had an FH diagnosis, and received LDL-C lowering therapy. We further analyzed how many patients achieved LDL-C levels at goal (defined as LDL-C < 70 mg/dL for patients with ASCVD or LDL-C < 100 mg/dL for all others in the cohort). Data were extracted from EPIC’s Clarity reporting database. Results: Of the 7026 patients included in our study, the median age was 62 years, 64.5% were female, 56.7% were white, 16.3% had an unknown/declined race, 9.7% were Hispanic, and 14.2% had an unknown/declined ethnicity. The highest LDL-C among the cohort averaged 216.4 (±43) mg/dL. The most recent LDL-C values recorded averaged 158.5 (± 63.7) mg/dL. We found 6.7% of the cohort had an FH diagnosis, 38.1% were seen by cardiology or endocrinology, and 66.6% were prescribed an LDL-C lowering therapy (63.1% any statin, 53% high intensity statin, and 11.8% a non-statin therapy). Additionally, only 19.1% of those receiving treatment achieved LDL-C levels at goal. Conclusion: We showcased how an EHR-integrated patient registry can provide rapid insights into the status of FH and severe hypercholesterolemia care at an institution while also elucidating opportunities for targeted intervention. Since EPIC is the most prevalent EHR system in the United States, our methodology can be readily adopted to improve care of patients with severe hypercholesterolemia and FH on a national scale.

Introduction: In people with T2D and preexisting ASCVD, either SGLT2i or GLP1RA are indicated by treatment guidelines to reduce MACE. We evaluated predictors of prescription of SGLT2i vs GLP1RA in a population eligible for either. Methods: An electronic health record (EHR) based registry was created to identify people with T2D and ASCVD who were indicated either a GLP1RA or SGLT2i for cardiorenal protection within a large, academic health system. Data pertaining to demographics, lab and imaging results, ICD9/10 diagnoses, prescriptions, provider and clinic characteristics were extracted. Eligible encounters occurred in a primary care, endocrinology, cardiology, or nephrology clinic between January 1, 2019 and August 23, 2023. For each eligible encounter where a drug was prescribed, the first treatment type (GLP1RA or SGLT2i) was determined based on medication history. We estimated a logistic regression using stepwise variable selection to identify a best-predicting model and forced the variables of age, sex, and race into the model. Results: A total of 315 patients with T2D and ASCVD were eligible for either treatment and were prescribed one of these medications: 142 were prescribed a GLP1RA and 173 were prescribed SGLT2i. Lower BMI was associated with use of SGLT2i (OR = 0.91, 95% CI 0.87-0.96), as was being an established patient (OR 2.32, 95% CI 1.14-4.72). Compared to treatment in a primary care setting, treatment in a cardiology clinic was strongly associated with prescription of SGLT2i (OR = 7.77, 95% CI 3.18-19.04), whereas treatment in endocrinology clinic was strongly associated with prescription of a GLP1RA (OR = 0.35, 95% CI 0.18-0.68). Area under the receiver operating characteristic curve for the model was 0.82. Conclusion: In a real-world dataset from a large academic center, the selection of guideline directed therapy for patients with T2D and ASCVD was strongly determined by the provider’s specialty, highlighting an important opportunity for education. Disclosure S. Agarwal: None. M.A. Basit: None. M.E. Bowen: Research Support; Boehringer-Ingelheim. D. Heitjan: Consultant; Bluejay Diagnostics, Medcognetics, Sebela, Abbott, Macrogenics, Guardant, Bristol-Myers Squibb Company, Gilead Sciences, Inc. C. Mai: None. K. Marble: None. Z. Xiang: None. I. Lingvay: Consultant; Altimmune, Astra Zeneca, Bayer, Biomea, Boehringer-Ingelheim, Carmot, Cytoki Pharma, Eli Lilly, Intercept, Janssen/J&J, Mannkind, Mediflix, Merck, Metsera, Novo Nordisk, Pharmaventures, Pfizer, Sanofi. Research Support; NovoNordisk, Sanofi, Mylan, Boehringer-Ingelheim. Consultant; TERNS Pharma, The Comm Group, Valeritas, WebMD, and Zealand Pharma. Funding This study was supported by Boehringer Ingelheim Pharmaceuticals, Inc. (BIPI) and Lilly USA, LLC. The authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors (ICMJE) and were fully responsible for all aspects of the trial and publication development.

Background:Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown. Methods:We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC. Results:During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular. Conclusions:We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.

Introduction: The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients. Methods: Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub's EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis. Results: One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; < 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation. Conclusion: Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy.

Background: Growing evidence suggests that intensive lowering of systolic blood pressure (BP) may prevent mild cognitive impairment (MCI) and dementia. However, current guidelines provide inconsistent recommendations regarding optimal BP targets, citing safety concerns of excessive BP lowering in the diverse population of older adults. We are conducting a pragmatic trial to determine if an implementation strategy to reduce systolic BP to <130 and diastolic BP to <80 mmHg will safely slow cognitive decline in older adults with hypertension when compared to patients receiving usual care. Methods: The Preventing Cognitive Decline by Reducing BP Target Trial (PCOT) is an embedded randomized pragmatic clinical trial in 4000 patients from two diverse health-systems who are age >= 70 years with BP >130/ 80 mmHg. Participants are randomized to the intervention arm or usual care using a permuted block randomization within each health system. The intervention is a combination of team-based care with clinical decision support to lower home BP to <130/80 mmHg. The primary outcome is cognitive decline as determined by the change in the modified Telephone Interview for Cognitive Status (TICS-m) scores from baseline. As a secondary outcome, patients who decline >= 3 points on the TICS-m will complete additional cognitive assessments and this information will be reviewed by an expert panel to determine if they meet criteria for MCI or dementia. Conclusion: The PCOT trial will address the effectiveness and safety of hypertension treatment in two large health systems to lower BP targets to reduce risk of cognitive decline in real-world settings.

Lay Summary We describe the development and implementation of a dynamic clinical pathway, the IBD CarePath, integrated into the electronic health record that applies custom risk stratification to identify patients with IBD who are overdue for clinical follow-up.