Objectives/Goals: To develop a personalized computational framework integrating computational fluid dynamics (CFD) and topology optimization for designing intracranial aneurysm implants. The primary objective is to reduce intra-aneurysmal blood flow velocity and enhance thrombus formation for improved treatment outcomes. Methods/Study Population: Patient-specific aneurysm geometries were extracted from pre-treatment rotational angiograms. A CFD-driven topology optimization framework was employed to design implants that reduce intra-aneurysmal flow velocity. The fluid dynamics were modeled using Navier–Stokes equations and the structural integrity of the implants was ensured by linear elasticity equations. The solid isotropic material with penalization (SIMP) method was applied to optimize the implant’s porous architecture, balancing flow reduction with structural support. COMSOL Multiphysics software was used to implement the optimization. Results/Anticipated Results: The optimized implants demonstrated significant reductions in intra-aneurysmal blood flow velocity and improved hemodynamic conditions. Flow velocity within the aneurysm was reduced by 77%, and the fluid energy dissipation ratio showed a 78.9% improvement compared to pretreatment conditions. The optimized porous structures were tailored to the aneurysm’s specific geometry, providing personalized designs that improve flow stasis and thrombus formation. Further validation of the implants will be performed in vitro and in vivo to assess their effectiveness and biocompatibility. Discussion/Significance of Impact: This personalized implant design framework could lead to better treatment outcomes by reducing aneurysm recurrence and complications compared to current devices. It provides a pathway for improved occlusion rates and patient-specific solutions for intracranial aneurysms.

Objectives/Goals: The goal of the RC2 Systems Marketing Analysis for Research Translation (SMART) special innovation program is to develop and test a structured approach for working with research teams and communities to accelerate the translation of clinical and community innovations to address health inequities by integrating social marketing with community-based system dynamics. Methods/Study Population: The SMART program is a consultancy service for CTS teams focused on selecting and tailoring implementation strategies for advancing equity. We use social marketing for understanding the alignment of practice innovation feature sets with community priorities for advancing health equity; and community-based system dynamics to understand and refine the dynamics of scaling up and sustaining the implementation of innovations with sufficient reach to address regional health inequities. The program is implemented as community-engaged group model-building workshops with research teams, with follow-up marketing analyses and computer simulation of implementation strategies of innovations and development of implementation roadmaps. We use developmental program evaluation to revise the SMART program. Results/Anticipated Results: Anticipated results from piloting the SMART innovation program with four research teams include (1) design matrices pre and post-workshop for each innovation; (2) system dynamics simulation models and analyses of implementation and scale-up of innovations; (3) analysis of the SMART program for highest impact, with priors for estimating subsequent SMART program performance; and (4) a revised SMART program based on results from the developmental program evaluation. Discussion/Significance of Impact: This work highlights the feasibility and benefits of combining methods that have been cited in implementation science for understanding the complexity of implementation to accelerate the translation of innovations into clinical and community settings for advancing health equity.

Objectives/Goals: Urinary tract infections (UTIs) cause significant morbidity, and many patients require multiple courses of antibiotics increasing the risk of antibiotic resistance. We determined the prevalence of urinary antibiotic heteroresistance (HR), which has been associated with treatment failures in vivo, to three first-line antibiotics for UTIs. Methods/Study Population: Clinical urine Escherichia coli isolates from patients in metropolitan Atlanta, Georgia in August 2023 were collected as part of public health surveillance performed by the CDC-funded, Georgia Emerging Infections Program (EIP). Only the first E. coli isolate collected for each patient was included in this study. Antibiotic susceptibility was determined through medical record review. HR to nitrofurantoin, trimethoprim-sulfamethoxazole, and fosfomycin was determined by population analysis profiling (PAP), where broth dilutions of E. coli were plated on increasing concentrations of the antibiotic. HR was defined as survival of >1 in 106 cfu but fewer than 50% survival at 1X antibiotic breakpoint (bp), resistant as > 50% survival at 1X bp and susceptible as survival of Results/Anticipated Results: Among 355 patients, 21 (5.9%) were resistant or intermediate to nitrofurantoin and 92 (26%) were resistant to trimethoprim-sulfamethoxazole. Antibiotic susceptibility data were missing from 5(1.4%) and 11(3%) of isolates for nitrofurantoin and trimethoprim-sulfamethoxazole, respectively. Susceptibility testing was not routinely performed nor reported for fosfomycin, thus excluded. PAP revealed that of the total 355 isolates, 3(0.84%) were heteroresistant to nitrofurantoin, 17(4.8%) were heteroresistant to trimethoprim-sulfamethoxazole, and 27(7.6%) were heteroresistant to fosfomycin. Of the isolates found to be susceptible by standard testing, 1(0.3%) and 9(3.6%) were heteroresistant to nitrofurantoin and trimethoprim-sulfamethoxazole by PAP, respectively. Discussion/Significance of Impact: Despite low rates of HR to nitrofurantoin and trimethoprim-sulfamethoxazole (0.84%, 4.8%), HR to fosfomycin was more frequent (7.6%). Given that susceptibility is not generally performed for fosfomycin, this could have implications for including fosfomycin as a first-line treatment for E. coli UTIs.

Objectives/Goals: Here, we utilize deep learning to automate the analysis of dual X-ray absorptiometry (DEXA) scans in the UK Biobank (UKB) imaging dataset to enable a large-scale assessment of lumbar spine disc degeneration, low back pain, and socioeconomic status. Methods/Study Population: Study Population: The UKB is a biomedical database that includes lateral spine DEXA imaging for 50,000 participants. Deep Learning Model Development: A computer vision model was developed that receives a DEXA scan as input and outputs a quadrilateral that corresponds to the corners of 5 lumbar vertebral bodies. The model is a deep, fully convolutional, encoder–decoder network using DeepLabV3. Statistical Analysis: To determine our preliminary model accuracy, we used the intersection over union (IoU) metric.We analyzed data using an ordinal regression model to determine the relationship between income/ neighborhood level multiple deprivation index (MDI) and low back pain (LBP), as well as a mixed effects model to estimate the relationship between income/MDI and disc height index (DHI). Results/Anticipated Results: Our model predicted vertebral body quadrilaterals in training and unseen test data (train IoU  =  0.96, test IoU  = .91) and was used to infer data for 10,440 participants. Confirming previous studies, there were significant relationships (p0.05) between income or MDI and DHI (Figure 2). Discussion/Significance of Impact: Low back pain is the world’s leading cause of disability, and socioeconomic factors play an important role. We found no relationship between disc height index and socioeconomic status. Thus, disc degeneration may not be a factor in this low back pain phenotype.

Objectives/Goals: Present a framework for hosting Community Grand Rounds, where community and academic partners showcase completed community-engaged research (CEnR) projects. This highlights innovative dissemination methods, engages diverse audiences, elicits community responses, and advances the translational science of CEnR. Methods/Study Population: Our approach involves planning and outreach to collaborate with promotion of academic and community engaged grantees to develop community dissemination events that translate the science of CE into accessible, relatable, culturally relevant formats for diverse audiences. These events incorporate interactive presentations that encourage active participation and feedback from attendees. Following each event, an evaluation is completed to assess community impact. Key strategies for hosting, facilitating, and utilizing diverse marketing to ensure that events are tailored to culturally diverse community groups, including regional implementation when practical. This collaborative approach meets a critical need and strengthens the bond between researchers and the communities they aim to serve. Results/Anticipated Results: These events create a feedback loop between the community and academic researchers. It was not just about telling people what was found. We created opportunities for community members and academics to build trust, give us feedback, ask questions, and discuss how findings could be practically applied. By presenting the findings in an accessible way within the community, community members are more informed and empowered to make decisions or advocate for changes in their own lives based on the research. Academics also benefited from community feedback, which provided new insights to help refine future research questions and methods. The goal is for shared conversation and understanding between community members and academics to inspire real-world applications and policy change directly informed by the research. Discussion/Significance of Impact: Community Grand Rounds are one dissemination strategy to leverage community–academic collaboration to present tailored research, fostering engagement, understanding, and action between researchers and community members. This approach effectively enhances the translational science of CEnR by involving and benefiting the community.

Objectives/Goals: Gait performance (GP) and global cognitive functions (GCF) are both critical for maintaining independence and quality of life in senior adults. Recent studies have explored the potential link between GP and GCF, encompassing executive functions. Methods/Study Population: PRISMA guidelines will govern this systematic review. This systematic review synthesizes published research from 2000 to 2024, including peer-reviewed articles, pilot studies, and randomized controlled trials, to examine the relationship between GP (how a person walks and stands) and GCP in older adults. The exclusion criteria will be based on studies focused on physical activities unrelated to balance, meta-analysis, and systematic reviews and those published in languages other than English or Spanish. Results/Anticipated Results: Our preliminary data indicate that gait, or walking speed, is significantly correlated with GCP in older adults, with slower walking associated with poorer global cognition. Specifically, gait speed during dual-task walking shows a strong correlation with working memory (p < .001) and processing speed (p < .05) in individuals aged over 60 years. Gender differences were observed, with women over 80 walking slower than men over 85 years, who walked faster, and women exhibited poorer global cognition than men. Discussion/Significance of Impact: Overall, a gait slowing between 0.68 and 1.1 m per second could predict a marker for the risk of developing dementia, indicating that monitoring gait speed in older adults may provide early warning signs, allowing for timely interventions. Enhancing GP and GCF can improve the quality of life and independence in older adults. Acknowledgments: Research supported by NIH: Award Number HCTRECD R25MD007607 from the NIMHD.

Objectives/Goals: This qualitative study evaluated facilitators and barriers to clinical research participation among lower-income, predominately racial/ethnic minority communities to inform a Co-Learning series. The Co-Learning series of community members, stakeholders, and researchers developed strategies to improve diversity in research. Methods/Study Population: Community focus group (FG) participants were recruited from urban communities experiencing poverty, whereas stakeholder FGs included diverse community leaders and researchers. The Social Ecological Model was used as the guiding theoretical framework throughout the qualitative design. Directed content analysis using three independent coders reaching 100% consensus identified prominent factors for increasing diversity in research. The co-learning series was comprised of community members, stakeholders, and researchers who discussed the prominent FG factors over seven in-person meetings to develop a toolkit to increase diversity in research. Results/Anticipated Results: Community (n = 51) and stakeholder (n = 50) FG participants were 54.0±16.0 years of age, 81.2% female, 39.6% Black/African American, 51.5% Hispanic, and 60% had Discussion/Significance of Impact: Due to the lack of inclusivity in clinical research, findings are typically not applicable to health disparity populations limiting the benefit of research to all. This study provides practical community-driven strategies to increase diversity in clinical research, highlighting the role of trust, relationships, and cultural relevancy.

Objectives/Goals: Second-generation antipsychotics (SGA) are used to treat mental disorders in youth but are linked metabolic syndrome (MetS). Most data on prescribing practices and risk factors are from short-term studies (6–12 months). We aim to characterize prescribing and identify clinical and genetic predictors of MetS using electronic health records (EHR). Methods/Study Population: EHR data were extracted from Cincinnati Children’s Hospital Medical Center (CCHMC) for patients aged ≤21 years prescribed SGAs from 7/1/2009 and 7/1/2024, identifying prescribing prevalence. Next steps are to create an SGA-MetS case–control dataset 8 weeks after an SGA prescription. A case will be defined by meeting 3 of 5 criteria: 1) BMI ≥95th percentile for age/sex; 2) fasting glucose ≥100 mg/dL or use of anti-diabetics; 3) triglycerides ≥110 mg/dL; 4) HDL-C ≤40 mg/dL; 5) systolic/diastolic BP ≥90th percentile for age/sex or use of antihypertensives. The prevalence of SGA-MetS will be calculated by dividing SGA-MetS cases by total SGA users. Logistic regression will identify clinical predictors of MetS, and we will evaluate the association of polygenic risk scores (PRS) of BMI and type 2 diabetes with SGA-MetS risk. Results/Anticipated Results: Our preliminary analysis identified 30,076 patients who were prescribed SGAs (mean age 12 years, SD = 4; 58.8% female; n =  17685). Most self-identified as non-Hispanic (95%, n = 28,595) and of White race (76%; n =  22,935), with 18.5% self-identifying as Black or African American (n = 5,579). The most commonly prescribed SGAs were risperidone (n = 12,382, 41.1%), aripiprazole (n = 9,847, 32.7%), and quetiapine (n = 5,263, 17.5%), with much lower prescribing rates of other SGA known of their low risk of MetS (e.g., ziprasidone 5.5%, lurasidone 1.4%, paliperidone (n = 316, 1.1%), or others cariprazine (n = 72), asenapine (n = 43), brexipiprazole (n = 39), iloperidone (n = 24), and clozapine (n = 20). Discussion/Significance of Impact: Our analyses found that risperidone, quetiapine, and aripiprazole were the most prescribed SGA, with risperidone/quetiapine linked to a higher risk of MetS. We will present ongoing work identifying risk factors for SGA-MetS and examining the association with PRS. Our work has the potential to identify high-risk patients for personalized treatment.

Objectives/Goals: This study aims to evaluate common features of mobile health (mHealth) apps and their role in helping caregivers make health decisions for children. Methods/Study Population: A scoping review of literature on caregivers’ use of mHealth apps (published since 2008) was conducted across 5 databases (i.e., Embase, PubMed, CINAHL, Clinicaltrials.gov, and IEEE Xplore). Selected papers were categorized based on app purposes, target users, and mHealth agile development phases. Common features were also identified and analyzed along with users’ pros and cons. Further, primary feature requests were summarized to inform future development. Results/Anticipated Results: This review included 62 studies. Most apps were about maternity and infant care and specific diseases. Major users were caregivers and pregnant women. Around 20% of papers covered multiple phases in the mHealth agile development lifecycle. The effectiveness/clinical trial (phase III) was the most common. E-learning, personalization and customization, and health tracking features were the three most common features of mHealth apps included in this review. More positive feedback was found regarding features than concerns. Caregivers perceived apps as helpful and empowered them to make informed decisions. Concerns were mainly over 1) technical issues, 2) inappropriate design, and 3) ambiguous terms. Requested new features included content comprehensiveness, user engagement, and usage flexibility. Discussion/Significance of Impact: To our knowledge, this is the first review to investigate the usability of mHealth app features in this area. The results offer feasible strategies for developers to improve the effectiveness of apps for caregiver decision-making.

Objectives/Goals: The goal of this study is to resolve the complexity of the adipose precursor cells and identify potential therapeutic targets/mechanism to treat obesity, diabetes, cancer cachexia, and related metabolic conditions in both white and brown adipose tissues. Methods/Study Population: White and brown adipose precursor cells were isolated from neonatal P0 mice and expanded in culture for single-cell RNA sequencing analysis. Unsupervised machine learning was used to unbiasedly cluster and categorize sequenced cells. Differentially expressed genes were used to identify populations via pathway analysis. Populations were then validated with published datasets via integration, reference mapping, and module scoring to ensure our dataset is reflective of known literature. Then, white and brown datasets were combined and unbiasedly clustered. Finally, signaling inferences using CellChat was used to identify significant signals being sent to and received from each cluster based on ligand–receptor pairs. Results/Anticipated Results: ScRNAseq revealed 7 subclusters in both white and brown adipose tissues. Differential expression and trajectory inferences revealed that white and brown precursors develop into two distinct fates: committed adipogenic precursors (CAPs), where these cells will be mature lipid-laden adipocytes; or fibro-adipogenic precursors-like (FAPLs), where these cells preferably stay in a fibroblast-like, antiadipogenic phenotype. Integrating white and brown cells with subsequent reclustering reveals that white and brown FAPLs are highly similar to one another by being clustered together. Cell signaling inferences and pathway analysis reveal that white and brown FAPLs may participate in the regulation of adipogenesis and angiogenesis of the adipose tissue. Discussion/Significance of Impact: Our results demonstrated that brown and white precursor cells share a common regulatory subpopulation with similar gene expression profiles, highlighting a more interconnected regulatory landscape in adipose tissue than previously understood. These findings reveal novel mechanisms of systemic metabolism and provide new therapeutic targets.

Objectives/Goals: Our goal for this project is to develop a metric that integrates the intersectional social and structural determinants of health and well-being into the existing policy development framework to impact the integration of such considerations on population mental health. Methods/Study Population: This project was developed from a case study module offered by the Translational Research Program at the University of Toronto. This course was designed to sharpen contextual inquiry skills and further develop a case through employing strategies, including outreach engagement with stakeholders, conducting informational interviews and formulating potential pathways forward based on the integration of insights from interdisciplinary perspectives. Results/Anticipated Results: The anticipated outcome would be improved mental health outcomes as measured by the Mental Health Commission of Canada’s Mental Health Indicators (Mental Health Commission of Canada, 2015) Discussion/Significance of Impact: Although there are established mental health indicators and policy development framework the two operate independently of each other. Our proposal bridge the gap between the sectors so that one may inform the other, and they can collectively formulate reflective and representative policies.

Objectives/Goals: The goal of the Accelerated Staff Assist Program (ASAP) is to help fill staffing gaps in clinical and translational research. The program offers centralized staff to fill short-term needs including project startup prior to hiring, project implementation, parental leave, and Spanish-language research support. Methods/Study Population: Promotion of ASAP in the first year was targeted to Penn State College of Medicine faculty to determine demand. Current outreach includes promotion to all Penn State campuses through PSCTSI’s newsletter, seminars, and presentations. Consultation intake data includes a project summary, staffing needs, and funding information. A project agreement, charter, and budget are drafted and agreed to by the principal investigator before work begins. Assessments occur at 6 and 12 months to assess satisfaction of the consultation process and quality of staff support, Net Promoter Score, and qualitative feedback about the program. Results/Anticipated Results: In its first year, ASAP conducted 26 consultations and supported 10 projects. Approximately 75% of staff effort has been recovered through agreements during the most recent 6 months. In anticipation of project delays, we found that booking FTE up to 115% results in a consistent recovery of 75% FTE. Consultee needs include short-term, partial effort support (76% of requests), project start-up (12%), staff leave (4%), and other (8%). ASAP staff tasks include participant recruitment and retention, data collection and analysis in English and Spanish, and community engagement for recruitment. Program assessments with research teams are ongoing; preliminary qualitative and quantitative data are unanimously positive. Discussion/Significance of Impact: The ASAP program has demonstrated fiscal success and sustainability in its first year. Hiring of a well-qualified, bilingual staff person allowed for quick onboarding and project support within one month of hire. ASAP enables CTSI to fulfill our mission by providing critical support for research teams to meet objectives and achieve equity goals.

Objectives/Goals: To develop an informatics framework that will allow study of environmental effects on stillbirth at large scale (i.e., US-level) and leverage recent advances in machine learning and artificial intelligence to produce reproducible results that can be compared across multiple institutional settings. Methods/Study Population: Experimental exposure data are often available in “absolute time,” where a clinical event can be anchored using a timeline transformation. We associate each stillbirth event with a set of {ti…ti+1}L shapelets [1] associated with a location, L, and time intervals for the entire dataset. These shapeless are aggregated using a state-of-the-art shapelet classifier [2]. An autoencoder is used to reduce the dimensionality of the stillbirth classification and to cluster stillbirth events according to their corresponding exposure patterns. The stillbirth cluster can be analyzed for other nonexposure (i.e., genetic, SDoH, and demographics) factors, which may be enriched and/or depleted. Results/Anticipated Results: The framework we are developing leverages a shapelet-based approach to produce clusters of stillbirth events according to their corresponding exposure patterns. These clusters can be analyzed for depletion or enrichment of nonenvironmental factors. This analysis will inform how to formulate (or not) class models of exposure that can be more informative and have better predictive power than overall population models. Moreover, the finding of depletion and enrichment of physiological properties of the individuals may lead to novel physiological hypotheses to better understand the injury mechanisms that the environmental exposure profile produces. Discussion/Significance of Impact: Nearly 20,000 babies are stillborn in the USA each year [3]. Environmental exposures, usually studied as time averages over certain periods of time, have produced mixed results for stillbirth risk [4]. However, temporal profiles matter [1], and we argue that they can be assessed using shapelet technology.

Objectives/Goals: Glucagon-like peptide-1 (GLP1) use prior to bariatric surgery may represent a novel approach to treating obesity. The objectives of this study were to describe trends in pre-bariatric GLP1 use, investigate social and clinical factors associated with their use, and evaluate differences in clinical outcomes based on preoperative GLP1RA use. Methods/Study Population: Patients who underwent bariatric surgery at three Indiana hospitals from 2018 to 2023 were identified. Patients who utilized GLP1 in the year preceding surgery were compared to those who did not. Social determinants of health included insurance, income, and unemployment. Outcomes included rates of GLP1 use, 30-day postoperative readmissions, ED visits, and percent total weight lost (%TWL) at one year. Associations between preoperative GLP1 use and outcomes of interest were evaluated using multivariable logistic and linear regressions. Results/Anticipated Results: Of 2,169 patients who underwent surgery, 293 (13.5%) utilized GLP1 preoperatively. The rate of GLP1 utilization increased threefold from 2018 to 2023. Males were more likely to receive preoperative GLP1 (20.1% vs, 12.2%, p<0.001). There were no significant differences in social determinants of health or 30-day postoperative outcomes between patients who did and did not use GLP1RA preoperatively. Similarly, there were no significant differences in %TWL at one year postoperatively between groups (median 25.5% vs. 27.3%, coefficient: -0.78, 95%CI: -2.26–0.70). Discussion/Significance of Impact: Utilization of GLP1 in the year prior to bariatric surgery has significantly increased. Preoperative GLP1 use is not associated with worse 30-day outcomes or differences in %TWL at one year postoperatively. Further work is needed to evaluate whether GLP1 dosing and duration of treatment impact postoperative outcomes.

Objectives/Goals: Delving into the intricate web of translational research collaborations, this study analyzed the evolving landscape of the Hispanic Alliance of Clinical and Translational Research from 2020 to 2024 using cutting-edge social network analysis (SNA). SNA is a powerful tool for visualizing, understanding, and harnessing the power of networks. Methods/Study Population: We conducted a systematic document review of all the Alliance IDeA-CTR Network Calls for Pilot Projects from 2020 to 2024 including key attributes of the investigators and collaborators (e.g., academic institution, highest degree, collaborator type). Scientific collaboration was defined as two or more researchers working together in a grant proposal for a pilot project application. Study data was recorded and tracked using an Excel spreadsheet. R-Statistical software was used to analyze and map the networks resulting from collaboration interactions comparing the 2020 Call and 2024 Call. Network statistics were performed including nodes, isolates, edges, components, density, diameter, average degree, and the size of the main component. Results/Anticipated Results: Within a vibrant network comprising over 150 investigators from local and national academic institutions, clinicians (49.3%), and basic researchers (25.4%) are predominant. Initial findings showcase a remarkable surge in interdisciplinary collaborations and affiliations over time. Preliminary findings demonstrated that the number of nodes/actors increased from 16 to 75 comparing 2020 to 2024 and the edges/relationships from 12 to 66. Notably, the number of translational research clusters surged from 4 to 18, with mentorship emerging as a critical conduit bridging diverse research clusters; 16 to 78 nodes in comparison from 2020 to 2024. More extensive collaborative clusters occurred across time with over 20 researchers collaborating. A mentor was the main actor connecting these research clusters. Discussion/Significance of Impact: This study unveils the intricacies and power of translational research dynamics, showing a palpable surge in collaboration diversity and depth. By harnessing data-driven insights, our approach catalyzes informed decision-making to amplify collaboration, diversity, and network efficacy, offering invaluable guidance for policy and practice.

Objectives/Goals: To determine the heterogeneity in CD4:CD8 ratio in a well-characterized cohort of PWH and to investigate the predictors of intestinal CD4:CD8 ratio reconstitution (CD4:CD8>1) and its impact on systemic inflammation. Methods/Study Population: We enrolled 52 PWH on ART and with peripheral HIV-RNA Results/Anticipated Results: PWH had a lower CD4:CD8 ratio both in the peripheral blood [p1. This subset of PWH was more likely female (62% vs. 38%, p = 0.0158), diagnosed with HIV for a longer time [p = 0.0347] have longer duration of most recent viral suppression [p = 0.0365] higher CD4+ T cells at enrollment [p =  0.0262] and higher CD4+ T cell nadir. Multiple logistic regression showed that duration of HIV infection [OR 1.13 (95% C.I. 1.02–1.3)] and CD4 =  T cell nadir[OR 1.01 (95% C.I. 1.001–1.016)] were associated with colonic CD4:CD8 >1. Colonic CD4:CD8 ratio partially correlated with the peripheral blood CD4:CD8 ratio (r = 0.274, p = 0.068) and with the pro-inflammatory cytokines IL-20 (r =  -0.413, p = 0.036) and SLAMF-1 (r =  -0.329, p = 0.074). Discussion/Significance of Impact: In PWH, CD4:CD8 ratio

Objectives/Goals: Some children with asthma benefit from care from asthma specialists: allergist/immunologists or pulmonologists. However, a limited supply of specialists poses access problems for some children. Our objective was to describe the state of specialist care for pediatric asthma in Maine. Methods/Study Population: Using Maine all-payer claims data for April 2018–April 2021, we identified children with asthma meeting criteria for subspecialist referral based on NIH Expert Panel Report criteria. We determined which of these children had encounters with an allergist-immunologist or pediatric pulmonologist during the study period and performed logistic regressions to determine what demographic traits were associated with receipt of care. Results/Anticipated Results: Among children meeting criteria for specialists referral, 33% had an encounter with an asthma specialist. Specialist encounters were associated with younger age (p<0.001) and male sex (p = 0.003). Encounters were negatively associated with Medicaid insurance (versus commercial, p<0.001) and living in more rural areas (RUCA codes 4–10, p<0.001), lower childhood opportunity index (high or less, <0.001), and longer travel time to pediatric asthma specialists in Maine (<0.001). Discussion/Significance of Impact: Specialist care for children with complex or severe asthma is an evidence-based practice that is not equally accessible to all children in Maine. This may restrict their access to specific asthma therapies such as allergic desensitization and monoclonal antibodies.

Objectives/Goals: Professional coaching greatly enhances faculty personal and professional development through fostered empowerment and a culture of continuous growth within the academic environment. The UMN Clinical and Translational Science Institute (CTSI)’s coaching program provides a variety of coaching formats (1:1, group, special programs). Methods/Study Population: CTSI provides professional coaching to faculty in the KAP, K12, KL2, and K-R01 and NLITeS programs. Typically, coaching begins with a HoganLead™ assessment and debrief. Scholars may pursue further coaching through individual sessions (up to 6 sessions during or 1-year post CTSI award) or a monthly peer coaching group facilitated by certified coaches. New URM faculty hires in the Early Career Research Awards (ECRA) program receive monthly coaching support to problem solve and attend to wellbeing. The NLITeS leadership development program for senior and mid-career faculty includes the HoganLead debriefing and 1–2 individual coaching sessions. All sessions are confidential. Results/Anticipated Results: Since 2016/2017, 80 scholars have taken the HoganLead assessment (72 debriefs), and 23 scholars have made use of 217 individual coaching sessions (most use between 6 and 12). Since 2021, 10 Scholars have participated in the Peer Coaching Group with 7 continuing over multiple years. Since 2021, 12 ECRA scholars have been supported in monthly coaching. Frequent coaching topics include self-awareness, work-life balance, overwhelm, negotiation, and leaving academic medicine. Scholar comments include: “I initially approached this professional coaching with some curiosity but fairly minimal expectations that it would change much. It has reshaped the way I approach my academic career and its associated challenges for the better, giving me confidence that I can handle the unique challenges that this career presents…” Discussion/Significance of Impact: The UMN CTSI coaching programs are extensively used and highly valued by participating faculty. Professional coaching with Hogan assessments provides faculty scholars with support that complements the mentoring they receive by going beyond a teach and learn model.

Objectives/Goals: The overarching goal of the GRAMM study is to address racial health disparities by increasing access to genetic counseling and testing among the Black community. Specific objectives are to determine patient acceptability of risk assessment at time of mammography and to evaluate subsequent access to and uptake of genetic counseling and testing. Methods/Study Population: All women presenting for screening mammography at the Ypsilanti Health Center under the University of Michigan were invited to enroll. After providing written informed consent, study participants entered family cancer and personal health information in the InheRET software tool which links to the National Comprehensive Cancer Network genetic testing guidelines. Upon completion, each participant was informed immediately if they did or did not meet the criteria to meet with a genetic counselor. For those who met the criteria, referral to genetic counseling was provided. All enrollees were invited to complete a post-assessment survey on acceptability of the service and genetics knowledge. Patients will be followed over time for completion of genetic counseling and testing. The study was approved by the Umich IRB. Results/Anticipated Results: As of 10/18/24, a total of 53 were enrolled, with 52 eligible for the study and were between the ages of 30–75 years. 51 identified as women and 1 identified as nonbinary. 21 (40.4%) identified as Black, 30 (57.7%) identified as White, 2 (3.8%) identified as Hispanic, and 1 (1.9%) identified as mixed race. Of the total enrolled, 25 (48.1%) met criteria to meet with a genetic counselor. Twelve (23.1%) have been scheduled to with meet with a genetic counselor and 2 (3.8%) of this group completed their appointment, but did not pursue genetic testing. 28 (53.8%) completed the survey and reported that they were satisfied with the service. Of the 16 people who screened positive and completed the survey, all 16 (100%) stated that they intended on proceeding with testing. Our study is still ongoing. Discussion/Significance of Impact: While this model has demonstrated acceptability so far, there are still possible barriers to genetic counseling and testing after the referral has been provided that need to be explored. However, this approach could provide a novel framework for combining risk assessment with screening mammography for all women nationwide.

Objectives/Goals: In alignment with the Clinical and Translational Science Awards (CTSA) UM1, continuous quality improvement (CQI) needs to be integrated into the elements and hub evaluation. As a first step to operationalizing this process, the University of Cincinnati hub (CCTST) evaluation team developed a systematic approach to prioritizing and sequencing tasks for aligning evaluation methods with CQI. Methods/Study Population: A scoring sheet was developed to provide a framework for prioritizing and developing the sequence and timeline for supporting elements in aligning their evaluation methods with CQI. The scoring sheet assessed: 1) impact – defined as the results from completing the task and implementing enhancements; 2) effort – defined as the amount of resources (time, personnel, and materials) needed to complete the tasks; 3) reach – defined as number of individuals (e.g., CTSA employees, members, researchers, trainees, and community members) impacted by the tasks or products of the tasks; 4) urgency – defined as a task that is time-sensitive due to a deadline and has a clear consequence if not completed on time. Each component was assessed using a 3-point scale (e.g., minimal, moderate, and high). Results/Anticipated Results: In Fall 2024, the CCTST evaluation team met with respective elements to collect data on their: 1) need from the evaluation team to support aligning their evaluation methods with CQI, 2) challenges and barriers to improving evaluation and aligning with CQI methods, 3) number of hours per month available to support improving evaluation methods, and 4) current resources to dedicated to conducting an evaluation. Next, the evaluation team will transcribe the data from the meetings and code the data into the scoring sheet for each element. The scoring sheet is anticipated to produce a score that will be used to develop the sequence, timeline, and initial tasks for supporting elements in improving evaluation methods and aligning with CQI over the first year of the UM1. Discussion/Significance of Impact: CTSA hubs’ evaluation teams operating at full capacity may encounter barriers to implementing CQI efforts. This systematic approach – assessing the impact, effort, reach, and urgency to sequence evaluation and CQI alignment – can support evaluation teams by ensuring a balanced workload and optimizing operations for quality improvement.