OBJECTIVES/GOALS: In line with NCATS funding requirements, the Michigan Institute for Clinical and Health Research (MICHR) established a continuous quality improvement (CQI) process and used the process to guide the implementation of a benchmarking project to evaluate and set goals for MICHR’s production of Clinical and Translational Science manuscripts. METHODS/STUDY POPULATION: We aimed to increase the number of Clinical and Translational Science papers MICHR produces and to set a reasonable goal for improvement. Benchmarking was used to obtain a baseline and inform the identification of a reasonable goal for improvement. 11 Peer institutions were identified with similar funding levels. 1,225 Publications from 2022 for all 12 CTSAs were obtained from NIH Reporter. All publications were reviewed by title to identify probable CTS content. Two staff reviewers confirmed a total of 108 CTS publications across all CTSAs, and coded each paper to characterize the theoretical approach, method (quantitative and/or qualitative), analytic method and topic. All publications that were selected for benchmarking were also tracked and compared using Altmetrics for Institutions and Overton platforms. RESULTS/ANTICIPATED RESULTS: A total of 108 CTS publications were produced by 12 benchmarked CTSAs in 2022; of those, 70% (77) regarded research infrastructure, 37% (41) regarded research methods, and 15% (16) regarded clinical care. Over half, 53% (58), of the benchmarked papers are empirical research papers; of those, 67% (39) used quantitative methods, 28% (16) used qualitative methods, and 5% (3) used mixed methods. A clear majority of the benchmarked papers, 70% (76), provided only descriptive analyses, 18% (19) provided inferential analyses, and 12% (13) provided predictive analyses. We identified an opportunity to produce more manuscripts with descriptive analyses of research infrastructure. In the long-term, we saw an opportunity to produce predictive analyses of translational initiatives designed to impact clinical care. DISCUSSION/SIGNIFICANCE: The benchmarking results helped MICHR identify goals for its production of Clinical and Translational Science to fill gaps in the field. Expanding the scope of this benchmarking project might achieve greater interrater reliability using larger representative sets of publications drawn from institutions across the CTSA Consortium.

OBJECTIVES/GOALS: - Illustrate findings of a translational science case study of multi-pronged research aimed at understanding of social determinants in health disparities and integrating patient-centered technology; - Illuminate translational mechanisms by analyzing and sharing research challenges, facilitators, and benefits. METHODS/STUDY POPULATION: Utilized novel TS evaluation methods and tools: - Translational Science Case Study protocol to examine translational path from innovation to practice, barriers and facilitators for that translational movement. - Translational Science Benefits Model (TSBM) Checklist for translational/research impact analysis. Triangulated diverse data sources: - Primary data: semi-structured interviews with research partners. - Secondary data: researchers’ grant applications, reports, and publications; public stories/news related to their research; scientific publications; organizational/policy documents; and interviews with research stakeholders featured in published sources. RESULTS/ANTICIPATED RESULTS: Translational challenges include: culturally tailored education and outreach; data analysis and intervention planning; engaging community stakeholders in the development and implementation; addressing economic and resource-related challenges. Translational facilitators are: UMN CTSA funding and other support; access to data and resources; use of open-source materials; evidence-based/best practice approaches; diversity and collaboration between researchers, community organizations, healthcare providers; researchers’ drive to translate. The research contributes to community and public health, clinical/medical, and economic benefits, health equity advocacy, catalyzing further research, and public awareness. DISCUSSION/SIGNIFICANCE: The evaluation case study contributes to translational science by providing evidence and lessons learned related to translational benefits, challenges, and facilitators of community-based, patient-centered research bringing people, knowledge, and technology together and contributing to health equity.

OBJECTIVES/GOALS: Empowering the Participant Voice (EPV) is a 6-CTSA Rockefeller-led collaboration to developcustom REDCap infrastructure to collect participant feedback using the validated Research Participant Perception Survey (RPPS), demonstrate its value in use cases, and disseminate it for broad adoption. METHODS/STUDY POPULATION: The EPV team developed data and survey implementation standards, and specifications for the dashboard and multi-lingual RPPS/REDCap project XML file. The VUMC built a custom At-a-Glance Dashboard external module that displays Top Box scores (percent best answer), with conditional formatting to aid analysis, and response/completion rates. Results populate site dashboards, and aggregate to a multi-site dashboard for benchmarking. Results can be filtered by participant/study characteristics. Sites developed individual use cases, leveraging local infrastructure, initiatives and stakeholder input. Infrastructure and guides were designed for dissemination through public websites. RESULTS/ANTICIPATED RESULTS: Five sites sent 23,797surveys via email, patient portal or SMS. 4,133 (19%) participants diverse in age, race, and ethnicity, returned responses. Sites analyzed their data and acted on selected findings, improving recruitment, communication and feeling valued. Aggregate scores for feeling listened to and respected were hight (>90%%); scores for feeling prepared by the consent process were lower (57-77%) and require action. Some groups experiences were better than others. Sites differed significantly in some scores. Dissemination of EPV is underway. Infrastructure and guides are downloadable free of charge, with advice from the EPV team. In 2023, a sixth site began piloting a lower literacy survey version and syncing data to the consortium dashboard. DISCUSSION/SIGNIFICANCE: The EPV RPPS/REDCap infrastructure enabled sites to collect participant feedback, identify actionable findings and benchmark with peers. Stakeholders and collaborators designed and tested local initiatives to increase responses and diversity, address disparities, and discover better practices.

Enrollment into a prospective cohort study of mother–preterm infant dyads during the COVID-19 pandemic progressed slower than anticipated. Enrollment occurred during the first week after preterm birth, while infants were still hospitalized. We hypothesized that slower enrollment was attributable to mothers testing positive for COVID-19 as hospital policies restricted them from entering the neonatal intensive care unit, thus reducing interactions with research staff. However, only 4.5% of 245 screened mothers tested COVID-19 positive. Only 24.9% of those screened, far fewer than anticipated, were eligible for enrollment. Assumptions about pandemic-related enrollment barriers were not substantiated in this pediatric cohort.

OBJECTIVES/GOALS: Securing seed funding and external support can be a daunting process. Institutions are increasingly looks for quantitative assurance of impact and accountability. This study investigates factors predictive of seed funding selection, including pace of submissions as well as external support. METHODS/STUDY POPULATION: Using Generalized Logistic Mixed Models (GLMMs), we model factors found to be predictive of researcher success, and model demographic factors as well, to understand the complex interplay of researcher background, professional networks and preparation, and researcher persistence. The following factors were modeled as potentially predictive of researcher success: faculty rank; co-PI; h-index; rate of application; prior award funding amounts; and research-focused social media posts. RESULTS/ANTICIPATED RESULTS: After effects are finalized, we expect that pace of seed fund applications and the strength co-PIs, as measured by h-indices, to be significant predictors of researcher success for both securing seed funding and external support. DISCUSSION/SIGNIFICANCE: This study identifies features associated with eventual research program success and can be used to support accountability and impact efforts at an institutional level. Research institutes strive to ensure equal access to these opportunities and train applicants to produce improved project proposals. Results from this study inform these efforts.

OBJECTIVES/GOALS: Using the NIH’s expanded definition of underrepresented populations in the biomedical, clinical, behavioral and social science research enterprise, we examined the impediments for conducting translational research experienced by those from underrepresented groups. [https://acts.slayte.com/calls/detail/740a13de-316c-11ee-90f4-0e0ce905385c/draft/389221c1-434e-11ee-90f4-0e0ce905385c#_ftn1] #_ftn1 METHODS/STUDY POPULATION: One hundred and ninety-nine people completed a survey distributed to 750 persons who had interacted with our Center’s service cores as users, awardees, mentors, committee members, seminar attendees, and/or participated Center sponsored programming (response rate = 26.5%). The survey addressed barriers to conducting clinical and translational research at the respondent’s institution, awareness of and interest in using specific Advance RI-CTR services, and satisfaction with their institution’s efforts to support clinical and translational research. RESULTS/ANTICIPATED RESULTS: Women reported access to collaboration across institutions as a barrier to clinical and translational research that existed to a great extent (28%) significantly more than men (10%). More than half (53%) of the other underrepresented researchers surveyed identified insufficient grant administration supportas a barrier that occurs to a great extent, compared with 35% of researchers who were not from an underrepresented group. Other barriers reported more frequently among underrepresented researchers included lack of pilot project funding, inadequate space for conducting research, lower access to collaborators across institutions, and difficulty obtaining advice on regulatory issues and commercial development. DISCUSSION/SIGNIFICANCE: Efforts to address the barriers identified by underrepresented groups will include, but not be limited to, improving collaborations across institutions, support for grant administration, and a discussion of plans for the Center to augment and advocate at the partner institutions on behalf of these underrepresented individuals.

Underrepresentation of people from racial and ethnic minoritized groups in clinical trials threatens external validity of clinical and translational science, diminishes uptake of innovations into practice, and restricts access to the potential benefits of participation. Despite efforts to increase diversity in clinical trials, children and adults from Latino backgrounds remain underrepresented. Quality improvement concepts, strategies, and tools demonstrate promise in enhancing recruitment and enrollment in clinical trials. To demonstrate this promise, we draw upon our team’s experience conducting a randomized clinical trial that tests three behavioral interventions designed to promote equity in language and social-emotional skill acquisition among Latino parent–infant dyads from under-resourced communities. The recruitment activities took place during the COVID-19 pandemic, which intensified the need for responsive strategies and procedures. We used the Model for Improvement to achieve our recruitment goals. Across study stages, we engaged strategies such as (1) intentional team formation, (2) participatory approaches to setting goals, monitoring achievement, selecting change strategies, and (3) small iterative tests that informed additional efforts. These strategies helped our team overcome several barriers. These strategies may help other researchers apply quality improvement tools to increase participation in clinical and translational research among people from minoritized groups.

OBJECTIVES/GOALS: In 2021, Frontiers CTSI revamped its evaluation infrastructure to be comprehensive, efficient, and transparent in demonstrating outputs and outcomes. We sought to build a platform to standardize measures across program areas, integrate continuous improvement processes into operations, and reduce the data entry burden for investigators. METHODS/STUDY POPULATION: To identify useful metrics, we facilitated each Core’s creation of a logic model, in which they identified all planned activities, expected outputs, and anticipated outcomes for the 5-year cycle and beyond. We identified appropriate metrics based on the logic models and aligned metrics across programs against extant administrative data. We then built a data collection and evaluation platform within REDCap to capture user requests, staff completion of requests, and, ultimately, request outcomes. We built a similar system to track events, attendance, and outcomes. Aligning with other hubs, we also transitioned to a membership model. Membership serves as the backbone of the evaluation platform and allows us to tailor communication, capture demographic information, and reduce the data entry burden for members. RESULTS/ANTICIPATED RESULTS: The Frontiers Evaluation Platform consists of 9 redcap projects with distinct functions and uses throughout the Institute. Point-of-service collection forms include the Consultation Request Event Tracking. Annual Forms include a Study Outcome, Impact, and Member Assessment Survey. Set timepoint collections include K & T application, Mock Study Section, and Pilot grant application submission, review, and outcomes. Flight Tracker is used to collect scientific outcomes and integrated with the platform. Using SQL, the membership module has been integrated into all forms to check and collect membership before service access and provide relevant member data to navigators. All relevant data is then synched into a dashboard for program leadership and management to track outputs and outcomes in real-time. DISCUSSION/SIGNIFICANCE: Since the launch of the evaluation platform in Fall 2022, Frontiers has increased its workflow efficiency and streamlined continuous improvement communication. The platform can serve as a template for other hubs to build efficient processes to create comprehensive and transparent evaluation plans.

OBJECTIVES/GOALS: Policy makers are interested in understanding scientific collaborations that translate knowledge into population health. The objective of this study is to compare the translational research collaboration of the Hispanic Alliance of Clinical and Translational Research in 2020 and 2023 by using Social Network Analysis (SNA). METHODS/STUDY POPULATION: We conducted a systematic document review of all the Hispanic Alliance Calls for Pilot Projects from 2020 to 2023 including key attributes of the investigators and collaborators such as academic institution, highest degree, and collaborator type. Scientific collaboration was defined as two or more researchers working together in 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 2023 Call. Network statistics were performed including nodes, isolates, edges, components, density, diameter, average degree, and the size of the main component. RESULTS/ANTICIPATED RESULTS: A total of 134 investigators comprised the overall network. The network are predominantly clinician (49.3%) and basic researchers (25.4%). Preliminary results shows that diversity of disciplines and affiliations in the collaborative relationships increased across time. Findings demonstrated that the number of nodes/actors increased from 16 to 65 comparing 2020 to 2023 and the edges/relationships from 12 to 53. The number of translational research cluster increased from 4 to 13 comparing 2020 to 2023. More extensive collaborative cluster occurred across time with over 15 researchers collaborating. A mentor was the key player connecting these research clusters. DISCUSSION/SIGNIFICANCE: This study provides critical data to mapping the IDeA CTR translational research collaboration patterns. Research collaboration increased across time. This innovative approach serves to foster data-driven decision-making to enhance collaboration, diversity, and program outcomes. It offers valuable insights for policy and practice.

OBJECTIVES/GOALS: An academic medical library evaluated an EHR data abstraction service by assessing uptake and publication metrics, including use by department, purpose of data abstraction requests and publication counts. METHODS/STUDY POPULATION: The evaluation included 167 requests for EHR data processed by the institution’s clinical research data management unit (CRDMU) and recorded in an intake form hosted on REDCap. These requests originated from various departments. The intake forms collected investigator and study information, as well as request completion dates. Information in the intake forms were matched with publications and meeting abstracts that were indexed in a database of faculty publications. Investigators who submitted EHR data requests that could not be readily matched to publications were contacted to verify the status of their studies and any associated publications. RESULTS/ANTICIPATED RESULTS: The evaluation included 167 data requests submitted to the CRDMU between 2016 and 2018. These requests were categorized into the following use cases: retrospective studies (n=93); patient recruitment (n=50); and 'other' (i.e., education, training, or process improvement; feasibility assessments; machine learning (n=14)). By the end of the evaluation period, an average of four years after the data requests were submitted to the CRDMU, 60 of all 167 EHR datasets (35.9%) led to publications as articles or meeting abstracts. 64.5% of the EHR datasets requested for retrospective studies, 56% of the datasets requested for recruitment, and 79.1% of datasets requested for other uses did not lead to publications. DISCUSSION/SIGNIFICANCE: These findings offer evidence that bibliometrics alone provide limited insight into the value of services and data utilized for secondary research. Data ecosystem stakeholders are encouraged to consider—and develop—scalable, reproducible, and more holistic assessments of the impact of their services.

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) was an extraordinary example of a public-private partnership (PPP) that brought together over thirty organizations and hundreds of individuals to address one of the most pressing global health needs in recent decades. In particular, ACTIV provided a key avenue for testing numerous therapeutics for their potential benefit in treating the SARS-CoV-2 virus or the resulting symptoms of acute COVID-19 infection. Given the speed and scale at which ACTIV designed and implemented master protocols across global networks that it was simultaneously working to create, the PPP can provide valuable lessons for best practices and avoiding pitfalls the next time the world is faced with a global pandemic of a novel pathogen. This report provides a general overview of the ACTIV partnership to set the stage and context for the subsequent articles in this issue that will relay these lessons learned.

OBJECTIVES/GOALS: METHODS/STUDY POPULATION: Utilized novel TS evaluation methods and tools: - Translational Science Case Study protocol adapted to examine translational support service practices, barriers and facilitators influencing translational movement. - Translational Science Benefits Model (TSBM) Checklist elements for translational/research impact analysis. Triangulated diverse data sources: - Primary data: semi-structured interviews with translational service stakeholders. - Secondary data: service’s applications, reports, and publications; public stories/news related to their research support; scientific publications; organizational/policy documents; and interviews with research stakeholders featured in published sources. RESULTS/ANTICIPATED RESULTS: Translational challenges include: complexity and constant change of health data; lack of data/informatics literacy amongst researchers; limited appreciation and funding for research data services; silos of functionality and data related to biomedical informatics. Translational facilitators are: the UMN CTSA support; available infrastructure and knowledge base; researchers as the best promoters for services; multidisciplinary collaborations with research/community/healthcare teams; best practice approaches; and learning by doing. The translational/research support service contributes to community and public health, clinical/medical benefits, data literacy, catalyzing data-rich research, and health equity. DISCUSSION/SIGNIFICANCE: The evaluation case study provides evidence and lessons learned related to translational benefits, challenges, and facilitators of a successful translational research support service integrating best informatics practices in clinical research and contributing to health equity improvement.

The Accelerating COVID-19 Therapeutic Interventions and Vaccines Therapeutic-Clinical Working Group members gathered critical recommendations in follow-up to lessons learned manuscripts released earlier in the COVID-19 pandemic. Lessons around agent prioritization, preclinical therapeutics testing, master protocol design and implementation, drug manufacturing and supply, data sharing, and public–private partnership value are shared to inform responses to future pandemics.

OBJECTIVES/GOALS: The objective of this initiative was to promote MICHR staff’s production of Clinical and Translational Science publications. MICHR leadership approved this initiative, including an evaluation plan with measurable outcomes goals, and contracted with an experienced scientific writing coach with over 20 years of experience working with CTSAs. METHODS/STUDY POPULATION: A sequential mixed methods program evaluation designs was used. Pre- and post-surveys were used to measure participating staff’s gain in skill, understanding & satisfaction. An interview with the instructor was then conducted to characterize staff performance, and identify possible areas of programmatic improvement. This initial phase of the program evaluation was conducted in the Summer of 2023. The results were used to inform an expansion of the program to include more staff in the the Fall of 2023. Pre- and post-program surveys of the participants were conducted and interviews with each program participant were conducted. Finally, interviews with non-participating staff were conducted to assess their need for writing support and the challenges and facilitators of their scientific writing. RESULTS/ANTICIPATED RESULTS: Preliminary evaluation results obtained in the summer of 2023 were positive. All participants completed the course, and spent an average of 3.3 hours working between sessions. Six manuscripts were developed, five of which are being readied for submission and one submitted as of August 2023. Analysis of the pre-and post-program surveys indicated that all participants gained writing skill and authorship knowledge. Specifically, they gained confidence in 7 writing skills and 6 first-author roles evaluated during the course. All participants were satisfied with their experience and recommended the course to their colleagues, and the course instructor was also satisfied with the course. However, the participants noted that competing work demands and variable preparation hindered their work in the course. DISCUSSION/SIGNIFICANCE: With the increasing focus on Clinical and Translational Science taking place across the CTSA Consortium it is important to involve research staff in paper writing teams, including in first-author roles. Professional development in scientific writing can support Clinical and Translational Research staff contributing to this emerging science.