OBJECTIVES/SPECIFIC AIMS: Lead (Pb) exposure can seriously affect nervous system and kidney. Young children are vulnerable to Pb exposure. However, the role of low-level Pb exposure in asthma in children and the age and racial disparity is not well studied. The objectives are to examine the relation between Pb level and asthma status and to determine the age and racial/ethnic differences in this relation. METHODS/STUDY POPULATION: We analyzed data from National Health and Nutrition Examination Survey 1999-2016 for 22,885 children 1-15 years old. Asthma information was collected by questionnaire. Blood lead level was measured using mass spectrometry. The association between blood Pb level and asthma status was assessed by logistic regression after adjusting for children’ age, gender, race/ethnicity, insurance status, and source of care; household poverty, mother’s age and smoking status. Data were analyzed using Stata 14 considering design and sample weight and p<0.05 is statistically significant. RESULTS/ANTICIPATED RESULTS: Pb level was associated with asthma status (Adjusted Odds Ratio (AOR)=1.4, 95% Confidence Interval (CI) = 1.2-1.7, p < 0.001). Stratified analysis by age showed that blood Pb level is related to asthma only in children 1-5 years old (AOR = 1.3, 95% CI = 1.1-1.5, p = 0.004). There was no racial/ethnic difference in this association. DISCUSSION/SIGNIFICANCE OF IMPACT: Pb level is associated with asthma status in children especially young children. Health risk of low Pb is a concern. Preventive measures by reducing potential sources of Pb should be introduced early.

OBJECTIVES/SPECIFIC AIMS: The goals of this project are to develop, disseminate, and evaluate an online, self-paced training module designed to help mentors better understand and support their mentees’ motivation. The module introduces learners to the CARES mentoring model, which is rooted in Self-Determination Theory (SDT), one of the leading theories of motivation. According to SDT, an optimal mentoring environment provides support for mentees’ psychological needs for Competence, Autonomy, Relatedness, Equity in extrinsic resources, and Structure (CARES). METHODS/STUDY POPULATION: Content for the CARES online module was drawn from a previously developed two-hour mentor training workshop designed for delivery in a face-to-face, small group setting. Content experts developed a slide deck and speaker notes. These materials were edited, adapted into a storyboard, and translated into a 60-minute interactive online module created with e-learning authoring software (Articulate Storyline). An evaluation survey was developed to assess mentors’ perceived skills gains related to course content (e.g., “Encouraging my mentees to think about how well their psychological needs are being met within the work/training environment,” “Recognizing how diversity, equity, and inclusion can be salient issues that impact a mentee’s motivation”) and mentors’ confidence gains in their ability to implement motivation-focused practices into their mentoring relationships (e.g., “Autonomy: Giving my mentees freedom in deciding what goals to pursue and how they to do their work,” “Competence: Working with my mentees to establish appropriate challenges to stretch their abilities”). The module was beta tested in October 2018 by 11 individuals with experience as mentors and in facilitating mentor training. RESULTS/ANTICIPATED RESULTS: The beta testing process produced useful recommendations for improving clarity of content, visual design, and navigation. Users expressed a high level of enthusiasm for the content, which included a combination of practical information and empirical support for the CARES mentoring model. They also appreciated specific functionality in the module, including the presentation of brief case examples of mentoring scenarios that enhance or diminish motivation, opportunities for self-reflection, and a downloadable guide for initiating conversations with mentees about different domains in the CARES model. Evaluation data (quantitative and qualitative) from beta testers (n=11) are being analyzed. A preliminary examination of these findings found that mentors report gains from before to after the training in their self-perceived skills and confidence levels. Moreover, all expressed an intention to makes changes in their mentoring practices as a result of the training. Comments indicated potential value in offering a follow up face-to-face experience in which mentors can hear from others who have successfully implemented the CARES approach and acquire practice in skillfully implementing the CARES conversation guide with their mentees. DISCUSSION/SIGNIFICANCE OF IMPACT: This innovative e-learning module offers a readily accessible and theoretically driven training approach to help mentors recognize the value of supporting their mentees’ motivation, and become more intentional in implementing motivation-focused practices into their mentoring relationships. In future work, the CARES module will be pilot tested with specific cohorts and in different implementation scenarios (as a standalone training, or combined with other programming) and made available to users nationally with support from the University of Minnesota Clinical and Translational Science Institute and the NIH National Research Mentoring Network.

OBJECTIVES/SPECIFIC AIMS: The Rockefeller University Center for Clinical and Translational Science (RU-CCTS), Clinical Directors Network (CDN), and Carter Burden Network (CBN), a multi-site senior services organization serving East Harlem, NY, formed a community-academic research partnership to characterize the health of the CBN seniors (many who are racial/ethnic minorities, low-income, and suffering from multiple chronic conditions) and to explore the use and associations of a measure of overall health status and frailty in this population. A simple validated measure of health status could standardize and streamline community-based translational research to study the impact of CBN’s services on health outcomes. The CCTS-funded Pilot Project aims to: 1) Engage CBN seniors and stakeholders in priority-setting, joint protocol development, research conduct, analysis and dissemination; 2) Characterize the health status of the CBN seniors using validated measures; 3) Establish an electronic database infrastructure for current and future research; 4) Understand how health and senior activities information can be used to implement programs to improve senior health and well-being. METHODS/STUDY POPULATION: 1) We used Community Engaged Research Navigation (CEnR-Nav) methods to facilitate partnership development, and to engage CBN seniors and stakeholders in each step of the research; 2) Research staff conducted recruitment, informed consent, and physical assessments (e.g., pulse, blood pressure, BMI); and administered validated surveys to collect health status information. 3) Data were captured on a REDCap-based platform. The primary outcome, frailty, was measured by the validated Short Physical Performance Battery (SPPB). 4) Secondary outcomes include the association of use of services/activities with the primary outcome. Research participants consented to sharing of their health, demographic and services utilization data compiled by CBN staff and the NYC Department for the Aging (DFTA). DFTA provided comparison datasets of de-identified health and demographic data for clients attending other NYC DFTA-funded senior centers. RESULTS/ANTICIPATED RESULTS: 1) 43 residents and stakeholders engaged in partnership-building, study design and implementation. 2) 218 participants from two senior centers were enrolled. Mean age, 68 ± 11 years; 58% Hispanic; 33% African American, 23% White, 1% Asian, 18% Unknown, 17% Other; 69% reported <$20000 annual income; 40% had not completed high school; 30% scored as moderately or severely frail; 83% were overweight or obese; and 33% reported a history of diabetes. 84% had uncontrolled high blood pressure; many participants were previously aware of their hypertension diagnosis. 3) A REDcap database was developed to store historical and prospective data. 4) Across frailty categories, there was a significant difference in utilization of non-meal (p = 0.0237) and meal services (p = 0.0127) and there was an inverse proportional relationship between the number of meal and non-meal visits, and frailty. Additional associations among health status measures (e.g., SPPB, demographics, biological measures: pulse, blood pressure, BMI; psychosocial and nutritional scales) and CBN service utilization (i.e., meals vs. non-meals activities) will be presented. DISCUSSION/SIGNIFICANCE OF IMPACT: We developed a community-academic research partnership, infrastructure and capacity, built through our Community-Engaged (CEnR-Nav) model, to conduct a pilot study characterizing the health status and services utilization of low-income minority seniors. Our pilot study identified an urgent health priority, uncontrolled hypertension in 84% of CBN’s seniors. We then leveraged the team’s expertise and CBN’s meal services program to develop a research proposal for external funding to conduct a community-based multi-component intervention study. Replacement of a typical Western diet with the Dietary Approaches to Stop Hypertension (DASH) diet has been proven to reduce blood pressure in hypertensive and normotensive individuals in as little as 14 days, yet effective implementation has been lacking, and it is relatively untested in community-living seniors who receive their meals in settings such as CBN. We are also exploring mechanistic questions that relate to blood pressure control, such as the impact of the DASH diet on inflammation, which may lead to a better understanding of the underlying mechanism of action of the DASH diet. Our community partner, CBN, was awarded the DHHS-ACL nutrition innovation grant to conduct this 2-year study with CDN and RU-CCTS. The resulting study developed out of the community engaged pilot study represents a unique combination of community-centered care, within an implementation science framework (with embedded mechanistic measures under development). This is an example of the novel, full-spectrum approach to translational research that the RU-CCTS/CDN Community Engaged Research Core has been developing over the last decade. The research to characterize CBN clients’ health status is now being extended to address cardiovascular health by way of intervening on diet quality and food insecurity, a key component of the social determinants of health, in partnership with agencies outside of the healthcare delivery system. The outcomes of the DASH Diet implementation study will also serve to inform the broader aging service provider network and the healthcare community about the impact of senior center congregate meal composition and services on health outcomes.

The Mountain West Clinical Translational Research – Infrastructure Network (MW CTR-IN), established in 2013, is a research network of 13 university partners located among seven Institutional Development Award (IDeA) states targeting health disparities. This is an enormous undertaking because of the size of the infrastructure network (encompassing a third of the US landmass and spanning four time zones in predominantly rural and underserved areas, with populations that have major health disparities issues). In this paper, we apply the barriers, strategies, and metrics to an adapted educational conceptual model by Fink (2013). Applying this model, we used four tailored approaches across this regional infrastructure network to: (1) assess individual faculty specific needs, (2) reach out and engage with faculty, (3) provide customized services to meet the situational needs of faculty, and (4) utilize a “closed communication feedback loop” between Professional Development (PD) core and MW CTR-IN faculty within the context of their home institutional environment. Summary statement results from participating faculty show that these approaches were positive. Grounded in best educational practice approaches, we have an opportunity to refine and build from this sound foundation with implications for future use in other CTR-IN networks and institutions in the IDeA states.

The Stanford Population Health Sciences Data Ecosystem was created to facilitate the use of large datasets containing health records from hundreds of millions of individuals. This necessitated technical solutions optimized for an academic medical center to manage and share high-risk data at scale. Through collaboration with internal and external partners, we have built a Data Ecosystem to host, curate, and share data with hundreds of users in a secure and compliant manner. This platform has enabled us to host unique data assets and serve the needs of researchers across Stanford University, and the technology and approach were designed to be replicable and portable to other institutions. We have found, however, that though these technological advances are necessary, they are not sufficient. Challenges around making data Findable, Accessible, Interoperable, and Reusable remain. Our experience has demonstrated that there is a high demand for access to real-world data, and that if the appropriate tools and structures are in place, translational research can be advanced considerably. Together, technological solutions, management structures, and education to support researcher, data science, and community collaborations offer more impactful processes over the long-term for supporting translational research with real-world data.

OBJECTIVES/GOALS:

• A web interface that allows for easy upload of CSV text data to time-based visualizations

• Implementation of change points analysis to identify and display points where event rates increased or decreased

• customizable plots where the user can change point shapes, color, etc.

• customizable and advanced filtering support

• support for plot comparisons and exports

METHODS/STUDY POPULATION: We used the R/Shiny framework to develop a web application for visualization of time stamped data. The Research and Exploratory Analysis Driven Time-data Visualization (READ-TV) application allows for user-friendly mining for longitudinal patterns in data. READ-TV is built specifically for FD analysis, but is easily adaptable to other clinical use cases, as we allow for the use of general metadata on events and cases.The building of a quantitative framework for event analysis starts with the application of homogeneous Poisson processes, which relate the times of occurrence of events in terms of an underlying rate. To understand the changes in this underlying rate, changepoint analysis is used to model the rate as a function of time using piecewise constant approximations. The changepoint analysis allows us to identify the specific periods of time where the rate of FD is increased relative to a baseline or a desired operating range. RESULTS/ANTICIPATED RESULTS: READ-TV application allows for import of time stamped event data from multiple cases. Event and case metadata are supported to facilitate filtering and mining of interesting subsets of data. Stem plots are used for visualization of selected event timelines in chosen cases. This visualization is accompanied with summary of the number and estimates of rates of occurrence of specific event types (e.g. types of FD). Change-point analysis is implemented using the ‘changepoint‘ R library. These analyses allow the users to quickly understand whether the rates of events (FD) is changing across the case timeline and where exactly these changes are occurring. DISCUSSION/SIGNIFICANCE OF IMPACT: We have demonstrated the READ-TV application to the team of the AHRQ-funded Human Factors and Systems Integration in High Technology Surgery (HF-SIgHTS) study. The ability to visualize and perform quantitative analysis of the study data was received with unanimous positive feedback and enthusiasm. We continue READ-TV development focusing on (1) increased user-friendliness using the HF-SIgHTS as our focus group, (2) increased functionality, and (3) use of more general localization terminology to allow for other applications.

OBJECTIVES/SPECIFIC AIMS: Our objectives with this project are to engage communities through technology creating a communication channel with affected communities and stakeholders about mosquito-borne illness, vector control and environmental health risk. Furthermore, engaging communities to electronically map ecological risks that impact mosquito-borne illness with the goal of creating a mobile application that will work as an ecological surveillance against mosquito proliferation and potential mosquito population reduction, and finally pilot test and evaluate potential benefits in communities where the application was used. METHODS/STUDY POPULATION: We propose a methodology to perform formative community work that will underscore a distributed, democratized ecological surveillance through an integration of multidimensional health behavior theories that address the challenges of ZIKV in Culebra, a marginalized island community off the coast of the main island of Puerto Rico. Using participatory design, we will develop, test, and evaluate users’ experiences towards mobile applications using qualitative (interviews) and quantitative (survey) methodologies. A mobile application with the capacity of mapping, use of social-media, crowdsourcing, and photo-voice in a dynamic and simple way will allow community members to alert “hot-zone” locations to the stakeholders interested in creating ecological action in their community. This multidimensional concept integrates explanatory and prospective approaches and will generate systematic short-term solutions for mosquito control and long-term solutions providing the necessary tools for community empowerment. RESULTS/ANTICIPATED RESULTS: Our proposed design will facilitate better understanding of the interactions between community members and socio-environmental determinants of mosquito-borne diseases. Furthermore, our proposed project will not only facilitate communication among members of a community, but also it will provide a platform for engagement and empowerment, establishing a change in the preventive paradigm of how communities face the negative impacts of micro-ecologies that surround them. DISCUSSION/SIGNIFICANCE OF IMPACT: Our proposed community collaboratory mHealth tool mZAP! (Zonas, Accion y Proteccion) will address the lack of community participation efforts against mosquito-borne diseases contributed simultaneously by the disengagement and disempowerment of community members. mZAP! will serve as an innovative tool to engage marginalized and communities made vulnerable in Puerto Rico. This approach should be successful as Puerto Rico is one of the most digitally connected countries in Latin America, with high mobile phone usage rates and social media use. Using mZAP!, communities will report and map breeding sites, use social media and crowd sensing, targeting against powerful tools against mosquito ecologies in their own environments. This application could result in an effective way to change the paradigms for public health approaches to use Information Communications Technologies (ICTs) to empower communities.

OBJECTIVES/SPECIFIC AIMS: Missing data is a common problem in research studies that may lead to inconclusive or inaccurate results. It may even lead to harm secondary to wrong research conclusions. The purpose of this ancillary study is to measure the differences in missing data following implementation of a variety of mechanisms to improve data quality and documentation in a global quality improvement study. Many of the sites involved in the study were in low-income or middle-income countries with minimal research infrastructure. Missing data is defined as “values that are not available that would be meaningful for analysis if they were observed” (The prevention and treatment of missing data, New Engl J Med 367; 14, nejm.org, October 4, 2012). METHODS/STUDY POPULATION: All study sites used REDCap software to enter various data points including hospital and ICU admission and discharge dates as well as whether items on a Checklist relevant to processes of care in the ICU were reviewed. After initial general data collection phase, we categorized data as “must have” and “good to have.” “Must have” variables were defined as data variables that were essential for the study outcomes. “Good to have” variables would not affect the main outcomes of the study if missing. We measured completeness of data using the in-built REDCap data quality check feature. We used several strategies to encourage reduction of missing data. We initially did random data checks but noted that the amount of missing data was substantial and could not be adequately addressed this way. Second, we created excel sheets highlighting missing data for each site and notified sites. This proved onerous to create and made it burdensome for sites to identify easily where data was missing. Third, we built a custom report form in REDCap specifically able to identify which “must have” data points were missing. This could be easily accessed by the principal investigator at each site and made completing the data forms more straightforward. We encouraged all sites to complete their data collection by sending weekly data reports to each site highlighting the patients with missing data. An instructional YouTube tutorial was also created and the link was shared with all sites to demonstrate how to use the custom built report form in REDCap and how to appropriately fill in the missing data. Since this was a global study, we communicated with sites using a variety of locally favored mechanisms including Zoom, FaceTime, WeChat, WhatsApp as well as email. By harnessing the buy-in of local champions our approach was successful. RESULTS/ANTICIPATED RESULTS: The total number of patients recruited for the CERTAIN study is 4843. The rate of all missing variables improved with the efforts described above. Hospital admission dates were missing in 8.4% pre efforts and 4.2% post efforts (p<0.01). ICU admission dates were missing in 5.5% pre and 2.0% post (p<0.01). Documentation of completion of processes of care (including central line review, urinary catheter review, consideration for blood transfusion) improved significantly from pre to post (p<0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: Missing data can be a problem in all types of research studies. This study provides some preliminary evidence for effective approaches that can reduce the problem of missing data when conducting a global study at sites with limited research infrastructure in place. By addressing the concern about missing data, we can be more confident that our results can be accurately analyzed and interpreted, improving the quality of the research.

OBJECTIVES/SPECIFIC AIMS: The aims of this project are to: (1) examine placebo effects on subjective and objective outcome measures, (2) determine if an increase in the placebo is associated with changes in benefit, (3) evaluate if the trauma related insomnia placebo group in our study has different side effect reports compared with insomnia placebo participants in previous suvorexant trials, and (4) (Exploratory) examine associations between the placebo group’s characteristics (e.g., trauma/PTSD severity, demographics) and placebo effects. METHODS/STUDY POPULATION: The parent study is a randomized double-blind placebo-controlled clinical trial (clinicaltrials.gov ID: NCT02704754) of suvorexant for treatment of adults (age 18–55) with insomnia that started or worsened after trauma exposure. Suvorexant is a first in class orexin antagonist and is approved by the FDA for the indication of insomnia. In this 6-week trial, all participants initially take 10 mg of suvorexant/placebo, and the dose will be increased to 20 mg if participants continue to experience clinically significant insomnia symptoms 1 week after starting the medication. Sleep outcomes will be measured by polysomnography, daily sleep diary, and the Insomnia Severity Index. RESULTS/ANTICIPATED RESULTS: We hypothesize that (1) within the placebo group data both subjectively and objectively measured outcomes will similarly show improvement in insomnia symptoms, (2) the increase of the placebo medication dose will result in an increased benefit, (3) the trauma-related insomnia placebo group will have the same type and similar rate of side effects reported in previous suvorexant trials. DISCUSSION/SIGNIFICANCE OF IMPACT: Most previous studies examining placebo effects focused on pain and depression. Information obtained from this project will complement our current understanding of placebo effects by characterizing placebo effects on trauma-related insomnia. This study will inform the development of novel strategies to maximize utility of placebos in future clinical trials.

OBJECTIVES/SPECIFIC AIMS: To create a searchable public registry of all Quality Improvement (QI) projects. To incentivize the medical professionals at UF Health to initiate quality improvement projects by reducing startup burden and providing a path to publishing results. To reduce the review effort performed by the internal review board on projects that are quality improvement Versus research. To foster publication of completed quality improvement projects. To assist the UF Health Sebastian Ferrero Office of Clinical Quality & Patient Safety in managing quality improvement across the hospital system. METHODS/STUDY POPULATION: This project used a variant of the spiral software development model and principles from the ADDIE instructional design process for the creation of a registry that is web based. To understand the current registration process and management of quality projects in the UF Health system a needs assessment was performed with the UF Health Sebastian Ferrero Office of Clinical Quality & Patient Safety to gather project requirements. Biweekly meetings were held between the Quality Improvement office and the Clinical and Translational Science – Informatics and Technology teams during the entire project. Our primary goal was to collect just enough information to answer the basic questions of who is doing which QI project, what department are they from, what are the most basic details about the type of project and who is involved. We also wanted to create incentive in the user group to try to find an existing project to join or to commit the details of their proposed new project to a data registry for others to find to reduce the amount of duplicate QI projects. We created a series of design templates for further customization and feature discovery. We then proceed with the development of the registry using a Python web development framework called Django, which is a technology that powers Pinterest and the Washington Post Web sites. The application is broken down into 2 main components (i) data input, where information is collected from clinical staff, Nurses, Pharmacists, Residents, and Doctors on what quality improvement projects they intend to complete and (ii) project registry, where completed or “registered” projects can be viewed and searched publicly. The registry consists of a quality investigator profile that lists contact information, expertise, and areas of interest. A dashboard allows for the creation and review of quality improvement projects. A search function enables certain quality project details to be publicly accessible to encourage collaboration. We developed the Registry Matching Algorithm which is based on the Jaccard similarity coefficient that uses quality project features to find similar quality projects. The algorithm allows for quality investigators to find existing or previous quality improvement projects to encourage collaboration and to reduce repeat projects. We also developed the QIPR Approver Algorithm that guides the investigator through a series of questions that allows an appropriate quality project to get approved to start without the need for human intervention. RESULTS/ANTICIPATED RESULTS: A product of this project is an open source software package that is freely available on GitHub for distribution to other health systems under the Apache 2.0 open source license. Adoption of the Quality Improvement Project Registry and promotion of it to the intended audience are important factors for the success of this registry. Thanks goes to the UW-Madison and their QI/Program Evaluation Self-Certification Tool (https://uwmadison.co1.qualtrics.com/SE/?SID=SV_3lVeNuKe8FhKc73) used as example and inspiration for this project. DISCUSSION/SIGNIFICANCE OF IMPACT: This registry was created to help understand the impact of improved management of quality projects in a hospital system. The ultimate result will be to reduce time to approve quality improvement projects, increase collaboration across the UF Health Hospital system, reduce redundancy of quality improvement projects and translate more projects into publications.

OBJECTIVES/SPECIFIC AIMS: To examine and compare the claims in Bzdok, Altman, and Brzywinski under a broader set of conditions by using unbiased methods of comparison. To explore how to accurately use various machine learning and traditional statistical methods in large-scale translational research by estimating their accuracy statistics. Then we will identify the methods with the best performance characteristics. METHODS/STUDY POPULATION: We conducted a simulation study with a microarray of gene expression data. We maintained the original structure proposed by Bzdok, Altman, and Brzywinski. The structure for gene expression data includes a total of 40 genes from 20 people, in which 10 people are phenotype positive and 10 are phenotype negative. In order to find a statistical difference 25% of the genes were set to be dysregulated across phenotype. This dysregulation forced the positive and negative phenotypes to have different mean population expressions. Additional variance was included to simulate genetic variation across the population. We also allowed for within person correlation across genes, which was not done in the original simulations. The following methods were used to determine the number of dysregulated genes in simulated data set: unadjusted p-values, Benjamini-Hochberg adjusted p-values, Bonferroni adjusted p-values, random forest importance levels, neural net prediction weights, and second-generation p-values. RESULTS/ANTICIPATED RESULTS: Results vary depending on whether a pre-specified significance level is used or the top 10 ranked values are taken. When all methods are given the same prior information of 10 dysregulated genes, the Benjamini-Hochberg adjusted p-values and the second-generation p-values generally outperform all other methods. We were not able to reproduce or validate the finding that random forest importance levels via a machine learning algorithm outperform classical methods. Almost uniformly, the machine learning methods did not yield improved accuracy statistics and they depend heavily on the a priori chosen number of dysregulated genes. DISCUSSION/SIGNIFICANCE OF IMPACT: In this context, machine learning methods do not outperform standard methods. Because of this and their additional complexity, machine learning approaches would not be preferable. Of all the approaches the second-generation p-value appears to offer significant benefit for the cost of a priori defining a region of trivially null effect sizes. The choice of an analysis method for large-scale translational data is critical to the success of any statistical investigation, and our simulations clearly highlight the various tradeoffs among the available methods.

OBJECTIVES/SPECIFIC AIMS: The purpose of this study was to summarize the existing literature on clinical research competencies and determine what competency assessments currently exist. We also wished to assess which competencies should be included in a research competency assessment tool and to evaluate the validity of current competency assessments. We also examined whether these competency assessments can be used for the purposes of formative and summative evaluation. METHODS/STUDY POPULATION: Prior to conducting our search of the literature, we first compiled a list of search terms (e.g., clinical, research, training, competencies) that could be used to locate articles. We then entered these search terms, in various combinations, on several relevant databases. We evaluated abstracts of the articles revealed by this search to determine whether they met three criteria. The first criterion was that the subjects of the article must be clinical investigators or clinical investigators in training. Relevant disciplines included medicine, public health, nursing, pharmacy, dentistry, and other related fields. The second criterion was that articles should focus on research-based (as opposed to clinical) skills. The last criterion was that research-based competencies (or related terms like skills, abilities, mastery, knowledge) must be assessed in some way. If the abstract suggested that the article met all three criteria, the full article was retrieved and analyzed in-depth. To identify articles that eluded literature search, we then examined the reference section of these articles and examined articles that cited these articles. When no additional articles could be located, the search for articles stopped. Once a pool of potentially eligible articles was identified, the articles underwent peer review by several researchers experienced with clinical research and competency-based education and assessment. Articles that were unanimously judged to meet the criteria were included in the systematic review. RESULTS/ANTICIPATED RESULTS: Approximately 75 articles were selected and reviewed for eligibility. After peer review, we found that only a small fraction of these articles met our criteria for inclusion in the systematic literature review. Our preliminary findings suggest that there are few assessments of clinical research competency and that many of these assessments are poorly validated. DISCUSSION/SIGNIFICANCE OF IMPACT: The findings of the present study suggest that the validation methods used thus far are limited and so the validity of many of these assessments is effectively unproven. Future research on assessments of clinical research competency ought to address these limitations by sampling clinical researchers, using more rigorous validation methods, and by confirming hypothesized factor structures in new samples. The use of better-validated instruments may enhance measurement of trainees’ knowledge and skill levels for the purposes of formative and summative assessment.

OBJECTIVES/SPECIFIC AIMS: Innovation in healthcare is increasingly dependent on technology and teamwork, requiring effective collaboration between disciplines. Through an intensive team-based competition event, Mount Sinai Health Hackathon 2017, aimed to harness the power of multidisciplinary and transdisciplinary collaboration to foster innovation in the field of cancer. Participants were immersed in an intensive weekend working in teams to develop technology solutions to important problems affecting patients and care providers in the field of cancer. The learning objectives were to enable participants to: Identify cancer-related healthcare problems which lend themselves to technology-based solutions. Delineate key behaviors critical to multidisciplinary team success Identify optimal strategies for communicating in multidisciplinary teams. Engage and inspire participants to apply knowledge of technology to meaningfully impact clinical care and well-being. METHODS/STUDY POPULATION: The Mount Sinai Health Hackathon is an annual 48-hour team-based competition, using a format adapted from guidelines provided by MIT Hacking Medicine. The 2017 event gathered a total of 87 participants (120 registered), representing 17 organizations from as far away as California, with a diverse range of backgrounds in bioinformatics, software and hardware, product design, business, digital health and clinical practice. The overall participation model included: Phase 0: Health Hackathon 101 summer workshops; Phase 1: pre-Hackathon priming activities using online forums Trello and Slack; Phase 2: a 48-hour onsite hackathon to catalyze innovation through problem sharing, solution pitches, team formation and development of prototype solutions; Phase 3: competitive presentations to judges and prize awards; Phase 4: a suite of post-hackathon support to stimulate continued development of innovations. The event sponsored by ConduITS, was also co-sponsored by Persistent Systems, IBM Watson, Tisch Cancer Institute, Sinai AppLab, Sinai Biodesign and other ISMMS Institutes. Mentors circulated throughout the event to support the teams in the technical, clinical, and business development aspects of their solutions. In total, the 14 teams formed during the Hackathon, created innovations ranging from diagnostic devices, networking apps, artificial intelligence tools, and others. The top 3 teams were each awarded $2500 to support their projects’ future development. RESULTS/ANTICIPATED RESULTS: Qualitative and quantitative post-event survey data revealed the Hackathon experience fostered collaborative attitudes and a positive experience for participants, providing insight into the potential benefits of team science. In the post-event survey (n=24) 92% of participants reported that the experience increased their ability to solve problems and 96% made new professional or personal connections. In addition, 96% of respondents would attend future Hackathon events and 75% reported they were likely to continue working on their project after the Hackathon. Qualitative feedback from 1 participant reported it was: “a wonderful event that really highlighted how much interdisciplinary team science can achieve.” Along with intermediate support interactions, including the winning teams participating in a Shark Tank style event with pitches to external entrepreneurs and investors, all teams will be followed up in 6 months time to determine if participants continue to work on projects, file new patents, create new companies, or leverage the new connections made through the Health Hackathon experience. DISCUSSION/SIGNIFICANCE OF IMPACT: Our experience indicates that a Health Hackathon is a compelling and productive forum to bring together students, trainees, faculty, and other stakeholders to explore tech-based solutions to problems in cancer and other areas of biomedicine. It is a valuable tool to foster collaboration and transdisciplinary team science and education. Follow-up analysis will determine to what extent the Mount Sinai Health Hackathon is contributing to an ecosystem that encourages professionals and trainees in healthcare and in technology development to work together to address unmet needs in healthcare with innovative technology solutions.

OBJECTIVES/SPECIFIC AIMS: (1) To explain and discuss minority health and health disparities and the mechanisms, for example, individual behaviors and lifestyle, genetics and epigenetics, physical and cultural environment, and clinical events and health care, that lead to health disparities. (2) To explore the intersection between health disparity science and clinical and translational science. (3) To present and discuss the NIMHD Framework and how it can be used to guide multilevel research to address minority health and health disparities. (4) To highlight examples of NIMHD-funded novel and innovative research relevant to clinical and translational research from a health disparities perspective. METHODS/STUDY POPULATION: The NIMHD Research Framework will be introduced that is currently being used by NIMHD to address minority health and health disparity research. The Framework looks at targeted populations in relation to biological, behavioral, physical, and sociocultural environmental domains of influence as well as the health care system. These domains have different levels of influence: individual, family/interpersonal, community, and population. Targeted populations include NIH-designated health disparity populations, that include racial/ethnic minorities, socioeconomically disadvantaged populations, underserved rural populations, and sexual and gender minorities. The following research opportunities are among the many opportunities offered by NIMHD: Disparities in Surgical Care and Outcomes Social Epigenomics for Minority Health and Health Disparities Addressing Health Disparities Among Immigrant Populations. RESULTS/ANTICIPATED RESULTS: Select examples of NIMHD supported minority health and health disparities research that intersects with clinical and translational research will be presented. Candidate examples include: Genetic Architecture of Lupus (SLE) in individuals with Asian ancestry; A Novel Racial Disparity Marker for Risk Prediction in Triple Negative Breast Cancer Patients; Self-Applied Wearable Ultrasound Therapy for Osteoarthritis Management in Rural Central NY; Design and Development of a Multifunctional Self-service Health Screening Kiosk. DISCUSSION/SIGNIFICANCE OF IMPACT: Despite notable improvements gained as a result of medical and scientific advances, there continues to be an alarming disproportionate burden of illness and lack of representation in research among minority and other socially disadvantaged and underserved populations. To meet this challenge, NIMHD is committed to supporting a wide range of clinical and translational research aimed at the development of innovative strategies and approaches to reduce and, eventually, eliminate health disparities. NIMHD’s mission, research priorities, and funding opportunities are relevant to the efforts and interests of clinical and translational scientists, especially those interested in the translation of research findings into interventions, products, and tools that may improve minority health and quality of life, increase adherence to medication and treatment regimens, increase access, and improve the delivery of health services.

OBJECTIVES/SPECIFIC AIMS: To use a systematic and iterative process to develop and refine toolkits to support dissemination and implementation (D&I) research. METHODS/STUDY POPULATION: Participants included research staff from the Dissemination and Implementation Research Core (DIRC), a research methods core from the Institute of Clinical and Translational Science at Washington University in St. Louis, other D&I experts from the University, and national experts from the D&I field. This project used education design research methodology and a systematic and iterative process involving several phases. The first phase (preliminary research and initial development) consisted of analysis of the educational problem and its context, and led to the development of toolkit prototypes and plans for their implementation. In the second phase (development and formative evaluation), toolkits were iteratively evaluated with emphasis on content validity and consistency and effectiveness as perceived by the users. Finally, in the summative evaluation, the toolkits were evaluated based on their use as intended. RESULTS/ANTICIPATED RESULTS: Our team identified the target audience as DIRC customers and investigators from disciplines across the University, and found that resources for beginners to D&I were lacking. The team developed 8 toolkits: (1) Introduction to D&I; (2) How to develop D&I Aims; (3) D&I Designs; (4) Implementation Outcomes; (5) Implementation Organizational Measures; (6) Assessing Barriers and Facilitators; (7) D&I Designs; and (8) Guideline research. These prototypes were iteratively revised for content validity and consistency. Finally, each toolkit was evaluated by two national experts in D&I science, and further refined. DISCUSSION/SIGNIFICANCE OF IMPACT: This systematic and cyclical process led to the development of 8 toolkits to support researchers in D&I science, which are now available on the DIRC Web site. This set the stage for development of new toolkits as additional needs are identified.

OBJECTIVES/SPECIFIC AIMS: The aims of this study are (1) to develop and characterize a novel nonhuman primate model of pneumococcal pneumonia that mimics human disease; and (2) determine whether Streptococcus pneumoniae can: (a) translocate to the heart, (b) cause adverse cardiac events, (c) induce cardiomyocyte death, and (d) lead to scar formation during severe pneumonia in baboons. METHODS/STUDY POPULATION: Six adult baboons (Papio cynocephalus) were surgically tethered to a monitoring system to continuously assess their heart rate, temperature, and electrocardiogram (ECG). A baseline transthoracic echocardiogram, 12-lead ECG, serum troponin-I levels, brain natriuretic peptide, and heart-type fatty acid binding protein (HFABP) levels were obtained before infection and at the end of the experiment to determine cardiovascular damage during pneumococcal pneumonia. Animals were challenged with 108 colony-forming units of S. pneumoniae in the right middle lobe using flexible bronchoscopy. Three baboons were rescued with ampicillin therapy (80 mg/kg/d) after the development of pneumonia. Cardiac damage was confirmed by examination of tissue sections using immunohistochemistry as well as electron and fluorescence microscopy. Western-blots and tissue staining were used to determine the presence of necroptosis (RIP3 and pMLKL) and apoptosis (Caspase-3) in the cardiac tissue. Cytokine and chemokine levels in the heart tissue were determined using Luminex technology. RESULTS/ANTICIPATED RESULTS: Four males (57%) and three (43%) females were challenged. The median age of all baboons was 11 (IQR, 10-19) years old, which corresponds to a middle-aged human. Infected baboons consistently developed severe pneumonia. All animals developed systemic inflammatory response syndrome with tachycardia, tachypnea, fever, and leukocytosis. Infection was characterized by initial leukocytosis followed by severe leukopenia on day 3 postinoculation. Non-specific ischemic alterations by ECG (ST segment and T-wave flattering) and in the premortem echocardiogram were observed. The median (IQR) levels of troponin I and HFABP at the end of the experiment were 3550 ng/mL (1717–5383) and 916.9 ng/mL (520.8–1323), respectively. Severe cardiomyopathy was observed using TEM and H&E stains in animals with severe pneumonia. Necroptosis was detected in cardiomyocytes of infected animals by the presence of pMLKL and RIP3 in cardiac tissues. Signs of cardiac remodeling indicated by disorganized collagen deposition was present in rescued animals but not in the other animals. DISCUSSION/SIGNIFICANCE OF IMPACT: We confirmed that baboons experience cardiac injury during severe pneumococcal pneumonia that is characterized by myocardial invasion, activation of necroptosis, and tissue remodeling in animals rescued by antimicrobial therapy. Cardiac damage by invading pneumococci may explain why adverse cardiac events that occur during and after pneumococcal pneumonia in adult human patients.

The purpose of this clinical improvement project was to instill a streamlined process of identifying social determinants of health (SDOH) in our clinic’s diverse patient population and provide resources that address these barriers to health and well-being. At each clinic visit, patients self-identified SDOH through an easy-to-use Social Assessment Form. Using an online database, Community Relay (CR), providers had access to location-based community resources. In addition to accomplishing the above-mentioned goals, we were left with a more well-rounded understanding of our patients. Unique struggles were identified and barriers to care were revealed, allowing for more patient-centered medical care.