OBJECTIVES/SPECIFIC AIMS: Of the six Centers for Medicare and Medicaid Services (CMS) monitored diagnoses targeted for readmissions reductions, reasons for readmissions within academic hospitals are poorly understood and reflect complex interactions between the patient, provider and organizational-level responses to initial hospitalization. Learning health systems (the organizational and orchestrated integration of research into evidence-based practice) can address the complexities of readmissions through an innovative approach to knowledge translation and patient-centered outcomes research. The objective of this review is to define and optimize the architecture of learning health systems to produce a dynamic pre-implementation framework of knowledge translation and patient-centered outcomes research, leveraging two engines (research and learning) within the academic and clinical settings for reducing readmissions. METHODS/STUDY POPULATION: Three databases were utilized for this scoping review (PubMed, Academic Search Premier, and Scopus) focusing on 1.) learning health systems and the methods of defining and building these systems within an academic hospital setting and 2.) the use of learning health systems in reducing readmissions within academic hospitals. Empirical articles and reviews pertaining to the architecture, development, conceptualization, definition, and translation of learning health systems were identified and compiled into a scoping review and proposed framework. RESULTS/ANTICIPATED RESULTS: The scoping review yielded 139 articles; from which 28 articles were retained. No articles were found utilizing learning health systems to address readmissions. Thus, a new architectural framework was developed incorporating common architectural themes from the literature with adaptations to fit the interests of patients, providers, and researchers in reducing readmissions within academic hospitals (Figure 1). DISCUSSION/SIGNIFICANCE OF IMPACT: Given the dearth of information applying learning health systems to readmissions, the proposed architecture for an integrative learning health system can be utilized as a dynamic foundation for adoption and pre-implementation planning for reducing readmissions within academic hospital settings. Additionally, the authors expect this model to be tested and continually refined to address historical and emerging issues for clinically-relevant and clinically-effective approaches to patient-centered practice and research.