MIELHSS - Research Education Core

Research Education Core Project Summary The Massachusetts Institute for Equity-focused Learning Health System Science (MIELHSS) aims to develop leading scientists in embedded research, accelerate innovation, and achieve widespread culture change in human-centered, equity-focused learning health system (E-LHS) science. Our framework for training and science aims to achieve the quintuple aim of healthcare: better health, improved patient experiences, care team wellbeing, and health equity, at lower cost. The Research Education Core provides a robust high-quality infrastructure of didactic, mentored, and experiential activities that allows for the application and mastery of AHRQ LHS Core Competencies and PCORI methods and prepares the future workforce of embedded LHS scientists. We propose innovative approaches to rapidly grow a diverse workforce of LHS scientists and provide them with the critical skills that they need to effectively engage health systems, patients, and communities to drive LHS advances in health equity. Specifically, our pathway approach to professional development across the entire professional spectrum, from student to faculty, multiplies the benefit of the educational infrastructure and applies a best practice in advancing diversity and equity in the workforce. Our training program, coupled with an individual development plan (IDP), tailors training to the level of experience, provides a tool for career planning and mentor conversations, and provides a shared understanding of outcomes and metrics to evaluate progress. With health equity as our focus, our proposed training program is anchored in equity-focused data science aimed at identifying and measuring equity-focused targets, processes, and outcomes and equity-focused health care delivery science, including training in human-centered co-design (HCD) and equity-focused implementation science. The robust mentored environment coupled with health system and community engagement provides an optimal learning environment for embedded learning health scientists.