SBIR Phase I: eLearning system that enables patient-centered, team-based care and reduces physician shortages in medically underserved areas

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to significantly reduce primary care physician shortages and improve quality of care for low income patients in the United States by developing a tool that analyzes clinical care team performance data at federally qualified health centers (FQHCs) to automatically deploy individually tailored eLearning support for staff members that enables patient centered team based care. FQHCs are funded by the U.S. Department of Health and Human Services to serve 22 million low income patients living in more than 10,000 of the poorest communities across the Nation. Well-implemented patient centered team-based care has the potential to significantly reduce physician shortages and burden of chronic disease which disproportionately affects low income communities. However, efforts to move and sustain FQHCs participation in this model have had limited success with only 66% attaining patient centered medical home (PCMH) recognition in 2016. Various public initiatives, including the Health Resources and Service Administration Quality Improvement Award and Medicare Access and CHIP Reauthorization Act (MACRA), are providing additional financial incentives to move primary care practices towards PCMH Recognition. However, current approaches to practice transformation are cumbersome and difficult to sustain. The proposed project seeks to disrupt continued health professional education at FQHCs by assessing the feasibility of developing a tool that leverages electronic health record data to identify gaps in patient centered team based care for diabetic patients and deploys tailored asynchronous individualized e-learning nudge type support to each member of the care team based on their performance. The research objectives of this SBIR Phase 1 are to establish the feasibility of using EHR data through an API to trigger individual user and team level flags for variation from a specific set of PCMH standards and diabetes clinical protocols; to develop algorithms that generate an individualized learner user profile and teams level reports; to generate data to design algorithms that learn from user preferences, impacts on flags and patient outcomes; to design user interphase for reward and recognition and to evaluate end user acceptance of eLearning tools. The research will be approached using user centric design, behavioral economics and adult learning principles to gather specific requirements and develop a minimum viable product focused on a subset of between five to 10 indicators.