Bring it Down San Francisco: Harnessing cloud-based technology to improve hypertension management in a low-income underserved population

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PROJECT SUMMARY/ABSTRACT This an application for a K23 Mentored Patient-Oriented Career Development Award for Dr. Valy Fontil, an Assistant Adjunct Professor in General Internal Medicine at the University of California San Francisco who is establishing himself as a young investigator in implementation research of health systems-based strategies to improve hypertension control in underserved, high-risk populations. This K23 award will provide him with the necessary support evaluation of a hypertension management invention in 12 safety-net clinics and test a novel technology-enabled intervention that engages patients and enables shared decision-making between patients and providers to optimize visit frequency, treatment intensification, and medication adherence for treatment of hypertension. To achieve these goals, Dr. Fontil has assembled a multi-disciplinary mentoring team comprised of a primary mentor, Dr. Kirsten Bibbins-Doming, a renowned expert in cardiovascular epidemiology, health disparities research, and simulation modeling, and two co-mentors: Dr. Mark Pletcher, renowned cardiovascular epidemiologist with added expertise in clinical decision-making, decision analysis, and use of emerging technology for improving health; and Dr. Charles McCulloch, Head of the Division of Biostatistics at UCSF and expert in advanced statistical analysis of longitudinal data. Safety-net healthcare institutions, which care for our highest-risk populations, must play a pivotal role in achieving national priorities for improved BP control and reducing HTN disparities. Therefore, it is essential to develop and test practical solutions that these healthcare systems can employ within their resource constraints. Dr. Fontil will build on findings from his previous work in simulation modeling and real-world pilot intervention to focus on optimizing two key processes of care (visit frequency, treatment intensification, and medication adherence) that can improve BP control to upward of 80%. First, he will evaluate race-specific effects of a health system intervention in safety net clinics (Aims 1&2) on improving these processes. Then he will adapt and test a technology-enabled intervention for feasibility of improving these processes in patients at safety-net clinics (Aim 3). The proposed research will provide the foundation and additional information needed to design a randomized controlled trial of a technology-enabled intervention to improve overall BP control and reduce racial disparities in BP control across a consortium of safety-net healthcare systems. This will form the basis of my future R01 proposal. Through a focused program of mentored training and coursework, the candidate will gain advanced skills and expertise in (1) training in using and analyzing electronic health record data for health services research, (2) advanced techniques in computer microsimulation modeling, and (3) foundational concepts and skills at the intersection of data science, technology and healthcare.