SBIR Phase I: RightFit: An Intelligent Patient-Provider Scheduling System for Healthcare Facilities

Rightfit Analytics Inc., West Lafayette IN

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from improving the quality of healthcare in the United States and reducing the associated costs for common elective surgery procedures through evidence-driven patient-physician matching. This technology will improve the quality of care and reduce the variation in costs associated with these procedures. The platform will better equip health facilities to deliver sustainable, high-quality care in an industry that is transitioning towards value-based care. The commercial impact of the project will result from generating savings to healthcare facilities. Personalized physician scheduling helps patients access the most beneficial care and has the potential to reduce complications and improve patient outcomes. Facility-level cost reduction and patient outcome improvement enabled by this technology not only translates to cost savings for patients, but also increased capacity for the healthcare facilities. This Small Business Innovation Research (SBIR) Phase I project will address the need for reducing the variations in outcomes and costs in elective medical care procedures with respect to factors including physician availability, the impact of care teams on medical outcomes and cost, and the effects of physician training and learning over time. The approach will be based on a unique combination of data analytics, stochastic processes, and machine learning, applied to the patient-provider matching problem. The technical challenges to be addressed in this project include the dynamic nature of physician strengths, the difficulty in attribution of outcomes to individual physicians in a team, and the challenges in adapting to the databases of health facilities. The team will closely collaborate with healthcare partners, leveraging historical data on physician and team performance over time as well as their feedback to develop an impactful and scientifically justified prototype. Anticipated technical results include documentation of the results of the proposed research and a prototype version of the technology for use at the healthcare facility level. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.