Luke Horvath

Luke Horvath is a health services researcher with over a decade of experience in value-based care, alternative payment models, risk adjustment, and health care data analytics. He specializes in developing, implementing, and evaluating policies designed to improve health care quality while limiting cost growth within the U.S. health care system.

Luke’s technical expertise includes designing rigorous empirical evaluations, developing predictive and inferential statistical models, leveraging multi-payer claims data to assess policy impacts, and collaborating with clinical and policy experts to design innovative care transformation approaches. At RTI, he implements and monitors financial benchmarking and patient attribution methodologies for value-based care initiatives and leads quantitative analyses for major cost efficiency, quality improvement, and pharmaceutical interventions. He is also a co-developer of RTI Fovea™, an advanced tool designed to detect malfeasance and fraud within Centers for Medicare & Medicaid Services (CMS) programs and other federal initiatives. In previous roles, he supported evaluations of value-based payment models and opioid-related policies. He also spent several years developing advanced machine learning methods to detect payment fraud at the Internal Revenue Service, and now applies these modeling and data engineering skills to CMS projects.

Luke is driven to advance the scalability and long-term impact of payment models and regulatory reforms that promote patient-centered care, improve health care efficiency, and strengthen health outcomes. He brings together analytical rigor, clear communication, and a collaborative spirit to support informed, data-driven policy decisions.