Matthew Willis

University of Michigan–Ann Arbor, University of Oxford

Papers

Total Citations

H-Index

About

Matthew Willis is a leading researcher at the intersection of healthcare delivery and artificial intelligence, with a primary focus on the automation of administrative tasks in primary care. His major contribution lies in developing rigorous, mixed-method frameworks to assess precisely which clinical and clerical workflows in general practice are most amenable to automation. His landmark 2020 study, cited 48 times, combined ethnographic case studies, focus groups, and expert surveys to map the potential for automating routine administrative burdens on National Health Service staff. This work is complemented by his 2018 protocol paper (19 citations), which established a systematic methodology for measuring task automation potential grounded in real-world primary care systems. Willis’s research is notable for moving beyond abstract debates about AI in healthcare, instead providing granular, evidence-based assessments that help policymakers and practitioners understand where technology can most effectively reduce workload without compromising patient care. His work has positioned him as a key voice in shaping the future of digitally-enabled general practice.