Peter Yeates

Biography

I am a consultant in acute and respiratory medicine and researcher focused on healthcare data science and technology enhanced clinical education. Previously I have worked extensively on assessor cognition within health professionals’ education. My research has used varied methods ranging from qualitative research, Realist evaluation, experiments, psychometrics and data science and AI. I’m particularly interested in developing and understanding applications of large language models in health professionals’ education.

I qualified from Newcastle University medical school in 2001 and have been involved in medical education since 2005. I studied for a PhD through the University of Manchester between 2009 and 2012. My doctoral research contributed to the beginnings of the field of “assessor cognition”, which studies the origins of judgemental variability in assessment within medical education. In particular that work focused on the influence of “contrast effects” on assessment judgements.

Post-doctorally I completed an NIHR matched clinical lectureship in medical education at the University of Manchester in 2013 and then moved to the School of Medicine at Keele University in September 2015. I was awarded an NIHR Clinician Scientist Award in 2018, which I completed in 2023. I have recently completed an NIHR Development and Skills Enhancement award focused on Healthcare Data Science.

Research and scholarship

My research is focused on assessors’ cognition and technology-enhanced assessment within clinical education. Recently I have shifted this focus to applications of AI and natural language processing within clinical education.

I am leading or supporting a variety of research either developing or exploring the implications of AI in medical education, including automated short answer question marking, applications of AI virtual patients, student perceptions of AI in assessment and application of AI to standard setting procedures. 

I led the ALIGN study, a multi-centre educational trial funded by the MPS Foundation, and in collaboration with the MSCAA which investigated the effectiveness of Video-Based Benchmarking (VBB) on calibrating OSCE examiners judgements.

Between 2018-2023 I lead an NIHR programme of research to develop, test and implement an innovation called Video-based Examiner Score Comparison and Adjustment (VESCA) to compare and adjust for examiner variability in large-scale distributed OSCE exams in clinical education. This culminated in the AD-Equiv study, a multi-centre complex intervention trial which aimed to enhance the equivalence and authenticity of graduation level OSCEs.

I have recently been appointed as Keele School of Medicine’s Director of AI in Medical Education. This role involves preparing students for the anticipated future impact of AI on healthcare. Within the role, I lead ongoing development and evaluation of Keele’s AI- virtual patient simulation system as well as developing and critically appraising other AI-based educational innovations. I lead teaching on the foundations of AI and their application to medicine.

I co-lead the faculty wide theme for research and scholarship in health professionals’ education. I am part of the leadership team of Keele’s Methodology Hub. I supervise a number of masters’ and doctoral students on a range of clinical education topics. I am lead for medical education within Keele’s NIHR-funded Integrated Academic Training programme. I am part of the executive group of the national incubator for clinical education research and led a national research priority setting exercise in 2023 which included funders, regulators, royal colleges, patients, trainees, universities and researchers. I am part of the Ottawa international consensus group for use artificial intelligence in assessment in health professionals’ education.