I am an Associate Professor and Chief of Section of Patient Centered Analytics at the MD Anderson Center.
The goal of my research is to improve patient outcomes by leveraging data science techniques to make better, more personalised, decisions to guide patient care. To progress towards this goal I focus on two complimentary areas of investigation : patient-centered data and predictive modelling.
Recently, we have shown that patient-reported outcomes measures (PROMs) can be used as a clinical intervention to improve processes and outcomes of care including quality of life, identification of need, and patient survival. We have consistently shown that it is possible to dramatically reduce the length of PROMs without sacrificing assessment accuracy by leveraging computerised adaptive testing (e.g., Harrison and Gibbons, 2022).
Our award-winning collaborative research on the development of AI-enhanced screening techniques to identify complete pathological response (pCR) to neoadjuvant chemotherapy for localised breast cancer suggests that it may be possible to safely de-escalate confirmatory surgery in a large proportion of patients. (e.g., J Clin Oncol, Eur J Can).
We strive to develop effective, safe, and unbiased AI tools to inform clinical decision making to improve outcomes, reduce costs, and ensure that appropriate care is provided at the end-of-life. I collaborate with Project Ronin to demonstrate successful implementation of these tools in real world settings.
I maintain links with the University of Cambridge as Director of Health Assessment and Innovation at the Psychometrics Centre and Health Director of the Concerto Platform. I was previously National Institute for Health Research (NIHR) Fellow based at The Healthcare Improvement Studies (THIS) Institute, and College Research Associate at Corpus Christi College, Cambridge. I then moved to Brigham and Women's Hospital and Harvard Medical School as a founding Co-Director of the Patient-Reported Outcomes, Value & Experience (PROVE) Center.
I have been invited to lecture on topics relating to data science and reported outcomes at institutions including NASA, Karolinska Institutet, and Harvard Business School. I deliver in-person training courses on modern psychometrics, big data, and machine learning at the University of Cambridge.
At MD Anderson, I am the founding Director of Institute for Data Science in Oncology Fellowship program which seeks to endow post-doctoral and junior medical staff with the skills and critical insight necessary to become leaders in oncologic data science.