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Dr Rob Saunders

Dr Rob Saunders

Lecturer (academic)

Clinical, Edu & Hlth Psychology

Div of Psychology & Lang Sciences

Joined UCL
15th Sep 2008

Research summary

My main research interest is in the use of data to improve healthcare delivery.

One focus is whether a better understanding of the interaction between clinical and socio-demographic patient characteristics can inform a more personalised and tailored approach to routine treatment for mental health conditions. This includes the potential development and use of algorithms to support clinical decision making.

I am particularly interested in how big data, especially around co-occurring mental and physical health issues, can improve our ability to predict the risk of mental health illness as well as individual treatment outcome.

I also have an interest in the measurement of clinical needs and symptoms, psychometrics and between-group differences in measure interpretation.

Teaching summary

I supervise a number of MSc and Doctorate in Clinical Psychology (DClinPsy) thesis projects. I am the statistics demonstrator for the DClinPsy course and teach the statistics module of this course.

Education

University College London
Doctorate, Doctor of Philosophy | 2018
University of Leicester
First Degree, Bachelor of Science | 2008

Biography

I am a Lecturer in Mental Health Data Science at the Centre for Outcomes Research and Effectiveness (CORE) at UCL, and co-lead the CORE data lab.


My first role at CORE involved supporting the development of National Institute of Health and Care Excellence (NICE) clinical guidelines for the management and treatment of mental health disorders. I later led a project developing novel analytic methods to support resource allocation system algorithms used by health and social care services across the UK. For this I developed both assessment tools to capture multidimensional needs of service users,and the algorithms used to determine resource provision from assessed need.


As part of my PhD I developed a patient profiling system for predicting response to psychological treatments using data collected by Improving Access to Psychological Therapies (IAPT) services. Building on this experience of IAPT data, I was invited to conduct a national evaluation of healthcare utilisation for IAPT patients with long-term physical health conditions, which involved linkage and modelling of healthcare episodes data and costs with IAPT treatment datasets. This collaboration with Imperial College London required the analysis of over 500 million hospital records and was used to inform a national roll-out of psychological treatment services for patients with co-occurring mental and physical health issues. I am a founding member of the North and Central East London (NCEL) IAPT Service Improvement and Research Network (SIRN), a collaboration between local IAPT services and researchers to use routinely collected data to inform clinical practice and develop strategies for improving patient care. I currently lead analytic projects through the NCEL SIRN project alongside Dr Joshua Buckman, and support ongoing national evaluations of the IAPT programme.


I have also led a number of evaluations of routine mental healthcare services, including psychiatric-liaison services, mental health wellbeing apps and parent-training programmes, and have supported analysis of datasets ranging from experimental studies, longitudinal cohort studies and randomised controlled trials. Through these, I have developed considerable experience in the use of complex healthcare and psychological datasets, as well as developing analytic methods to better understand mental health and treatments. I collaborate on a number of research projects with both UCL and non-UCL colleagues,where I typically offer consultation and advice on methods and data analysis.


I am a visiting researcher at the Centre for Health Economics & Policy Innovation (CHEPI) at Imperial College London Business School.


Publications