Imperial College London

Dr Tayana Soukup

Faculty of MedicineDepartment of Surgery & Cancer

Research Fellow in Human Factors - Artificial Intelligence







508Medical SchoolSt Mary's Campus





Tayana Soukup, BSc, MSc, PhD. A psychologist by training, Dr Soukup has completed an NIHR-funded PhD at Imperial College London focused exclusively on cancer multidisciplinary team (MDT) functioning, has worked extensively in the field, and has published numerous papers on evaluating and improving MDTs. Dr Soukup’s expertise includes evaluations of MDTs in real-time, video-based team analytic methods, psychometric development of tools for MDTs, team-based quality-improvements, mixed methodology and implementation science.

Dr Soukup has a longstanding experience of studying MDTs, delivering MDT improvement, and training MDT members, in the UK and overseas, which has been well received and given excellent feedback. Together with her team, Dr Soukup has scientifically studied the workings of cancer MDTs, and has built an extensive evidence-base – with evidence on the factors that promote and those that hinder teams to review patients holistically within a meeting and make implementable and suitable for the patient care recommendations. Dr Soukup has also with her team developed evidence-based tools for the assessment and improvement of the performance of MDTs. These can be used by clinicians, administrators or researchers to gain a reliable and valid understanding of how their MDTs are performing and can be used as part of audit or quality improvement initiatives to improve the delivery of care for patients. They can be applied at different points along the MDT pathway: for pre-MDT meeting case selection; for intra-MDT meeting streamlining; and for team reflection, assessment and team building.

One of the main goals of Dr Soukup’s work is contributing to research on MDT communication and decision-making to inform quality improvements in MDTs by translating evidence into practice and providing means through which to prevent and mitigate unintended detrimental consequence of human factors. The strength of Dr Soukup’s scientific approach is in a unique mix necessary for the study of MDTs, incl. language, cognitive, team and implementation sciences – these underpin the appreciation that a combination of different approaches and innovation are needed to drive improvement, as well as more accurately identify inefficiencies and preventable errors, design appropriate methods/tools, develop effective innovations, and implement/promote their uptake.

Dr Soukup’s affiliations are with Imperial College London, King's College London, University of Suffolk, and The State University of New York at Buffalo (USA).

Dr Soukup's collaborations comprise diverse group of key stakeholders, such Cancer Alliance Network, Department of Health and Social Care, NHS England and NHS Improvement, Public Health England, Roche Diagnostics, National Cancer Institute (USA), East Carolina University School of Medicine. 



Baker N, Bick D, Bamber L, et al., 2023, A mixed methods systematic review exploring infant feeding experiences and support in women with severe mental illness., Matern Child Nutr, Vol:19

Thusini S, Soukup T, Chua K-C, et al., 2023, How is return on investment from quality improvement programmes conceptualised by mental healthcare leaders and why: a qualitative study., Bmc Health Serv Res, Vol:23

Sadler E, Khadjesari Z, Ziemann A, et al., 2023, Case management for integrated care of older people with frailty in community settings, Cochrane Database of Systematic Reviews, Vol:2023, ISSN:1469-493X, Pages:1-119

Soukup T, Lamb BW, Green JSA, et al., 2023, Analysis of communication styles underpinning clinical decision-making in cancer multidisciplinary team meetings, Frontiers in Psychology, Vol:14, ISSN:1664-1078, Pages:1-13

Soukup T, Winters D, Chua K-C, et al., 2023, Evaluation of changes to work patterns in multidisciplinary cancer team meetings due to the COVID-19 pandemic: A national mixed-method survey study, Cancer Medicine, Vol:12, ISSN:2045-7634, Pages:8729-8741

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