PhD Studentship: Improving Reliability and Efficiency of Medical Processes through Patient-centred Modelling and Technological Solutions

Updated: 4 months ago
Location: Nottingham, ENGLAND
Job Type: FullTime
Deadline: 28 Feb 2023

Location: UK Other

Supervised by Rasa Remenyte-Prescott (Faculty of Engineering)

Aim: To investigate how deviations in healthcare service can be reduced using patient-centred simulation models and computer vision techniques


Adverse events and preventable failures in healthcare services represent a key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which influences process reliability, efficiency of usage of hospital resources and risk to staff and patient safety. Computer vision approaches can be used to identify deviations in both technical and potentially non-technical skills of medical staff, such as poor team dynamics, problems with communication and a lack of leadership. The obtained data can then be fed into computer-based simulation models that are used to evaluate a range of deviations from guidelines and their effects on procedure outcomes and used to support operational and strategic decisions. Undoubtedly, the usage of such approaches can only become successful if patients are placed in the heart of technology usage, which is designed with patients’ perspective in mind.

Proposed project

This project would investigate commonly observed deviations in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models, which are used to evaluate effects of deviations and to support decisions. It will focus on investigating how deviation data can be used in real time decision-making process, how accepting patients and staff are for such technologies and what integral role they should play in evaluating and ensuring an uptake of such technologies. The proposed method will be potentially applied to processes carried out in an operating theatre.

Summary: Open to UK/EU/overseas students. Look for funding sources at

Entry Requirements: Starting October 2023, we require an enthusiastic graduate with a 1st class degree in engineering, maths, psychology or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered).

To apply visit:

For any enquiries about the project and the funding please email Rasa Remenyte-Prescott ( )

This studentship is open until filled. Early application is strongly encouraged.

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