A fully-funded 3-year PhD scholarship, funded by the University of Strathclyde Strategic Technology Partnership with Capita, is available with a start date of October 2017. The project, entitled "A Mixed-Methods Approach for Clinical Triage to Improve the Patient's Journey and System Performance", will be under the supervision of Prof. Alec Morton and Dr. Kerem Akartunali. All applications need to be submitted by 30 June 2017, using the application submission link at the following page:
The scholarship will cover a fee waiver at Home/EU rate and annual stipend of £14,510. International students may also apply, however, they will need to demonstrate further funding to cover the difference between international and Home/EU fees (approximately £10k per year). In exceptional cases, further funding may be also secured for excellent international students, however, this is not guaranteed.
The PhD project requires a numerate graduate with interests in healthcare. Candidates should have at least a strong Honours degree or equivalent (a strong 2:1 Honours degree, or a B.Sc. degree with 3.3 GPA in a 4.0 system), or preferably a Master's degree, in a relevant discipline such as management science, industrial engineering, operations research, mathematics or computer science (amongst others). Experience/knowledge in relevant MS/OR techniques is not essential but desirable. Candidates who are not native English speakers will be required to provide evidence for their English skills (such as by IELTS or similar tests that are approved by UKVI, or a degree completed in an English speaking country).
Project details are provided below. For queries regarding the project, please contact Prof. Alec Morton and Dr. Kerem Akartunali.
Clinical triage has been an increasingly popular area of research in the operations management, analytics and operational research (OR) communities due to its significant impact on the downstream health system. A patient's journey starts in the system with triage, and patient data including basic demographics, presenting complaint and physiology (heart rate and blood pressure) influence ongoing management and resource utilization. Decions made at triage have significant impact on the hospital system, since the triage category directly influences the location in which patients are seen, and therefore, a system under stress fails to achieve KPIs, resulting in a degradation in patient care.
Optimising patient flow within the Emergency Department (ED) requires an integrated approach to patient management that extends beyond the ED back to the community following treatment within the hospital. Triage is the landfall moment in a patient's journey, where their condition requires the resource intensive (and costly) management within a hospital rather than community based services.
In this project, the main objective is to better understand patient flows and build a decision support tool that integrates various OR tools in the most effective way in order "to better understand how a patient's journey can be determined and influenced by enhanced processes at triage." How data generated at triage can be linked to the patient's record to create sophisticated predictive modelling of the patient's journey and resource requirement during the episode of care within the hospital and broader healthcare system. The project will involve a continuous collaboration with external clients Capita and local NHS hospitals for the purposes of data collection and implementation/experimentation. We consider in particular three OR toolboxes in order to design and implement such a mixed-methods framework:
1) Simulation will enable us to build models that will be able to evaluate what-if scenarios when the system involves various uncertainties.
2) Optimization will enable us to build models that can make the most out of the system while taking into account its limitations and constraints.
3) Multi-Criteria Decision Analysis will enable us to encounter the often contradictory preferences of various stakeholders of the system.
These toolboxes will be integrated to each other in the final framework in order to minimize their own limitations.
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