​​​​A Patient-Centric Approach to Healthcare Complaints - Using Artificial Intelligence for Improved Support and Resolution​ ​

Summary

​​Complaints to the NHS generate large volumes of data that should inform improvements to quality of care and patient safety. This PhD project will explore the application of Large Language Models (LLMs) in improving complaint management and resolution systems within a healthcare setting. The research will investigate how LLMs can streamline and optimise the management and resolution process through automating key processes such as complaint categorisation (text classification) and analysis, sentiment analysis, and response generation (text generation). Efficient complaint handling is important in maintaining patient trust, improving patient care quality, and addressing inequalities in patient complaint processes and experiences. It is anticipated that this project will assess the accuracy and performance of using LLMs in handling patient complaints and examine the potential of AI to reduce response times, and support complaint management to ultimately enhance patient satisfaction using formalised key performance indicators (KPIs).​

The following study areas will address the technical, practical, and communicative aspects of exploring the integration of AI in healthcare complaint management to optimise processes for effective outcomes.

1. Exploring AI Integration in Complaint Handling 
This study will focus on exploring techniques, frameworks, and case studies for integrating LLMs into complaint management systems. The study aims to explore ways to improve efficiency while ensuring necessary human oversight ”human-in-the-loop”.

2. Exploring LLMs Architectures for Complaint Management 
This study area will focus on the capabilities, limitations, of LLMs specifically for complaint management. The objective is to adapt and optimise LLMs to effectively handle complaint scenarios, addressing unique NLP challenges, ethical considerations, and system integration requirements.

3. Evaluation and validation of AI Supported Complaint Management Prototype 
This study area will evaluate prototype with selected stakeholders  and measure the impact of the AI system on critical performance indicators, such as complaint resolution time, classification accuracy, and using pre-defined benchmarks for comparison.   ​

The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education. We particularly welcome female applicants, as they are under-represented within the School.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Sound understanding of subject area as evidenced by a comprehensive research proposal
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• For VCRS Awards, Masters at 75%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.