Funded PhD: EduEHR – An AI-integrated interprofessional electronic health record platform for health professions education

• Principal investigator(s) Prof. Sudipto Das, Prof. Muirne Spooner
• Research theme Health Professions Education

Electronic health records (EHRs) are now central to healthcare, yet many health professions students have limited opportunities to learn how to use them before entering clinical practice.

Access to real clinical systems is understandably restricted by patient confidentiality, governance and safety requirements. Existing educational EHRs also tend to focus on individual professions rather than reflecting how doctors, pharmacists, nurses and other healthcare professionals work together around the same patient.

This PhD asks a simple but important question: can we build a better way for future healthcare professionals to learn how to deliver safe, collaborative and digitally enabled patient care before they enter the clinical workplace?

Students will be able to work with realistic synthetic patient records, document care, make and track referrals, develop shared care plans and experience the digital workflows increasingly encountered in modern healthcare. The platform will also explore how artificial intelligence can provide formative feedback, identify omissions and support reflection and learning, while allowing the researcher to investigate when AI support is useful, when it is not, and the risk of over-reliance.

The PhD researcher will be involved throughout the full innovation cycle, from understanding the needs of students, educators and clinical stakeholders to co-designing workflows and developing and iteratively refining a functional prototype. They will then evaluate the platform through simulation and within the student-led interprofessional community clinic, examining how learners use EduEHR and whether it improves digital health competency, documentation quality, clinical reasoning and readiness for interprofessional collaborative practice.

What makes this PhD particularly exciting is the opportunity to build something tangible and test it with the people who could ultimately use it. It sits at the intersection of AI, digital health, education, clinical practice and human-centred design, giving the researcher the opportunity not simply to study the future of healthcare education, but to help create it.

Key objectives

The PhD researcher will:

• Co-design EduEHR with students, educators and clinical stakeholders to ensure that it reflects authentic interprofessional healthcare practice.
• Develop and refine a functional platform integrating realistic patient records, shared clinical workflows, competency tracking and AI-supported learning.
• Evaluate its educational impact, including effects on digital health competencies, clinical reasoning, documentation and interprofessional collaboration.
• Investigate responsible AI in education, examining the safety, explainability, usefulness and potential over-reliance associated with AI-generated feedback.
• Explore real-world implementation, identifying what is needed for EduEHR to be adopted and sustained across health professions education and student-led clinical environments.

Tenure: Four years

Start date: March 2027

Specification

Minimum requirements

• Lower second class (2.2) honours degree (or equivalent) in a relevant subject.
• IELTS 6.5–7.0 (other English language tests are accepted – please see English language requirements.

Desirable candidate specifications

• Experience or a strong interest in digital health, electronic health records, clinical informatics or healthcare technologies.
• Knowledge or experience of artificial intelligence, data science or machine learning, particularly their application in healthcare or education.
• Experience of health professions education, simulation-based learning, curriculum development or educational research.
• An understanding of interprofessional healthcare, including how different healthcare professions communicate, document information and coordinate patient care.
• Experience with qualitative or mixed-methods research, for example interviews, focus groups, surveys, thematic analysis or evaluation of educational interventions.
• An interest in human-centred or participatory design, including working with end users to understand requirements and iteratively develop and evaluate digital solutions.
• Experience of usability or user-experience evaluation of digital platforms would be advantageous.
• Some experience of quantitative data analysis, using tools such as R, Python or equivalent analytical software, would be beneficial.
• An interest in responsible AI, particularly issues surrounding the safety, explainability and appropriate use of AI-supported feedback and decision support.

Please note: No specific wet-laboratory techniques are required for this PhD. Rather, the project will involve stakeholder research, co-design, development and iterative testing of an educational EHR, followed by mixed-methods evaluation in simulation and the student-led inter-professional community-clinic setting.

Application process

Please apply for the research project through the link below.

Applications must include:

• A completed application form
• English language requirements