Eliciting Patient, Carer and Clinician Preferences for Virtual Ward Models in acute Atrial Fibrillation Care

About the Project

Atrial fibrillation (AF) is one of the most common cardiac arrhythmias and associated with increased risk of stroke, hospitalisation, and reduced quality of life [1], [2], [3]. Recent development in healthcare delivery have introduced Virtual wards (VWs) as an alternative model of care. Evidence suggests that VWs, for acute atrial fibrillations (AF), can lower healthcare costs by shortening hospital stays, reducing avoidable hospital admission and prevention of readmissions, and operate at lower costs [1], [3] . Kotb et al. (2023) reported that a digitally enabled virtual ward at Glenfield Hospital in Leicester prevented 49 hospital admissions and saved between 98 and 245 hospital bed days, with high patient satisfaction [1]. Similarly, Saleh et al. (2024) demonstrated a reduction in emergency visits and inpatient length of stay using app-based ECG monitoring and symptoms tracking [3].

However, successful implementation depends on how well the model aligns with the preference, expectations, and experience of those directly involved in care - patients, carers and clinician. It also relies on the willingness and readiness of hospitals and trusts to invest in transitioning to virtual ward services.

This project aims to elicit and compare the preferences of stakeholder (patients, carers, and clinicians) regarding virtual wards for acute AF management, using structured preference elicitation methods (i.e., discrete choice experiment or willingness-to-pay approach). We will identify which attributes of VWs care are most valued by each group. Understanding these preferences is essential for designing patient-centred and clinically acceptable virtual care models. The findings will improve shared decision-making between clinicians and patients and inform policy and service design decision.

Training opportunities:

The candidate will have opportunities to attend Post Graduate Research masterclasses run by the College and Life Sciences as well as sitting in some modules in Master’s Degree courses such as clinical trials, health economics and medical statistics.

Apply at:
https://le.ac.uk/study/research-degrees/research-subjects/cardiovascular-sciences

PhD entry requirements:https://le.ac.uk/study/research-degrees/entry-reqs

Supervisor contact details:
Prof Guiqing Lily Yao - gy38@leicester.ac.uk