Geriatric Medicine

ImPreSs-Care Study

Dr Lucy Beishon (lb330@le.ac.uk), Dr Hari Subramaniam and Professor Tom Robinson

People of all ages with serious mental illness experience reduced life expectancy compared to the general population known as “the stolen years”. Older people have a number of unique physical health challenges due to higher rates of frailty, cognitive and physical impairments, multimorbidity, polypharmacy and complex social needs. Mental and physical health services are fragmented, and access to physical healthcare remains patchy across the country. The ImPreSs-Care study is a mixed methods study using a combination of qualitative, semi-structured interviews and a large quantitative dataset from NHS Digital to develop service recommendations to improve access to physical healthcare for older people in mental health settings. This project is in collaboration with Age UK, University of Loughborough and Nottingham with opportunities to model different pathways of care for older people. Within this project there is scope to investigate a number of related themes including but not limited to:

• Deprescribing approaches to physical health medications on mental health wards;
• Managing frailty and multimorbidity in mental health settings;
• Advanced care planning and end of life care;
• Use of digital technologies and improving care transitions

Successful candidates may also develop their own research project, which must be in line with the College of Life Sciences research strategy & be approved by the Clinical Academic Training Committee prior to commencement of the research, providing there is adequate supervisory capacity at the University of Leicester.

Evidence Synthesis Focused Programme

Professor Kamlesh Khunti (kk22@le.ac.uk)

Utilising evidence synthesis (through various methods such as umbrella reviews and meta-analyses) to address outstanding evidence gaps on the management/treatment and outcomes of MLTC’s. This could for example include reviewing evidence on novel pharmacological therapy (e.g., SGLT2 inhibitors) impacts on wide ranging mental and physical health outcomes in patients with MLTC’s.

Data Analytics Focused Programme

Professor Kamlesh Khunti (kk22@le.ac.uk)

Utilising pre-collected data analytics to produce a series of analyses (through our extensive experience working with and harmonising electronic health records and biobanks) to generate new evidence on underexplored health outcomes and therapies relating to MLTC’s. This could for example include examining data on quality-of-life outcomes for people living with MLTC’s using UK biobank data.

Culturally tailored interventions to improve medication adherence in MLTCs

Professor Kamlesh Khunti (kk22@le.ac.uk)

Investigation into previous interventions designed to improve medication adherence in people with MLTCs from diverse backgrounds, utilising evidence synthesis techniques such as systematic review and meta-analysis. Potential for further qualitative or observational investigation into barriers and facilitators to medication adherence in diverse populations living with MLTC in order to inform development of culturally tailored supportive intervention.

Innovative Care Models for Comprehensive Management of Diabetes and Concordant Long-Term Conditions in Primary Care

Professor Kamlesh Khunti (kk22@le.ac.uk)

This academic clinical fellowship is dedicated to pioneering transformative care models aimed at efficiently addressing the complex intersection of diabetes, kidney disease, heart conditions, and other coexisting long-term illnesses within a single primary care consultation. Our research initiative will focus on designing integrated care protocols, optimizing clinical workflows, and harnessing digital health tools to streamline the management of multiple chronic conditions. By enhancing the coordination of care and providing holistic patient-centred solutions, our project seeks to improve patient outcomes, reduce healthcare disparities, and offer a blueprint for more effective and sustainable primary care practices in the context of complex, concurrent health challenges.