PhD Research

NIHR PSRCs SafetyNet PhD Network event poster presentation on “Uncovering opportunities for mental health support in everyday lives of families with multiple long-term conditions”

I am a mental health occupational therapist. I have worked in various roles across healthcare practice, higher education and research before starting my PhD.

My research ideas have developed through reflecting on the world around me and having conversations with insightful people: researchers, people with personal experience of struggling with their mental health, family carers and other practitioners. My work in inpatient psychiatric services has made me interested in early support in local communities.

My PhD is looking at the use of inappropriate medication in older patients admitted to critical care. As the population of older people is increasing within our society, subsequently so is the number of older patients admitted to critical care. Research has highlighted that medication started acutely during critical care can be unintentionally continued post-discharge. As older patients are living longer, multimorbidity and polypharmacy are on the rise and the addition of critical care medications, can lead to negative patient outcomes. We are hoping to examine the types of medication assessment measures used within critical care, determining if current interventions exist and the clinical outcomes associated with inappropriate medication use in older critical care patients.

I am very fortunate to also be enrolled with the NIHR Greater Manchester PSRC, as this PhD studentship is co-funded by PSRCs in both Newcastle and Manchester. I am invited to attend events in both PSRCs, enabling me to establish contacts and to hear of the great work happening in both networks.

Twitter/X: @Jess_e_mccann

Rajeev’s PhD research broadly focuses on optimising medication use in palliative care patients. Patients with life limiting conditions often experience polypharmacy and inappropriate medication use that can adversely affects in healthcare outcomes as well as increases financial burden. Timely identification and optimisation of these issues through effective intervention such as deprescribing of inappropriate medication can reduce the associated burden. His research aims to understand the pattern of inappropriate medication with polypharmacy among palliative care patients in UK utilising the CPRD (Clinical Practice Research Datalink) data. Moreover, the potential outcomes of deprescribing (discontinuing medicine and medication dose) effects in this population will be explored.

I am a PhD student in the NIHR Newcastle PSRC disadvantaged communities theme, and I previously graduated from Newcastle University with an MSci in Biomedical Sciences. My research explores the financial impacts of emergency childhood illness for families, with a focus on fever and febrile neutropenia.

Although healthcare is free at the point of delivery for children in the UK, families can still face non-medical costs of accessing healthcare – such as transport, food, or childcare. Non-medical costs could form barriers to care if parents cannot afford to pay them or could have knock-on effects including struggling to pay bills or having to borrow money. My research aims to explore what costs families face, how much they are spending, how the costs financially impact families and what could help families struggling financially and improve healthcare access.

I am a PhD student in the NIHR Newcastle PSRC, within the Polypharmacy and Disadvantaged Communities themes. I hold an MSc in Public Health and Health Services Research from Newcastle University, which I undertook during my time as a research programme coordinator within clinical cancer research. In this role I focused on facilitating patient and public involvement and engagement (PPIE) and promoting equality, diversity, and inclusion in research recruitment, which sparked my interest in patient safety within the context of cancer inequalities and intersectionality.

My PhD is investigating the effects of polypharmacy and potentially inappropriate medications (PIMs) across the lung cancer pathway. Most lung cancer patients experience multimorbidity before their diagnosis, and subsequent anti-cancer treatment can worsen these health conditions or result in the onset of new ones. This increases the risk of polypharmacy and inappropriate prescribing. Using a multi-methods approach, I will combine analysis of UK-wide healthcare data with insights from healthcare professionals and patients to understand prescribing and deprescribing decisions and experiences. As the risks of both lung cancer and multimorbidity are higher for people experiencing deprivation, I will also explore whether polypharmacy and PIMs have a disproportionate impact on patients from underserved groups. PPIE will be embedded throughout this PhD.

I am a PhD student in the Data Science and AI theme. Before joining NIHR Newcastle PSRC, I completed an MSc in Data Science at Durham University, which motivated me to explore applicable AI tools that can make a tangible impact on patient care. My research focuses on individuals living with multiple long-term conditions (MLTCs), who often face complex health needs and are frequently prescribed multiple medications—a practice known as polypharmacy. Polypharmacy often stems from the treatment of MLTCs but can also lead to adverse outcomes such as drug–drug interactions. The dynamic interrelationship between MLTCs and polypharmacy is poorly understood, posing challenges for patient safety.

My research uses a data-driven approach to evaluate the appropriateness of polypharmacy and applies machine learning to identify prescribing patterns and predict their impact on patient outcomes. The goal is to generate actionable insights that support more personalised, safer, and more effective healthcare delivery.

Current projects include:

• Developing a dynamic model to improve risk stratification and medication safety (main project).
• Causal machine learning for cardiometabolic diseases.
• MLTCs and polypharmacy in psoriasis cohorts.