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402a4c2a-6e60-4ba0-ab22-b08ca49f80a9 Deprescribing and Optimisation of Medicines IN Older people with Heart Failure and Frailty (DOMINO-HFF) Chief Investigator: Dr Eloise Radcliffe, Senior Research Fellow School of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton Team: Dr Kinda Ibrahim, Associate Professor, School of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton Dr Sara Mckelvie, Clinical lecturer, School of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton. Dr Stephen Lim, Principal Clinical Research Fellow, Consultant Geriatrician, Medicine for Older People, University Hospital Southampton, Southampton General Hospital. Dr Chris Young, Consultant Geriatrician, Medicine for Older People, University Hospital Southampton, Southampton General Hospital. Dr Nina Fudge, Lecturer, Centre for Primary Care, Wolfson Institute of Population Health, Queen Mary University of London. Dr James Sheppard, Associate Professor, Nuffield Dept of Primary Care Health Sciences, Medical Sciences Division, University of Oxford. Mrs Clare Howard, Clinical Lead for Medicines Optimisation, Health Innovation Wessex. Prof Simon Fraser, Professor of Public Health, School of Primary Care, Population Sciences and Medical Education,Faculty of Medicine, University of Southampton. Dr Peter Cowburn, Consultant Cardiologist, University Hospital Southampton, Southampton, General Hospital. Ms Rajneesh Kaur, Patient and carer representative . Partners: University Hospital Southampton NHS Foundation Trust, University of Southampton, Health Innovation Wessex, Queen Mary University of London, University of Oxford. Start: 1 October 2024 End: 31 March 2026 Background Heart failure ( HF) is a long-term disease with symptoms including breathlessness, tiredness and leg swelling. HF is more likely to affect older people and is the leading cause for hospital admission in the UK for those aged over 65 years. Most people with HF have other health conditions therefore taking multiple medication is common. Guidelines for doctors to treat HF recommending multiple medications to help improve symptoms and help people live longer, have led to concerns about further increases in numbers of medication for patients. The application of these guidelines in older adults has had the unintended problem of more complex medication regimes, and possible impacts on physical ability and quality of life. More generally, taking multiple medication can increase risk of side-effects, hospital admission and death for older people. The research studies used to decide guidelines for doctors to treat HF, may underestimate the risks of taking multiple medicines as they do not include populations most vulnerable to potential harms such as older adults and those with frailty. This leads to uncertainty about the long-term benefits and risks of HF medications in the very old and frail populations who are, nonetheless, still treated based on the guidelines. Prescribing should ideally be tailored to each patient’s health condition and their preferences. These factors will change over time, supporting the need for regular medication reviews, and where appropriate, the need for reducing, stopping, or switching drugs in order to improve outcomes. However, this may be challenging due to the lack of research studies, as patients and multiple health care professionals involved in caring for older patients with HF, may experience uncertainty and have differing approaches to the application of the guidelines. Aim To examine research studies on prescribing and deprescribing of HF medication in older people, including those living with frailty. This will inform current guidelines for doctors to treat HF. It will also identify gaps in the research on this vulnerable group commonly prescribed HF medication, but at the greatest risk of experiencing harms linked with taking multiple medications. Design and methods Two literature searches will be carried out, guided by an information specialist librarian, following the established guidelines. Patient, public and community involvement This study has patient and public involvement (PPI) throughout. We will have PPI group of older people and carers living with HF, chaired by our PPI lead who is also a research team member and has contributed to study development. The group will contribute to the interpretation andcommunication of findings on a wider scale. Dissemination Findings will be promoted to the wider research and local clinical community through ARC Wessex networks and our links with Health Innovation Wessex , and in journal publications and conference presentations. We will also promote findings through the links that we will make with local and national charities such as Age UK Southampton, Wessex Heartbeat and the British Heart Foundation.

6dc4c269-ddb7-41c3-afd8-8173c69a4651 ADOPTED ActMed-VW - Healthcare professional's experiences of Access to Medication for people on Virtual Wards who are in their last year of life Virtual wards provide acute, hospital-level care in an individual’s own home, rather than in a hospital or hospice. They are also known as Hospital at Home services. We know that virtual wards can care for people who are in their last year of life. For individuals approaching the end of life, control of symptoms requires prompt access to medication. We know access to palliative care medication can be challenging in the community. There have also been reports of difficulty accessing medication on virtual wards; however, it is not known if there are specific issues accessing palliative care medications on virtual wards. This study aims to investigate access to medication for adults on virtual wards who are in their last year of life. We aim to understand the experiences of healthcare professionals so that we can make recommendations on how to improve access to medication in the future. We will ask healthcare professionals working in virtual wards to answer questions in an online survey. We will ask doctors, nurses, pharmacists, and allied health professionals such as physiotherapists to complete the survey. We will ask them about what works well and what does not. We will ask them about the challenges they have faced, and what would help them to minimise or eradicate these. We will also interview 20 healthcare staff. This will include both professionals who completed the survey and individuals who oversee the management of virtual ward services. We will explore in more detail examples of good practice and the processes that need to be in place to ensure straightforward, fast access to medication. We will consult with clinical and policy experts on potential solutions to the challenges identified in the study findings. We will also work with these experts to develop recommendations for policy and practice. Project team includes: Co-PI - Dr Nicola Andrews Co-PI - Prof Sue Latter Co-I Dr Natasha Campling Co-I Dr Sara McKelvie Research Fellow Dr Dan Aze

b369496b-453f-489e-9d44-7a954ac3f6d7 COMPLETED: Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways (STIMULATE) This project is part of a national consortium Contact: Professor Nisreen Alwan MBE , University of Southampton Currently in England, there are 90 specialist Post Covid services in which assessment and treatment of Long Covid, and other complications of COVID-19, are informed by NICE guidelines and growing expertise in the field. However, there is evidence that access to such clinics and related care pathways, the nature of those pathways, and patient experience, varies. Research is required to inform diagnosis, care, public health strategies, policy planning, resource allocation and budgeting. It is likewise essential to define the usual care pathway in Post Covid services, and to understand patient presentation, and the effectiveness and cost of care. The STIMULATE-ICP consortium includes: University College London Hospitals NHS Trust, University College London, University of Central Lancashire, LongCovidSOS, UK Doctors #Longcovid , Royal College of General Practitioners, University of Liverpool, Liverpool University Hospitals Foundation Trust, Perspectum, Living With, University of Hull, Hull University Teaching Hospitals Trust, University of York, University of Leicester, University of Exeter, University of Southampton, University of Sussex, Alliance Medical, GE Healthcare, Olink, Francis Crick Institute, NIHR Applied Research Collaboration South West Peninsula, NIHR Applied Research Collaboration East Midlands, NIHR Applied Research Collaboration North Thames, NIHR Applied Research Collaboration Yorkshire and Humber, NIHR Applied Research Collaboration North West Coast, British Heart Foundation Data Science Centre, BHF Data Science Centre, Health Data Research UK, Office of National Statistics, Royal Devon and Exeter NHS Trust, as well as NIHR Clinical Research Network support. Plain English Summary of findings: 23 interviews were completed with people with probable Long Covid We found… There was a lack of awareness of Long Covid, its symptoms and the support available for people with Long Covid An assumed lack of awareness of Long Covid within healthcare People with Long Covid symptoms experienced doubt and uncertainty about the cause of their symptoms Experiences of stigma and discrimination were commonly experienced by people with probable Long Covid. This included experiences of age and gender discrimination, experiences of being dismissed, unsympathetic attitudes and social exclusion. People with probable Long Covid reported feeling embarrassment, feeling tainted and/or different to others because of their Long Covid symptoms. In addition, they expected disbelief and/or judgement from others because of Long Covid People with Long Covid were sometimes reluctant to seek care due to worries surrounding possible investigations and medications, or worries about symptoms being wholly attributed to mental health conditions. There were also concerns about burdening the NHS. The nature of Long Covid symptoms made accessing care difficult. Long Covid symptoms can often come and go or fluctuate, and sometimes one symptom may be more prominent than others. This can mean some symptoms can be overlooked by patients and healthcare professionals. Experiences of people with Long Covid are also constitute epistemic injustice, or inequality surrounding creating, interpreting and conveying knowledge. This is due to the lack of awareness and knowledge of Long Covid both in the community and within healthcare. What we did Research findings from this study and the NIHR funded HICOVE study have been translated into an easily-usable webtool. This tool aims to encourage people with probable Long Covid who have not yet sought help and support from the NHS or other services to do so. It covers topics of self-doubt, stigma and effects on mental health as well as offering resources, tips, and advice on next steps. This tool is primarily aimed at people who may have Long Covid but are not currently accessing care but may also be helpful to those who are. It is also aimed at healthcare professionals, social prescribers, as well as community organisations to raise awareness about the difficulties and stigma people, particularly those from disadvantaged backgrounds, may face when considering reaching out for a consultation or community support. The webtool is available here: Supporting Long Covid Care ( long-covid-care.org.uk ) Where next? We are working on disseminating the Supporting Long Covid Care webtool as widely as possible. We will create an offline version of the tool so this is accessible to people who are not ‘online’. We will also include translations of this into community languages. This will be available to download from the website and from community organisations. We are also looking at ways to evaluate the webtool. See our news article

535f16ee-e98a-4782-81fa-97a73abd8468 ADOPTED: Improving patient safety, workforce wellbeing and NHS efficiency through improved shift patterns for nursing staff: study protocol Principal Investigator: Dr Chiara Dall'Ora, University of Southampton Project partners: University of Southampton; Nottingham University Hospitals NHS Trust; Herefordshire and Worcestershire Health and Care NHS Trust; Northumbria Healthcare NHS Foundation Trust; Sheffield Children’s NHS Foundation Trust; Southern Health NHS Foundation Trust; Nursing and Midwifery Council Team: Dr Hannah R. Barker (Qualitative lead), Prof Peter Griffiths (Senior Mentor), Dr Chiara Dall’Ora (Project lead) Public & staff involvement: Nursing staff, ward managers and matrons from 5 Trusts helped shape the DCE survey and future research priorities Funded : Academy of Medical Sciences Springboard grant Started: 1/9/23 Ended: 31/8/24 Lay summary What is the problem? If the COVID-19 pandemic has taught us something, it is how important the wellbeing of the health workforce is. Nurses form a big part of the health workforce, yet many leave their job because of poor working conditions. In recent years, hospital managers introduced long shifts for nurses, hoping nurses would be happier with their work-life balance. However, our research found that long shifts have negative effects for nurses and patients. We still do not know what good shift patterns look like. What we asked: How can shift patterns be designed to better support nurses’ wellbeing and help the NHS retain staff? We conducted interviews with nursing staff, ward managers and NHS directors across five Trusts, and a large UK survey (discrete choice experiment) with 1,449 registered nurses. What we found: Nurses value (1) consistency and predictability in rotas; (2) adequate rest between shifts; and (3) opportunities to enjoy work through meaningful time with patients and teams. Rigid, last‑minute rosters and very long shifts erode wellbeing. From the national survey: Night‑only patterns and having no whole weekends off are the least acceptable rota features and require the largest compensation to tolerate. Predictable schedules and having scope to request shifts are strongly valued. Nine‑to‑ten‑hour shifts are preferred over 12.5‑hour shifts. What this means: Collaborative rostering that balances service needs with personal circumstances can improve satisfaction and reduce turnover. Guaranteeing protected weekends where feasible, improving predictability, and avoiding very long duties are practical levers for better retention and patient care. What we did with the new knowledge: We ran 5 dissemination and co‑design workshops with NHS Trusts (Jan–Feb 2025) to share qualitative findings and plan next steps. Used findings to refine a national discrete choice experiments (DCEs) on rota preferences (n=1,449) and generate policy‑ready benchmarks for rota design and enhancements. Engaged workforce matrons and managers to shape future studies on flexible rostering and shift design. What's next? - Publish the DCE paper. - Produce a policy brief (ongoing with Public Policy | Southampton) - Attract funding to evaluate how flexible rostering can reduce sickness absence, turnover and costs - Co‑design of a shift‑work intervention with staff and managers (Hannah Barker NIHR Development & Skills Enhancement Award) - Support Trusts to pilot more predictable rotas, protected weekends and 9-10‑hour options where feasible. See article: Moving Beyond 12 Hour Shifts: How Evidence is Powering Change

a0531f94-b063-4041-908b-5830a10b5f66 ADOPTED: Community pharmacy alcohol-related liver disease risk identification and linkage to care through development of a complex intervention (CIP-LINC) Prinicpal Investigator: Dr Alexander Smith Start Date: 16 February 2023 End Date: 31 March 2025 Background Liver scarring (known as cirrhosis) is a frequent and ever more common reason for dying in the United Kingdom (UK). The most common cause of liver scarring in the UK is alcohol. Death from liver scarring can be prevented if liver disease is found at an early stage. This can be hard because many people with liver scarring do not look or feel unwell until they develop liver failure. At this stage it is too late to prevent complications. Alcohol-related liver disease can be found earlier by assessing for it in people who drink too much alcohol. This is advised in national guidelines. Local pharmacists are one of the most accessible health professionals. There are over 12000 local pharmacies in England. Lots of these pharmacies are in areas where more people have alcohol problems. Local pharmacists are able to identify people who drink too much alcohol and provide them support to drink less. However, it is not known if local pharmacists can get these people assessed for alcohol-related liver disease. This study looks at how this could be done with the aim of creating a Toolkit to make it happen.

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15c54097-9d85-4170-b90f-d0f5767a45d4 COMPLETED: Predicting Patient Deterioration Risks in COMMunities Team: Principle Investigator – Professor Michael Boniface, University of Southampton Co-Investigator - Dr Francis Chmiel and Dr Dan Burns, University of Southampton Clinical Lead – Dr Matt Inada-Kim, Hampshire Hospitals NHS Foundation Trust Completed What did we learn? We found evidence for policies and practices supporting safe COVID-19 integrated care pathways in community settings for early identification of deterioration and timely escalation to hospital. Research validating home oxygen saturations as a marker of clinical deterioration in patients with suspected COVID-19 informed national policies and was critical and rapid evidence necessary to support the COVIDoximetry@home ( https://doi.org/10.1101/2020.11.06.20225938 under peer review at BMJ Open) What difference did it make? £ 500K NHSx RECOxCARE (Remote COVID oximetry care) project for COVID Virtual Wards in collaboration with HHFT, North Hants Primary Care Network, Mid Hants Primary Care Network, South Central Ambulance Service NHS Foundation Trust, WAHSN and University of Southampton IT Innovation Centre. Scaling nationally as the COVID oximetry@home programme, the guidance for people at home to purchase a pulse oximeter published on the BBC News Website https://www.bbc.co.uk/news/health-55733527 and broadcast on BBC News at 10 on Thursday 21st January 2021 (citing the ARC publication) Clinical model was adopted by the World Health Organisation Digital and data analytics approach for remote monitoring of patients in communities was presented by Inada-Kim and Boniface as part of the NHSx@home innovators engagement event 16th Sept 2021. COVID oximetry@home received the overall winner of the prestigious for HSJ Patient Safety Award 2021 Service evaluation demonstrated improved patient outcomes Boniface, M., Burns, D., Duckworth, C., Ahmed, M., Duruiheoma, F., Armitage, H., Ratcliffe, N., Duffy, J., O’Keeffe, C. and Inada-Kim, M., 2022. COVID-19 Oximetry@ home: evaluation of patient outcomes. BMJ Open Quality, 11(1), p.e001584. What impact has it had on patient and the health system? Remote monitoring of patients in communities is important for improved patient outcomes, hospital attendance/admissions avoidance and resource planning. Remote monitoring is a key NHS transformation within the NHS@Home programme Remote monitoring is being extended from COVID to all Acute Respiratory Infections, and is likely to be extended to other conditions in the future What's next? We are working with Hampshire Hospitals and NHS England to transfer the learning from COVID to more general approaches. This research is being conducted in: HDRUK rapid insight project (Jan22-Sep23) called PHILOSARIP “ Predicting Hospital Length of Stay in Acute Respiratory Infections Patients” Wessex ARC PARIEDA project which is tacking “ Prediction of Acute Respiratory Infection outcomes prior to Emergency Department Attendance” Resources Covid Oximetry at Home Toolkit - via AHSN Wessex Publications https://doi.org/10.1101/2020.11.06.20225938 https://doi.org/10.1136/bmjopen-2022-067378 Original Project outline ARC Wessex is supporting research to explore COVID patient risks (deterioration, admission and readmission) in community settings working with Hampshire Hospitals NHS Foundation (HHFT) Trust who are co-leading the development of national pathways linking community, primary and secondary care. According to leading acute care clinicians (Dr. Inada-Kim - HHFT) working at the forefront of UK’s COVID-19 emergency response and policymaking, two of most pronounced COVID-19 Unmet Medical Care Needs (UMCN) include: UMCN-1) Risk prediction tools on triage and admission to emergency care: Evidence shows that early identification of physiological deterioration risks improves patient outcomes through timely and appropriate interventions, including escalations to higher levels of acute care through hospital admissions and intensive care [1] . UMCN-2) Rapid follow up of patients post discharge: There is little evidence to predict the occurrence of COVID19-related complications following discharge, particularly for vulnerable patients with multiple long term conditions at high risk of adverse complication events, and therefore rapid follow up and continuous monitoring of a patients recovery is needed to reduce risk of readmission to hospital. In addition, consideration of population infection risks resulting from contact and transmission from infected individuals has demanded alternative care delivery models. During the initial phase of the pandemic patients freely made their way to GPs and hospitals increasing infection rates within the general population and the healthcare workforce, leading to policies aimed at reducing contact between infected patients and health care workers (HCWs) [2] . This has driven then need to reimagine care pathways that minimise physical interaction using virtual care (video conferencing, mobile symptom reporting/scores, real-time remote sensing, and surveillance) delivered through telemedicine solutions. Virtual care not only protects the population and HCWs during highly infectious periods of a pandemic but importantly offers significant benefits to patients who can now be treated longer in community settings reducing the number of admissions to hospital, the length of stay and mortality. PPDRCOMM proposes to undertake research to develop predictive models for early warning detection arising from a COVID-19 infection, capable of running in residential settings such as care homes. Models will use near-patient observation data (e.g., temperature, respiration rate, and blood oxygen levels), patient demographics, and comorbidities from patients in the community who are in the early stages of a COVID-19 infection. The measurements will be collected with high frequency such that machine-learning algorithms will be able to report real-time risk scores of imminent deteriorations. Overall, this models will allow for real-time detection of deterioration earlier than currently possible with conventional techniques. This will help address the clinical need for pre-emptively stopping the severe deterioration of those with a seemingly mild case of COVID-19. Read the Evaluation Pre-Print evaluation paper

ARC Wessex is part of the National Institute for Health and Care Research. We conduct research together with universities, health and care services, the NHS, charities, people and patients to improve the lives of people in our community. Read about Vikki's work with dementia patients Latest news Moving Beyond 12 Hour Shifts: How Evidence is Powering Change Have you forgotten me - bridging the gap with dementia diagnosis Thanking patients and the public for helping shape our research Compromise shifts the balance for nurses ARC research heads to Westminster to talk about the challenges of over-prescribing medicines. Research input to influence NHS 10 year workforce plan Read more NIHR ARC Wessex in numbers 200+ Members 100+ Academy members £18M Invested in research 155 Research projects How can we help? For professionals & researchers Read more For public & patients Read more For training & development Read more

91dc7d16-9cb6-45e1-b40a-33037865948b COMPLETED: Digital support for maintaining physical activity in people with long-term conditions What promotes and prevents health professionals using ‘digital’ technologies to support people with long-term conditions (LTCs) to maintain physical activity and improve their health and wellbeing? Principle Investigator - Professor Mary Barker ( meb@mrc.soton.ac.uk ) Senior Research Assistant – Dr James Gavin ( j.p.gavin@soton.ac.uk ) Team Prof Mary Barker (PI), Prof Maria Stokes (Co-Lead), Prof Suzanne McDonough (Co-Lead at RCSI), Mrs Luisa Holt, Dr Aoife Stephenson (RCSI), Mr Paul Muckelt, Dr Nisreen Alwan, Dr Katherine Bradbury, Dr James Faulkner (University of Winchester), Dr Dorit Kunkel, Dr Euan Sadler, Prof Sandy Jack, Mrs Rachael Eckford, Mr Jem Lawson (PPI) and Mr Ranj Parmar (PPI) Project partners • Royal College of Surgeons in Ireland • University of Winchester What did we find? We interviewed 15 GPs and health professionals to find out their experiences of using digital technologies, such as online consultations, mobile-phone applications (or ‘apps’) and websites, to support people with LTCs to manage their health. We now have a better understanding of the factors preventing and promoting the use of digital technologies by health professionals to support people with LTCs in the NHS. These included: Preventing : one ‘app’ will not suit all LTCs, ‘apps’ must be user-friendly and accurate, clinicians need to dedicate time to the technology, security risks, patients need to have digital literacy, and long-term investment is required (time and finance). Promoting : ‘apps’ being evidence based, peer/social support of GP networks (including positive feedback), charity endorsement, COVID-19 changing people’s attitudes to digital health, ‘apps’ being linked to a hospital’s IT systems, accountability/monitoring of ‘apps’, and digital champions What difference will this make? Better understanding of the factors preventing and promoting the use of digital technologies by NHS healthcare professionals can help researchers develop new assessments and interventions to help people with LTCs to self-manage their conditions. In future, it could inform a regional evaluation of existing self-management programmes and initiatives to support people with LTCs to maintain their health and physical activity, from a digital perspective What are we doing with this? We have published one journal paper in PLOS One ( 2024 ) and co-investigator, Prof O’Donough published one systematic review paper in Digital Health ( 2024 ) In conjunction with the ‘non-digital’ MOTH study, we are in the process of applying for funding for: A PhD studentship, and NIHR Research for Patient Benefit (RfPB) award Maintaining physical activity and social connections for people with multiple LTCs: intervention development. The aim is to produce a plan for how best to proceed with improving partnership working within Wessex. The aim is to produce a plan for how best to proceed with improving partnership working within Wessex. What next? We plan to combine the non-digital and digital findings from the MOTH programme and apply for NIHR RfPB funding to co-design a 12-week follow-on maintenance intervention to sustainphysical activity for people with multiple LTCs following existing PA programmes between healthcare and community settings. The intervention will be developed informed by and aligned to the NHS Neighborhood Health agenda (2025) and current Southampton Integrated Neighborhood Hubs project . A suitable funding call is the NIHR Research for Patient Benefit (RfPB) programme (tier 3), with a stage 1 deadline of February 2026. Digital MOTH summary Non-Digital Moth Summary Publications https://doi.org/10.1177/20552076221089778

0b30aba5-25eb-4a0f-ba09-0cc56d28cb07 PROCED-DST: PROactive, Collaborative and Efficient complex Discharge – Decision Support Tool Chief Investigator: Dr Chris Duckworth, Senior Research Engineer, University of Southampton Email: C.J.Duckworth@soton.ac.uk Team: Professor Michael Boniface, Director of the IT Innovation Centre, University of Southampton, (HEI) Dr Carlos Lamas-Fernandez, Associate Professor, Southampton Business School Dr Dan Burns, Senior Research Engineer, University of Southampton Dr Mark Wright, Patient Flow Lead, University Hospital Southampton NHS Foundation Trust (NHS) Rachel Leyland, Complex Discharge Team Manager, Hospital Southampton NHS Foundation Trust (NHS) Ian Dickerson (PPIE) Partners: Hampshire and Isle of Wight NHS Foundation Trust, Hampshire Hospitals NHS Foundation Trust, Isle of Wight NHS Trust, Portsmouth Hospitals University NHS Trust, University Hospital Southampton NHS Foundation Trust, University of Southampton, Health Innovation Wessex. Start: 1/10/24 End: 31/3/26 Summary As of January 2023, 14,436 patients a day (14% of total capacity) remained in hospital despite being well enough to leave. This is due to delays in arrangements for onward care. Discharge delay occupies beds putting pressure on a wide-range of NHS services. There are currently 7.6 million patients waiting for treatment and an average waiting time of 15 weeks. Leaving hospital at the right time is also better for patients for many reasons. It reduces physical and mental deconditioning and chance of hospital infections. Part of the problem is organising further care required after a hospital stay. For patients in hospitals for seven days or more, 65% are delayed because they are waiting for after-care including care at home, short-term reablement and permanent care or a nursing home. Discharge planning involves lots of people and organisations from patients through to clinical teams in hospitals, community care, and local authorities. Organising care takes time considering the availability of social care services and mediation with patients and their families. It is therefore important that patients are assessed, and needs identified as early as possible within a hospital stay to give time for planning and conversations. An initial discharge assessment is supposed to be made with the first 24 hours of hospital admission. In practice this planning is provided for less than 50% of patients. Staff workload and inability to identify care requirements can delay assessments. Aims: In a previous project called PROCED, we developed a machine learning model to predict onward care needs when someone is admitted to hospital. Machine learning is a computer programme that can learn from information about patients and the services they use to make predictions. We have compared the model against predictions made by clinicians, and the results have shown it works well. In PROCED-DST we aim to investigate how a machine learning prediction can support better discharge planning. By planning care earlier during hospital stays gives more time for patients and families to discuss care needs with care workers. Ultimately we aim to improve the chance that patients can leave hospital on time. Approach: We will consider how a computer algorithm can help clinicians organise onward care by predicting admitted patient’s potential onward care needs. We will organise collaborative sessions with clinicians, patients, and computer programmers to understand how it could be used in the hospital and consider how it may benefit or impact patients. Patient and Public Involvement: Patients and Public will be directly involved in designing, testing and evaluating a decision support tool and help decide how it should be used by care providers to help plan onward care. PPI will influence data usage, patient journey, algorithms and how this should be communicated. The public will participate in a steering committee who will organise a series of workshops to engage patients and public in the research. Dissemination : Communication materials will engage the public and decision makers. We will work with PPIE support networks to develop accessible communication and ensure distribution to diverse communities. Evidence of effectiveness, safety and acceptance will be published. A decision support tool with computer-based decision support will be demonstrated. The outcomes will be championed with institutional, regional, and national implementation teams.

3a7ef7ca-de0e-49f1-be5c-8349df40131c ADOPTED: Community Alternatives to aCute Hospitalisation for Older People who have Fallen (CAtCH-Falls) Principal Investigator: Dr Sara McKelvie, GP & NIHR Clinical Lecturer at the Primary Care Research Centre, University of Southampton. Team members: Lois Woods, Southampton Health Technology Asessments Centre, University of Southampton. Dr Rachel Dewar-Haggart, Primary Care Research Centre, University of Southampton. Professor Peter Griffiths, Health Sciences, University of Southampton Associate Clinical Professor Jacqui Prieto, Health Sciences, University of Southampton Dr Dan Baylis, Chief Medical Officer, NHS Solent Foundation Trust Dr Syed Hasan, Clinical Lead for Virtual Wards, NHS England Dr Elizabeth Angier, PhD student Main funding: NIHR School For Primary Care Research Starts: 1 April 2024 Ends: 31 March 2026 Summary Each year 30% of older people living in the community fall and are often taken to hospital for assessment. National guidelines recommend that after a fall, older people have a thorough check up and help to prevent further falls. We currently don’t know what the best assessment is for older people who fall and are assessed at home. There are several health services which can assess people in the community without a hospital visit. These can be described as “Community Alternatives to aCute Hospitalisation” (CAtCH) services. In different areas in the country these services have different team members, resources and ways of working. Research is needed who and what is needed to work in CAtCH services, particularly to support older people who have fallen. This study plans to look at previous work in this area by looking at published articles, service reports, government documents and internet resources to find out what is essential for these services. We also plan to survey and interview people who work in CAtCH services in the UK to understand what is available for older people who have fallen. The research findings will be used to develop resources for patients, the public and healthcare workers to showcase CAtCH services. The team also plan to produce a report for healthcare commissioners and support policy-makers. It will also allow the team to apply for further research funding in this area including further projects to look at public awareness of CAtCH.

Senior Research Assistant < Back Gabrielle Palermo Senior Research Assistant Ageing and Dementia Gabrielle Palermo is a Senior Research Assistant at the NIHR ARC Wessex Mental Health Hub, University of Southampton. She supports quantitative research on alcohol use disorder in older adults and contributes to other Hub projects involving complex routine datasets, including the OLA study. With over 20 years of experience in applied statistics, Gabrielle specialises in quantitative methods for epidemiological, socioeconomic, and public health research, particularly in the analysis of survey and administrative data. Her expertise includes multilevel modelling, complex survey design for cross-sectional and longitudinal data, data cleaning and linkage, and the treatment of missing data. She holds an MSc in Population Studies and a BSc in Statistics from ENCE–IBGE (Brazil). Her doctoral research focuses on statistical methodologies for unbalanced longitudinal data in sample-based educational panel studies, with emphasis on school effectiveness and pupil mobility. Since 2022, she has worked across multiple departments within the Faculty of Medicine at the University of Southampton, contributing to research in epidemiology and clinical trials. Previous Next