Objective 4

Developing AI tools to reduce adverse events in those with MLTCs.

As people age they become likelier to experience unexpected health problems, known by researchers as ‘serious adverse events’. Objective 4 aims to improve how we deal with these problems. The first step is to improve the recording of such events. Electronic health records use a combination of codes and free text – notes written by the medical professionals treating the patient. We will use a computerised analysis technique called Natural Language Processing to develop the information we can get from free text. This will provide data on adverse events e.g. falls, delirium, and the resulting outcomes, such as loss of independence and care home admission. It will also give information on other important details such as where people live, and who they rely on for care, which influence adverse events. This enhanced data will allow us to better predict adverse events. We know roughly which groups of people will have unexpected health problems (older people, single people), but if we can predict which individuals will develop them, we can apply more effective care.

The next step is to understand the routes patients take through the healthcare system, referred to as “care pathways”. A patient with a hip fracture might typically start in A&E for rapid surgery, move to an orthopaedic ward, and finally transfer to medicine for the elderly for rehabilitation. But adverse events can change this pathway, so we will use various Artificial Intelligence techniques to develop an in-depth understanding of care pathways, and use this understanding to develop new pathways of care for those vulnerable to adverse events.

Clinical

Bruce Guthrie - Co-Lead in Community Interventions

Bruce is Professor of General Practice at the Usher Institute, in the Edinburgh Medical School. He is also the director of the Advanced Care Research Centre.

Bruce is a mixed methods health services researcher with an interest in the quality and safety of health and social care, particularly in relation to multimorbidity and polypharmacy. As well as research, he works clinically as a GP and works closely with the NHS and government to improve healthcare quality and safety. Find out more about Bruce at the link below:

Bruce's profile page

Atul Anand - Lead on Complex Multimorbidity in Acute Care

Atul is an academic geriatrician, senior clinical research fellow and clinical lead for the Lothian DataLoch. His research focuses on routine data-enabled trials of accelerated care pathways and development of automated tools for identifying frail patients at the hospital front door. He will contribute clinical and frailty expertise across the programme, particularly in relation to objective 4 work examining adverse events associated with complex multimorbidity and polypharmacy in acute care. Find out more about Atul at the link below:

Atul's profile page

Stella Arakelyan - Health Services Researcher

Dr Arakelyan’s expertise is in public health research and practice. Her research focuses on examining health system responses to prevention and control of chronic conditions and co-development and evaluation of health service improvement interventions. She has a research track record spanning a period of 13 years in which she published over 25 scientific articles, reports, and briefings. Dr Arakelyan currently uses participatory and system thinking methods in partnership with patients, caregivers, health and social care professionals, and wider stakeholders to explore systems problems and co-design hospital- and community-based complex interventions to optimise health and care services for people with multimorbidity and their informal caregivers.

Stella's research profile page

Stella Arakelyan photograph — Stella Arakelyan

Nazir Lone - Co-Lead on Clinical and Health Services Research

Nazir is Senior Clinical Lecturer in Critical Care and Director of Research for UK Intensive Care Society. He has methodological expertise in epidemiology/data science, particularly applied to large datasets in acute/critical care health service settings. In national roles, he leads data-driven programmes focussed on healthcare improvement in Critical Care. He will contribute clinical and multimorbidity expertise across the programme and lead the objective 4 work in relation to complex multimorbidity in acute care. Find out more about Nazir at the link below:

Nazir's profile page

Marcus Lyall - Clinical and Frailty Expertise

Marcus is a consultant physician who leads regional data-driven innovation in acute medicine, part of the governance team for the Lothian DataLoch, and a clinician data scientist researching outcomes and challenges in unscheduled care clinical pathways. He will contribute clinical and frailty expertise across the programme, particularly in relation to objective 4 work examining adverse events associated with complex multimorbidity and polypharmacy in acute care.

Lucy Stirland photograph — Lucy Stirland

Lucy Stirland - Old Age Psychiatry

Lucy is a psychiatrist and epidemiological researcher. In August 2022, she completed her specialty training in Old Age Psychiatry and finished her Clinical Lectureship funded by NHS Education for Scotland and the Chief Scientist Office. In 2020, she completed a PhD in the epidemiology of multimorbidity and polypharmacy with mental and brain health. Her clinical experience includes a year's training (endorsement) in liaison psychiatry. She is now an Atlantic Fellow for Equity in Brain Health at the Global Brain Health Institute (GBHI) and is based at the University of California San Francisco (UCSF) for this one-year programme. Find out more about Lucy at the link below:

Lucy's profile page

Natural Language Progamming

Beatrice Alex - Applied AI and Complex Intervention Development

Bea is a Chancellor’s Fellow at the University of Edinburgh and has over 15 years of expertise in text mining and natural language processing with applications in the healthcare sector. She co-leads the Edinburgh Clinical NLP group with Dr. Honghan Wu. She will lead the objective 3 Natural Language Processing (NLP) geoprofiling activity, lead the objective 4 NLP to identify adverse events work in Edinburgh, and support external validation/transferability work with Dr Wu in UCL. Find out more about Bea at the link below:

Bea's profile page

Honghan Wu - Lead in NLP at UCL

Honghan was a lecturer and group lead (https://knowlab.github.io/) at Institute of Health Informatics, UCL when the AIM-CISC programme started, although he is now Professor of Health Informatics and AI at the University of Glasgow. His research uses text analytics and Knowledge Graph techniques for health data research. His text-analytics tool (CogStack-SemEHR) is routinely run at 5 NHS Trusts on > 3.5m patient records and used by > 60 clinicians. He will lead the Natural Language Processing work in UCL, and lead external validation/transferability work using large-scale data at London NHS Trusts. Find out more about Honghan at the link below:

Honghan's profile page

Scott Prentice photograph — Scott Prentice

Scott Prentice - Research Annotator

Scott Prentice was recently a lecturer at the University of Cumbria. Prior to this, he was a lecturer at the University of Stirling teaching students from various healthcare backgrounds. He is also an Advanced Clinical Practitioner, working in General Practice at the University of Glasgow and is qualified as a Registered Nurse and a Registered Health Visitor. Scott has also worked in Clinical Research within NHS Scotland and NHS England on various clinical studies.

Scott's clinical interests focus around General Practice/Primary Care, specifically in long term conditions. He was part of a small team of GPs and ANPs who participated in a Scottish Government Pilot to reduce avoidable hospital admissions for patients using the Community/Virtual Wards Model and Telehealth. Scott also has experience working with the Homeless Community, having worked at the Edinburgh Access Practice.

Artificial Intelligence

Jacques Fleuriot - Lead on applied AI process mining and Integration of AI Tools with Care Pathways

Jacques is Personal Chair of Artificial Intelligence, and Director of the Artificial Intelligence and its Application in the School of Informatics. His research focuses on AI modelling, which spans areas such as formal verification, process modelling, and explainable AI in healthcare and other complex domains. Find out more about Jacques at the link below:

Jacques' researcher profile page

Paola Galdi - Machine Learning PDRA

Paola is computer scientist with a background in machine learning and statistical modelling. She has worked for several years with neuroimaging and biomedical data with a focus on predictive modelling. Paola is interested in multi-modal data integration and applications of AI to health data, and will deliver analysis of serious adverse event occurrence and prediction tool development. Find out more about Paola at the link below:

Paola's Researchgate page

Jake Palmer - Knowledge Representation PDRA

Jake is a computer scientist with a background in artificial intelligence, including interactive theorem proving and machine learning. He has extensive experience working on issues in and around knowledge representation and automated reasoning. Jake is interested in applications of symbolic (and other) AI techniques and process mining to clinical data and will deliver analyses of serious adverse event occurrence and prediction.

This article was published on 2024-09-24