Using data and technology to improve services for alcohol related illness
|Researchers involved:||Led by Dr Keith Bodger, Clinical Lead for alcohol; and Dr Steve Hood, Deputy Clinical Lead for alcohol|
|Disease area impacted:||Alcohol Related Liver Disease and associated alcohol misuse|
|Key partners:||LHP LARA (Liverpool Alcohol Research Alliance); Professor Simon Maskell, Professor of Autonomous Systems; Dr Kate Fleming, LJMU Public Health Institute|
|Start and end dates:||Jan 2016 to Dec 2018|
Health problems linked to alcohol misuse are diverse. There are over 60 conditions which place a major burden on the NHS. Alcohol-related health problems are often accompanied by complex social issues for the individual (eg. employment, benefits, housing and homelessness), their family and friends (eg. safeguarding of children, domestic violence) and wider society (eg. road traffic accidents, crime). Current services for alcohol misuse are delivered by a wide range of statutory and non-statutory agencies, and vary greatly from area to area.
This project will use data and technology to improve services for alcohol-related illness. New approaches to the way information is linked, analysed and shared will give the health system better ways to understand the factors associated with good or poor outcomes, including characteristics of patients themselves, the area where they live and the services available to them. This will improve the system’s ability to target resources and adapt services to meet the complex and challenging problem of alcohol misuse and the life-threatening consequences of liver damage.
The key activities of the CHC Healthcare Data Laboratory and Pathway Profiling Team undertaking this work include:
- Improving the data available to front-line teams to support risk-stratification, a tool used to identify patients who are at risk of serious illness leading to hospital admission who may need more care and support. This will help them to predict outcomes and inform decisions.
- Mapping variation in the local organisation and provision of key services to identify factors linked to good or poor outcomes to inform service design and commissioning.
- Generating better information about engaging with ambulatory services (outpatient care) to minimise missed appointment and facilitate support to multiple agencies to provide better use of resources.
- Developing smarter algorithms, pathway analytics and data visualisations to reflect the diversity of patient groups and their journeys and key milestones of disease progression – to allow more precise targeting of patient sub-groups for co-ordinated intervention.
- Redesigning pathways to avoid emergency re-admissions for defined patient sub-groups
Why is the research important?
Alcohol related health problems, and in particular Alcohol Related Liver Disease (ARLD), place a major burden on the NHS and are often accompanied by a variety of social issues involving unemployment, homelessness and family issues. However, professionals providing care in hospitals, general practice, social services and elsewhere will often only know part of the story for those individuals they try to help.
There are huge amounts of data collected and we believe that we could use technology to bring data together in such a way it could then be used by care services, for the benefit of the patient. This should improve patient outcomes, and if people are supported to manage conditions better themselves, there would be a reduced need for emergency department visits and hospital admissions.
What data are being used in this project?
We currently have access to anonymised commissioning datasets, including all A & E attendances, inpatient hospital admissions, and outpatient attendances for the whole of the North West Coast. In the early phases, we will be linking this data to open source aggregated data (a process where raw data is gathered and summarised for statistical analysis) with an index of deprivation and off license premises data.
Are the data anonymised?
The data we are currently working with is anonymised patient data where the patient can’t be identified. If use of identifiable data is needed in later phases of the project, we will seek consent from the patients to whom the data relates.
What methods are you using to conduct this work?
There will be two strands to the approach we take in conducting this work and various research methods will be employed.
One strand of the work will be undertaken by the Healthcare Data Laboratory established within the University of Liverpool’s Department of Biostatistics. This team will be analysing anonymised commissioning datasets for the whole of the North West Coast; developing algorithms that accurately capture all interactions that patients have with provider Trusts across the patch and seeking to understand patterns in admission frequencies and any significant trends and connections within the data.
By linking our analytical expertise with a programme of engagement with front-line NHS clinicians across the North West Coast region, the team will co-produce clinically validated analytics and data-visualisation for defined patient pathways with NHS staff and stakeholders. This will drive the development of a Learning Health System linking information systems to innovative health informatics research.
In parallel to the work undertaken by analysts within the Healthcare Data Laboratory, a Pathway Profiling team comprising two Qualitative Researchers will work with healthcare teams within provider organisations to build a detailed profile of the people, data, and systems involved in the care of patients across the various pathways. This team will map out the patient data trails that are created within and across health and social care providers and assess points along the patient pathway at which better systems or processes may facilitate better data capture and accessibility.
Who will benefit from your research?
The ultimate aim of the project is to optimise patient pathways and to improve outcomes for patients with ARLD and associated alcohol misuse. We will do this by identifying data-driven solutions to the problems we find in patient pathways and equipping the professionals involved in the provision of care to these patients with the tools and knowledge needed to make better decisions about patient care.