Improving specialist referral and follow-up of emergency seizure admissions
|Researchers involved:||Prof. Tony Marson, Clinical Lead for unplanned seizure admissions; Prof. Hedley Emsley, Deputy Clinical Lead for unplanned seizure admissions|
|Disease area impacted:||Epilepsy|
|Key partners:||NIHR CLAHRC; Liverpool Health Partners|
|Start and end dates:||Jan 2016 to Dec 2018|
Seizure control is an important factor determining quality of life for people with epilepsy and failure to control seizures has a significant impact on individuals living with the condition. Previous research has shown that 1.4% of all emergency medical admissions across Merseyside and Cheshire are as a result of seizure. This suggests inadequate control for many patients with epilepsy as well as insufficient strategies to manage seizures in the community. Whilst many patients with epilepsy can remain seizure free, a high proportion, up to 30%, have persistent seizures and require specialist management. In spite of this, most seizure admissions are not being referred for the help that could prevent future admissions. Building on findings of the National Audit of Seizure management in Hospitals, the Connected Heath Cities programme of work presents new opportunities for tracking journeys of patients presenting to emergency departments with seizures and for targeting more effective specialist referral and follow-up.
Using analytics to identify ineffective specialist referral
Ineffective referral to or active follow-up within specialist services increases the risk of unplanned admissions for people presenting to A & E with seizures. We will analyse anonymised commissioning datasets to identify where high rates of unplanned admissions and readmissions for seizures are occurring and target appropriate interventions.
In the post-hospital phase in particular, new algorithmic approaches will provide more intelligent monitoring or follow-up by specialist outpatient services after discharge from hospital. Improving the identification of failures in post-discharge pathways, whether due to ineffective referral systems (eg. non-referral to epilepsy clinics) or failure of patients to engage, will allow more targeted interventions.
We will develop predictive models for success and/or failure of follow-up emergency re-admission, based not only on patient characteristics but also on variables relating to their place of residence, GP practice, pattern of previous attendance, organisation of local services and model of care. Smarter metrics to identify and understand variation in follow-up readmission for seizures across NWC, based on characteristics of the patient, their place of residence, and the services around them.
The key activities for our CHC Healthcare Data Laboratory and Pathway Profiling Team undertaking this work include:
- Developing analytical algorithms to generate clinically validated reports on seizure admission and readmission rates across the North West Coast
- Co-producing data reports and visualisations with front-line staff who understand both how the data is generated and how it relates to the realities of clinical care
- Mapping the patient journey from admission to discharge (in terms of personnel, teams and flow through acute areas of the hospital) and onwards ambulatory care (elective follow-up in epilepsy clinic)
- Gaining insight from front-line staff around the key challenges to the effective and efficient collection, recording retrieval, access and sharing of richer data generated during the care process.
- Capturing information about the provision and organisation of local services to identify key variations across the North West Coast and recent service changes, providing opportunities to deploy new informatics tools to evaluate impact.
Why is this research important?
Seizure control is an important factor determining quality of life for people with epilepsy and failure to control seizures will therefore have a significant impact on individuals living with the condition.
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 fewer hospital admissions.
This project brings together clinical and technical expertise from two major universities and a local technology company that has some of the most advanced and secure data stores in the UK and it will also be working with clinical and managerial staff from across the whole NWC region, as well as NWC citizens.
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 Northwest Coast. We may look to overlay this data with some aggregate data from other sources.
Are the data anonymised?
The data we are currently working with is anonymised patient data. If use of identifiable data is needed in later phases of the project then 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 a combination of 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 correlations within the data.
By linking our analytical expertise with a programme of engagement of front-line NHS clinicians across the North-West Coast region, the team will support the co-production of 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 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 improve patient pathways and outcomes for patients with epilepsy. 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.