Development and evaluation of the electronic frailty index+ (eFI+) tool: integrated prognostic-decision modelling to target interventions for older people with moderate or severe frailty

Development and evaluation of the electronic frailty index+ (eFI+) tool: integrated prognostic-decision modelling to target interventions for older people with moderate or severe frailty

Principal Investigator: Prof. Andrew Clegg, Leeds Institute of Health Sciences

 

About the study

Frailty is common in older age. It develops because as we get older our bodies change, and can lose their inbuilt reserves, for example we lose muscle strength. These changes mean that older people with frailty can experience sudden, dramatic changes in their health as a result of seemingly small problems, such as an infection or new medication.

 

People with frailty are at risk of losing their independence, and help from home care services may be

needed. They are also at higher risk of falling, admission to nursing homes and death. These problems can reduce quality of life and are costly for the NHS and social care. Previous research has shown that treatments such as community rehabilitation, falls prevention programmes and comprehensive geriatric assessment (provided by a team of doctors, nurses, therapists and social workers) can improve independence, reduce falls and reduce nursing home admission for people with frailty. Also, advance care planning (which is a conversation between people, their families and those looking after them to decide on future wishes) can increase quality of care and reduce hospital admission for people nearing end of life. We have developed a tool called the electronic frailty index (eFI), which uses routine information from the GP record to help identify frailty.

 

However, the problem at the moment is that we do not know which older people living with moderate or severe frailty are most likely to benefit from these treatments. In this study, we will develop an improved version of the eFI, the eFI+, to help health and social care practitioners know which people with moderate and severe frailty are most likely to benefit from treatments. To do this, we will use anonymous patient information from three very large databases that include detailed health and social care information, and data from a national study – the Community Ageing Research 75+ (CARE75+) study.

 

The first step in eFI+ development will be to use information from the three very large databases to

predict, in the next 12 months, which older people with moderate or severe frailty are at risk of:

  • Needing new or increased home care services.
  • Hospital admission with a fall or fracture.
  • Nursing home admission.
  • Dying.

 

We will also use CARE75+ data to see if simple tests like measuring walking speed can help us

identify people with frailty at risk of losing independence. The second step will be to use this data on risk prediction to find out how much benefit we might expect from the treatments, using a process called ‘decision modelling’. The third step will be to test whether offering such treatments is likely to be cost-effective – important information for the NHS and social care.

 

We will work closely with older people, carers, policy makers, doctors, nurses, therapists, and commissioners of services to make sure that our work is useful for the NHS and social care. We will also work with companies that provide software to the NHS and social care to ensure that the eFI+ is made available at no extra cost.

 

Our research to develop the eFI+ will enable identification of older people with moderate or severe

frailty who are most likely to benefit from treatments to improve health and wellbeing. We expect to

have major positive impact on the health and wellbeing of older people living with frailty, their families

and carers along with major benefits to the NHS and social care.

 

Privacy Notice

Where do we obtain data from?

This study uses data from multiple sources, to allow models to be tested in different populations. In particular we make use of the SAIL Databank (https://saildatabank.com/) , Connected Bradford (https://www.bradfordresearch.nhs.uk/our-research-teams/connected-bradford/), and ResearchOne (https://tpp-uk.com/products/data-and-research/).

 

These datasets contain anonymised information on the care and treatment that individuals receive. Only use of ResearchOne requires an extract of data to be transferred to machines controlled by the University of Leeds, the other datasets are accessed remotely.

 

What data do we hold?

The data does not contain patients’ names, addresses, phone numbers, or NHS numbers. It contains the admissions, diagnoses, and treatments administered to individuals, along with information about their date of death, use of homecare services, and admission to a nursing home.

These data do include a unique identifier which, if combined with data held by the various data controllers, would allow identification of an individual and therefore these data are classed as ‘personal data’ under the General Data Protection Regulation (GDPR).

Who will process my personal information?

The data will only be accessed by university employees funded by the project, and only used for the purpose of this project. Only summarised and aggregated data will be disseminated in the form of academic presentations, peer-reviewed journals and lay summaries. The data will not be used for commercial purposes, provided in record level form to any third party or used for any direct marketing. There will be no requirement or attempt to re-identify any individuals within the data.

There will be no transfers of the data to third countries or international organisations, and there will be no automated decision making or profiling in use with these data.

What is the purpose and legal basis of the processing?

Under the General Data Protection Regulation (GDPR), the University of Leeds has to identify a legal basis for processing personal data and, where appropriate, an additional legal basis for processing special category data.

As a publicly funded organisation, the University of Leeds processes personal data to undertake scientific research which is in the public interest (further details here: https://dataprotection.leeds.ac.uk/wp-content/uploads/sites/48/2019/02/Research-Privacy-Notice.pdf). The legal basis for processing data is under Article 6 (1) (e) of the GDPR: Processing is necessary for the performance of a task carried out in the public interest. Special category data is processed under Article 9 (2) (j): Processing is necessary for archiving purposes in the public interest, or scientific and historical research purposes or statistical purposes.

How will you keep my data secure?

The data controllers for this study are the SAIL Databank, Connected Bradford, and TPP ResearchOne. The first two of these offer only remote access to their datasets, and have appropriate security measures in place. For the latter, the University has in place appropriate technical and organisational measures to protect your personal data and/or special category data.

Information will be treated confidentially. The University is committed to the principle of data protection by design and default and uses the minimum amount of data necessary for the project.

How can I access my personal information?

Various rights under data protection legislation, including the right to access personal information that is held about you, are qualified or do not apply when personal information is processed solely in a research or archival contact. This is because fulfilling them might adversely affect the integrity of, and the public benefits arising from, the research study or project.

The full list of (qualified or inapplicable) rights is: the right to access the personal information that is held about you by the University, the right to ask us to correct any inaccurate personal information we hold about you, to delete personal information, or otherwise restrict our processing, or to object to processing (including the receipt of direct marketing) or to receive an electronic copy of the personal information you provided to us.

If you have any questions regarding your rights in this context, please use the contact details below. Please note as we do not hold names or addresses for this study we cannot remove participants from this study, correct any information we hold about you or provide you with an electronic copy of the personal information we hold about you.

How long is my information kept?

The datasets are kept for the length of the project, and are then archived for 3 years to ensure all work is complete and any corrections can be handled. After this, the data is securely and permanently deleted.

Who can I contact?

If you have any questions about this research study, please contact the principal investigator Prof. Andrew Clegg at A.P.Clegg@leeds.ac.uk

If you have any general questions about how your personal information is used by the University, or wish to exercise any of your rights, please consult the University’s data protection webpages. If you need further assistance, please contact the University’s Data Protection Officer (Alice Temple: A.C.Temple@leeds.ac.uk).

Our general postal address is University of Leeds, Leeds LS2 9JT, UK.

Our postal address for data protection issues is University of Leeds Secretariat, Room 11.72 EC Stoner Building, Leeds, LS2 9JT. Our telephone number is +44 (0)113 34 37641.

Our data controller registration number provided by the Information Commissioner’s Office is Z553814X.

How can I complain?

If you wish to raise a complaint on how we have handled your personal data, you can contact our Data Protection Officer who will investigate the matter. If you are not satisfied with our response or believe we are processing your personal data in a way that is not lawful you can complain to the Information Commissioner’s Office (ICO).

This notice was last updated on 22nd October 2020.