As our countdown to the Forward Healthcare Awards 2021 continues, we platform our finalists to provide a glimpse of the great initiatives and ideas that have helped to make a difference in healthcare across the last 12 months.
Sponsored by CCube Solutions, our week-long focus on the entrants will commence from 6 September 2021 and be filled with fantastic video and feature content. But, before that, join us by reading all about the innovative ways in which organisations have been harnessing information.
Here are the stories and submissions from our finalists from the ‘Excellent Use of Data’ category. From a range of COVID-19 research projects, through to workforce analytics, ICSs and connected cancer care, it’s fascinating to see the variety of ways datasets are being applied..,
NHS Shared Business Services and Medway NHS Foundation Trust – NHS SBS Workforce Analytics solution
NHS Shared Business Services (NHS SBS) and Medway NHS Foundation Trust have partnered to develop the Workforce Analytics solution, which uses data science techniques to ‘improve NHS staff retention by predicting – with 95 per cent accuracy – which individual employees are at increased risk of leaving’.
According to figures from The Health Foundation, the NHS in England is facing a workforce shortfall of over 115,000 full-time equivalent (FTE) staff, with projections that this will double by 2025/26. This means that there is a focus on NHS trusts to retain their existing employees, with the ‘high levels of attrition amongst nursing staff’ and the financial impact of this, of particular concern.
Medway has tried to address its own nurse retention challenge by developing a model that could also be rolled-out by others across the country. With over 1,200 registered nurses and an annual turnover rate of 14 per cent, its workforce team explored how they could to use data to improve nurse retention.
James Kendall, Head of Workforce Intelligence at Medway NHS Foundation Trust, explained: “We worked with NHS SBS to pilot a solution that analyses workforce data to predict employees who are at high risk of leaving and the reasons why.
“Whilst the potential benefits to our own organisation were significant, we also knew that any success we had could be replicated elsewhere and have a far-reaching impact for the wider NHS.”
The solution they created, by working alongside data scientists and workforce experts from NHS SBS to analyse historic data from staff and leavers over a five-year period, aimed to prove that statistical modelling could be used to ‘accurately predict an employee departure’.
The subsequent Workforce Analytics solution analysed employee information – predominately from the NHS Electronic Staff Record (ESR) – to produce a ‘forecast of expected leavers’. It identifies and assigns a ‘weighted numerical risk score’ to a range of factors which, when combined, can ‘determine the probability of an individual leaving’.
Factors analysed include salary, age, length of time in the current role, the distance traveled to work, the area someone works in, and personal circumstances like recorded stress or special leave.
As part of the solution, analytical reports identify those at risk and also provide actionable insights, allow organisations to focus interventions on those who are in posts that are difficult to fill, and highlight particular wards or areas that tend to lose more staff.
The result was the creation of a bespoke NHS solution that is helping Medway to target appropriate interventions, such as: more line manager engagement through appraisals and 1:1s, opportunities for new or changed roles, flexible working, and financial wellbeing support.
James added: “We expect this to be completely game-changing when it comes to implementing our People Strategy successfully – saving the trust considerable time and money when it comes to recruitment costs, but also helping us to make the right decisions to support employee wellbeing.”
Health Data Research UK – COVID-19 research questions
Health Data Research UK, the Office for National Statistics and UK Research and Innovation are funding 12 COVID-19 data research initiatives.
The projects, which will use national data to ‘answer some key COVID-19 related research questions’, are:
Irene Higginson, King’s College London
A project which looks at the relationship between regional COVID-19 palliative care responses and disease prevalence, mortality, admissions, discharges and other factors.
Till Hoffmann, Imperial College London
A look at how National Core Studies healthcare data could be connected with wastewater surveillance of COVID-19 in a ‘privacy-preserving fashion’, to inform epidemiological models and democratise data access.
Trisha Greenhalgh, University of Oxford
Research questions including ‘can phenotypes developed from enhanced remote primary care assessment of COVID-19 be used to identify a cohort of community cases, and enable comparison of recovered and long COVID?’
Kevin Wyche, University of Brighton
Focusing on transmission and environment, Wyche will consider whether exposure to airborne fine and ultrafine particulate matter is a determining factor in COVID-19 infection and outcome within the UK.
Paul Elliott, Imperial College London
This work will seek to ‘characterise and quantify’ the ‘biological, social and environmental drivers of medium-term health outcomes following infection with SARS-CoV-2’.
Aziz Sheikh, University of Edinburgh
In the area of vaccine research, this study asks if we can ‘enable harmonised, near real-time, data on pharmacovigilance of COVID-19 vaccines using routinely collected linked national datasets across the UK?’
Andrew Hayward, UCL
This project considers what the ‘relative contributions of different exposures and settings’ are to COVID-19 community transmission.
Kamlesh Khunti and Professor Tom Yates, University of Leicester
This University of Leicester project will consider the risk factors, effect modifiers and mediators of the excess risk of SARS-CoV-2 infection and the associated complications of COVID-19 in minority ethnic communities using national linked datasets?
Rachel Denholm, University of Bristol
This project focus on COVID and education, and will ask: how do school COVID-19 transmission dynamics differ across studies? Do children experience long-COVID? Do COVID-19 outcomes differ for those with/without symptoms? How common is COVID reinfection?
Julia Hippisley-Cox, University of Oxford
Hippisley-Cox will ask: ‘What is the uptake and comparative safety of new COVID vaccines by age, sex, region, ethnicity, co-morbidities, medication, deprivation, risk level and evidence of prior COVID infection?’
Stephen Machin, London School of Economics
This LSE project will focus on ‘economic scarring from the COVID-19 induced crisis: monitoring inequality in economic and education outcomes.’
Tracey Warren, University of Nottingham
The last of the 12 data and COVID projects, will consider ‘how is COVID-19 impacting women and men’s working lives in the UK?’
North East North Cumbria ICS – Trusted Research and Evaluation Environment strategy
Next we head to the North East and North Cumbria ICS and its strategy for providing data capability to ‘support health and care projects for service improvements, new innovations and research’.
Its ‘Trusted Research and Evaluation Environment strategy’ (TREE) aims to support ‘joint collaboration between health, care and academic institutions’, via governed processes and a data platform.
By doing this it hopes ‘unlock’ the full ‘potential of its data’, and bring together academics, health and care communities, and citizens, with the ultimate goal of improving health outcomes.
To ‘better understand health trends and challenges, inform decision making and provide intelligence’, the ICS has four strategic outcomes:
- Develop public and partner trust and assurance on use of data through a transparent, safe and effective capability
- Cultivate health, care and academic expertise through collaboration and a ‘learning health system’, to improve real-world, regional challenges
- Deliver projects that are focussed on improving population health and wellbeing, using a safe and secure data analytics capability
- Provide a nationally assured, safe, scalable and sustainable capability to support the regions digital development and economic growth.
The ICS commissioned the Academic Health Science Network to produce the TREE strategy for the region. The next step for the programme is to start implementation, with the first priority to create the platform.
The Scottish Cancer Registry and Intelligence Service – SACT data
Our last stop while looking for excellent uses of data is the Scottish Cancer Registry and Intelligence Service (SCRIS).
The SCRIS connected Systematic Anti-Cancer Therapy (SACT) data from all of Scotland’s five cancer centres – consequently providing the Scottish NHS with national coverage.
According to the University of Edinburgh, following the connection of the final two ChemoCare databases, the SACT data view is now complete for the whole population of Scotland. The next move for the SCRIS team is to now make this information available to view via a dashboard.
Adding this capability will mean that clinicians and organisations can ‘benchmark’ their services against others in Scotland and create a ‘learning healthcare system’ for Systematic Anti-Cancer Therapy, with the goal of ultimately boosting clinicians’ patient offering.
Data is already been used by NHS Scotland and SCRIS to help ‘understand the impact of the COVID-19 pandemic on cancer services’, with a prototype dashboard currently being refreshed weekly and producing an activity report for the Scottish National Cancer Recovery Group.
Viewable dashboard data includes the number of attendances – broken down by cancer type, chemotherapy type or by the specific Cancer Network. This is set to be further refined across the next two years, so that datasets provide improved analysis.
Gregor McNie, Lead of the Cancer Policy Team at The Scottish Government, said: “The work of the SCRIS and the wider cancer data team in developing a national view of SACT data from across Scotland is a great achievement. This will ensure improvements in treatments for patients are based on evidence from a national level.”
