One of HTN’s favourite categories, here we explore the entries in the ‘Best Use of Data’ category.
Across eight finalists, we highlight how data is driving improved decision making and intelligence across a range of areas from NHS staff retention, patient demand, population health management to patient risk indicators.
Here we explore the programmes…
Synopsis
Synopsis Healthcare, the company behind an electronic patient record for preoperative assessment services, has introduced algorithms to support the clinical decision process, a tool used by trusts to tackle the elective surgery backlog.
Its technology uses an ‘integrated’ and ‘standardised approach’ to pre-operative data gathering, to deliver what the company terms ‘patient load balancing’, using algorithms to calculate risk.
The system allows hospital staff to access data from patients who complete a pre-op questionnaire from home, directly alongside data from patients who attend hospital for their pre-op questionnaire.
The company states: “This standardised approach to data gathering then allows a hospital to accept a patient/s for a scheduled operation who may have been triaged elsewhere, thus allowing hospitals to transfer patients between them based on theatre capacity and availability and significantly improve load balancing. This is a significant improvement in the design of the pathway to surgery, rather than relying solely on the most local hospital to the patient.”
The tool is currently used by trusts including North Bristol NHS Trust, Worcestershire Acute Hospitals NHS Trust, and King’s College Hospital NHS Foundation Trust.
Jonathan Lofthouse, Site Chief Executive, King’s College Hospital NHS Foundation Trust, commented on the system: “Synopsis allows us to access patients for pre-operative care who ultimately might not go on to have their operation at the King’s site but may have their care transferred to another provider in the south-east London area. The tool allows us to initiate diagnostics elements, initiate a strong, structured and quality marked pre-operative assessment processes, and transfer that information with the patient to another elective care unit in the south-east London area.
“In addition, using Synopsis across the King’s College group is really supporting our efforts to improve patient safety across planned surgery, by harnessing digital technology and algorithms that are calibrated and based to identify immediate risk, clinical concerns, and in so doing, really aid the triaging process to allow clinicians to make more informed decisions.”
Combined Intelligence for Population Health Action (CIPHA)
CIPHA, a programme launched in April 2020 when Cheshire and Merseyside needed a real-time population health analytics platform to manage the COVID crisis and drive recovery. The platform went live across 40 organisations and 359 GP practices in 3 months; CIPHA has now expanded to cover c16m people, inform national policy and drive local action.
CIPHA, a population health management platform, developed by Graphnet, launched across Cheshire and Merseyside in April 2020.
Graphnet was contracted to provide the single source command and control regional intelligence platform, with real-time analytics, dashboards presenting information to allow prompt co-ordinated actions, and the data to be able to predict, identify and control outbreaks quickly.
The system draws data from 15 acute trusts, 359 GP practices, eight community trusts, three mental health trusts, nine local authorities and emergency services. The information is combined with information from multiple national data sources, such as Public Health England’s data on COVID cases and tests, NHS Pillar 2 testing data on a 30-minute feed, NIMS vaccination extract, NHS Improvement COVID admissions reports, and ONS death rates.
The platform provides teams across the region with real-time intelligence and analytics, including dashboards that cover three areas: capacity and demand; epidemiology and population stratification.
HAS Technology and ADASS East
ADASS East has worked with HAS Technology to improve social care data quality.
The partnership uses a mantra, ‘do once, not 11 times’, to provide a view of the local care market to drive improvements.
The system was introduced to replace manual reporting and monitoring, and enable market intelligence, quality and financial data to be accessed in one place, in real-time. The tool provided:
– Real-time market insight and analysis at the push of a button with reporting on: cost, volume, quality and value for money
– Effective risk management, including early warning of suppliers in possible difficulty
– Compliance with responsibilities under the Care Act 2014
– Measurable improvements in provider quality and evidence of interventions
– A strong partnership, with expertise within health & social care and ability to deliver innovative secure and scalable technological solutions.
The company said: “By bringing together care quality and financial data from 11 local authorities, 2,000 contracted providers and 20,000 service users, alongside automatic data from the CQC, PAMMS has enabled comparison between ratings and council findings to ensure a comprehensive overview, while delivering capital savings of £550,000 with further estimated ongoing annual savings of over £550,000.”
Sensyne Health and Chelsea and Westminster Hospital NHS Foundation Trust
Sensyne Health utilised de-identified and anonymised patient datasets to support the clinical decision-making process for COVID-19 patients with the SYNE-COV prediction algorithm for Chelsea and Westminster Hospital NHS Foundation Trust.
The tool, a COVID-19 patient outcome prediction algorithm, in collaboration with Chelsea and Westminster Hospital, helps clinicians proactively manage patients by utilising machine learning and artificial intelligence to predict patient outcomes and inform near real time clinical decision making.
The entry cited: “The volume of data points generated for patients in hospital has increased exponentially, and the breadth increases as the disease progresses. For example, one patient in ICU is expected to produce 20,000 – 30,000 points of data per day, including vital signs, respiratory tests and laboratory results. During the pandemic, early intervention was essential, not only to understand the likely impact on intensive care resources but more importantly to save lives.”
The hospital and Sensyne Health worked together to develop the solution, that provides clinicians with an individual patient risk score to aid critical clinical assessment of three potential COVID outcomes when a patient enters hospital:
- Admission to intensive care
- Invasive mechanical ventilation
- In-hospital mortality.
NHS Shared Business Services and Medway NHS Foundation Trust
NHS Shared Business Services (NHS SBS) and Medway NHS Foundation Trust developed a new 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.
Citing figures and predictions from The Health Foundation, the NHS is facing a workforce shortfall of over 115,000 full-time equivalent (FTE) staff, with projections this will double by 2025/26 and exceed 475,000 by 2033/34.
In common with NHS organisations around the country, Medway NHS Foundation Trust looked to address its nurse retention challenge. With over 1,200 registered nurses and an annual turnover rate of 14 per cent, its workforce team explored innovative ways to use data to improve nurse retention.
Working with data scientists and workforce experts the partnership analysed historic data from staff and leavers over a five year period, with an aim to prove that statistical modelling could be used to accurately predict an employee departure.
The model identifies and assigns a weighted numerical risk score to a range of primary and secondary factors, which when combined can determine the probability of an individual leaving.
To increase the accuracy of the predictive analytics, a large number of factors are analysed. These include an employee’s salary, the length of time they have been in their current role, the distance they travel to work, the area they work (e.g. hospital ward), and personal circumstances such as recorded stress or special leave taken.
James Kendall, Head of Workforce Intelligence at Medway NHS Foundation Trust, explained: “Like the vast majority of NHS trusts we have needed to increase our nursing numbers in recent years to be able to meet rising demand for our clinical services. And we have done so successfully, with the number of NMC registered staff steadily growing from around 1,110 FTE nurses in 2015, to over 1,200 today – with a nursing vacancy rate that has reduced from 34 per cent to 9 per cent in the last five years.
“Attracting staff to the trust in the first place is obviously essential, but what we are increasingly focused on is how we then keep them.
“In most cases an employee’s decision to leave is made up long before they resign from their role. With this in mind, 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.”
Healthcare Gateway
Healthcare Gateway, via its Medical Interoperability Gateway platform, has provided care settings across the country with real-time patient data uniting clinical systems across the UK.
The middleware technology provides real-time feeds of mental health, community, social care, acute and primary data into any system and any setting.
Highlighting integration with over 80 system partners, the platform achieved 20,271,617 data transactions in May 2021 alone.
The company notes one of its programmes, with South West London CCG, as an example of a shared care record across the region for 1.5 million citizens. The system connects data from 180+ primary care settings, two community and two social care settings into their Health Information Exchange platform.
Sally Wiltshire, Nautilus Consulting, commented on this project: “It has been our pleasure to be working so closely with Healthcare Gateway for two phases of one of the largest health interoperability programmes in South West London over the last two and a half years. During this time they have worked with us to deliver connections from 180+ GP practices, two Community Services and two (first of type) Social Care services to our health information exchange platform. It has been our experience that their project delivery teams are enthusiastic, knowledgeable and competent, with robust project and issues management processes, including going out of their way to develop and deliver a fast-track solution to an unexpected data sharing issue with an external partner to ensure programme timelines were not breached. Their client executive team are super-approachable and engage directly in support of local projects far in excess of that experienced with many other such providers. I can confidently say that Healthcare Gateway go the extra mile, with a smile!”
CorLife
CorLife, a welltech platform designed by ex-NHS doctors/consultants and scientists, helps people take control of their health by tackling threats of Westernised diseases and ill health costs on businesses. The platform supports long-term behavioural change through personalised programmes, using medical data to track, monitor and educate users.
CorLife is a reinvention of clinical coaching by leveraging technology to help businesses improve workforce productivity at scale.
The CorLife platform collects data from blood results, smart watches and scales to inform participants of their current health status. This data is then used to personalise a programme for the individual by looking at their whole health.
In 2018/19, CorLife ran a proof of concept with Samsung, BP and FujiFilm – and achieved substantial results via technology and data platform (in line with individual results) and delivering positive ROI for the entire workforce.
The results:
- Average weight loss in 6 months – 5.1kg
- Reduction in fat mass – 13.7 per cent
- Improvement in self-reported view of health and energy levels – 8 per cent and 13 per cent
Diaceutics’ application of machine learning and AI
Diaceutics’ application of machine learning and AI helps to identify the best possible testing journey for patients.
The diagnostic commercialisation platform for precision medicine, integrates multiple pipelines of diagnostic testing data from a global network of laboratories. Through the application of machine learning and standardisation of millions of aggregated de-identified patient testing events, Diaceutics identify the best possible testing journey or “Deductive Diagnostic Pathway (DDP®)” for patients at disease level, providing the industry with a guide to getting the right medicines to the right patients, faster.
In late 2020 the company launched a digital, scalable solution for precision medicine diagnostics in line with therapy launches by integrating multiple pipelines of real-world diagnostic testing data with a vibrant diagnostics marketplace.
The company combines data from multiple sources including laboratory result data, diagnostic profiling meta data and CMS and commercial claims data into its DXRX platform providing access to 365m+ de-identified patient records globally in 53 countries.
The company said: “With 476 potential precision medicine therapies now in late phase of development and over 30 per cent of all FDA approvals between 2018-2020 being for Precision Medicines, the pipeline of therapies requiring a companion diagnostic solution is rapidly growing.
“To date the company has leveraged deep disease level data analytics and implementation solutions to improve the diagnostic testing infrastructure for over 600 projects with 39 of the world’s leading pharmaceutical companies.”
