Case studies

Shaping the future of UK healthcare

SMART digital solutions in action

In our report, Closing the gap: Shaping the future of UK healthcare, we outline a number of common ‘SMART’ characteristics that we identified could help encourage adoption of digital technologies at scale.

The case studies below are linked to each of the following SMART characteristics:

Straightforward and easy-to-use

Healthy IO- A simple solution to a complex and time consuming problem.

Urine analysis is the second most common diagnostic test in the UK with 42 million tests undertaken annually. It is used in all sectors of healthcare, including key clinical pathways such as chronic kidney disease (CKD), diabetes screening, antenatal care, urinary tract infections (UTIs), and paediatrics and outpatient management.

‘Traditional’ urine analysis involves a urine dipstick with different chemical pads that react to the composition of the urine by changing colour. The colour change on the dipstick is then compared to a reference chart which indicates the presence of specific analytes, aiding the diagnosis of a condition. The manual and subjective nature of the test, makes it prone to errors in diagnosis or require the patient to return to the clinic for repeat tests. This is both inconvenient for the patient and costly for the healthcare provider.

Healthy.IO is a healthcare start-up, based in Israel with a global presence, that has developed technology combining smartphone cameras, a mobile app and a home-based urinalysis test kit, to enable patients to self-test at home and share the results with their care provider through the mobile app. Healthy.IO has two urinalysis solutions currently: Dip.io which is similar to a typical urine test, and ACR which tests for micro albumin and creatinine levels within urine.

The use of the technology is improving a number of key clinical pathways, including:

  • CKD: Home-based screening of albumin and creatinine (ACR) for people with diabetes or high blood pressure has increased adherence to NICE clinical guidance and the diabetes care process by successfully reaching 72 per cent of eligible previously untested patients. This resulted in 11 per cent newly found cases of elevated protein, indicating previously unknown kidney disease.
  • UTI: Self-testing for UTI can shift uncomplicated UTI management from the GP to the community pharmacy setting and can reduce unplanned hospital admissions among people with chronic conditions.
  • Antenatal: Dip.io is currently used for self-management in hypertensive pregnancies by Israel’s leading health maintenance organisations, and has demonstrated strong positive outcomes. Digital home-testing has the potential to reduce outpatient appointments by 60 per cent and reduce antenatal consultation time by 25 per cent. Both products have been CE-approved and ISO 13485, and are used in partnership with a number of key NHS organisations within both primary and secondary care.

Measurable impact

DrDoctor - Creating smart, data driven value-based healthcare systems.

DrDoctor is working with the NHS to create smart, data driven value-based healthcare systems, with patients at the centre and patient engagement as the driving force England there were around one million hospital outpatient appointments where the patient failed to attend. As each outpatient appointment costs approximately £120, the cost of missed appointments was close to £960 million.

The DrDoctor Patient Portal is a tool that allows patients to book and change medical appointments online, through notifications via their communications channel of choice. Once patients have been onboarded to the platform, they are encouraged to use it to take control of their own health.

DrDoctor is currently live in 16 NHS Trusts across the country, scheduling over 9 million appointments and serving almost 5 million patients.

Trusts using the DrDoctor tool estimate that they are each saving around £2 million a year, with the number of missed appointments falling by a third, and cutting their postage costs by more than a quarter. Other outcomes include:

  • improvements in clinical utilisation
  • improvement in patient and staff satisfaction with over 90 per cent of patients and staff recommending the service
  • improved attendance
  • one Trust reported financial benefits of £2.6 million in 2016-17, with further savings in the ensuing years

Agile solutions

Increasing patient safety by using Real Time Locating Technology (RTLS) across all hospital areas: The Royal Wolverhampton NHS Trust

To improve performance around patient flow and prevention and control of hospital-acquired infections, the Trust implemented ‘SafeHands’ (TeleTracking), a Department of Health part-funded innovation project using real-time locating system (RTLS) hardware and software to improve patient safety. The Trust installed more than 5,000 infrared beacons and virtual walls across its acute hospital site, establishing virtual rooms. This allows tracking of badges worn by staff, patients and medical devices at bed level in multi-bed bays. The Trust distributed 4,000 individualised badges to clinical staff, and all in-patients are badged on admission. The system also allows staff to identify where patients are at any time and captures staff-patient interaction, as well as staff-device interaction, in real time.

The software captures and stores location data and can provide analytics indicating where equipment is located that needs preventative maintenance, as well as registering which members of staff have interacted with which patients. This accelerates identification of at-risk staff where a patient is diagnosed with an infectious disease. Staff can call for assistance from colleagues by pressing a button on their badge, triggering an audible alarm and flagging the location and patient identification in a message sent to staff on the ward. Patients badges are removed on discharge from the hospital, which automatically triggers a message to housekeeping asking for the patient bed to be cleaned and discharges the patient from the patient administration system.

All admissions and transfers are managed centrally via the command centre, which enables patients to be placed in the right bed first time. The programme has helped to deliver quantifiable efficiencies, including:

  • Breaches in ED 4 hour waits (due to bed capacity) reduced from 50% to 15% in 2016 and has stayed at that level, despite an increase in ED attendances and admissions.
  • The number of medical patients in surgical beds has significantly reduced, with the patients in the right bed first time in 95% of cases, as a result of increased visibility and availability of specialty beds.
  • There has been a statistically significant reduction in the number of cancelled operations due to lack of bed availability from 40 per month to about 5.
  • With real time locating, RWT tracks 102,000 total interactions with patients or 1.5 years of staff to patient interactions per day

Reliant on industry collaboration

Use of AI at Moorfields Eye Hospital.

In the UK two million people are living with sight loss, and 360,000 people are registered blind or partially sighted. By 2050 the projected number of people suffering from sight loss in the UK is expected to double. However many cases are preventable or can be managed effectively if diagnosed and treated early. Since 2016, Moorfield’s Eye Hospital in London has been collaborating with DeepMind Health to explore whether AI can help clinicians improve the way sight threatening conditions are diagnosed and treated, in order to improve patient care.

In August 2018, Moorfields and DeepMind Health announced ground-breaking results of the first stage of the partnership. The results showed that the AI system developed by DeepMind Health researchers could match world-leading experts in diagnosing a range of eye conditions, recommending the correct referral decision for over 50 eye diseases with 94 per cent accuracy.

It has also been used to develop new treatments. The next phase of this work is to see whether AI models can not only detect eye disease, but predict it. To do this work reliably and at scale, researchers will use Google’s secure cloud computing infrastructure. The successful development and implementation of this technology could help ophthalmologists in the future to identify eye conditions earlier, and provide effective treatment before the damage caused by a condition becomes irreversible.

Tailored to end-user needs

STREAMS for Acute Kidney Injury: Royal Free London NHS Foundation Trust

Acute Kidney Injury (AKI) affects one in five hospitalised patients in the UK, causing at least 40,000 deaths each year and with costs for the NHS exceeding one billion pounds. When diagnosed on time, it is a largely treatable condition, and it has been estimated that more than 25 per cent of AKI deaths are preventable. Since 2017 the Royal Free London NHS Foundation Trust, a large tertiary referral hospital with a dedicated renal response team, has been using Streams, an app developed by DeepMind Health. The Streams app detects the early signs of AKI and delivers real-time clinical insights, enabling an immediate intervention. By the end of February 2017, more than 26 nurses and doctors at the Royal Free were using it, with clinicians alerted to an average of 11 patients at risk of acute kidney injury per day. The application is easy to use, providing real-time access to the most relevant clinical information, such as blood test results and medical history. The availability of the information at a glance allows doctors and nurses to make informed decisions and act within a few minutes rather than several hours.

Early anecdotal evidence suggest that the workload of nurses using Streams is reduced by two hours every day, releasing time to care for patients. Healthcare professionals reported that the new interface was user-friendly and only takes a few minutes to learn how to use. They also commented that smartphone technology “is something that you are familiar with out of work as well as in work”. “The app is delivering cultural change to the way technology is being used to improve patient care. The technology is no longer passive, but is actively helping us to provide better and timelier care to patients”: Chris Laing, a renal consultant who has worked with DeepMind to develop Streams. In November 2018, it was announced that, with the aim of scaling up Streams, Google, which acquired DeepMind in 2014 will be directly leading the team working behind the app.

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