The impact of AI at The Royal Bolton NHS Hospital, United Kingdom

Introduction

COVID-19 is a contagious vascular and respiratory disease caused by SARS-CoV-2, a novel variant of the SARS virus. First identified in December 2019, the World Health Organisation declared COVID-19 a ‘Public Health Emergency of International Concern’ in January 2020 and a pandemic in March 2020. As of November 2020, the disease has been confirmed in approximately 48 million people worldwide.

Be it the first world or the third, rapidly rising COVID-19 infection caseloads have placed health systems under enormous pressure, often threatening to overwhelm available resources. Numerous research studies have shown that imaging procedures are the most efficient method of evaluating the lung condition of patients with COVID-19 as well as the disease’s rate of progression. In resource challenged situations, chest X-rays augmented by Artificial Intelligence (AI) have been used for mass screening for COVID-19.

An NHS Hospital Case

The Royal Bolton Hospital in Farnworth, Greater Manchester is home to the Bolton National Health Service (NHS) Foundation Trust, providing healthcare services for people in the Metropolitan Borough of Bolton and the surrounding areas. The Trust was the first in the United Kingdom to use qXR, an imaging interpretation tool developed by Qure.ai, to help medical staff effectively monitor the extent and progression rate of COVID-19 in patients through the automated analysis of chest X-rays.

NHS Bolton

Challenge(s)

The initial months of 2020 saw an alarming spike in COVID-19 cases in the UK. It resulted in an immediate impact on the NHS, medical and social care systems as they faced the challenge of ensuring adequate testing. Patients suffering from the illness placed unprecedented demands on acute care services, particularly on intensive care units (ICUs) and the already burdened medical workforce. This resulted in a substantial rise in mortality rates.

As in other parts of the UK, Bolton NHS also faced an influx of COVID-19 patients and needed a system in place to improve efficiency in prognosis and alleviate the workload of the hospital staff. And Qure.ai was able to help Bolton NHS do that with qXR

Solution

COVID-19 clinically presents itself as consolidation, which are accumulations of fluid and/or tissue in pulmonary alveoli preventing gas exchange or ground-glass opacity, and through nodular shadowing. They primarily affect peripheral and lower areas of the lungs.

Qure.ai’s deep learning-based automated chest X-ray interpretation platform — qXR — can detect, localise, and quantify a total of 29 findings, including COVID-19 related lesions. It had been trained and tested using a growing database (over 3.6 Million) of X-rays from diverse sources. The solution gives 91% sensitivity and 77% specificity in predicting COVID-19 changes on chest X-rays. qXR could also monitor the extent and rate of progression of the infection, creating graphs showing the percentage area of lung affected and tracking changes on subsequent X-rays.

Selection Criteria

The COVID-19 pandemic has brought forth an unprecedented number of challenges for the medical community to resolve. Across the world, healthcare organisations have been forced to reevaluate their systems and processes and the NHS is no different. The rise and implementation of technology to enable medical staff to work with better safety and efficiency has been a key development. While it has proved invaluable in resource-starved, developmentally challenged parts of the world, this trend has also impacted other areas in a positive way.

Qure.ai is EU-GDPR compliant and ISO/IEC 27001 certified while qXR is Class 2A CE certified. The Qure server was located onsite and no data was sent offsite. The Bolton NHS team validated the solution on a test set of 11479 CXRs with 515 PCR-confirmed COVID-19 positives.

Results

During the peaks of the pandemic, when PCR testing turnaround time was more than 24 hours, the NHS clinicians relied on qXR to interpret chest X-rays reviews for the rapid assessment and triage patients into high, medium and low priority categories. qXR gave almost instantaneous feedback to clinicians, providing out-of-hours clinical decision support and assisting accurate evaluation by clinicians with less expertise in chest X-ray reviews. By providing workflow support to improve efficiency and increase reporting capacity, qXR can also help mitigate any shortage of trained radiologists in the long-term.

Success and Next Steps

The Bolton NHS Foundation Trust had been exploring the use and potential benefits of Artificial Intelligence in support of medical diagnoses and treatments for a considerable amount of time. However, the COVID-19 pandemic accelerated this process and resulted in the collaboration with Qure.ai. Not only did deploying qXR in the field of radiography help the hospital staff manage the diagnosis and treatment of patients, but also established the reputation of the Bolton NHS Foundation Trust as a leader and pioneer in the development of the use of AI as part of clinical workflow. Now that the tangible benefits of qXR have been documented at such a prestigious institution, Qure.ai is poised to partner with and assist other healthcare organisations to ensure that the benefits of technology are received by every stakeholder.

AWS Infrastructure

• Qure is tackling artificial intelligence (AI) challenges in the healthcare industry, advancing digital healthcare through medical imaging AI solutions.
• On AWS, we are using EC2 for heavy processing and easy scalability.
• AWS provides us 99.8% SLA which improves our performance. We have automated backups and failover in real-time.
• Our data is stored in S3 for better security, scalability, performance and data availability. Also we have RDS for database reliability.
• We are using cloudtrail which monitors and records account activity throughout AWS infrastructure.
• We have AWS WAF which is a web application firewall at perimeter level to secure our web apps & APIs against malicious traffic, web exploits, botnets, etc.
• AWS environment complies with data privacy and security guidelines