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Medica Group, the UK's leading provider of teleradiology services, has established a long-term strategic partnership with Qure.ai, a global leader in artificial intelligence-driven healthcare solutions. This collaboration is aimed at significantly improving the efficiency of NHS radiology scan workflows, which have been under considerable strain in recent years. Since 2020, Medica and Qure.ai have deployed the AI-powered decision support tool, qER, specifically designed for CT head scan examinations. This innovative technology has been instrumental in prioritizing critical cases, helping clinicians make faster and more accurate decisions, particularly in neuro-critical scenarios.

In their joint efforts, Medica and Qure.ai have released a new white paper that delves deeply into the evolution of AI within the radiology industry. This document sheds light on how AI is reshaping medical imaging, with particular emphasis on neuro-critical workflows. One of the key findings highlighted in the white paper is the remarkable accuracy of the qER tool, which demonstrated 93% accuracy in detecting intracranial hemorrhages (ICH) during a post-market surveillance study. This achievement underscores the transformative potential of AI in not only improving diagnostic accuracy but also enhancing patient outcomes by ensuring faster identification of life-threatening conditions.

The white paper offers an in-depth look at the reliability and integration of AI into teleradiology services, providing valuable insights into how AI-assisted workflows are revolutionizing the management of acute neurological conditions. By leveraging AI technology, clinicians can now navigate complex cases with greater precision, reducing diagnostic errors and expediting urgent treatment decisions. 

To explore these insights and understand how AI is shaping the future of radiology, fill out the form below to access the full white paper. Discover how this partnership between Medica and Qure.ai is transforming the landscape of teleradiology and improving the quality of patient care.

Fill the form to download the whitepaper now

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Data Driven Insights: The Role of AI in Radiology's Evolution

AI biases can emerge if algorithms are not validated on diverse populations.

qER, Qure.ai's AI solution for head CTs, has been rigorously evaluated using real-world, multi-regional data. As a result, qER reliably delivers excellent outcomes as a fully operational product for diverse populations globally. It has been extensively tested, deployed, and proven accurate across diverse patient demographics and scanning equipment, instilling true confidence in qER's reliability anywhere.

Qure's FDA-cleared qER software has gained traction in North America for its ability to swiftly and accurately triage, detect, and quantify pathology on head CTs. Covering four critical markers - hemorrhage, mass effect, midline shift, and fractures - qER delivers comprehensive insights to prioritize critical cases.

Monitoring severity over time aids in the long-term management of conditions such as hemorrhagic stroke and hydrocephalus. Input from North American hospitals and teleradiology groups guided qER's emphasis on essential CT measurements for emergency triage.

Additionally, qER-Quant leverages intelligent algorithms to precisely quantify volumes of intracranial structures and lesions. By determining the severity and progression of conditions like hemorrhagic stroke and hydrocephalus, qER-Quant further augments diagnostic and treatment decisions.

A study reviewed by vRad validated the qER algorithm against radiologist findings on more than 300,000 head CT scans. In one of the largest* evaluations conducted, qER delivered an outstanding AUC of 0.96, showcasing its ability to reduce door-to-scan interpretation times by up to 96% and accelerate communication of critical results to stroke teams within 5 minutes.

A noteworthy study published in The Lancet demonstrates a crucial validation of deep learning's capabilities in detecting urgent abnormalities on CT scans, using a diverse 300k scan dataset sourced from 20 centers in India. Key findings demonstrate exceptional diagnostic accuracy, with AUC values of 0.92 for detecting intracranial hemorrhage and over 0.90 for other specific bleed types.

Aarthi Scans and Labs, one of India's largest diagnostic chains, has adopted AI to enhance their teleradiology reporting - including for remote Tier 3 cities lacking nighttime radiologist coverage. This enables faster diagnosis and treatment for time-sensitive trauma cases. One deployment at Aarthi's Tenkasi center showed great insight into AI's clinical impact.

In Tenkasi, patients with conditions like stroke or traumatic brain injury used to wait over 7 hours

from the onset of symptoms to receive treatment due to delays in scan analysis, transfer to tertiary hospitals, etc.

According to Dr. Arunkumar Govindarajan, Aarthi's Director, "qER reduced symptom-to-treatment time by 30-70%, allowing more patients to be managed locally. By getting AI's assistance for faster diagnosis 24/7, cities like this could revolutionize outcomes for time-sensitive neurological injuries and disease."

A study detailed in Diagnostic Neuroradiology further cements the value of qER, focusing on the crucial aspect of intracerebral hemorrhage (ICH) management—hematoma volume quantification. Hematoma volume is a pivotal predictor of patient outcomes post-ICH, and the study aimed to validate a novel, fully automated software developed by Qure.ai for this purpose.

The study analyzed a significant patient population from the Swedish Stroke Register, including all patients diagnosed with intracerebral hemorrhage (ICH) in Region Skåne from 2016 to 2019. It compared ICH volume measurements from qER–NCCT, Qure.ai's automated quantification tool, against traditional methods like ABC/2 and manual segmentation using Sectra's software.

The results demonstrate qER–NCCT's ability to identify ICH with 97% sensitivity, proving highly efficacious in detecting bleeding. Volume measurements also showed excellent concordance between qER–NCCT and manual segmentation, considered the gold standard, with an interclass correlation of 0.96.

qER has gained widespread recognition and adoption within the United Kingdom's National Health Service (NHS) for its ability to expedite the identification of critical markers on head CT scans. Implemented in over 20 NHS trusts and health boards spanning England, Scotland, and Wales, qER processes over 1 million emergency scans every year, demonstrating high accuracy and reliability.

qER achieves exceptional AUC scores above 0.95 for the detection of intracranial hemorrhage and other hemorrhages. The deep learning algorithms also showcase near-perfect correlation with specialized neuroradiologist reporting for hematoma volume quantification, with an interclass correlation coefficient of 0.96.

Moreover, Medica, a leading teleradiology provider in the UK, has integrated Qure.ai's qER solution into its acute imaging workflow. qER serves as an "augmented intelligence" tool that analyzes non-contrast CT scans of the brain, flagging potential abnormalities and allowing for priority reporting based on clinical urgency.

As Dr. Garry Pettet, Consultant Radiologist, explains: "The qER algorithm is handy to reporting clinicians when interpreting acute brain CTs. It not only facilitates the rapid allocation of critically abnormal scans to our reporters but also helps to increase our reports' accuracy by lowering human error."

Recognizing the immense potential to augment emergency care pathways, the NHS selected qER as one of the inaugural winners of the prestigious Artificial Intelligence in Health and Care Award. The £140 million award spans 4 years to assess promising AI innovations in various clinical settings thoroughly. For qER, the aim is to widely implement it in Accident and Emergency (A&amp;E) departments to enhance diagnostic turnaround times for critical conditions like hemorrhagic strokes, ischemic strokes, and traumatic brain injuries.

The extensive piloting of qER technology within the NHS reflects an understanding of the pivotal role AI can play in bolstering overburdened care teams. With A&amp;E departments experiencing surging footfalls and exponential growth in required imaging, advanced analytics offered by solutions like qER could help alleviate clinical workload while boosting diagnostic precision.

Integrating AI-driven measurements into clinical practice could revolutionize diagnosing and monitoring neurologic and craniofacial conditions. It would provide a standardized reference supporting more informed decision-making and follow-up. Furthermore, initiatives like the AI-Based Stroke Care Network launched by Zydus Hospitals and Medtronic in Gujarat, India, aim to bridge significant gaps in stroke care, particularly in regions with limited access to specialized healthcare facilities, by leveraging AI to interpret CT scans remotely. Such innovations are pivotal in enhancing the timeliness and efficacy of stroke treatment, thereby improving survivability and reducing the incidence of long-term disability.&nbsp;

qER's seamless integration into healthcare systems across continents has accelerated the detection of neurologic emergencies, notably reducing response times and facilitating timely interventions. Through ongoing innovation and partnerships, algorithms like qER stand poised to radically improve healthcare delivery, offering tailored, efficient, and equitable medical solutions on a global scale.&nbsp;

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Qure.ai's qER: The Globally Proven Algorithm for Head CTs

Medica Group, a leader in UK teleradiology services, has partnered with Qure.ai, a globally recognized AI innovator in radiology, to integrate artificial intelligence into radiology workflows. This collaboration aims to enhance efficiency and prioritization within Medica’s radiology services, focusing on two impactful areas: improving CT head scan triage and refining study allocation processes.

One of the primary outcomes of this partnership will be an AI-driven decision support tool for CT head scans. This tool is designed to identify urgent cases quickly, allowing them to be flagged and prioritized based on clinical need rather than order of arrival. By doing so, Medica’s radiology teams can respond to high-priority cases more swiftly, integrating AI-identified critical findings directly into their diagnoses. This tool will initially support Medica’s NightHawk service, an out-of-hours radiology offering designed for urgent cases, and promises to streamline the process for rapid, effective clinical decision-making.

The second focus of the partnership is a bespoke AI-based workflow tool aimed at optimizing study allocation for Medica’s large network of over 435 radiologists. With this tool, Medica can handle its extensive workload more efficiently, automatically directing studies from NHS clients to the appropriate reporting teams. This kind of automation ensures smoother workflow management and allows radiologists to focus on interpreting images rather than on administrative processes.

Medica CEO Stuart Quin emphasized the company's ongoing commitment to adopting AI solutions that improve radiology efficiency and support clinical decision-making, seeing Qure.ai as an ideal partner due to its proven success in similar teleradiology applications. Qure.ai’s CEO, Prashant Warier, expressed enthusiasm for collaborating with Medica to bring AI’s potential to the forefront of the UK’s radiology market, highlighting the opportunity to support Medica’s expert radiologists in delivering high-quality care.

Through this partnership, Medica and Qure.ai are set to redefine teleradiology workflows, combining AI technology with expert radiological insights to advance patient care in the UK.

Fill the form for full case study

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24/7 emergency teleradiology reporting of stroke and neurocritical concerns

<a href="https://blog.vrad.com/in-the-wild-mednax-and-qure.ai-partnership-guiding-ai-advancements">vRad</a>, a leading teleradiology provider in the U.S., has teamed up with Qure.ai to integrate AI-driven solutions in stroke care. This collaboration addresses the urgency required in treating over 795,000 stroke patients annually in the U.S., where each minute is crucial.

A stroke claims a life every 3.5 minutes, so an immediate medical response is crucial. The healthcare industry grapples with challenges such as limited capacity and increased demand for imaging, making quick and accurate decisions imperative.

Qure.ai's AI tool, <a href="https://www.qure.ai/product/qer">qER</a>, seamlessly integrates into vRad's workflows. Certified by FDA 510(k) and CE Class IIb, the tool interprets head CT scans, allowing for expedited and confident clinical decisions.

In a recent case at a rural Iowa medical center, a 68-year-old female was diagnosed and treated promptly due to AI prioritization, significantly improving her condition.

The vRad and Qure.ai partnership exemplifies how AI can revolutionize time-sensitive and critical healthcare sectors like stroke care. For more in-depth insights and metrics, download the complete case study.

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Elevating Radiology Care with Qure.ai & vRAD

When it comes to stroke and traumatic brain injuries (TBI), experts say “time is brain" because avoiding treatment delays can mean the difference between life &amp; death or permanent paralysis for patients. This urgency increases the burden on radiologists.

However, powerful AI solutions like Qure's&nbsp;<a href="https://www.qure.ai/product/qer/" target="_blank">qER</a>&nbsp;assist in faster detection, risk reduction, and subsequent improvement in the quality of life.

<a href="https://aarthiscan.com/" target="_blank">Aarthi Scans and Labs</a>&nbsp;is one of India largest integrated diagnostic chains with imaging centers across India including in Tier 3 and Tier 2 cities. The organization has adopted Artificial Intelligence (AI) in their Tele-radiology reporting. Tier 3 cities usually lack neurologists in hospitals and any trauma cases need to travel for a couple of hours even to reach a tertiary hospital, which is difficult at night. The main aim of Aarthi Scans is to implement AI in their service for the night reads of Non-Contrast Head CTs (NCCT), in absence of a Neurologist or a Radiologist to aid the treatment faster for time sensitive and emergency trauma cases.

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Impact of AI in treating trauma and stroke patients

Haris Shuaib, Head of Clinical Scientific Computing at Guy’s and St Thomas’ NHS Foundation Trust hopes so. In a freewheeling conversation with Reena Rajan, Head of Marketing at Qure.ai, they touch upon facilitating technology into the healthcare workflow and how a boring walk triggered the London Medical Imaging &amp; Artificial Intelligence Centre for Value Based Healthcare’s AIDE initiative that’s currently being used for Stroke care and Neonatal care. Haris also discusses how the partnership with Qure.ai is a way to demonstrate how AI solutions can have meaningful impact in hospital ops and patient outcomes and the endless potential applications of AI in healthcare.

A boring hospital corridor walk sparked what would become a groundbreaking healthcare AI initiative. In an engaging conversation with Reena Rajan of Qure.ai, Haris Shuaib, Head of Clinical Scientific Computing at Guy's and St Thomas' NHS Foundation Trust, reveals how his reluctance to walk between two connected hospitals led to transformative change in healthcare technology.

Five years ago, as a trainee seeking a way to transfer scanner data for analysis, Shuaib wrote a simple automation program. This seemingly modest solution caught his colleagues' attention, who saw potential for their own analytical needs. That small efficiency tool evolved into AIDE, now a major Office of Life Sciences-funded program spanning 10 teaching hospitals across London and the southeast. Built on free, open-source technology, this platform has become a comprehensive solution for integrating AI into clinical workflows securely and efficiently.

As Transformation Lead for the London AI Centre, Shuaib's work extends far beyond the original automation tool. His team tackles the complex challenge of translating cutting-edge technology into practical healthcare solutions. This involves comprehensive staff training, developing robust policies that align with national regulations, and ensuring new technologies enhance rather than disrupt existing care pathways. The goal is seamless integration that benefits both healthcare providers and patients.

The partnership with Qure.ai, established through the NHS XAI award, represents a crucial step forward in demonstrating AI's real-world impact. While AI solutions have shown impressive results in academic papers - including Qure.ai's publications in The Lancet - Shuaib emphasizes the need to prove their practical value to commissioners. The focus now is on demonstrating tangible improvements in hospital operations and patient outcomes, moving beyond technical validation to meaningful implementation at scale.

The applications already in place show promising diversity. At King's College Hospital, AI assists with stroke care, while at Guy's and St Thomas', the focus includes neonatal care applications. But this is just the beginning. Shuaib envisions AI applications expanding into numerous areas: early detection of brain tumors, tumor differentiation, addressing COVID-19 backlogs, optimizing surgery times, and managing waiting lists. The potential seems boundless, though he cautions that meaningful healthcare transformation takes time and requires close collaboration between technology providers and medical professionals.

Perhaps most intriguingly, Shuaib's ultimate vision for AI in healthcare is surprisingly modest: he wants it to become as unremarkable as an MRI machine. Despite the quantum mechanics behind magnetic resonance imaging being revolutionary, MRI machines are now simply part of routine healthcare - reliable, trusted, and unexciting to all except the technologists who truly understand their complexity. 'Only the technologists should know how cool it really is,' he says, looking forward to the day when AI in healthcare becomes wonderfully ordinary - a standard tool that quietly saves lives and improves care without fanfare.

This vision of normalized excellence represents a mature approach to healthcare technology - where innovation is measured not by its novelty, but by its reliable service to patient care. Through initiatives like AIDE and partnerships with companies like Qure.ai, Shuaib and his team are steadily working toward this future, one automated process at a time.<br><br>(<a href="https://www.youtube.com/watch?v=hCzRJcxuuAQ">LINK TO FULL CHAT</a>)

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Can the use of AI become as conventional as that of MRI machines?

Samantha Davey and David Evans from Medica Group recently shared insights into Medica’s integration of AI technology into their teleradiology workflows. Medica, one of the largest teleradiology companies in the UK, provides critical diagnostic support to over 100 NHS hospitals. With over 500 radiologists and operations spanning the UK, Europe, and beyond, Medica has steadily grown from its early days in the town of Battle to a publicly listed company, now based in Hastings. Today, Medica is widely known for both its elective reporting services, which offer flexible 24- to 48-hour turnaround times, and its 24/7 emergency service, NightHawk, which guarantees rapid reporting within 23 minutes.

David, Medica’s Functional Architect, described the company's evolution and dedication to innovation. Having worked at Medica since 2008, David played a key role in integrating Qure.ai’s QER AI technology into Medica's emergency NightHawk portal, a system designed to support acute care by prioritizing urgent cases like intracranial hemorrhage detection. Medica's decision to adopt Qure.ai’s QER technology was driven by a commitment to pioneering healthcare technology that benefits both clinicians and patients, with a specific focus on improving speed and accuracy in acute settings. 

The collaboration with Qure.ai began after careful planning and pilot testing. Samantha, Medica’s Head of Program Delivery, noted that the process included feedback from Medica’s radiologists, which helped guide the integration. She explained that Medica’s priority was to ensure QER’s impact on workflow efficiency, particularly by allowing radiologists to prioritize critical cases more quickly. This integration with NightHawk enables the Medica team to identify high-priority cases like potential hemorrhages flagged by QER, allowing immediate action and faster decision-making for frontline healthcare professionals.

For organizations considering teleradiology partnerships, Samantha and David stressed the importance of selecting a clinically led provider with robust governance. Medica’s approach is to act as a strategic partner rather than simply a service provider, aiming to supplement a hospital’s existing radiology resources. This focus on clinical oversight, supported by Medica’s in-house technology team, underscores the company’s commitment to patient outcomes. Medica's model provides radiologists with full access to a patient's medical history and prior imaging, creating a seamless experience that aligns closely with in-house clinical practices.

NightHawk’s emergency reporting service epitomizes Medica’s dedication to rapid, clinically governed diagnostics. Each night, NightHawk’s radiologists manage high volumes of cases, providing consultative support to emergency doctors and advising on the necessity of imaging when appropriate. In situations where urgent findings are detected, radiologists notify clinicians directly, ensuring that critical cases receive immediate attention. Integrating QER into NightHawk's portal has enhanced Medica's ability to prioritize these cases even more effectively, as the AI flags potential issues in real time. This allows Medica to deliver on its commitment to high-speed, accurate reporting, even with substantial data transmission requirements across wide networks.

Looking forward, both David and Samantha highlighted that Medica’s partnership with Qure.ai continues to evolve as they fine-tune their AI integrations to optimize response times. By innovating with AI and maintaining a clinician-centered approach, Medica reinforces its role as a leading teleradiology partner for hospitals across the UK and beyond.

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How qER helps UK’s largest Telerad firm Medica Group Plc

Dr. Garry Pettet, Consultant Radiologist at Medica, shared his experiences on integrating AI technology into Medica’s teleradiology workflow and its impact on patient care and operational efficiency. Medica, one of the UK’s largest teleradiology firms, collaborates with over a hundred NHS trusts, handling around 1.5 million imaging studies annually, including CT, MR, and plain film. Dr. Pettet, with his unique background in radiology and software engineering, has been at the forefront of Medica’s Future Tech initiatives, focusing on innovations to make imaging safer, more accurate, and faster.

The partnership with Qure.ai began over a year ago, with Medica implementing Qure’s qER algorithm, designed to detect critical abnormalities like intracranial hemorrhage on head CTs. Dr. Pettet noted that the integration of AI was motivated by the need to improve patient safety, reduce turnaround times, and enhance accuracy. With qER, Medica can now prioritize scans flagged as abnormal, getting them into the hands of radiologists more quickly, which has been crucial for managing cases that require immediate attention. Dr. Pettet explained that qER’s ability to prioritize scans based on clinical urgency allows Medica to move away from a strict first-in, first-out system, resulting in faster responses to high-risk cases and better patient outcomes.

AI integration with Medica’s bespoke systems has been seamless, thanks in part to Qure.ai’s flexibility and the technical support provided by its team. Dr. Pettet emphasized the collaborative nature of the partnership, noting that Qure.ai’s agile approach has allowed for smooth adjustments to suit Medica’s unique requirements. Beyond faster reporting times, Dr. Pettet and his colleagues have seen the qER algorithm improve diagnostic accuracy. Radiologists have expressed gratitude for qER's "second-look" capability, which has helped catch potential oversights, contributing to safer and more reliable reporting.

While turnaround time remains critical, Dr. Pettet underscored that the broader benefits of AI extend to overall operational efficiency and cost savings. With AI enhancing the speed and accuracy of reporting, Medica can process a higher volume of scans with the same resources, reducing costs. For the NHS, similar AI applications could yield significant cost savings through more efficient workflow management. Although AI is not yet ready to independently generate full diagnostic reports, its role as an adjunct tool has proven invaluable for prioritization and error reduction.

Reflecting on the future, Dr. Pettet envisions an even greater role for AI in healthcare, where it acts as a powerful assistant to radiologists. He appreciates the positive impact Qure.ai has had on Medica’s operations and is optimistic about the potential for AI to transform teleradiology. This collaboration has not only enhanced patient care but also positioned Medica at the cutting edge of digital healthcare technology.

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How can Artificial Intelligence help make medical imaging safer, better and faster?

One article by Dr. Justy Antony Chiramal MD, DTMH, focuses on the challenges and advancements in stroke and COVID-19 care in India and the UK, emphasizing the role of artificial intelligence (AI) in healthcare.

In rural Assam, India, a 45-year-old tea plantation worker suffered a stroke but faced delays in treatment due to remote healthcare facilities and lack of specialists. This case exemplifies the plight of many in low-and-middle-income countries, where stroke cases have doubled in the past decade due to high prevalence of risk factors like hypertension and tobacco use. In India, with a population of 1.4 billion, there are only about 2,500 neurologists and 10,000 radiologists, leading to delays in diagnosis and treatment of strokes.

To address these issues, the Baptist Christian Hospital (BCH) in Tezpur, Assam, adopted&nbsp;Qure.ai’s AI technology, qER, for rapid interpretation of head CT scans. This FDA-approved technology detects various brain conditions, including strokes, and significantly reduces reporting time from over an hour to less than five minutes. This advancement aids non-specialist clinicians in rural areas, empowering them to make faster, more accurate decisions in emergency situations.

The article also discusses the impact of COVID-19, particularly how it overwhelmed healthcare systems worldwide. It mentions the use of AI in managing the pandemic, specifically highlighting the Royal Bolton Hospital in the UK, which used&nbsp;Qure.ai’s qXR for automated chest X-ray analysis. This technology helped monitor the progression of COVID-19 in patients, proving vital in the rapid assessment and triage of cases. qXR’s quick feedback and high accuracy relieved the burden on medical staff and increased efficiency in patient management during the pandemic’s peak.

Qure.ai’s solutions are noted for their compliance with EU-GDPR and ISO/IEC 27001, ensuring data privacy and security. The use of AI in medical imaging is further supported by Qure’s infrastructure on AWS, which offers scalability, security, and reliability.

In summary, the article highlights the critical role of AI in transforming healthcare, particularly in stroke care and COVID-19 management. It underscores the challenges faced by healthcare systems in resource-limited settings and illustrates how technology, like that offered by&nbsp;Qure.ai, can bridge the gap, improve patient outcomes, and support medical professionals in their decision-making processes.<br>

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Managing Stroke using AI in rural India | Tezpur

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