[London, 7 September 2022] – Shiraz Austin, Augnito Co-Founder and expert in AI-driven speech recognition addresses the current challenges and risks associated in radiology reporting.
Radiologists are facing increased pressure to manage NHS resource shortages. With unprecedented backlogs, delays in training newly qualified consultants and demand increasing with every passing day, Trusts and healthcare providers need new ways to reduce discrepancies in diagnostics and radiology reporting errors to ultimately drive the cost of risk down.
Shiraz Austin, Co-Founder of Augnito, stated: “There is a financial cost and a very real human cost to risk and errors in radiology. Issues with radiology reporting – often due to workloads, reporting accuracy, or radiologist cognitive overload expose Trusts to litigation, expose radiologists to burnout and withdrawal from the profession at a time when they are most needed, and expose patients to inferior care/health standards, or worst still, life limiting outcomes.”
According to NHS statistics ¹, 12,629 clinical claims were made against the NHS in 2020/21 at a cost of around £2 billion. Perhaps more alarming is that this number of claims was 133% higher than nine years ago demonstrating a significant increase year on year.
Austin continued: “These numbers are unacceptable, the human cost is unacceptable. While radiologists are addressing diagnostic risks by taking proactive steps to reduce errors at every stage, ensuring reporting accuracy, backlogs, and checking accuracy standards in the solutions they use, remain vital components of their service, there are digital solutions that can help support them and radiology as a whole. Solutions using speech recognition (SR) technology can ease the workload backlog and mitigate risks.”
“Advances in today’s SR solutions help to streamline workflow, improve transparency and promote clinician efficiency. Augnito’s voice-AI-driven technology is highly accurate straight out of the box and works with radiologists however and wherever they need to work. It assists radiologists to report faster without errors, whilst embracing reporting standards through consistently structured formats and a natural learning processing engine with natural language understanding.
The cost of errors and delays to the NHS – through litigation, or in time lost as each day passes without accurate solutions being implemented – and in patient care, placing a risk to life, cannot continue in the current upward trend. In its first year of launching, Augnito’s technology is already deployed across a large percentage of the UK’s radiology reporting and teleradiology platforms ̶ accurately supporting radiologists every day in their key patient-care role. Our mission to democratize speech recognition across the whole continuum of care has only just started” concluded Austin.
Read the full blog here https://www.scribetech.co.uk/2022/08/30/the-costs-of-risk-and-errors-in-radiology-reporting/
For further information, interview opportunities or accompanying graphics please contact: Georgina Pavelin, Mixed Media – [email protected]
Augnito is a secure, cloud-based, AI-driven clinical speech recognition product suite. It offers fast, easy ways to capture live clinical data on any device with 99% accuracy, support for multiple medical specialties, and no need for voice profile training. Augnito brings seamless speech recognition to daily workflows and third-party clinical systems, turning medical information into clinical documentation and making healthcare intelligence securely accessible everywhere. Augnito was developed by its parent company Scribetech, a clinical voice solutions innovator, fusing 20 years of transcription and digital dictation services to the NHS, speech-to-text and clinical coding solutions for the healthcare sector, and its own speech recognition engine with advanced voice AI technology.
While next generation speech recognition has the potential to further transform radiology, no change comes without some degree of cost and complexity. But with rising backlogs, a culture of litigation, and growing risk for radiologists in the UK, the costs of doing nothing could be significantly greater.
As with every facet of healthcare, radiology departments are no strangers to the idea of controlled risk. A delay or discrepancy in a radiology report always has the potential for severe consequences and a domino effect.
However, with radiologists facing increased pressure to keep up with NHS resource shortages and impossible workloads, that risk is rapidly growing. As a result, entire Trusts and healthcare providers need new ways to reduce errors, deliver consistency, and drive risk down.
The cost of errors and delays to the NHS
At the most fundamental level, issues with radiology reporting – often due to workloads, reporting accuracy, or radiologist cognitive overload – expose Trusts to litigation.
According to NHS statistics, 12,629 clinical claims were made against the NHS in 2020/21. The cost of these claims to the NHS was around £2 billion.
From emergency care to oncology, departments encountered more litigation – and higher compensation amounts – than ever before. In fact, the number of clinical claims was 15% higher than five years ago and 133% higher than 9 years prior. The level of that litigation is not decreasing.
Radiology also reported a significant increase in claims between 2015/16 and 2020/21 – a growth of almost 10%, reflecting 376% growth over the past 9 years. This may have been partly driven by increased usage and reporting – but also the widespread staff shortages, overworked radiologists, and a backlog that was intensified by the pandemic.
Worse, this financial cost is only a reflection of the more human cost – an impact on patient care, standards of practice, and outcomes.
How radiologists are addressing risk
For radiologists, mitigating this significant financial and human cost does not just mean accepting that mistakes happen, but taking proactive steps to reduce the likelihood at every stage. Reporting accuracy is vital, as is checking the standard of accuracy.
Clinical analytics is a growing priority around the world, with signed-off reports analysed for accuracy, errors and outcomes like referrals. In some instances, this data can be used to drive radiologist performance, flagging issues like too few or too many referrals, or identifying overdue exams to avoid adverse outcomes. In this context of increased scrutiny, high quality report data is essential.
While not new, a layer of peer reporting is another way to significantly raise standards in radiology. The Royal College of Radiologists published a detailed report in 2014 on quality assurance and peer feedback, outlining expectations that at least 5% of radiology reports should be screened by peers – that was 8 years ago.
Time has not made this best practice any less challenging in an environment where there is a severe lack of peers to do the reviewing and the profession continues to already be overworked. This kind of initiative depends on the availability of radiologists, free from the pressure of an endless backlog. It also requires reports to be clear and consistent in their format via structured reporting.
However, the right digital approach to reporting can help – and voice-AI driven speech recognition can play a key role.
Speech recognition reduces risk for radiology
Highly accurate, AI-powered speech recognition has the potential to reduce or stop the domino effect of errors at the source. Augnito doesn’t just give radiologists a way to report faster and with fewer errors, but also embracing standards through consistently structured reporting.
Built in partnership with clinicians and radiologists, Augnito delivers 99.3% accuracy out of the box, available on any device: desktop, web, mobile or integrated with existing clinical systems. Clinicians can work however and wherever they need to – without compromising on reporting quality.
Augnito is also designed to support secure sharing, empowering radiologists to adopt more peer review as part of their daily routine. And, because it’s a 100% cloud-hosted solution, there’s no complexity in implementation or ongoing management and maintenance of hardware and infrastructure – which can add unnecessary risk to data loss, costs, and reporting down-time.
Radiologists – and any other department – will always face a measure of risk when it comes to their reporting. Augnito brings increased control to every radiologist, significantly reducing risk – personally, professionally, to the Trust and to patients.
Adopting any new technology is a cautious process for many, balancing the wellbeing of radiologists with the needs of patients and concerns over privacy and risk. However, modern, next-gen speech recognition not only delivers compliance, but can de-risk the way you already create and manage reports.
Driven by Government expectations and its strong recommendation to the public sector, hospital Trusts are pressured to replace legacy systems and adopt new technology that demonstrates better value for money. The Cloud First policy is just one example: a comprehensive initiative to increase cloud adoption throughout the NHS.
Radiologists tend to explore new technology with confidence – they were one of the first to adopt speech recognition. However across entire departments and frontline healthcare organisations, several barriers can make more widespread adoption difficult. According to Matthew Chase, former CTO at Guy’s and St Thomas’ NHS Foundation Trust, these include concerns over cost and complexity – but security is an issue that’s raised most often.
Security in particular holds Trusts back from innovations that could empower radiologists, improve collaboration, and ultimately improve patient care.
More than anything else, radiology reports are valuable sources of data and insights that will inform patient management. Protecting that data is a critical task.
Creating consistent, compliant reports
Traditionally, the narrative reports from different radiologists vary in language, length and style. As a result, they’re not always clear when shared with referring clinicians, adding a layer of translation and decryption to an already difficult workload.
Increasingly, technology is used to bring consistency and control to the way radiologists report. This significantly improves reporting quality – but it also means entrusting sensitive patient data to the platforms you use as a department.
In part, effective security is about protecting this data from leakage, loss and malicious interception. But it’s also about safeguarding the integrity of the valuable report data created using years of radiology experience and learning, particularly when it’s used to determine an overall path of care.
The three security barriers for speech recognition
Accurate speech recognition has the potential to further transform radiology as a field and transform the lives of radiologists. However, until now, adoption has been limited by the understandable concerns of Trusts that don’t want to be exposed to additional risk.
#1 The transfer of data to the cloud
The cloud and electronic health records are already making it easier for clinicians to share information, monitor cases at every stage, and understand every patient interaction in context. Despite this significant benefit, many are concerned about the safety of data as it is transferred outside of the local infrastructure.
More than servers and connections, the cloud is built on trust. It’s a major consideration in cloud adoption, with users expecting guarantees on:
- How data is made accessible to specific individuals
- How data is secured against unauthorised access
- How data is protected against tampering or manipulation
- Availability, resilience and low or no risk
The most effective, accurate speech recognition uses cloud computing to support complex AI models. Robust data protection and security is vital.
#2 The use of data to improve AI
Speech recognition doesn’t just absorb voice data and create reports. Any machine learning AI will need to process and learn from data, contributing towards natural language processing and natural language understanding. As standard, this data should always be anonymized and encrypted before it is used in training.
In this context, the integrity and security of voice data is a concern that should stretch beyond radiology or individual Trusts. A speech recognition provider can only deliver accuracy that continually learns and improves by embedding robust security and data protection – removing any identifiable data, or risk of data breach and loss.
#3 Maintaining compliance at every touchpoint
With the rise of remote working, governance has become a big challenge for healthcare. Compliance with regulatory expectations is no longer confined to the hospital and its core systems. It’s something that needs to go wherever users do – and wherever data does.
Native speech recognition on smartphones and tablets creates a complex compliance minefield. When using solutions like Siri, for example, do you, the user, know where the audio is being routed to for processing? Do you know what data/personal detail is being stored and where? Could there be a risk of cross-border routing in a way that’s likely to breach GDPR?
Overcoming this compliance concern takes speech recognition that’s expressly built for the needs of healthcare and radiology, with an acute focus on keeping data safe, secure and compliant.
How next-gen speech recognition keeps data secure
Developed in partnership with clinicians, for clinicians, Augnito’s AI-driven speech recognition and voice transcription offers industry leading security. It’s not just a dictation platform for accurate transcription, but a powerful tool that radiologists and Trusts can feel comfortable about using.
A few of Augnito’s parent company’s security and compliance credentials include:
- ISO 27001:2018 certification and GDPR compliance
- A speech recognition engine hosted by Amazon Web Services (AWS) in the UK
- Anonymised, encrypted data at rest, store exclusively in the UK
- Automated backup options in AWS to prevent data loss
In these ways, Augnito goes beyond accuracy to offer security, data protection and peace of mind.
At the same time, Augnito doesn’t just take the risk out of adopting speech recognition – it’s a powerful way to raise your security standards in the cloud compared to traditional, manually typed reports, and offers value for money compared to legacy, or non-clinical voice recognition solutions.
By bringing consistency and reproducibility to every radiological report, enabling role-based, secure sharing, and enabling secure transcription on any device, Augnito is making radiology data safer than ever before.