From GP practices to acute care, hospitals, diagnostics, and imaging, the UK healthcare system is complex for patients and professionals alike. Patient journeys are touched by a vast number of people, all with their own expertise and unique roles to play along the way. In many cases, journeys go beyond the boundaries of the NHS, moving into private healthcare or complementary services like social care.
As a result, there is significant pressure to maintain effective collaboration, eliminate bottlenecks, and streamline administrative processes wherever possible. Day-to-day, healthcare providers encounter three major challenges around the flow of information and, ultimately, the flow of patients from first contact to diagnosis, treatment, and recovery.
Integrated, effective technology has the ability to help overcome these challenges – and AI-powered, highly accurate speech recognition specifically provides a single holistic solution that results in improvements across the board.
#1 The unexpected is to be expected
The nature of healthcare is that things change fast. Few of us would have predicted a devastating pandemic at the end of 2019. Recent leaps forward in AI with the likes of ChatGPT have the potential to redefine how people, including medical professionals, interact with the world around them. The NHS is also undergoing its own transformation, from a strong digital roadmap to evolving models of care like Hospital at Home.
Meanwhile, Virtual Clinics are emerging as a significant way to reduce the Delayed Transfer of Care (DTOC). The NHS has begun to introduce virtual wards, allowing more people to get the care they need, in a home environment, not in hospital, which also helps to alleviate pressure. This now creates significant change in how care is delivered and how teams work with patient data.
The need for adaptability is significant. Taking radiology as an example, a study from February 2023 describes an urgent need to make radiology ‘antifragile’ – to increase resilience and adaptability, so we can thrive in an uncertain world. Some key considerations are building capacity, enabling new ways to collaborate, and prioritising information quickly and effectively.
Integrated speech recognition technology, like Augnito, helps with this challenge by empowering radiologists with more flexibility in the way they work – from transcribing reports on the go, to directly capturing information in clinical systems using speech. Speech also helps connect increasingly complex workflows across the patient journey, whether that’s in a clinical back-end, or, surfaced to other teams in different areas of the organisation. Beyond saving time for an individual healthcare professional, speech recognition transforms the availability and accuracy of clinical information. At the same time, the ability to capture information faster enables a greater degree of analysis, spotlighting the most critical information to anyone across the continuum of care.
#2 Incomplete information impairs decisions
If it wasn’t documented, it didn’t happen. That’s the reality of taking patients through journeys that are complex, often non-linear, and involve the work of multiple individuals, Trusts, private providers, and care partners. In this fast moving environment, information capture and sharing is pivotal.
- If it was just a thought, it wasn’t documented
- If it wasn’t signed off, it wasn’t documented
- It was misplaced, it wasn’t documented
- If it wasn’t saved, it wasn’t documented
- If the detail was lost, it wasn’t documented
- And if it wasn’t documented, it didn’t happen.
Wherever humans are involved in transcribing and capturing information, that information is at risk. Misplaced documents, typing errors, and incorrect data are a considerable challenge at every touchpoint. And, as information is shared across disciplines or among teams, this risk multiplies. With multiple single points of failure, a report that was accurate in the first instance misplaced or lost, affecting dozens of steps along the patient journey, with back tracking and retrieval a difficult, time-consuming task.
Healthcare has an economic and humanistic value. Gaps and failings come with financial and human impact—in some cases, irreversibly. Augnito is designed to close the gaps between medical professionals, multiple healthcare systems, the reporting technology, and their colleagues. Interoperability is key, with speech connecting disparate systems right along the patient journey and creating a single version of the truth. With highly accurate transcription available without the delays or risks of manual handling, only then can everyone make decisions based on the full, up-to-the-minute story – with complete confidence in its accuracy and validity.
#3 Harnessing collective experience and expertise
By definition, Multi-Disciplinary Teams (MDTs) are there to provide a breadth of expertise across distinct areas, each with an important role to play in patient outcomes. But close collaboration across these teams is made more difficult when ways of working and communicating aren’t unified.
A major challenge of any new technology in healthcare is adoption – especially when considering the differing budgets of those across the health and social care system. If a new technology isn’t within reach for under-funded mental health teams or understaffed GP surgeries, its impact will always be limited.
That’s why Augnito doesn’t just provide always-available, accurate speech recognition and transcription. It’s built to be widely accessible, from the low complexity nature of a cloud-hosted solution to a simple subscription model with no need for capital expenditure or complex infrastructure changes.
Holistic improvements to how people work
Technology alone isn’t lifesaving. It’s the unique expertise and talent of people across healthcare that make better patient outcomes possible. Voice-driven AI speech recognition influences outcomes in an integrated, holistic way by focusing on the needs of the people that deliver care every day.
Developed in partnership with medical professionals, Augnito is tailored to the biggest challenges our healthcare system is facing, from rising backlogs to surging DTOC figures and a widespread bed shortage. Delivering incremental improvements to the speed, accuracy and quality of reporting and communication, Augnito brings new efficiency to everyone who touches the patient journey.
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While Delayed Transfers of Care (DTOCs), bed shortages, and needless hospital stays negatively affect every patient, the NHS still has a responsibility to pay special attention to the most vulnerable people in our society. But, given the nature of acute hospital beds and potential transfers to social care, the frail elderly and sick children make up a considerable part of the pressure that the NHS faces in handling its current backlog of more than 7 million people waiting for treatment.
In an effort to improve collaboration between disciplinary teams, the NHS has been taking steps to rectify the specific challenge focussed on the vulnerable and . Between 2013 and 2015, 25 integrated care pioneer sites were selected by the NHS to develop and test new ways of joining up health and social care services across England. In 2015, 50 vanguards were chosen to lead the development of new care models, becoming blueprints for the wider NHS moving forward and the inspiration to the rest of the health and care system moving forward.
Through the new care models programme, a complete redesign of whole health and care systems was being considered. That care model was to take into account improving care not simply for older people, but with a focus on frailty vs. age and the differing needs of our ageing population. An ageing population that is living longer and presenting with more complex illnesses that require complicated care. At the same time, similar complexity can be found in a vulnerable group at the other end of the patient age spectrum – the young (children). These factors compound today’s NHS bed shortages, understaffing, burdened workflows, bottlenecks and burned-out clinicians and nurses. They also add to the DTOC problem.
While DTOCs can occur for a wide variety of reasons in the patient journeys of the above two mentioned vulnerable groups, data shows significant challenges in bed capacity, particularly for children. For older patients, awaiting care packages in their own home or nursing home availability are among the most common causes. Meanwhile, Multidisciplinary Teams (MDTs) have a pivotal role to play in enabling seamless journeys, without being limited by inaccurate patient reports, loss of reports, and delays in information sharing (a topic we’ll go into more detail in our next blog post).
In this post, we focus on how DTOCs affect the vulnerable most frequently and how speech recognition technology could help improve this situation to deliver a more consistently available level of care and, ultimately, improve outcomes.
Treating severely ill children
Recent data from Nuffield Trust examined the impact of NHS pressure on children, looking specifically at intensive care beds across the challenging winter period.
According to the report, December 2021 saw just 314 beds per day across the whole of England. While this was marginally higher than availability in previous winters, occupancy was higher too. On average, 89% of these beds were occupied, leaving just 35 beds available to new admissions.
This is by no means the direct consequence of DTOCs and patients failing to be transferred or discharged appropriately. But, it is a sign of a healthcare system in crisis, dealing with peak demand and increased instances of flu, scarlet fever and Strep A with little room to manoeuvre. Bed stocks have been reduced to an extent where any unexpected demand – or delay – could have disastrous consequences.
DTOCs and older patients
For older frail patients, effective care takes a seamless approach between the NHS, community services, and social care providers. It is often these cases where the discharge and transfer process is most complex, requiring collaboration between multiple parties and effectively prioritising what are often multifaceted, intricate needs.
According to a study in Age and Ageing, Volume 50, Issue 4, the average cost to the NHS of DTOCs in older patients was £820 million each year. However, the study highlights the importance of keeping patients central, even where most data gathering is focused on wasted costs.
The reality is that DTOCs aren’t just a cost centre. They create a ripple effect across our entire healthcare system – and out into the lives of patients and our wider communities. Reducing wasted costs is simple: discharge patients faster and more effectively – that’s just one part of the story.
For older patients – and patients of any age – the discharge and transfer process is a key part of their experience. Delays create distress and negatively impact healthcare outcomes. And the knock-on implications of bed shortages, soaring occupancy, and unavailability of care, tend to lower standards across the entire system.
The human cost of DTOCs and bed shortages
At the end of 2022, Landmark Chambers reported on a specific judicial review of an individual Integrated Care Board (ICB). A patient with complex physical needs and autism was stuck on a ward for 8 months when the NHS and social care bodies failed to agree on a discharge plan.
The ICB was ordered to pay the patient’s legal fees as well as their own costs – a legal bill estimated at more than £100,000. The real cost in this, and sadly many similar DTOCs isn’t financial. The real cost is to the patient: a vulnerable individual, already in a challenging environment, needlessly kept waiting for almost a year.
Look behind the scenes, and there’s also a human cost to the overworked, under-pressure MDTs based on the disjointed transfer of care process itself, providing these teams with unwieldy, often outdated reporting platforms and slow, manual processes that make efficient discharge and transfer more difficult than they need to be.
How can technology help?
Augnito’s AI speech recognition empowers all healthcare professionals to save time, increase productivity and, ultimately, reduce costs. It was created to play a part in rethinking models and workflows in healthcare, to actively improve the patient journey by making accurate, agile technology available to entire MDTs across Trusts and across primary care. The challenges the NHS continues to face are sizable, constantly evolving, and not easily solved. We believe a way for professionals to work more flexibly, cope with considerable workloads, and focus their efforts on delivering exceptional patient care will be key steps towards a solution.
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Augnito is already impacting the patient journey through a growing list of UK resellers, distributors and technology partners.
Request an Augnito evaluation version to see its benefits first-hand.
With the NHS under immense pressure, bed stocks are infamously limited. However, this pressure shows no signs of slowing – and the number of beds across the NHS shows no sign of growing in a way that’s substantially impactful. What other approaches can we take to address this major challenge and, crucially, how can technology help?
From healthcare professionals to the general public, most of us are intimately familiar with the continued lack of beds in our healthcare system. Even pre-pandemic, few health experts felt we were well equipped with beds and ample resources. Now, the BMA continue to stress the severity of this problem: data from December 2022 reports occupancy rates consistently exceeding safe levels and call capacity a ‘critical limiting factor’ for the NHS.
Beyond those early adopter areas like radiology and pathology, speech recognition technology has the potential to reduce costs across entire Trusts – potentially freeing up resources to invest in new ways to grow capacity and bring occupancy down to reasonable levels.
The impact of DTOC on bed capacity
Recently, in our previous blog post, we wrote about the significant challenge of Delayed Transfers of Care (DTOCs) – those periods when a patient is ready to be discharged from an acute care bed but remains in the bed regardless. Typical bottlenecks and obstacles to discharge/transfer include:
- Awaiting completion of assessment, including incomplete documentation
- Awaiting care packages
- Awaiting nursing home placement
- Awaiting community equipment and adaptations
- Awaiting further non-acute NHS care
- Awaiting care packages in own home
- Disputes and legal challenges
Across all these areas, faster documentation and reporting time can help keep people moving along the patient journey. If not, DTOC dramatically worsens the problem of poor bed stocks and low capacity.
Every day a patient stays in an acute care bed unnecessarily, beds remain unavailable to those who need them. While this is obviously a barrier to delivering timely, effective treatment and care, it also creates unnecessary cost.
The costs of a widespread bed shortage
Bed shortages, driven by needlessly extended hospital stays and DTOCs, lead to significant costs to the NHS. This is a wasted expense that does nothing to improve patient journeys, experiences, and outcomes.
In February 2020, DTOC metrics reported by the GSS show on average 5370 people were delayed per day. The actual cost of these delays is significant by any measure. According to Age UK, in 2019, the cost of a DTOC bed per day was £346. whereas Department of Health figures from 2017 put the cost at £400 per day. Even if we assume the NHS’ own £350/day cost was accurate in February 2020, this means that month’s cost for 155,700 days was over a staggering £54 million.
An effective, accurate speech recognition technology like Augnito can reduce this cost and deliver a considerable saving by enabling clinicians and healthcare professionals to work and report more efficiently, removing some of the above mentioned common obstacles to prompt discharge or transfer. And the cost of adopting Augnito is significantly less than the cost of adding and maintaining more beds.
Repurposing even just 5% of February 2020’s estimated DTOC cost into Augnito licences could empower tens of thousands of clinicians to work more efficiently, reduce reporting time, and focus their energy on patients. Even a seemingly small 1% efficiency gain could dramatically improve both staff workloads and, more importantly, patient journeys overall.
Addressing the consistent fall in NHS beds
Over the past three decades, the total number of NHS hospital beds in England has more than halved. In part, this reflects changes to the ways patients are treated and is a trend we can see reflected in other advanced healthcare systems. For example, an increase in day surgery and long-term policies to move patients into care in the community have partly driven this ongoing reduction in capacity.
Of course, we all know that demand hasn’t followed this proposed downward trajectory. While the number of beds may have decreased, the number of patients treated has continued to rise sharply. Today, the UK has fewer acute beds relative to its population than most other European countries.
Worse, the longer-term outlook is bleak. The Health Foundation’s REAL Centre analysed bed stocks against best-case demand and found a significant gap. According to the report, 35% more beds will be required by 2030 – even if NHS initiatives to reduce hospital stay durations succeed. Apply the estimated DTOC rates we’ve shown above and the cost skyrockets.
The impact of speech recognition on efficiency and cost
As the NHS has consistently found for more than three decades, expanding bed stocks isn’t a simple task. Capacity is a complex issue and, as demand continues to surge, occupancy rates of 99% and above aren’t likely to improve without significant change.
It’s not that technology like Augnito AI powered speech recognition can solve the DTOC challenge overnight. It’s that incremental improvements to the way healthcare professionals work, collaborate, and share information creates consistent improvements over time. Eliminating the slow reporting and typing into cumbersome, often outdated systems saves time, reduces costs, and enables budgets to be repurposed into wider, systemic changes.
Augnito is already used widely across healthcare, helping those in diagnostic and reporting roles capture clinical data quickly, securely, accurately, and more cost-effectively. Crucially, Augnito’s flexible licensing means it’s available to Trusts for a fraction of the cost of adding capacity or keeping patients in beds for longer than they need them.
For Trusts, this creates time and money savings with a compound effect. The ease of implementing Augnito across multiple individuals, departments and parts of the patient journey means even small efficiency gains for healthcare professionals create a significant, meaningful saving overall. The facts speak for themselves: the cost of a single extra bed per day is close to if not 10 times more than the cost of a single Augnito licence for a month.
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In a climate of continued and yet unprecedented pressure on the NHS, Delayed Transfer of Care (DTOC) is not just another step in the patient journey. It’s a crucial step on the path to positive care outcomes. Since 2014/15 the number and rate of delayed transfers has been consistently rising.
Today, nine years on, delayed transfers of care (DTOCs) contribute to intensifying backlogs, rising costs, and more distress for patients. Can technology built to make healthcare more efficient influence both the extent of DTOC incidents and Trusts’ ability to deal with them?
Shiraz Austin, Managing Director at Scribetech (UK) Ltd – UK distributor for Augnito solutions – takes a deep dive into this topic.
Over the past few years, the number of available beds within the NHS has continued to decline.
In December 2022, the average daily number of beds was just 136,508. This reflects a ratio of 2.4 beds per 1000 people in the UK population – significantly lower than countries like Austria (7.1 beds/1000 people) and Germany (7.8 beds/1000 people).
There are a range of systemic, complex issues that contribute to the UK’s lack of NHS beds. Initiatives like the Urgent and Emergency Care Plan promise to improve this situation, but this is a slow, ongoing process. The results may only be seen years into the future, leaving Trusts, CCGs and healthcare providers to instead pay attention to a metric that’s more meaningful in the short-term: Delayed Transfers of Care, or DTOCs.
The scale of the DTOC problem
DTOC describes patients who are clinically ready to be transferred or discharged from acute or non-acute care, but continue to occupy a bed. This can result in needlessly long hospital stays for individual patients, as well as delays for other patients who are waiting for a bed.
While Delayed Transfers of Care should be minimised through effective discharge planning and joint working between NHS and social services to ensure safe, person-centred transfers, unfortunately, for the past two decades, this planning process hasn’t been as effective as it could be.
We might assume that the NHS carries the majority share of responsibility for delays, however, social care carries its fair share too. The overall pattern of DTOCs is not uniform between the two organisations responsible for the delay. Percentage increases for patients delayed, per day over a 10-year period, have fluctuated between these organisations’ systems, showing patients either awaiting a social care package in their own home, or awaiting further non-acute NHS care as being the main reasons for the DTOC.
In 2017 the NHS DTOC goal was just 3.5%. The gap between this goal and reality is significant.
If we look at data between August 2010 and 2017, NHS delays increased 25%, while social care delays were up 130%. By December 2018, the number had decreased by over one third to 4,155 patients delayed on average per day. Since then, data for February 2020 shows that the number increased again by 29%, to an average of 5,370 patients delayed per day.
What does this mean in terms of days and cost? In February 2020, there were 155,700 delayed days across the NHS. While NHS England paused reporting DTOC data as the COVID-19 pandemic intensified, a common-sense approach tells us the number of delayed days is likely to have worsened over the past three years.
For patients, DTOC severely impacts the quality of care being delivered and creates difficult, often distressing patient journeys. For the NHS, DTOC creates added staff pressures, workload burdens and a significant, unnecessary cost.
The financial impact of DTOCs
Findings published by the Government Statistics Service (GSS) for February 2020 show the average number of people delayed per day that month in England was 5370. While some sources like Age UK estimated the NHS excess bed day rate at £346 in 2019, the Department of Health report average costs in 2017 of around £400 depending on treatment. Multiply the delays per day by the day rate and we have an estimated cost of DTOC of £2,148,000 per day for February 2020 alone.
Yearly figures seem to have stopped being used past 2016, when a report by the National Audit Office (NAO) showed delays in discharging older patients from hospital when they no longer need care was costing the NHS £820 million per year.
The complexities of calculating excess bed day rates and recorded bed stays have been compounded by treatment tariffs and care cost models that do nothing to reduce the financial burden that DTOCs clearly carry. They reflect a direct cost in the £millions to the NHS – for maintaining patients in beds when they are ready to be discharged, or transferred, to home care or social care. And let’s not discount the financial ripple effect that DTOC has throughout the whole healthcare process that is even more difficult to track: poor bed availability, high occupancy and growing waiting lists. All resulting in patients entering the NHS system later, when their conditions may be more acute and, ultimately, more costly to treat.
Throughout the COVID-19 pandemic, the UK Government looked to help tackle this issue through funding designed to financially assist discharges to social care. However, with this funding planned to end after March 2023, the NHS will need to look at new ways to maximise limited budgets.
How speech recognition can support DTOC improvement
Technology like clinical speech recognition (SR) has the capacity to increase productivity and streamline the creation of medical documentation for healthcare professionals, easing the burden of growing admin workloads with faster, more flexible and mobile ways of working. We believe it can also influence key metrics such as DTOCs – as well as create savings for NHS budgets.
Reducing internal delays to discharge or transfer
In part, DTOC is affected by internal delays – the technical and logistical barriers to getting patients discharged swiftly and effectively. The administration involved in discharging or transferring patients must be efficient and accurate if they are to be discharged on time.
Developed in partnership with medical professionals, Augnito delivers cloud-based, AI-powered speech recognition on any device or operating system. Augnito empowers clinicians to capture live clinical patient data easily and wherever they need to, with extreme accuracy and none of the delays of manual transcription or digital dictation.
Patient notes, referrals, follow-up letters and care package instructions can be ‘spoken’ directly into an electronic patient record (EPR), simplifying the patient discharge or transfer process. This not only saves valuable time and money for the NHS and social care system, but also helps reduce the patient journey and, ultimately, improve care outcomes.
Reducing external factors on DTOCs
Efforts to tackle the DTOC problem will need a whole system-wide approach addressing the consistent lack of capacity across all parts of the system.
As outlined earlier in this document, DTOCs are not exclusively an NHS problem. The data referenced in ‘The scale of the DTOC problem’ highlights that in many cases, patients are unable to be discharged due to a lack of onward care, including from space in care homes to funding for home care services. Many of these challenges are the result of a health and social care system that continues to be under significant pressure, as well as a longstanding lack of investment in important provisions like community nursing.
It’s in the DTOC that the impact of clinical SR technology, like Augnito, has the potential to be most transformative. Switching to Augnito and using streamlined, automated clinical workflows can create an efficiency gain of around 5% per day. This time saving has a very real financial impact. It can provide a reduction in document turnaround time, patient referral record keeping, and clinical documentation inaccuracies/errors – as part of the discharge process and the patient onward care journey. This could save the NHS hundreds of thousands of pounds per month.
Currently, these productivity bottlenecks are a wasted administrative cost, not influencing or improving the patient experience. Transforming efficiency is significantly more cost-effective than trying to grow bed stocks. With a new, more seamless way of working, savings can be focused on what matters most: replacing the soon to cease March 2023 Government funding, and reinvesting in patient care by improving healthcare provisions outside the hospital environment, raising the standards of community care, and ensuring every patient can be discharged effectively and at the right time for a better outcome.
In our next blog, we’ll discuss in more depth how the financial implications of DTOC extend across the whole of the health and social care system and how savings could be repurposed for medical efficiency gains and an improved continuum of care.
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– when they matter most
With growing waiting lists, strict government targets, and increased demand, everyone involved in diagnostics is under pressure to work faster. But efficiency and speed are also vital to improving the most important thing of all: patient outcomes.
In November 2022, NHS England announced a landmark move to speed up cancer diagnosis or all-clear for patients. For the first time, GPs across the country can access fast-track testing, with direct orders of CT scans, ultrasounds, and brain MRIs. Crucially, the availability of these tests extends to those patients whose symptoms fall outside the NICE guideline threshold for urgent referrals.
For patients, this reflects a continued effort from the NHS to accelerate pathways through the diagnosis to treatment. However, for already overloaded diagnostic teams, radiologists and pathologists, it heightens the need to transform – and accelerate – ways of working.
Early diagnosis creates better patient outcomes
According to Cancer Research UK, 4 in 10 cancer cases are diagnosed through an urgent suspected cancer referral. This creates a significant gap between the most urgent referrals and those patients with concerning symptoms who would experience a longer wait for screening.
Easier access to tests across the NHS is an important step towards better outcomes. But this also moves the potential bottleneck in diagnosis and treatment to radiologists and pathologists, now facing unprecedented demand.
More than ever, healthcare professionals need faster ways to report – without compromising accuracy and precision.
How speech recognition delivers speed, accuracy and quality
As an intuitive, natural way to create reports and transcribe information, speech recognition (SR) has the potential to dramatically accelerate how pathologists report. Compared to typing, speech is as much as five times faster.
At the same time, these speed and efficiency gains are only as meaningful as they are accurate. Increasingly, AI and machine learning mean SR can deliver accuracy beyond 99%, in any accent, with a language model developed for clinical terminology.
As a result, diagnostic teams can keep pace with the rest of the NHS as it continues its transformation to faster, more efficient and secure ways of working and delivering care.
How Augnito fast-tracks pathology workflows
The NHS is understandably focused on new ways to make frontline care and patient journeys faster. But these journeys are all interwoven – and ultimately limited – by the speed with which the departments involved in diagnosis can work.
Augnito was developed in partnership with healthcare professionals to make workflows faster and more flexible, while preserving accuracy and quality. With standalone applications or integrated into existing clinical systems, Augnito delivers the accuracy that patient outcomes depend on.
However, Augnito also empowers pathologists and radiologists to improve the way they work day-to-day. Creating reports is as easy as speaking, sharing information can be highly automated and secure, and our suite of platforms means professionals can report from anywhere.
It’s more than an alternative way to create the same reports. It’s a way to rethink how diagnosis works and dramatically improve patient care with a measurable impact on productivity and efficiency.
Finally, Augnito makes workflow transformation more available and accessible with a flexible, cost-effective approach to implementation and management. As a cloud-hosted technology, Augnito doesn’t require changes to infrastructure and IT. It’s easy to switch on and start using on any scale, with data security, compliance and management taken care of by our expert team.
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Augnito is already impacting the patient journey through our growing list of UK customers and partners. Request an evaluation version or try the Augnito app to see how you can start to benefit from faster reporting, efficient diagnostics and securely impacting the patient journey for a better continuum of care.
… how speech recognition can enhance pathology and the wider patient journey
Pathology as a critical department on the path to diagnosis and treatment, has a vital role to play in simplifying and improving the patient journey – but with structured reporting, restrictive workflows, and legacy technology, unlocking mobility, efficiency and accuracy is a significant challenge.
Patient journeys across healthcare are, in some ways, unavoidably complex. Successful diagnosis and treatment require numerous departments to work together, sharing information and data, often under significant pressure and time constraints. Restrictive technology makes this task needlessly difficult for departments like pathology and, more importantly, it negatively impacts the patient experience and, ultimately, outcomes.
Like radiology, pathology must evolve to meet rising demand, considerable backlogs, and waiting lists that remain at record levels. Flexible, accurate speech recognition has the potential to deliver this evolution.
The challenges for pathology
The health of patients depends on a healthy, high-performing healthcare system. However, like radiology and many other departments, pathologists face considerable challenges in coping with the number of samples and analyses required to address NHS backlogs. These challenges are the main contributing factor to stress, burnout and poor work-life balance, more so than quantity of workload alone.
In August 2022, the number of people on NHS waiting lists reached 7 million. This landmark figure, in the height of summer, paints the picture of a difficult winter. For departments like pathology, it’s an issue that is perpetual.
In part, these difficulties are the product of high demand from patients and little to no transformation in how pathologists record and report on their work. Many departments are tied to deeply embedded, often antiquated workflows. With a need for structured reporting and a lot of complex detail, changing these workflows is seen as a significant risk.
At the same time, the pressure to change is immense. In 2015, the National Advisory Group on Health Information Technology in England found that pathology was key to diagnostic support outcomes and should be at the forefront of NHS digitisation. Since then, funding for AI and digital pathology services has been forthcoming and the NHS has begun to introduce new information standards for pathologist reporting.
However, transforming pathology and improving the patient journey also means rethinking how pathologists work day-to-day.
Investing in core clinical workflows and pathology efficiency
Unlike radiology, pathology is not traditionally an early adopter of new technology. Many pathologists find themselves using outdated, legacy systems every day as part of their routine. It’s in these ever-present, often limiting systems that Trusts can achieve the biggest return on investment.
Technology like voice-AI powered speech recognition allowing all too needed handsfree dictation now help to accelerate the pathology reporting workflow directly into the LIMS, enhancing and making them significantly easier for pathologists. Standalone or integrated into an EPR, EMR or LIMS, intuitive and contextual speech recognition gives pathologists a more efficient way to work, creating measurable time savings and improved reporting speed.
Ultimately, this influences the patient journey, waiting lists, and outcomes. Speech recognition enables a faster, more agile department, delivering a quick return on investment that empowers the radiologists and pathologists, to support the Trusts and patients alike.
At the same time, closer integration across pathology and radiology is a necessity. A study published in BMC Medicine identified this opportunity to bring diagnostic reporting systems together, improving clinical efficiency, research, innovation and, ultimately, patient care.
How Augnito is transforming pathology and patient care
Pathology is chronically underfunded and dependant on legacy technology, often unseen in depths of a hospital campus. Across complex workflows from macroscopic and microscopic analyses to final diagnosis, pathologists need best-in-class, hands-free technology to stay on top of rising workloads and play their important role in the patient journey.
Cloud-hosted
Augnito is a cloud-hosted, AI-powered speech recognition solution, that can now enable pathologists to create those structured reports using their voice to describe the biological make up and structure in precise detail. This provides seamless follow-on specialities with an easy, fast way to decipher the diagnostic next steps. Crucially, it’s the innovative and disruptive technology solution built in partnership with healthcare professionals, accounting for the reporting language specifics and complexity of every department across the patient journey.
Accuracy
Augnito delivers beyond 99% accuracy on any device, in any accent, with no need for voice profile training or a long onboarding process. The solution also includes a specific histopathology language modelling, capable of handling the complex detail and unique terms of pathology.
Mobility
It fits effortlessly into pathology workflows, any new technology especially when it needs to be completely mobile. Augnito is available on any device, anytime, anywhere, wherever and whenever it is needed.
Integration
Augnito includes a flexible API & SDK, “Augnito Voice Services”. This can be used to integrate the best-in-class medical speech recognition with the LIMS, enabling pathologists to work better, more accurately, more efficiently, and crucially within the existing workflow structure.
Flexibility
Finally, a cloud-hosted speech recognition like Augnito is available quickly with no complex changes to infrastructure. Departments can start using Augnito on any scale, especially where budgets are strained. By delivering measurable improvements to pathology workflows in days, not months, Augnito delivers a fast return on investment and soon pays for itself many times over.
Challenge Augnito – try it. Partner with Augnito
Try the Augnito App or request an evaluation version. Challenge it with the longest most complex medical terminology in a noisy environment and let us know what you think! Talk to us about reselling Augnito, or about its easy integration capabilities. Talk to the growing UK list of Augnito Partners to find out how their customers successfully transferred from legacy SR products to benefiting from this next-gen voice-AI driven speech recognition solution.