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Health Technology, Digital Healthcare
Article | September 8, 2023
Since ChatGPT’s launch in November 2022, artificial intelligence (AI) tools have become disruptive to nearly every industry. While there's been controversy about whether AI would benefit the healthcare industry, it has proven to be just as capable in healthcare as in other sectors.
In the medical field, there is reason to believe AI tools may be an even more reliable and useful resource than other sectors. Medical students have been panicking over AI's threat to their career prospects. But as these systems mature, the experts increasingly believe that AI may serve as a counterpart to human medical expertise rather than a threat.
How AI Tools Are Expected to Aid Medical Professionals?
Again and again, as the debate over modern AI tools rages on, we encounter the analogy of the calculator. No one feels threatened by calculators, not even professional mathematicians. Instead of throwing up their hands, math experts embrace the power of these now archaic computerized devices. If the experts are correct, this may be similar to the future of the alliance between AI and humans.
According to the designers and programmers who understand how these systems work as well as how information technology tends to progress, AI can be expected to help the medical profession in the following ways:
Cosmetic Surgery Consultations
One of the farthest-reaching applications we see develop is in consultations for plastic surgery and similar applications. Perhaps one of the easiest aspects to understand is hair-loss consultations. In our practice, we use a device known as HairMetrix, which uses an AI-driven analytical system to help determine what is causing a patient to lose their hair and which treatment options would be the most effective.
Because it is AI-driven, it is fully based on visual scans and is completely non-invasive. Just like this, AI can be used in an abundance of other ways to minimize the use of exploratory surgery and improve healthcare outcomes.
Improved Diagnostics
Artificial intelligence is already helping medical providers deliver diagnoses more quickly. These tools can identify anomalies that might otherwise take human hours or even weeks to identify. This has improved the rate of cancer detection, among other things, which will predictably improve survival rates.
Developing New Pharmaceuticals
The development of new medicines is notoriously slow. Not only is testing a painstaking process, but even seeking FDA approval can take years. AI is expected to help the development of pharmaceuticals through simulation on the molecular level, allowing researchers to see how the active mechanisms in a drug will work in the body.
Improved Administrative Efficiency
In the medical field, administrative tasks are notoriously slow. It is believed that generative AI will be able to automate many administrative functions and innumerable office chores. It could streamline sorting patient files, accelerate the interpretation of data, and much more.
Patient Access
In an area where information technology is already improving patients' lives, access to medical advice is still a bottleneck in the system. AI tools have the potential to slowly bridge the gap in health disparities. Combined with the power to diagnose, this could dramatically increase the capability of online patient portals.
Of course, this list of anticipated AI capabilities is far from exhaustive. Researchers and medical professionals have high hopes for these tools, and some are already proving to be more than mere speculation.
In a world where AI is reshaping industries at an unprecedented pace, the healthcare sector stands poised to benefit significantly from this technological revolution. From streamlining administrative tasks to revolutionizing diagnostics, the potential of AI in medicine is vast and diverse. As we witness AI-enabled tools like HairMetrix, enhancing the cosmetic surgery consultations and AI algorithms expediting diagnostic accuracy, it's clear that we are only at the beginning of a healthcare transformation that is set to improve patient care, increase survival rates, and revolutionize medical practices.
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Health Technology, AI
Article | July 18, 2023
COVID-19 has been a catalyst for change, with the diagnostics industry taking centre stage and rising to the challenge of a global pandemic. One of the silver linings of this mammoth task has been the unprecedented time and focus dedicated to finding new technologies and solutions within the sector.
The lessons learned from the pandemic now need to be taken forward to improve breast and cervical cancer detection, prevention and treatment across the UK over the coming years.
In the more immediate term, the diagnostics industry, alongside public health leaders, faces a daunting backlog as screening programmes for breast and cervical cancer were put on pause for months. These two life-saving tests have been some of the most overlooked during the pandemic and getting back on track with screening is critical as we start to turn the corner. We believe innovation in diagnostics, particularly artificial intelligence guided imaging, is a key tool to tackle delays in breast and cervical cancer diagnosis.
The scale of the backlog in missed appointments is vast. In the UK, an estimated 600,000 cervical screening appointments were missed in April and May 2020. And an estimated 986,000 women missed their mammograms, of which an estimated 10,700 could be living with undiagnosed breast cancer. It is clear that hundreds of thousands of women have been affected as COVID-19 resulted in the reprioritisation of healthcare systems and resource allocation.
Both cervical and breast cancer screening are well suited for digital technologies and the application of AI, given both require highly trained medical professionals to identify rare, subtle changes visually –a process that can be tedious, time-consuming and error prone. Artificial intelligence and computer vision are technologies which could help to significantly improve this.
What does AI mean in this context?
Before examining the three specific areas where digitisation and AI can help, it is important to define what we mean by AI. It is the application of AI to medical imaging to help accelerate detection and diagnosis. Digitisation is the vital first step in implementing an AI-driven solution – high quality images demand advanced cloud storage solutions and high resolution. The better the quality of the input, the more effectively trained an AI system will be.
The first area where AI-guided imaging can play a role is workflow prioritisation. AI, along with increased screening units and mammographers, has the potential to increase breast cancer screening capacity, by removing the need for review by two radiologists. When used as part of a screening programme, AI could effectively and efficiently highlight the areas that are of particular interest for the reader, in the case of breast screening, or cytotechnologist when considering cervical screening.
Based on a comparison with the average time taken to read a breast screening image, with AI 13% less time is needed to read mammogram images, improving the efficiency with which images are reviewed. This time saving could mean that radiologists could read more cases a day and potentially clear the backlog more quickly.
For digital cytology for cervical cancer screening, the system is able to evaluate tens of thousands of cells from a single patient in a matter of seconds and present the most relevant diagnostic material to a trained medical professional for the final diagnosis. The job of a cytotechnologist is to build a case based on the cells they see. Utilising these tools, we are finding that cytotechnologists and pathologists are significantly increasing their efficiency without sacrificing accuracy to help alleviate the backlog of cervical screening we are seeing in many countries.
Prioritising the most vulnerable patients
Another key opportunity is applying AI to risk stratification, as it could help to identify women who are particularly at risk and push them further up the queue for regular screening. Conversely, it would also allow the screening interval for those women at lower risk to be extended, creating a more efficient and targeted breast screening programme.
For example, women with dense breast tissue have a greater risk factor than having two immediate family members who have suffered from breast cancer. What’s more, dense breasts make it more difficult to identify cancerous cells in standard mammograms. This means that in some cases cancers will be missed, and in others, women will be unnecessarily recalled for further investigation.
A simple way to ensure that those most at risk of developing breast cancer are prioritised for screening and seen more regularly would be to analyse all women on the waiting list with AI-guided breast density software. This would allow clinicians to retrospectively identify those women most at risk and move them to the top of the waiting list for mammograms.
In the short term, to help tackle the screening backlog, prior mammograms of women on the waiting list could be analysed using the breast density software, so that women at highest risk could be seen first.
Finding new workforce models
Being able to pool resources will allow resource to be matched to demand beyond borders. Globally, more than half a million women are diagnosed with cervical cancer each year and the majority of these occur where there is a lack of guidance to conduct the screening programme. The digital transformation of cervical screening can connect populations that desperately need screening to resources where that expertise exists. For example, developing countries in Africa could collect samples from patients and image these locally, but rely on resources in the UK to support the interpretation of the images and diagnoses. Digital diagnostics brings the promise of a ‘taxi-hailing’ type model to cervical cancer screening – connecting groups with resources (drivers with cars) to those who are in need (passengers): this is an efficient way of connecting laboratory professionals to doctors and patients around the world.
It’s going to take many months to get cancer screening programmes up and running at normal levels again, with continued social distancing measures and additional infection control impacting turnaround times. But diagnostic innovation is on a trajectory that we cannot ignore. It will be key to getting cancer screening programmes get back on track. AI is a fundamental piece of the innovation puzzle and we are proud to be at the forefront of AI solutions for our customers and partners.
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Health Technology
Article | September 12, 2023
Global efforts to tackle gender inequality have grown in recent years. But there is still so much to be done. Figures from the United Nations show that outcomes for women and girls continue to lag across a range of issues, including poverty, education, work and health. And according to the World Economic Forum, at the current rate, it will take 108 years to close the gender gap.
Although healthcare is founded in objectivity and science, gender bias is still remarkably common. We wanted to understand more about female perceptions of healthcare, so we undertook consumer research that delved into the experiences of women compared to men. The results pointed to a clear disparity, finding that women are less likely to visit the doctor when they have symptoms of ill health and, in some cases, are taken less seriously when they do seek medical advice.
Women being left behind
According to our research, a significant proportion of British women feel disappointed in the healthcare they receive, with one in five reporting they weren’t taken seriously when presenting symptoms to a healthcare provider. What’s more, a staggering one in four said they are reluctant to seek medical advice at all for fear of wasting a GP’s time. These statistics suggest that, not only are female experiences of healthcare damaging their relationship with clinicians, but they could be eroding confidence in recognising and acting on warning signs and symptoms too.
This sentiment is particularly evident when focusing on cardiac care. One in eight women (13%) feel ignored when presenting symptoms of heart disease to healthcare professionals, compared to just 4% of men. And of UK adults who have received a coronary heart disease (CHD) diagnosis, women experiencing symptoms were 55% more likely than men to visit the doctor multiple times before receiving a referral for further investigation. On top of this, women are five times more likely to receive a false finding from the cardiac stress tests that are traditionally used to assess heart health.
“There does appear to be a gender bias in onward referral to secondary care and for diagnostics in the local area, which is influenced by the attending healthcare professionals’ risk assessment. Traditional teaching has led to gender bias, as we are programmed to attribute a lower level of pre-test probability and risk to females. This may have contributed to a general lack of awareness around cardiovascular health in women. For example, in a survey I carried out among more than 600 female employees working within North West Anglia NHS Foundation Trust, 82% said they didn’t feel informed about their cardiovascular health. Considering participants included some of the most medically informed women in the UK, the results speak volumes about how we view cardiac health among women.”
- Dr Rebecca Schofield, consultant cardiologist at North West Anglia NHS Foundation Trust
These widespread misconceptions around heart disease and heart attacks are often exacerbated by what we see in the media – think of the countless TV stereotypes of male characters clutching their chests and falling to the floor.
But given that CHD is responsible for one in 13 female deaths, it appears that public health efforts have failed to make people aware of the risks for women. It is, perhaps, not surprising then that 42% of women with CHD did not immediately recognise their symptoms as signs of heart disease. In short, women are missing out on time-critical diagnoses and treatment due to a lack of awareness and education among both healthcare providers and the public.
Technologies making a difference
Thankfully, progress is being made to improve healthcare outcomes for women. Innovative technologies are increasingly providing diagnostic solutions that can reduce incidences of human bias and give clinicians greater clarity on the presence or severity of different conditions in their female patients.
For example, AI is already being used to detect diseases such as cancer more accurately. Its adoption is facilitating reviews and translations of mammograms 30 times faster, with 99% accuracy, reducing the need for unnecessary biopsies.
There’s extraordinary potential for AI and healthcare, and it’s something the NHS continues to recognise, most recently with the launch of its Artificial Intelligence Laboratory (AI Lab) and NHS England’s (NHSE) MedTech Funding Mandate. The latter aims to accelerate the uptake of selected innovative medical devices, diagnostics, and digital products to patients.
As part of the NHS efforts, NHSE has mandated the HeartFlow Analysis for use in hospitals across England for patients, male or female, who might otherwise be sent for a cardiac stress test. The HeartFlow Analysis is a gender-neutral technology that takes data from a coronary CT scan of the heart and leverages deep learning (a form of AI) and highly trained analysts to create a personalised, digital 3D model of each patient’s coronary arteries. This then helps clinicians to quickly diagnose CHD and decide the appropriate treatment for patients of any gender. Time spent in hospital is minimised for patients and often layered testing and unnecessary invasive diagnostic procedures can be avoided.
Final thoughts
While AI is helping us tackle gender bias in certain areas such as oncologic and cardiac testing, healthcare professionals are not absolved of responsibility when it comes to confronting this problem. It remains incumbent upon clinicians to recognise unconscious bias that would deter them from referring women or minority patients for much-needed testing.
Outside of the hospital, public health education efforts must expand so that far more of us can recognise shortness of breath, nausea, vomiting, back or jaw pain, and other symptoms beyond chest pain to be indicators of a heart attack in a woman. Knowing what to look for and overcoming personal bias that might lead to these signs being disregarded, may allow us to help one of the more than 100 women who will experience a heart attack in the UK today.
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Healthtech Security
Article | November 29, 2023
NIS2 Cybersecurity Rules Approaching: Is Your Organization Prepared? The EU NIS cybersecurity regulations are evolving for 2024, and if you’re not currently aware of how they’ll apply to your organization, now is the time to get up to speed with the desired requirements. Not only is the directive being tightened, but an extended range of healthcare and related organizations will be added to the list of ‘critical entities’ that must comply. These include certain medical device manufacturers, pharmaceutical companies, and organizations that carry out R&D. The Network and Information Systems (NIS) standards were set up in 2016 to protect essential services – such as water, energy, healthcare, transport, and digital infrastructure – from online cyberattacks. The updated legislation, NIS2, will have stricter rules,reporting requirements, and higher penalties for non-compliance. They will apply to medium-sized and large businesses that operate within one or more EU countries. Those based only in the UK can’t sit back; however, the original NIS regulations will still apply as part of British law. What’s more, a UK version of the rules is coming very soon, and it’s likely that the framework will closely resemble the EU’s. What will the requirements cover? There are a number of cyber risk management measures that all organizations that come under the scope of NIS2 will be required to put in place. For instance, they will need to conduct regular security assessments and risk analyses, adopt incident response and handling plans, and appoint a chief information security officer (CISO), among other obligations. The new directive will streamline and strengthen incident reporting requirements. Entities must notify regulators of any incident that has compromised data or had a significant impact on the provision of their services, such as causing severe operational disruption or financial loss. Applying information system security policies and business continuity plans will form part of the obligations, as will conducting cybersecurity testing and training for all staff. The use of multi-factor authentication (MFA) and encryption, wherever appropriate, will also be mandated. There is plenty of focus within the directive on the cornerstones of cybersecurity best practices particularly, the proper control of administrator-level account credentials, privileged access, and endpoints, all of which are prime targets for attackers. Under NIS2, organizations are being separated into ‘critical’ and ‘important’ entities. It’s important to determine which category yours’ will fall under, as each has different requirements. The third-party threat will also be addressed in NIS2 by pulling in managed service providers (MSPs) to the list of ‘critical entities’, with the aim of keeping digital supply chains secure. MSPs are often granted privileged access to clients’ corporate systems and networks, which creates security risks. What are the consequences of non-compliance? Organizations that come under the regulations’ purview will be subject to random checks, regular security audits, on-site inspections, and off-site supervision. For those found to be in breach, sanctions could include warnings, temporary suspension of certain activities, and temporary prohibition to exercise certain managerial functions. Financial penalties could be as high as 10 million Euros or 2% of an organization’s global turnover, whichever is higher. What steps should healthcare organizations take now? Organizations should take action to establish whether the EU or UK NIS2 regulations will apply to them and what their responsibilities will be. Having identified any gaps in existing cybersecurity processes, policies, and practices, they must determine what changes need to be made to address them. As a priority, they must review their incident response plans and incident management and reporting procedures. It’s also a good idea to begin assessing the security posture of partners and third parties in the supply chain and incorporating relevant security requirements into contracts. Given the framework’s focus on protecting privileged admin accounts, organizations should implement controls limiting the number of staff members with these robust credentials. Implementing privileged access management (PAM) will allow IT to control who is granted access to which systems, applications, and services, for how long, and what they can do while using them. Preparing for the introduction of the EU NIS2 regulations should be considered more than just a compliance exercise. By meeting the strengthened requirements, healthcare organizations will be building a foundation of resilience that protects them, their customers, and the essential services they provide.
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