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Report Says Cloud Technology Can ‘Optimise Health Outcomes’

Cloud Computing Technology And Online Data Storage For Business

Cloud technology has an important role to play in improving the health and wellbeing of patients, according to a recent report.

The Health Policy Partnerhsip has produced a document entitled “Exploring the evolving role of cloud technology in health”, which looked at how it can transform health systems by sharing patient data.

Dipak Kalra, president of the European Institute for Innovation through Health Data, which supported the report, commented on the use of cloud computing.

He told Digital Health: “Cloud technology is a critical enabler for scaling up the use of health data to optimise health outcomes, improve patient safety, rapidly detect public health concerns and accelerate research into new medicines and medical technologies.”

It was noted the technology enables data access across organisations, leads to more efficient care, encourages a population-based approach to healthcare, enables research that can drive innovation, and supports sustainable health systems.

The report recognised several barriers to the adoption of cloud computing, including a lack of knowledge about the technology, and concerns around security and privacy.

In response to this, HPP said standards should be maintained through collaboration between cloud service providers and users.

It added that all stakeholders, which in the context of healthcare includes patients, “must be engaged in its use to optimise the benefits for individual and population health”.

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AI Set For A Larger Role in NHS Imaging Diagnostics

Blurry Medical Ultrasound Machine With 3d 4d Image In A Hospital

The importance of medical image sharing in helping to provide access to crucial data and help specialists make diagnoses is well known, but it could gain even more significance in an age when the capacity for images to be used effectively in identifying conditions is increasing.

A key factor in enhancing diagnostic capacity is the use of artificial intelligence (AI). While there are ways in which this technology has been seen by some as a threat to humanity, the Department for Health and Social Care has just announced £21 million of ringfenced funding to roll out AI across the NHS.

The announcement listed cancers, strokes and heart conditions as examples of the sort of things AI can help identify.

AI is available in 86 per cent of stroke network settings, but the government is committed to increasing this to 100 per cent by the end of 2023.

Health secretary Steve Barclay said: “AI tools are already making a significant impact across the NHS in diagnosing conditions earlier, meaning people can be treated more quickly.”

Adding image-sharing services using facilities like the Cloud can maximise this benefit, by helping get the information from more accurate and speedy diagnoses to those who need it as fast and efficiently as possible. This will enable the right treatment to begin quickly.

A separate announcement will provide a further boost to those who may be suffering from lung cancer, with the full roll-out of a new £270 million targeted lung cancer screening programme being launched.

This will focus on people aged between 55 and 74 with a history of smoking, who may benefit from having the condition spotted at an earlier stage.

It will involve nearly a million scans a year and is expected to provide a potentially life-saving early diagnosis for around 9,000 cancer patients.

The move follows an initial phase in which 76 per cent of the lung cancers detected were at an early stage.

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AI Shown To Improve Diagnosis Of Inherited Retinal Disease

Doctor Holding Red Heart In Hands. Healthcare And Medical Concep

Artificial intelligence (AI) has been used a lot to support the medical sector, including helping to diagnose inherited retinal diseases (IRD).

The European Society of Human Genetics (ESHG) has revealed researchers have used AI to develop a system that can identify the cause of IRDs from scans of the retina, improving the efficiency of testing.

This will also enable more centres to provide tests to those exhibiting symptoms.

Group leader at the UCL Institute of Ophthalmology and Moorfields Eye Hospital Dr Nikolas Pontikos revealed the development of Eye2Gene.

“Identifying the causative gene from a retinal scan is considered extremely challenging, even by experts. However, the AI is able to achieve this to a higher level of accuracy than most human experts,” he stated.

Eye2Gene could eventually become part of a standard retinal examination. While it would likely start out as an ‘assistant’ to provide a second opinion, it may eventually be used by itself as a diagnostic tool.

Speaking at the annual conference of the ESHG on June 10th, Dr Pontikos added: “We hope that AI will help patients and their families by making specialist care more efficient, accessible, and equitable.”

IRDs are caused by defect genes, which can result in the deterioration of eyesight, even leading to blindness.

Currently, IRDs are diagnosed by an ophthalmologist, who looks at the patient and family history, and conducts an eye examination.

To find out more about medical imaging storage, get in touch with us today.

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NHS Pilots Artificial Intelligence To Cut Missed Appointments

Missed hospital appointments cost the NHS millions of pounds every year, which is why it is piloting artificial intelligence (AI) software to reduce the number of incidents.

AI will use algorithms, data, and external insights, such as weather, traffic, and jobs, to determine the likelihood of a missed appointment, so that a booking is arranged for a more convenient time. This will lower the probability of the patient missing their slot.

It also provides back-up bookings, so no appointment is wasted, increasing efficiency of the health service.

Chief executive of the NHS Amanda Pritchard said: “[The new pilot] shows the NHS testing the latest technological advancements to address the real world challenges we face.”

She added: “The system will help ensure patients receive ‘smart’ appointments, that are convenient and fit into people’s increasingly busy lives.”

The scheme is being trialled in Mid and South Essex NHS Foundation Trust, where there is an average did not attend (DNA) rate of eight per cent. Data will be collected and analysed to determine whether the DNA will improve with the AI.

It is hoped an extra 80-100,000 patients will be able to be seen at the Trust every year, as a result of the technology.

Every year, eight million appointments are missed, costing the NHS around £1.2 billion.

The new software could help the health service reduce its huge backlog of patients waiting for appointments. It was recently revealed that 39,903 people are currently waiting more than 18 months for a referral.

If this pilot is successful, AI technology could become more commonplace in the NHS, from being used as a diagnostic tool to remote radiology reporting.

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How AI Is Used In Medicine

Artificial intelligence (AI) is an incredible tool that can achieve some amazing results if used correctly. Perhaps one of the most groundbreaking uses for AI is in medicine and advancements could change the world of medicine forever.

AI is relevant to so many different aspects of life and the general public even has access to it at this point. There are many different versions of AI out there and tailoring them to be used within the medical sphere has been incredibly helpful.

One way we can utilise AI in medicine is to help with detecting and diagnosing diseases. AI can be used to minter and observe patients around the clock. This helps to reduce the need for doctors and nurses to be constantly monitoring patients.

AI is also able to collect information about the patient and therefore detect issues as they arise, meaning doctors can be alerted to signs of disease early and help to treat it. This constant monitoring of patients could help in catching issues earlier and therefore treating them better.

AI can also be used in clinical imaging. AI is able to analyse images and locate and detect signs of various conditions such as cancer.

This is a great advancement as AI is able to study these images far quicker than a human would be able to, which can help in speeding along the process of imaging analysis and therefore diagnosis.

Another way AI can be used in medicine is by improving the efficiency and organisation of clinical trials. AI is able to quickly store and analyse medical results and can find information far quicker, meaning clinicians wouldn’t have to spend as long searching for the correct results and medical code.

AI is also able to detect similarities in results far quicker and compile the similarities and differences in patient responses to new drugs and vaccines meaning trials could be completed much more quickly and efficiently.

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Rounded Heart Images Could Indicate Cardiovascular Disease

Medical images of rounded hearts could be an early sign of cardiovascular disease.

The National Institutes of Health revealed research in the journal Med that suggests analysis of pictures of the shape of hearts could become a diagnostic tool.

David Ouyang, co-corresponding author or the study and a Smidt Heart Institute of Cedars-Sinair cardiologist, said: “These findings might allow physicians to gain greater clinical intuition on how patients are likely to do at a very rapid glance.”

The scientists used the shape and measurements of heart chambers, as well as anatomical changes, to determine a heightened risk of cardiomyopathy or other heart ailments.

They used machine learning and big data for their study, looking at the UK Biobank, which has clinical and genetic information on around half a million people. The researchers examined 38,000 participants who had normal MRI images of their hearts and made a correlation with those who went on to develop heart diseases based on subsequent medical records.

They discovered that those who had increased cardiac sphericity had a greater chance of future heart problems. There was also a link between the genetic drivers for heart roundness and cardiomyopathy.

Using deep-learning analysis, they determined that intrinsic heart muscle disease resulted in cardiac sphericity.

Mr Ouyang added: “Just as we’ve previously known that a bigger heart isn’t always better, we’re learning that a rounder heart is also not better.”

More data taken from medical imaging storage is required for greater analysis, according to the scientists, including ultrasound images instead of MRI screenings to see if these confirm what they have found already.

If further research can be carried out, this could help the 7.6 million people living with heart and circulatory diseases in the UK. It may also help to reduce the number of heart disease-related fatalities from one person every three minutes.

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Genomics England Uses Medical Imaging For Cancer Research

Brain Disease Diagnosis With Medical Doctor Seeing Magnetic Reso

Genomics England has revealed it will enhance its cancer research programme by accessing a medical image storage system.

The organisation, which looks at genetics to find causes of diseases and create new treatments, will use the technology in conjunction with NHS data for its multimodal cancer research platform, Digital Health reported.

Director of clinical data and imagine and Caldicott Guardian for Genomics England Dr Prabhu Arumugam said: “The imaging system is already a very recognisable interface in NHS clinical settings, but we are using it in new ways.”

It was added: “It will help us to harness imaging that we can then match to our genomic data, whilst de-identifying data to ensure confidentiality.”

It will transport images from NHS trusts that are participating in the programme, enabling Genomics England to find patterns in genome sequencing, pathology and radiology data.

This will provide a better understanding of cancers, which could help with the development of treatments. It could also lead to the creation of cancer-targeting artificial intelligence (AI) in the future.

Dr Arumugam stated the cloud-based research platform will enable more people, other than bioinformaticians, to access data regarding genomics, pathology and radiology.

Around 250,000 pathology images and 200,000 radiology scans from 30 NHS Trusts will be included in the data acquisition.

After these are matched with genomics information, the researchers will be able to investigate what the markers are for cancer, helping with diagnoses and treatments.

This comes after Genomics was given £175 million in funding for the research of rare genetic conditions in newborns, which it hopes will lead to earlier detection and quicker access to medical intervention.

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How Stable Diffusion Could Advance Medical Imaging

medical imaging doctor examining screen

As the use of medical imaging grows, the work involved can be more specialised and means that getting enough training to help make the best use of medical imagining solutions is a challenge.

However, new developments may help make this task easier, including a new innovation that follows on from one devised and launched only last year.

As Venturebeat reports, the launch last August of Stable Diffusion, a text-to-image foundational model, by Stability AI, prompted an idea from Stanford University radiologist Christian Bluethgen. He asked whether in fact it was possible to combine a genuine medical need with the creating of high quality images using basic text prompts.

The result was his collaboration with Stanford Graduate student Pierre Chambon, a mathematical and computational engineering researcher, which led to a study designed to establish the capacity of stable diffusion to generate X-rays. To their delight, they found it achieved this task very well.

All this, Mr Bluethgen, will help with the training of medics who might otherwise see very few scans relevant to their specialist area. He observed: “When you are working in a setting with scarce data, your performance correlates with experience – the more images you see, the better you become.”

Such a development may be just one indication of how better use of data technology is enabling medical imaging to be used with increasing effectiveness as a diagnostic tool, with improved training further boosting the capacity of specialists to identify medical problems when they emerge.

A further development in X-ray imaging may have emerged at the University of New South Wales in Sydney. In a paper published in the journal Nature Communications, researchers have revealed how a new algorithm has been devised that can enhance images of hydrogen fuel cells. It notes that the very same technique could be used to improve medical imaging.

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Could Cloud Computing Lead To Health Equity?

world cloud medical

Cloud computing in healthcare could help balance the disparity between medical services around the world.

Over the last few years, use of cloud services has increased in the healthcare sector. They have advanced to store medical images and data, while artificial intelligence (AI) is being used more frequently to enhance treatments, diagnostic tools, and preventative procedures.

Dr Rowland Illing, director and chief medical officer, International Public Sector Health at Amazon Web Services (AWS), told ITP that cloud computing can improve access to technology. This makes it easier for healthcare providers with lower budgets to benefit from AI tools.

“The true potential of cloud computing in healthcare lies in its ability to democratise access to critical data, advanced tools for machine learning and artificial intelligence, and to make these resources accessible to researchers, developers, and pharmaceutical companies globally,” he stated.

As cloud computing does not require on-premises computer resources and large investments in advanced technology, it means it is more accessible for everyone.

According to the World Health Organization health equity is only achieved when everyone is able to “attain their full potential for health and wellbeing”.

It revealed nearly a third (30 per cent) of the global population are still unable to access essential health services. This was exacerbated by the Covid-19 pandemic, which caused disruption in health services in 92 per cent of nations.

The Universal Health Coverage (UHC) data stated that nearly two billion people currently face “catastrophic or impoverishing health spending”.

To find out more about cloud based medical imaging and how it can improve healthcare data storage in your team, give us a call today.

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How Cloud Storage Cost Savings Can Boost NHS

It will come as news to nobody that the NHS faces a tough winter. Fears of a ‘twindemic’ of high rates of Covid and flu infections, the backlog of operations caused by the pandemic remains and pay strikes among nurses and ambulance staff all speak of a health service under severe pressure.

Other outstanding cost concerns faced by the NHS include the high cost of agency staff, with doctors paid as much as £5,234 for a single shift according to data uncovered by the Labour Party in a Freedom of Information request, while many hospitals have outstanding maintenance issues as well.

The question of just how much money could be needed to fix buildings, solve shortages of resources and settle pay disputes, alongside the question of where the money will come from, arises at a time when the UK is believed to have begun a protracted recession.

Never has it been more important for cost-efficiency and the elimination of waste to be brought to bear on the NHS. That is where the low cost of cloud based medical imaging may be critical when keeping patient scans and other records, enabling easy access without high expense.

As Tech Radar reports, cloud storage specialists Backblaze have noted that hard disk drive prices have been falling, with prices now set to fall to as low as US$0.1 per GB of data. This compared to $0.11 in 2009.

Not only is this a rare example of something getting cheaper in a world beset by inflation, but also offers a considerable cost-saving opportunity to the NHS. While this alone will not solve all the problems, it will certainly help, not least by delivering better outcomes for patients, which is the whole point of the service in the first place.

While the NHS faces many challenges, it seems that at least the services the staff will use could include some cases of very low cost.

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