May 17, 2020

The five key principles for building a patient-centric data-sharing platform

Digital health
healthcare services
Health IT
Saduf Ali-Drakesmith, EMEA Hea...
4 min
Enter any modern hospital and you’ll find that most specialist departments still operate a mixture of paper records and proprietary data storage syste...

Enter any modern hospital and you’ll find that most specialist departments still operate a mixture of paper records and proprietary data storage systems. Data may be shared, but it’s the clinician that’s doing the sharing, not a system, and this inevitably means that practitioners only have a partial view of a patient’s records.

At the very least, having part of a patient’s data trapped in ‘information silos’ where it is unavailable in the EMR is inefficient, hampering clinical decision-making and introducing variations in the standard of care across the organisation. In the worst-case scenario, crucial patient information could be unavailable to clinical staff in an emergency, despite the hospital being in possession of those facts somewhere in an outmoded filing system.

With the advent of the Internet of Things (IoT), these problems are being compounded by automated systems that only function effectively if they have access to the most up-to-date details. Indeed, there is a risk that without an appropriate unifying platform, the core data derived from connected devices will simply create further data silos, unavailable to the wider healthcare ecosystem.

One solution to such fragmentation is a standards-based clinical visualisation system built around the clinician, to unite disparate data sources in one place. It is more efficient, more productive and, most importantly, improves decision making and reduces unnecessary variations in care.

Unfortunately, there is frequently resistance to further technology by staff who are wary of disruptive IT projects that often don’t serve their needs. That shouldn’t be the case. With these five steps, every healthcare organisation can ensure the smooth delivery of an effective patient-centric data sharing platform.

1. Change the Culture

Professionals are naturally wary of the introduction of complex new processes, and sceptical of the promised benefits of new technology. But they do want a system that works and facilitates the care they provide. This means a system designed around their needs, working patterns and devices —rather than built to a management concept to which they are then forced to adapt.

That’s why introducing a new system within a clinical setting should be viewed as more than a technical challenge: the whole programme should be about developing new ways of working that are designed around the clinician, and all stakeholders should be closely involved in the development process. This doesn’t just ensure a better end product, but also encourages a cultural change throughout the organisation so that technology is viewed as an enabler of excellence, rather than a nuisance.

2. Focus on outcomes

A clear understanding of how and why clinicians use information sharing systems is essential in order to pinpoint the desired effect on the clinical outcome of a project. That outcome should then be the key force driving implementation.

 For example, when Hyland Healthcare developed a zero-footprint viewer and streaming technology to improve the diagnosis of stroke patients, it worked with clinicians to understand their working practices and needs. What emerged was a remotely accessible system to view CT scans, whereby clinicians could use their mobile phones to securely access data, and make an immediate decision to thrombolyse or not — potentially saving lives.  By focusing on the clinical outcomes, and understanding the way clinicians work, a system was devised that ultimately benefited patients.

3. Invest in standards-based systems

Radiology departments across the world have embraced PACS as the primary means for storing and viewing DICOM medical images. While based on the DICOM standard, many of these systems wrap the DICOM asset in a proprietary code set that makes the image and study difficult to share with a PACS from a competing vendor. Therefore, costly image migrations and CD/DVD image exchanges have become the norm.

 Furthermore, the world of medical imaging consists of much more than DICOM images in today’s healthcare environment. Images captured in specialty departments ranging from dermatology to gastroenterology to pathology come in many formats, including JPEG, TIFF and MP4. Hospitals need to invest in truly vendor neutral platforms that can centrally manage a wide variety of images in their native formats to simplify image exchange and collaboration.

4. Think big, but start small

While it is tempting to embark on a huge project where potential savings or improvements can be expected, it’s wiser to exercise caution and start small. There are untold numbers of failed projects that promise much, but fail to deliver the outcomes.

 New systems should be thoroughly trialled, starting with teams where there is the highest chance of success, rather than the highest potential rate of return. As lessons are learned, improved versions can be rolled out to the wider enterprise.

5. Appoint a clinical champion

Every project needs a clinical champion who can bring the medical perspective to the table, providing representation for stakeholders and advising on patient interests too. You will need to choose someone who can remain enthusiastic and committed to the project, is data driven, and can help define what constitutes high-quality care, as well as what is required to deliver it.

Credit: Hyland Health

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Jun 18, 2021

Skin Analytics wins NHSX award for AI skin cancer tool 

2 min
Skin Analytics uses AI to detect skin cancer and will be deployed across the NHS to ease patient backlogs

An artificial intelligence-driven tool that identifies skin cancers has received an award from NHSX, the NHS England and Department of Health and Social Care's initiative to bring technology into the UK's national health system. 

NHSX has granted the Artificial Intelligence in Health and Care Award to DERM, an AI solution that can identify 11 types of skin lesion. 

Developed by Skin Analytics, DERM analyses images of skin lesions using algorithms. Within primary care, Skin Analytics will be used as an additional tool to help doctors with their decision making. 

In secondary care, it enables AI telehealth hubs to support dermatologists with triage, directing patients to the right next step. This will help speed up diagnosis, and patients with benign skin lesions can be identified earlier, redirecting them away from dermatology departments that are at full capacity due to the COVID-19 backlog. 

Cancer Research has called the impact of the pandemic on cancer services "devastating", with a 42% drop in the number of people starting cancer treatment after screening. 

DERM is already in use at University Hospitals Birmingham and Mid and South Essex Health & Care Partnership, where it has led to a significant reduction in unnecessary referrals to hospital.

Now NHSX have granted it the Phase 4 AI in Health and Care Award, making DERM available to clinicians across the country. Overall this award makes £140 million available over four years to accelerate the use of artificial intelligence technologies which meet the aims of the NHS Long Term Plan.

Dr Lucy Thomas, Consultant Dermatologist at Chelsea & Westminster Hospital, said: “Skin Analytics’ receipt of this award is great news for the NHS and dermatology departments. It will allow us to gather real-world data to demonstrate the benefits of AI on patient pathways and workforce challenges. 

"Like many services, dermatology has severe backlogs due to the COVID-19 pandemic. This award couldn't have come at a better time to aid recovery and give us more time with the patients most in need of our help.”

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