Jun 29, 2021

Clinithink's AI cuts diagnosis time for newborn baby

AI
Genomics
geneticdisease
diagnostics
3 min
Clinithink's AI cuts diagnosis time, saving a baby's life
AI technology from Clinithink helped to diagnose a rare disorder in a new-born baby, saving its life

Applications of AI in healthcare keep growing - the most recent developments have included the use of algorithms to detect cancerous skin lesions, and to identify geographical areas where there may be a high prevalence of poor mental health among the population. 

Now comes news from Clinithink, a healthcare AI specialist, whose software helped to identify a rare genetic disorder in a critically-ill newborn baby.  Clinicians from the American Rady Children’s Institute for Genomic Medicine (RCIGM), have published a letter in the New England Journal of Medicine (NEJM) describing how they were able to make this diagnosis.  

The RCIGM team used AI technology as part of their Whole Genome Sequencing (WGS) method. This included the use of CLiX, AI software developed by Clinithink to give healthcare professionals human insights. 

The five-week old baby had been born healthy, but became seriously unwell and was admitted to the neonatal intensive care unit at Rady Children’s Hospital-San Diego. 

Tests showed he had encephalopathy, a condition affecting the brain that can be caused by a variety of issues, from infections like meningitis to brain tumours. 

As the child’s condition deteriorated and he had multiple seizures, the clinical team performed genome sequencing to assess whether he had an underpinning genetic disease. Given that the child's brain was affected, fast diagnosis and prompt treatment was crucial to prevent long-lasting neurological damage, or even death.  

The team used CLiX to carry out deep phenotyping, a type of analysis of a patient’s characteristics and clinical findings to compare with over 12,000 phenotypes known to be associated with over 7000 rare diseases. This complements genomic data and is essential to confirming a diagnosis, however it's usually done manually and can take hours if not longer, even when done by highly trained geneticists. 

CLiX enabled this to be done in one minute, helping the team to reach a diagnosis in a total of 13.5 hours. The disease they identified was thiamine metabolism dysfunction syndrome 2 (THMD2), a rare disorder that can be treated effectively with vitamin supplements if diagnosed early. 

Treatment was started, and the child was able to leave the hospital three days later; he is now thriving at seven months of age. 

“Naturally we are absolutely delighted that the team at RCIGM have been able to deliver such a profoundly important outcome for this patient using their pioneering approach to rapid rare disease diagnosis which includes CLiX focus" said Chris Tackaberry, CEO and Co-founder at Clinithink of the outcome. 

"As healthcare technology specialists it is incredibly inspiring for us to know that the software we develop can help to make this kind of difference at the clinical sharp end. It’s why we come to work" he added. 

In addition to RCIGM, Clinithink's AI technology is being used at the UK's Barts Hospital and Newcastle Upon Tyne Hospitals NHS Foundation Trust.  

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Jul 25, 2021

Getting ready for cloud data-driven healthcare

Data
healthcare
CloudComputing
Technology
 Joe Gaska
4 min
Getting ready for cloud data-driven healthcare
 Joe Gaska, CEO of GRAX, tells us how healthcare providers can become cloud-based and data-driven organisations

As healthcare continues to recognise the value of data and digital transformation, many organisations are relying on the cloud to make their future-forward and data-centric thinking a reality. In fact, the global healthcare cloud computing market was valued at approximately $18 billion and is expected to generate around $61 billion USD by 2025. 

At the forefront of these changes is the rapid adoption of cloud-based, or software-as-a-service (SaaS), applications. These apps can be used to handle patient interactions, track prescriptions, care, billing and more, and the insights derived from this important data can vastly improve operations, procurement and courses of treatment. However, before healthcare organisations can begin to dream about a true data-driven future, they have to deal with a data-driven dilemma: compliance. 

Meeting regulation requirements

It’s no secret that healthcare is a highly regulated industry when it comes to data and privacy – and rightfully so. Patient records contain extremely sensitive data that, if changed or erased, could cost someone their life. This is why healthcare systems rely on legacy technologies, like Cerner and Epic EHRs, to manage patient information – the industry knows the vendors put an emphasis on making them as secure as possible.

Yet when SaaS applications are introduced and data starts being moved into them, compliance gets complicated. For example, every time a new application is introduced into an organisation, that organisation must have the vendor complete a BAA (Business Associate Agreement). This agreement essentially puts the responsibility for the safety of patients’ information — maintaining appropriate safeguards and complying with regulations — on the vendor.

However, even with these agreements in place, healthcare systems still are at risk of failing to meet compliance requirements. To comply with HIPAA, U.S. Food and Drug Administration 21 CFR Part 11 and other regulations that stipulate the need to exercise best practices to keep electronic patient data safe, healthcare organisations must maintain comprehensive audit trails – something that gets increasingly difficult when data sits in an application that resides in the vendor’s infrastructure.

Additionally, data often does not stay in the applications – instead healthcare users download, save and copy it into other business intelligence tools, creating data sprawl across the organisation and exposing patient privacy to greater risk. 

With so many of these tools that are meant to spur growth and more effective care creating compliance challenges, it begs the question: how can healthcare organisations take advantage of the data they have without risking non-compliance?

Data ownership

Yes, healthcare organisations can adhere to regulations while also getting valuable insights from the wealth of data they have available. However, to help do this, organisations must own their data. This means data must be backed up and stored in an environment that they have control over, rather than in the SaaS vendors’ applications.

Backing up historical SaaS application data directly from an app into an organisation’s own secure cloud infrastructure, such as AWS or Microsoft Azure, makes it easier, and less costly, to maintain a digital chain of custody – or a trail of the different touchpoints of data. This not only increases the visibility and auditability of that data, but organisations can then set appropriate controls around who can access the data.

Likewise, having data from these apps located in one central, easily accessible location can decrease the number of copies floating around an organisation, reducing the surface area of exposure while also making it easier for organisations to securely pull data into business intelligence tools. 

When healthcare providers have unfettered access to all their historical data, the possibilities for growth and insights are endless. For example, having ownership and ready access to authorised data can help organisations further implement and support outcome-based care. Insights enabled by this data will help inform diagnoses, prescriptions, treatment plans and more, which benefits not only the patient, but the healthcare ecosystem as a whole. 

To keep optimising and improving care, healthcare systems must take advantage of new tools like SaaS applications. By backing up and owning their historical SaaS application data, they can do so while minimising the risk to patient privacy or compliance requirements. Having this ownership and access can propel healthcare organisations to be more data-driven – creating better outcomes for everyone. 

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