May 17, 2020

Health start-up Medial EarlySign is utilising machine learning to support diabetic patients

EHR
Technology
Technology
EHR
Catherine Sturman
2 min
machine learning (Getty Images)
Located in Kfar Malal, Israel, healthcare start-up Medial EarlySign has worked to develop a machine-learning solution to provide a long-term solution to...

Located in Kfar Malal, Israel, healthcare start-up Medial EarlySign has worked to develop a machine-learning solution to provide a long-term solution to diabetes patients. The technology will support the ongoing management of diabetes, improve clinical data and provide better patient outcomes.

Recent clinical data has highlighted and identified patients who are most at risk of having renal dsyfunction after just one year. The technology has analysed a number of areas within Electronic Health Records (EHRs), including laboratory tests results, demographics, medication, diagnostic codes and many more, to enable the prediction of those who are most at risk.

By isolating less than 5% of the 400,000-diabetic population selected among the company's database of 15 million patients, the algorithm was able to identify 45% of patients who would progress to significant kidney damage within a year, prior to becoming symptomatic. Kidney problems are one of the most common symptoms of diabetes-related complications.

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"Immense efforts are invested in developing treatment protocols to reduce the number of patients who will develop renal dysfunction due to diabetes," said Dr. Ran Goshen, Medial EarlySign's Chief Medical Officer.

"Medial EarlySign's algorithm can aid decision-makers, drug developers, insurers and providers to better allocate their capped resources and secure preferential clinical outcome as well. This can help reduce the likelihood for diabetes related end stage renal disease (ESRD)."

By leveraging EHR data, medical professionals can widen their clinical knowledge and expertise, redefine the management of chronic diseases, improve patient outcomes and lower healthcare costs.

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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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