How This Startup Is Transforming Healthcare Through Data

How This Startup Is Transforming Healthcare Through Data

The personalization of almost everything continues to raise consumer expectation levels across the world of retail. However, similar technology is already leading a data-driven revolution across the healthcare industry as medical professionals wake up to the possibilities of adopting advanced data analytics.

IBM Watson has already become a household name, but Apixio is probably still under the radar of most people reading this. However, the data science company for health care is playing a significant role in the data-driven revolution that has infected the healthcare industry in a positive way.

With the help of cognitive computing in the cloud; we are starting to analyze massive amounts of data to personalized treatment. The digital health experience is no longer just another buzzword but a concept capable of delivering tangible results.

Try and imagine the ability to compare patients with the same lifestyle, blood type, and lifestyle to offer better healthcare. Could this data also provide a complete understanding of illnesses and the success of future treatments?

Apixio has its sights set on tackling the fragmented landscape to solve these very problems. There is an increasing realization that the only way to make real progress is to break down frustrating silos.

Darren Schulte, the Chief Executive Officer at Apixio, believes with cognitive computing in the cloud; we can analyze massive amounts of data to enable care tailored rather than the traditional one size fits all approach to medicine.

Powered by a cognitive computing platform, Apixio is aiming to extract and analyze previously trapped unstructured medical record data. The long term goal is to deliver unprecedented access to groundbreaking insights learned from unlocking the secrets from the previously scattered data.

After analyzing more than 5.9 million patients’ charts. Apixio’s profiler solution mines medical charts and Medicare chronic condition data to work more efficiently and accurately provide risk scores. But, what problem does it solve?

Traditionally, risk scores are based upon the diagnosis codes provided by physicians on their insurance claims to receive payment for services they provide. Issues often arise when individuals are treated for a condition that is not listed on the diagnosis codes on claim forms.

Despite an on-demand economy across our digital landscape, what typically follows is a draconian process before a claim can be made. A slow retrieval of medical charts for review before an appropriate diagnosis can be completed to secure an accurate risk score is clearly in need of a 21st-century upgrade.

Apixio’s HCC Profiler for commercial is aiming to eradicate this issue by leveraging cognitive computing. It is hoped that these technological advances will dramatically speed up the processing of hospital records and the identification of conditions.

Apixio has already announced a risk adjustment solution to strengthen plans in health insurance exchanges. But, could this also pave the way for data science to play a huge part in the future healthcare and commercial risk?

The success will ultimately be judged on the adoption of advanced data analytics in the healthcare industry. Thankfully, there does seem to be an element of cautious optimism for how technology can improve efficiency. The recording of risk scores to reflect conditions treated for individuals in a timely manner with minimal human intervention certainly seems like a step in the right direction.

An entire overview of patient conditions should also help deliver affordable care by enabling insurers to accurately predict healthcare costs for patients. Eager to find out more, I recently spoke to Darren Schulte the Chief Executive Officer at Apixio on my podcast who revealed how he envisions technology will affect healthcare.

This post is part of our contributor series. It is written and published independently of TNW.

This post is part of our contributor series. The views expressed are the author's own and not necessarily shared by TNW.

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