The future of health care - Tomorrow’s data scientists

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The future of health care - Tomorrow’s data scientists

February 16, 2016
Jeroen Tas
From the January/February issue of HealthCare Business News magazine
Data is a critical player in the success of integrating health care networks, and will be a crucial component in how health care systems address today’s key issues, including a growing aging population and the rise of chronic and lifestyle-related diseases. The future of managing population health truly lies in data-driven health care, focused on performance and outcomes.

Take radiology, for example. Today, there is a vast amount of radiology data available to work with, providing the opportunity to analyze images and associated clinical data to improve patient care — from prevention to diagnosis and treatment. Images are becoming far more sophisticated and accurate, and we’re able to view and quantify the inner depths of the human body.

As we look toward tomorrow, we see the opportunity for health care providers across the continuum to enhance their impact by incorporating richer data sets analyzed by machine intelligence. We are interpreting images through deep learning, while quantifying more data, adding more sources and combining modalities that were once disjointed. So why is this extra perspective important? The answer lies in the richness of contextual data and how we use it.

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Not only are we capturing more data, but we also are gaining more contextual data. By looking at patients longitudinally, clinicians can detect early signs of health deterioration while understanding how their patients’ conditions change. This leads them to determine the effectiveness of specific therapies and treatments, and if additional interventions are needed. When a rich data pool from an entire clinical department or, better still, a network of hospitals is available, and all other longitudinal patient information is transparent and actionable, doctors can compare and contrast patients with similar conditions.

Wearables and electronic medical records (EMRs) also are playing an important role in contextual data, so personal health information — not just clinical — can be factored into a patient’s care routine. We are now getting near-real-time information at the point of care — from mobile ultrasounds to handheld blood test devices. With this growing pool of data points, we know more, which means we can do more. Clinicians can be more precise, delivering better care and more personalized treatments.

But, at Philips, we see the bigger trend in data, where we must not just optimize devices, but also optimize workflows that incorporate multiple data-driven services. With our ever-expanding ecosystem of connected devices, new data sources and increasing usage of EMRs, it’s increasingly difficult for clinicians to see it all, know it all and use it all.

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