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Today’s radiologist, tomorrow’s data scientist

Playing an essential role in an integrated healthcare network

 

 

As the RSNA Annual Meeting has shown, it’s evident that radiologists are analyzing their patients on an entirely different level than a decade ago. Developments in digital technology are greatly transforming the role radiologists play in a health system. Radiology is now viewed less as a department in a hospital and more as an essential part of an integrated healthcare network.

A radiology department

 

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 diagnosis. Images are becoming far more sophisticated and accurate, and we’re able to view and quantify the inner depths of the human body.

 

However, as we look toward tomorrow, we see the opportunity for radiologists 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. We are going deeper and deeper into human physiology. With digital pathology we drill-down and analyze patients at a cellular level. We can even learn how these cells are “wired” by analyzing their DNA. So, why is all of this extra perspective important? The answer lies in the richness of contextual data and how we use it.

Philips’ Digital Pathology solution

 

Importance of Contextual Data in Healthcare

Not only are we capturing deeper data, but we also are gaining more contextual data. Oncology provides an excellent example of where the richness of data plays a major role in treatment, and we’ve seen significant progress in how contextual data helps diagnose and support patients to propose the best therapy.

 

For example, by looking at patients longitudinally, radiologists can detect early signs of health deterioration while understanding how their patients’ conditions change. This leads them to determine how effective specific therapies and treatments are, and if interventions are needed. When a rich data pool from an entire radiology department or, better still, a network of radiologists is available and all other longitudinal patient information is transparent and actionable, clinicians can compare and contrast patients with similar conditions.

 

This greater transparency and context leads to increased visibility for radiologists, more personalized and effective treatment options for oncologists and – most importantly – better results for patients. Leveraging richer data also is giving them more information about specific types of illnesses, which can then be added to the overall available body of knowledge for caregivers and clinicians around the world.

 

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. In addition, we are getting near-real-time information at the point of care – from mobile ultrasounds to handheld blood test devices – which gives us more medical data. 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.

Philips Lumify mobile ultrasound

Handheld blood testing[1] for point of care diagnostics ( [1]In development. The shown device is currently not available for sale.)

 

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 current, ever-expanding ecosystem of connected devices, new data sources and increasing usage of EMRs, it has become increasingly difficult for radiologists to see it all, know it all and use it all. Thus, it is imperative to have it all linked to a core informatics data and device platform – like the Philips HealthSuite digital platform – so that we can expose the disparate data points to algorithmic intelligence to construct a more comprehensive picture. However, this presents both new challenges and new opportunities for radiologists

 

Intersection of Radiology and Data Science

The growing amount of information available coupled with advancing technology is directly empowering radiologists, creating a new front in the field: radiologists as clinical data scientists. As cancer rates unfortunately continue to rise and clinical decisions become more complicated, radiologists can play a bigger role.

 

Complex disease patterns require stitching together fragmented pieces of information across many data sets to create a better picture. Radiologists capture more longitudinal data, while at the same time going deeper by quantifying imaging data and combining this with cell level data (using digital pathology) and even deeper with genomics, thereby creating a more precise diagnosis.

 

In addition, each observation, patient case and treatment can add to the cumulative body of knowledge: data is aggregated, analyzed and compared for insights. For radiologists to meet the challenge, we must provide the tools that amplify their expertise through advanced algorithms and machine-learning capabilities. Take for instance Philips’ IntelliSpace Portal 8.0, which just launched at RSNA. Here you have an advanced data-sharing, analytics and visualization platform that allows the use of data-algorithms. What once took an almost insurmountable amount of time, resources and careful analyses is now available through a few clicks. It is a prime example of how the access to a wealth of data – dense, deep and wide – is now being realized to create a quantified patient.

Quantitative tumor viability (qEASL) (For research use only)

 

All of this data collection and integration is great, but it’s irrelevant if it doesn’t support clinical decision-making or improve patient outcomes. Data about an individual’s life, activity and potential health risks are all critical pieces of the puzzle as well, but they must be captured and analyzed within the context of clinical care. Monitoring a patient at home to support their recovery and ensure that caregivers can intervene when they see a change allows us to influence and improve care across the health continuum.

 

Specifically for radiologists, the wealth of data available in our burgeoning connected-care environment only takes us so far without a comprehensive data analytics solution like IntelliSpace Portal 8.0. Using a multi-modal approach that applies machine intelligence, IntelliSpace 8.0 supports the expanding role of radiologists as data scientists, to be more productive parts of a multidisciplinary care team.

 

Being efficient in identifying the right diagnosis is no longer enough – transforming the diagnostic, treatment and follow-up process is truly the next frontier in healthcare. Rich data sources can point the health trajectory for patients in the right direction from diagnosis to treatment to monitoring to prevention.

 

Radiologists are the healthcare data scientists of the future – the wielders of powerful algorithms – that mine and combine data to paint a quantified patient picture. They are a key player in a multidisciplinary team that helps clinicians make more intelligent and personalized decisions.

 

Philips’ Radiology Solutions will be available for consultation at booth #6736 at the RSNA Annual Meeting through Dec. 4 in Chicago, Ill. Follow @PhilipsLiveFrom on Twitter or visit www.philips.com/rsna for more information on Philips’ presence at #RSNA15.

Jeroen Tas

CEO, Healthcare Informatics Solutions and Services Philips

Jeroen Tas has more than 30 years of global experience as an entrepreneur and senior executive in the financial services, healthcare and information technology industries. Currently he is the CEO of the Philips Healthcare Informatics Solutions and Services Business Group.

 

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