Mastering the Big Data Challenge in Cognitive Healthcare

May 4, 2018

Patrick Chain, genomics researcher at Los Alamos National Laboratory, posed a question in a recent blog: What if a nurse could swipe a patient’s saliva and run a quick genetic test to determine if the patient’s sore throat was caused by a cold virus or a bacterial infection? If the test results for bacteria are positive, the patient gets the antibiotics. If the results are negative, the patient is prescribed decongestants and plenty of rest. The use of this genomic information would take the guesswork out of the process – and help to curb the use of unnecessary antibiotics.

The case for genomics stretches far beyond the treatment of irritating sinus infections, though. For example, liquid biopsies, which test for cancer via a simple blood draw – removing the need for invasive surgeries – can have a positive impact on the early diagnosis and effective treatment of various life-threatening forms of cancer. In fact, in addition to colds and cancer, genomics can help to improve treatment for a wide range of diseases from irritable bowel syndrome to Alzheimer’s to Crohn’s disease and more.

The potential is plentiful, but there’s a pitfall. Genomics requires the ability to access, manage and analyze significant amounts of data. Indeed, a whole genome sequence requires the same amount of data storage as 100 feature-length movies or 150 gigabytes of data storage, according to a research report from the Workgroup for Electronic Data Exchange (WEDI).

Therein lies the unfortunate – yet increasingly common – big data rub. While the proliferation of data holds unprecedented potential for healthcare organizations, the need to effectively manage data is emerging as a considerable, if not overwhelming, challenge.

A recent study – the HIMSS Analytics Cognitive Healthcare Study –confirms that the rapid adoption of biomedical advances, artificial intelligence, connected devices, digital pathology, population health, genomics, connected health, and other technologies is contributing to an unprecedented explosion in healthcare data. The HIMSS study finds:

  • Healthcare data is experiencing a 48% annual growth rate that will lead to 2.314 Exabytes of data by 2020
  • If all data in healthcare were loaded onto the memory in a stack of tablets, it would reach 82,000 miles high, one third of the way to the moon
  • Between electronic medical records, digitized diagnostics, and wearable medical devices, the average person will leave a trail of more than one million gigabytes of health-related data in their lifetime.

The mere existence of data, however, is not enough. Instead, healthcare organizations need to leverage modern information technology to transform this proliferation of unwieldly data into actionable information today – and eventually move toward the transformation that could come with cognitive computing models that offer the insight needed to derive even greater value from data assets.

But the truth is, most organizations lack the IT infrastructure, data management capabilities, or skilled resources to truly leverage data in a transformative manner. And healthcare decision-makers understand this. The HIMSS study finds that:

  • Clinicians feel the inability to have a single integrated view of enterprise data is a major weakness at their organizations
  • Nearly 88% of respondents identify the need to improve data access, analysis, and utilization as the top driver for today’s investment in data infrastructure
  • 32% of the respondents marked data management as the #1 priority
  • Analytics, data management, interoperability and connectivity were ranked among the top five IT investment priorities of healthcare providers in 2017

Healthcare leaders are recognizing the need to invest in modern technology that can help them better manage data, integrate information into a single view, empower clinicians to collaborate – and stand ready to take on more advanced initiatives such as cognitive computing in the future. The move will enable a future where organizations will rely upon data to create the cognitive healthcare system that can truly move biomedical research and clinical care to a whole new sphere.

Drawing on results of the study as well as insights from industry thought leaders, the HIMSS Analytics report Modernizing Healthcare Technology for Today’s Needs and Tomorrow’s Possibilities takes a broad look at where the industry stands on this journey toward implementing the modern technology that can expertly handle today’s data challenges while also positioning healthcare organizations to experience transformation and enablement through cognitive computing capabilities.

Read the white paper and learn how IBM is positioned to help accelerate the transformation of the healthcare industry toward this exciting, cognitive future.

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