Analyzing healthcare's big data of real-world evidence

None of the above is fiction, but an emerging reality - and they are the tip of the iceberg of innovations and discoveries emerging from an unexpected source: Big Data. Like so many other medical advances today, these are examples of how hugely powerful computer processing and analyzing vast amounts of data are changing the way healthcare is conducted and administered.

“Genome testing of cancer is critical because the disease is driven by genetic mutations,” said Ya’ara Goldschmidt, leader of IBM’s Healthcare Analytics work at the company’s Research lab in Haifa, Israel. “That’s why a great deal of the genomics work that has been done in the past decade focuses on the sequencing of this particular disease.” 

Goldschmidt was speaking at the conclusion of two days of workshops discussing clinical genomic analysis and medical informatics innovations that brought together a full mix of academia, industry, health providers and policymakers from Israel’s healthcare ecosystem, as well as from abroad.

“With the enormous amounts of genomic data available today, the challenge is to analyze it methodically to better understand and control disease, ultimately providing treatment recommendations at the point of care. With the technological breakthroughs of the last few years and sequencing costs dropping rapidly, today we can do things we couldn't have imagined just a decade ago,” said Michal Rosen-Zvi, Senior Manager of Analytics at IBM Research - Haifa.
Recent years have seen a dramatic increase in the availability of data collected in the practice of healthcare. Analyzed properly, these data (known as real world evidence or RWE) are transforming healthcare for everyone, from providers to practitioners to patients. IBM's Haifa lab is playing a leading role – both in the analysis itself, and in bringing players together to engage in dialog and the exchange of ideas.

Scientists at the lab have developed decision support solutions that blend cloud, and mobile technologies with advanced analytics to gather, manage, analyze, and visualize data on different kinds of cancer and disease.  These technologies include machine learning to infer the complex  associations between genetic factors, demographic data, disease progression, and treatment options.

“Even the policymakers are conscious of the tremendous benefit we can derive from data analysis,” Rosen-Zvi said. “The legal and ethical obstacles that obstructed progress are slowly being resolved, and this is allowing us to make headway. The fact that the head of Israel’s Ministry of Health attended the event illustrates the legislature's awareness.”

A keynote presented by Isaac Kohane of Harvard Medical School explained how data analysis of patients “bouncing around” (or constantly checking into hospitals with a variety of issues) a health system can pinpoint likely domestic abuse. He also explained how medical informatics could have identified the dangers of the painkilling drug Vioxx by collecting information about heart attacks from different hospitals earlier on. The drug was removed from the market after clinical studies.

“It's imperative that we improve data sharing among all partners in our health systems,” said IBM's Ranit Aharonov, who organized the Genomic Analysis Workshop with the Safra Center for Bioinformatics at Tel Aviv University. “Technological barriers exist, as well as legal, and of course, commercial. Drug companies, for example, spend enormous sums on research so they're not enthusiastic about sharing their data freely. But even they are recognizing that improved data exchange is for their benefit too.”

Among the many presentations, Fresenius Medical Care, the world's largest integrated provider of products and services for people undergoing dialysis, explained how they gather data about alternating-day visits of their dialysis patients. Dozens of factors in the data are analyzed and processed, then guidelines are provided to the attending physician during each subsequent patient visit. Studies showed that when physicians adhere to the guidelines, patient outcome is improved.

Prof. David Sidransky of Johns Hopkins University explained how human cancer cells are transferred to a mouse - a process called xenografting - allowing genetic testing to be conducted without harming the patient. When the correct formula is found to counter that particular cancer, it can be administered to the patient. 

“In past gatherings, we'd talk about what it will be possible to do in the future,” Rosen-Zvi said. “But these two days showed us that the future is already here. The data is now available and we've begun using it to improve healthcare for everyone.”

Many of the current IBM healthcare advances address chronic care and cancer because of its potential impact on society.  With new possibilities for genomic sequencing, cognitive computing and other analytics technologies, IBM is providing decision support to enable more reliable diagnosis and care plan, including treatment options. The company is also working with healthcare partners across the globe on exciting technologies for medical training and other chronic-care areas, such as diabetes, heart disease and mental health.

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