Machine learning and analytics provider Cloudera is teaming up with health care analytics company MetiStream to launch a new health-focused, machine learning-powered medical records solution for hospital systems and outpatient clinics. Today, the firms jointly announced Ember, a product that “accelerates the time to patient insight” from handwritten clinical notes and other medical data.
Ember, which is built on the backbone of Cloudera Shared Data Experience (the software framework that powers Cloudera Enterprise), ingests genomics, imaging, and electronic health record data and correlates them across patient populations, allowing clinicians to “identify patient risk” and “improve service quality.” It can also merge clinical datasets with genomics information and apply analytics, “cost-effectively” improving genomic research, according to Cloudera.
This year, Cloudera and MetiStream deployed Ember in Rush University Medical Center, a health system comprising four hospitals in Chicago, on Microsoft’s Azure cloud computing platform. With the system in place, Rush was able to digitize 7.2 million clinical notes in less than two days.
“I see [it] as an exciting breakthrough for the future of health care,” Dr. Randall Hawkins, a neurologist at Sharp Rees-Steal Medical Group, said in a statement.
Separately, Cloudera and MetiStream worked with Sharp Healthcare and Sharp Rees-Stealy Medical Group to process a 10-year archive of patient notes and medical records. Thanks to Apache Spark and a natural language processing engine that transcribes clinical terms to ontology codes, they were able to develop a system that extracts, processes, stores, and analyzes clinical text data. Better yet, it’s searchable — clinicians at Sharp can sift through the notes for any text, phrase, term, acronym, or code, and get results in milliseconds.
“We believe that machine learning and analytics are powerful tools for understanding diseases, improving outcomes, containing costs, and delivering better care where it’s needed most,” Cloudera founder Mike Olson said in a press release. “Today, health care organizations can do what was previously impossible. They can integrate complex datasets from EHR, genomics, and imaging with machine learning and analytics at massive scale for momentous transformations in patient care, engagement, and outcomes.”
Cloudera isn’t the only big data company investing in health care. In March, Philips unveiled HealthSuite Insights, an ecosystem of machine learning products that analyze and curate health care data. In February, Google subsidiary DeepMind teamed up with the Veterans Administration (VA) to churn through the historical medical records of about 700,000 U.S. veterans. And more recently, Microsoft announced an AI health care initiative, Healthcare Next, that’ll see its cloud computing and storage platforms applied to cardiology and genomics research.
Big data in health care is estimated to grow over $68.75 billion by the end of 2025, according to analytics firm BIS Research.
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