Big Data in Healthcare & Life Sciences
Better, faster, deeper insights and patient intervention with big data. When data from gene sequencing, electronic health records , sensors and wearables, and clinical notes are combined and secured, it enables a precision medicine approach. The result is better overall patient outcomes for providers, payers, pharma, and device manufacturers. Further, all organizations in the value chain, including healthcare data companies, can rely on the easiest route to low total cost of ownership and modern architectures to store the most molecular data, the most wide, linked, and unstructured data, the most streaming data, and the most secure data.
Quality of care optimization
Apache Hadoop helps providers capture, combine, secure, and analyze bedside sensors, bio-monitor, HL7, FHIR, and other streaming and internet-of-things scale data feeds. Environmental and epigenetic factors such as ambient light and noise, stress, and clinical interventions represent examples of enriching data that Cloudera enables physicians, researchers, and others to easily and elastically add studies for evaluating ways to impact patient outcomes.
Analysis of the relevant DNA sequences, whether whole genome, exome, methylation or multi-omics, puts us in reach of precision medicine and high confidence biomarker discovery for the first time. Hadoop can drive a hundred-fold improvement in expense over traditional high-performance compute approaches in tertiary or downstream molecular analytics at scale, and can integrate with market-leading storage approaches. Cloudera open-source project software and support helps enable use cases from health system pathology departments performing pharmacogenomics to research labs doing genome-wide association studies. Cloudera enables to fastest path to merge ‘omic data with clinical/phenotype data from any technology in the market. Over a dozen organizations have selected Cloudera as their precision medicine repository or enterprise variant store for unlimited scale.
Machine Learning in the Clinic
By bringing together the world’s health data and making it secure, searchable, and available for a variety of analytic workloads by multiple users, organizations have begun to determine and prevent the most prevalent causes of illness, from readmission to risky lifestyles.
Streaming from the bedside for care optimization
Apache Spark™, Spark Streaming and other Cloudera supported technologies help providers capture, combine, and secure data feeds from bedside sensors, bio-monitors and other devices, at Internet-of-Things scale. Environmental and epigenetic factors such as ambient light and noise, stress, and clinical interventions represent examples of enriching data that Cloudera enables physicians, researchers, and others to easily and elastically add. Today, clinicians and researchers want the ability to, at a low cost, store years rather than hours of streaming bedside vitals and waveforms. Using Apache Hadoop as a storage paradigm, our customers store bedside data, analyzed both during the streaming and then while stored in their data lake. Often these bedside, sensor or device repositories are also fed by HL7 and FHIR feeds. Together, these capabilities enable improved patient outcomes and a deeper understanding of the effects of interventions.
National children’s hospital applies enriched data analysis