Modern Healthcare Architectures Built with Hadoop

In January 2013, McKinsey & Company published a report named “The ‘Big Data’ Revolution in Healthcare”. The report points out how big data is creating value in five “new value pathways” allowing data to flow more freely. Below we present a summary of these five new value pathways and an an example how Hadoop can be used to address each. Thanks to the Clinical Informatics Group at UC Irvine Health for many of the use cases, described in their UCIH case study:

From a long-term perspective, the sensor data enables something much more profound: predictive analytics that can allow caregivers to respond before a patient’s vital signs ever cross a dangerous threshold.

Most of those minute-by-minute snapshots of vital signs will be unremarkable, but the data points they generate are the building blocks for algorithms that can predict near-term outcomes with an ever-increasing degree of certainty. Like the previous example with heart patients, this data will reduce average time to insight for important medical decisions the staff needs to make.

This is because an increased temperature, heart rate or respiratory rate in isolation of other data may not be cause for concern. But those same vitals, combined with all of the prior data on that patient, combined with years of data on other patients with similar risk factors, combined with unique characteristics of that patient’s medical history, physical characteristics, gender and age—all of that will eventually paint a far more detailed picture, with more predictive power.

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