Use Case

How big data is saving lives


Data produced by equipment such as heart monitors, ventilators, and wearable devices come in many different forms including images, video, and audio and are produced in virtually infinite volume. In the past, it has been difficult for EMR systems to handle that kind of structured and unstructured data. This meant physicians were often unable to access the latest data about their patients.

In a medical emergency, data must be available in real-time for immediate retrieval and analysis. Health care professionals must know what just changed in the context of the patient’s entire medical history. Lack of data access and data timelines can truly be a matter of life and death.

WANdisco works with the hospital to digitally collate, store, and analyze all data relating to its patients’ conditions in real-time. This eliminates unacceptable downtime in a hospital environment where a patient’s condition can change drastically in minutes. UCI can now process accurate pattern-set recognitions, use algorithms to monitor patient recovery for non-linear complications, and build predictive-modeling systems to minimize deaths caused by medical error.
  • The level of care offered to patients has improved with hospital staff alerted as soon as vital signs cross a key threshold, enabling them to focus attention on patients who need it most. It has also helped ease the burden on doctors and nurses whose heavy patient load prevents round-the-clock observation.
  • When patients leave the hospital environment, care is now proactive instead of reactive. Real-time access to data from home monitoring devices makes it possible to predict the likelihood of hospital readmission after discharge for serious conditions such as heart failure and pneumonia so that outpatient care can be provided.
  • The ability to quickly analyze massive amounts of clinical data in combination with the patient's genetic information makes it possible to determine the best medication at the right dosage for an individual patient for virtually any disease.
  • Now, massive amounts of all types of patient data can be anonymized and accessed from a single source, giving medical researchers faster access to greater volumes of data than previously possible.
  • All types of data can be stored, retrieved, and analyzed at incredibly low cost in comparison to traditional data warehouse solutions.

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