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Using Data to Transform an Industry

Technology Category
  • Analytics & Modeling - Real Time Analytics
Applicable Industries
  • Healthcare & Hospitals
Applicable Functions
  • Logistics & Transportation
  • Quality Assurance
Use Cases
  • Real-Time Location System (RTLS)
  • Remote Asset Management
Services
  • Data Science Services
The Challenge
The Ottawa Paramedic Service was facing challenges with its static and siloed data. The service was relying on a reactive dispatch procedure for proactive care, which was not efficient. Hospitals had little access to information about when ambulances would be arriving, what injuries the patient had sustained, and what treatment had already been provided by paramedics. This lack of information led to a manual process susceptible to delays. With millions of rows of data being generated every week, the Ottawa Paramedic Service knew they could do more than plan for the next 24-hour period. They needed a way to improve patient response times, and effectively plan resourcing availability.
About The Customer
The Ottawa Paramedic Service is a performance-driven organization that provides emergency medical services in Ottawa, Canada. The service is responsible for responding to emergency calls and providing immediate medical care to patients. The stakes of its decisions are extremely high, with life and death literally on the line. Therefore, making intelligent use of real-time data is critical to its success. The service generates millions of rows of data every week, which can be used to improve patient response times and effectively plan resource availability. However, the service was facing challenges with its static and siloed data, which was hindering its ability to make informed decisions and provide efficient care.
The Solution
The Ottawa Paramedic Service implemented Qlik Sense® to transform their approach to patient transport and care. The solution enabled the service to create synchronized, real-time dashboards for hospitals and dispatchers. This provided comprehensive visibility, from ambulance location and system delays, to patient injury, status, and expected arrival. The service was able to deploy ambulances with greater precision and send patients to the best hospital for their condition. The solution also enabled the service to consolidate disparate sources of data to exponentially speed up analytics at the corporate level. The process of examining and manually interpreting the millions of rows of data generated by the service once took hours, days, or even weeks. Now leaders are able to see the whole picture instantaneously, allowing them to make confident, intelligent policy adjustments in mere minutes.
Operational Impact
  • Smarter decisions driven by real-time data
  • Quicker ambulance response times
  • Improved patient care
Quantitative Benefit
  • Moved closer to its goal of reducing response time by five minutes
  • 38,000 more minutes a year to get the sick and injured to the best available caregiver

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