Qlik Case Studies Using Data to Transform an Industry

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	Using Data to Transform an Industry Qlik

Using Data to Transform an Industry

Qlik

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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 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.

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.

Impact #1	Smarter decisions driven by real-time data
Impact #2	Quicker ambulance response times
Impact #3	Improved patient care

Impact #1

Smarter decisions driven by real-time data

Impact #2

Quicker ambulance response times

Impact #3

Improved patient care

Benefit #1	Moved closer to its goal of reducing response time by five minutes
Benefit #2	38,000 more minutes a year to get the sick and injured to the best available caregiver

Benefit #1

Moved closer to its goal of reducing response time by five minutes

Benefit #2

38,000 more minutes a year to get the sick and injured to the best available caregiver

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Overview

Using Data to Transform an Industry

Operational Impact

Quantitative Benefit