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Racing against the clock

In an emergency, getting the right help to the right place at the right time can literally be a matter of life or death. As a small, rural municipality in Japan, Saga Prefecture faces several challenges—from tight budgets and stretched health resources, to an aging population. But their emergency dispatch system was based on manual methods, with dispatchers and first-responders relying on local knowledge and gut instinct to decide on the best clinic to go to and the fastest route to get there. Too often, this meant emergency crews had to reach out to multiple hospitals to find one with the capacity or expertise to help.


That’s why the Governor of Saga Prefecture, Japan, challenged us to find a better way to coordinate emergency responders with medical services. By proving we could optimize the end to end emergency dispatch process, we could find a way to gather and share data with an integrated system to solve the problem—and help save lives.



Arriving on time with advanced analytics
Our mission was simple: Get patients to the right hospital, faster. But the data challenge involved made this anything but simple, with the journey from first call to arrival at a hospital relying on a highly complex data supply chain. Everything from the patient’s location and injuries, to the availability of specialist doctors and optimal routes, needs to be made available in real-time. We had to understand the role of each link in the chain to make the overall process more efficient. Even the smallest enhancement could shave vital seconds.


Arriving on-time with advanced analytics
So we utilized a liquid workforce—leveraging the best talent from the US and Japan. This allowed us to work flexibly with the most impactful IT resources, no matter where they were. With this global team, we analyzed 150,000 cases of transport data collected from iPads installed inside emergency vehicles in Saga Prefecture. We then examined a vast amount of hospital data. By combing these two sets of data, we created a detailed picture of how patients were being transported and what we could do to speed things up. And by applying artificial intelligence and machine learning to the data, we found new opportunities to improve coordination between the government, hospitals and emergency agencies.


That meant we could optimize the end-to-end emergency dispatch process. In doing so, we showed we could reduce up to 40 percent of the cases where hospitals have difficulty accepting patients, and cut average transportation time by up to 1.3 minutes. And when it comes to saving lives, those precious seconds could make all the difference.



Life-saving intelligence



Life-saving intelligence
This powerful data science is now helping doctors, emergency responders and Saga Prefecture officers work in unison to implement this optimized, end-to-end emergency dispatch process. And Saga Prefecture is accelerating its effort to create even more data-driven policies and train officials with data science.


Recognizing this success, in November 2016, the project was awarded the highest prize from the Japanese government in the first ever awards for the use of statistics by local public authorities. It’s helping improve the lives of citizens by enabling emergency responders to operate with the certainty that only a data-powered approach can deliver. In this case, analytics has proved that it’s more than a game-changer; it can be a life saver too.