Helping save lives with Analytics



Racing against the clock

Getting the right help to the right place at the right time can literally be a matter of life or death in an emergency. In Japan, patients can lose precious seconds waiting for dispatchers to match them with a hospital that has the capacity or expertise to help. As a small, rural municipality, Saga Prefecture faces even greater challenges, including tight budgets, stretched health resources and an aging population. The district's overloaded dispatch system was based on manual methods, with dispatchers and first-responders relying on local knowledge and gut instinct to decide 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 before finding care for their patients.


That’s why the Governor of Saga Prefecture, challenged us to find a better way to link emergency responders to medical services. By proving we could optimize the end-to-end dispatch process, we could find a way to gather and share data within 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 task 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 must be available in real time. We had to understand the role of each link in the chain to increase overall efficiency. Even the smallest enhancement could shave vital seconds.




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 dispatch process, reducing the cases where hospitals can't accept patients by up to 40 percent and cutting average transportation time by up to 1.3 minutes. When it comes to saving lives, extra seconds make all the difference.



Life-saving intelligence
This powerful data science is now helping doctors, emergency responders and Saga Prefecture officers work in unison to refine the emergency dispatch process. It’s improving the lives of citizens by enabling responders to operate with greater certainty. What’s more, Saga Prefecture has accelerated its effort to create additional data-driven policies and train officials with data science.


Recognizing this success, the Japanese government gave the project its highest prize in November 2016 in the first-ever awards for the use of statistics by local public authorities. Yet again, analytics has proved that it’s more than a game-changer; it can be a life saver too.