The Use Of Big Data In Healthcare

Big Data is almost everywhere. Picture: Unsplash User Franki Chamaki

Digitization and technical progress are part of everyday life. Using online-banking, carsharing, or virtual reality has become a normal thing to do. Every issue seems to be touched. Even the healthcare sector, an industry with highly confidential data, is using Data-Logging for several years.

Every day the healthcare sector generates a lot of data. Personal data about the patient, the course of diseases, the family’s history of diseases, doctor’s reports, and medical costs are just one part. Additionally, there are more specific data gathered by treatments, e.g., blood samples, x-rays, or MRTs.

Saving up to 400 billion US Dollar is not unrealistic

Analyzing this heterogeneous amount of data can gain new insights regarding medical care. Some therapies may be more effective in a particular group of people than others. Factors that originate diseases and which people are more likely to be affected. This way, insurance companies gain the possibility to compare disease patterns and prevent misdiagnosis.

At the same time, the healthcare sector has the chance to reduce costs drastically. According to the Network for Excellence in Health Innovation, 21 billion US-Dollars a year can be saved in the USA by preventing prescription errors. McKinsey & Company has researched that Big Data can reduce costs in healthcare by 400 billion US-Dollar within the next years.

Big Data in politics

Big Data is a topic for politicians as well. At the latest conference of German-speaking health ministers in Lindau, Jens Spahn, health minister of Germany, talked about approaching the challenge of Big Data […] together. Closer cooperation of the countries will be done in a shared project.

“Worldwide the amount of data in the healthcare sector is growing due to digitization. […] We have to connect the data, which is gathered at different places within our healthcare system, to spot new correlations and use them for science and supply.”

Final declaration of the German-speaking health ministers, 03. September 2018

In Germany, the connection of medical data is still struggling. The federal structure of the healthcare system is prohibiting an easy solution to connect the public authorities. Adding to this, doctors, hospitals, and insurance isn’t well connected among each other. Against all these difficulties, there are already several projects targeting Big Data in healthcare.

Best practice examples

The Technical University Munich (TUM) is using crowdsourcing to sort the vast numbers of data they gathered. To use the collected data sets in practical use, scientists at the TUM developed a computer game. By playing the game, the player shoots cancer cells. This way, the computer learns to distinguish between a healthy cell and a cancer cell.

In September 2018, the health app Vivy was launched. Developed by several German insurances, Vivy is available to more than 13 million people. Within the app, it’s possible to send your x-rays to other doctors, remind users of their vaccination running out or warn them of potential negative interactions of medications.

In France, four Parisian hospitals combined their patient data from the last ten years. Their goal: creating a statistical value regarding patients coming to the hospitals. This data is then used to calculate how many employees should work on specific days. This not only saves money on less busy days but also improves medical services on more stressful days.

NelumBox is part of Big Data

The NelumBox takes lane risk profiling to the next level by using data that is collected while runtime and connecting this information with other data sources. Furthermore, the live-tracking of relevant data calculates risks in the last part of the shipment precisely. The courier can live-check any differences in temperature or humidity within or outside of the medicine cooler box on his smartphone or computer. Besides, weather data and a variety of other external parameters help to optimize energy usage in real-time.

The same is for traffic data. When a permanent high traffic volume occurs on a route, the NelumBox detects this problem. It then takes this information within calculating the route. Also, statistics regarding customs control and the time it takes to enter a country at certain borders are collected. If this takes longer than usual, the delay counted into route planning and battery usage. That leads to the minimization of risk. Energy-saving options can be accessed in real-time.

Safety on the highest standard

The NelumBox cloud also enhances safety in connection with cargo theft. While opening and closing the box, several data points are created. Through this data, it’s possible to see the exact time and place in which a wrongful abstraction in medicine transportation has happened. The personalized electronic lock also works to see who the last person was, that had access to the NelumBox.

To make efficient use of Big Data at Tec4med, we take our data from our Smart-Devices and add data from external sources. This creates the most innovative, safe, and user-friendly solution for you.