The foundation of digitalization

Is Martin Bierach a revolutionary? As the director of data intelligence and data innovation, he works with many other B. Braun employees on utilizing the possibilities of data analysis and artificial intelligence (AI) for medical technology. Bierach can see how important this job is with every news website or academic paper he reads, every podcast or convention speech he listens to: AI is revolutionizing the health care system. AI is supporting hospitals by automating routine tasks. AI is helping to develop new treatments. In short: AI can fundamentally change health care.​

Clean up the data before you change

Bierach is part of a radical transformation. He puts it more modestly: “The public is talking a lot about the disruptive power of artificial intelligence. But not so much about the homework that needs to be done before you can use it. The first thing you need is a uniform data base.” That is exactly what Bierach and his team have built—and have been continually developing ever since. “A clean, high-performance pool of data makes it possible to effectively employ data analytics and artificial intelligence,” Bierach says. “The more specific the data is to the given use case, the more informative the knowledge we get.” His day-to-day work stands in contrast with the popular image of the AI revolution, of self-learning, magical algorithms that practically do the job by themselves. “Instead, we are dealing with a lot of small, intricate problems,” says Bierach. “But that's exactly what makes the job so interesting.”  

It all starts with these questions: What product do we want to develop? What processes do we want to optimize? What data do we need to do this? And where is it? This is where Dr. Michelle Heber comes in, as the AI Hub Lead at B. Braun. She and her team help colleagues identify concrete use cases for AI and data analysis. “I see myself as a translator: business to AI, AI to business,” says Heber. “For one, I need to understand our employees’ concerns. And I need to explain what is technically feasible.” There are currently over 170 use cases for data at B. Braun, all in vastly different stages, from approved project to prototype, to finished solution.

Increasing the value of data

“We use the formula ‘data quality times data availability times data usage equals value’,” says Dr. Heber. The point is to make data accessible to users in the company. B. Braun's internal Data & Analysis Community has more than 1,300 members who access the database using application programming interfaces, APIs. Data governance policies determine who is permitted to work with what data, in which way, and for what purpose. In this way, data protection and data security can also be ensured. With the appropriate analysis and AI tools, users explore the data, test solutions, implement these solutions—and then turn information into knowledge. And knowledge into health care products.  

B. Braun combines these into four central systems. For extracorporeal blood treatment, the data management system Nexadia^®, developed by B. Braun, facilitates the planning and improvement of renal care center processes.​

“Using clinical data in our renal care centers secures more than just quality of treatment. By analyzing individual patient groups, treatments can be increasingly customized, and the implementation of new scientific knowledge into practice can be monitored,” explains Prof. Claudia Barth, Chief Medical Officer at B. Braun. “After we combine this pool of clinical data with data from our dialysis machines, we can create the database to develop predictive algorithms using AI. These algorithms can be used to prevent drops in blood pressure or to monitor vascular access. The result is fewer complications, fewer hospital stays, better quality of life and more time for patients by using real-time automation and prediction, even during treatment.”​

In surgical asset and supply management, data analyses help ensure that the right instruments are available in the right operating room at the right time. Surgical instruments that would not have been used anyway are not even sent to the OR in the first place—they don't need to be sterilized, which saves time and money. “For the solutions in this area, we need to combine our own data with our customers’ data in the cloud, which is challenging,” says Dr. Jan Lessing, who works on B. Braun’s specific data solutions as director of digital innovation. But it is worth it. Hospitals can now even automate procurement, saving highly valuable working hours.​

The solutions in smart infusion management, in turn, increase safety, such as preventing oncology patients from receiving the wrong dose of medication. At the same time, the data can be used to develop treatments that are easier on the body. In digital surgery, data analyses can help doctors plan and perform neurosurgical procedures. 

At the end, the patient benefits

The medical community is also convinced of the huge potential in using data. This is echoed by British surgeon and AI expert Professor Tan Arulampalam: “Huge amounts of data are generated in the OR: on work processes, on instrument use, on surgical techniques.” It is then a matter of cleaning up this data, enhancing it, consolidating it and analyzing it—to gain new knowledge. Professor Arulampalam gives a tangible example: “Experienced surgeons operate with precise hand and finger movements inside a very confined space—let's say a cube of just one centimeter on a side.” Surgeons in training, on the other hand, perform bigger, more erratic movements. By analyzing camera data, surgical residents can now receive feedback and quickly improve their techniques.

In the vast field of AI and medicine, it is always a matter of concrete ideas and solutions. In this context, the individual solutions B. Braun offers can be seen as building blocks set on the foundation of clean data. This is how B. Braun is becoming a data-centric medical technology company—and helping to shape the transformation of health care. Data-driven analyses and technologies make efficient processes, early diagnoses and customized treatments possible. “We are achieving this goal one step at a time,” says Bierach. He describes digital transformation not as a revolution but as a continuous evolution: “We are just now discovering the multitude of possibilities for advancing health care.”