Seamless data exchange in healthcare
Why read this paper? Providing effective, high-quality healthcare demands greater integration—more seamless sharing of information between hospitals, within networks, and even across international borders. Efforts are underway in Southeast Asia to enable more streamlined healthcare data exchange as part of a commitment to improve efficiency and enhance collaboration. Just one example: greater consistency in standards and platforms to reduce the need for costly patient retesting. Progress demands collaboration between providers and governments, as well as the active support of experienced technology suppliers. Learn more about the opportunities which are being explored in ASEAN to build interoperable digital health systems across borders. Key takeaways Frictionless, secure data exchange is key to leveraging the benefits of digital transformation Interoperability can increase efficiency and ease workforce burden The first step is to establish a framework of shared standards for data exchange Cross-border interoperability would allow ASEAN health systems, their workers, and their patients to benefit from easier, more efficient processesModeling the human liver
Liver conditions like tumors or fatty liver disease are affecting an increasing number of people. Liver cancer alone is the third deadliest form of cancer worldwide with only a 16% five-year survival rate. But there are many stages in liver disease and patients could be treated if they were diagnosed early enough. So there is a need for both early diagnosis and better therapy options. Chloé wants to do her part in meeting this need. I think it’s very rewarding to try and apply science to build solutions that could help patients live longer and healthier lives. Chloé Audigier, Senior AI Research Scientist at Siemens Healthineers Based in Switzerland, Chloé is one of our Senior AI Research Scientists. Currently, she’s working on a project developing a digital twin of the human liver: “Digital twins are computer models that aim to represent for example an organ of a patient in an individualized, accurate and virtual way,” she explains. “Such models could help clinicians simulate or test several therapy options virtually before performing them on the actual patient.”
