Relevant Press
Lack of a Platform for Innovative Applications (Extract from: PCAST - President’s Council of Advisors on Science and Technology Report)
“Lack of a Platform for Innovative Applications: Many healthcare systems use enterprise systems customized to fit the needs of the particular provider. Other organizations rely on idiosyncratic “legacy” systems that often were initially used primarily for billing or pharmacy refills. Neither type of system provides an open and robust platform for software developers to build applications to improve data entry processes, provide decision support, or other functionality. The fact that existing systems often use record formats based on messages and page formats also makes it harder to access, retrieve, and analyze individual data elements. In addition, existing systems typically are not interoperable, so that data cannot easily be shared or aggregated across organizations.”
Addressing Semantic Interoperability is Key (Extract from: EU eHealth Strategies Report)
It is widely recognized that semantic interoperability is the key factor for realizing a wide range of expected benefits from the implementation of eHealth infrastructures and applications. This holds not only for the regional or national level, where in many countries multiple languages may be involved, but even more so in trans-border and pan-European situations, where potentially more than 20 languages and three alphabets are concerned. For improving health services quality and patient safety it is mandatory that the electronic exchange and analysis of health and clinical data allows the involved professionals to fully understand and act on the information received.
More than words (Source: Science Careers from the Journal Science)
Most biomedical research laboratories make up their own private language to describe their particular techniques, materials, and measurements. Even medical practitioners have more than a hundred ways to describe a simple fact such as a patient's blood glucose. Talking to other scientists about data is like having a conversation without agreeing which words to use, or what they mean. With no lingua franca, how can biomedical researchers make the most of the vast amounts of data out there?