Data value mining and new data sources
In my new book "The Big Unlock", some leading technology executives in the medical industry exchanged views and explained how to use new technologies and analytical methods to make full use of data from more and more data sources to promote Digital transformation of the medical industry. They all agree on this point: Value-based care is a train leaving the platform, and the ability to gain insights from data will determine success in the new digital medical era. Big data technology vendors and enterprises have formulated data-oriented strategies, hoping to occupy a place in the medical field in the future. The CEO of Epic Systems even coined a new word for this (see the article I wrote https://www.cio.com/article/3234678/healthcare/out-with-the-e-in-with-the- c-the-new-battleground-for-digital-health.html). In many ways, the key to the merger of CVS Health and Aetna is the combined database, which emphasizes the benefits of closer integration of data and analysis technology to the medical system: improved medical results and reduced costs. The emergence of new data sources will bring a series of new challenges: whether they can be accepted for use in clinical environments, integration of common data models such as streaming media and other non-traditional data sources, and data coordination and standardization.
Artificial intelligence has a firm foothold
A year ago I predicted that the term big data analysis will give way to cognition and artificial intelligence. Not only has this become a reality, we seem to have gone to the other extreme. Although the power of artificial intelligence is beyond doubt (people are anxious that this technology may eliminate jobs), it is still difficult to find convincing cases to prove how artificial intelligence has a real impact. At the beginning of last year, I discussed many promising and emerging use cases of artificial intelligence in an article. Among the many artificial intelligence tools, the most widely adopted seems to be robotic process automation (RPA), which is widely used in large quantities. Transaction areas, such as claims settlement and collection cycle operations. In contrast, the most complex and advanced technologies (such as IBM Watson Health’s cognitive computing platform) are still difficult to change the market’s perception of the technology’s ability to achieve its promise so far.
Blockchain is still a new hot spot
One or two bold ideas can coexist in the technical field at any time, but they may not be able to cope with them, especially in conservative industries such as medical care. Now the industry is increasingly focusing on aggregating and sorting out a large amount of health and medical data, and this aggregation and mining of the demand for advanced technology may be an important factor in the rise of blockchain in 2018. Advanced technology can protect privacy and security at the same time. Convenient for public access. Some of the early related projects were supported by the U.S. Food and Drug Administration (FDA) and the U.S. National Office for the Coordination of Information Technology (ONC). Because these projects have rich potential application scenarios in the field of precision medicine, the speed of commercialization is relatively fast. .
Digital transformation of the medical industry
The prerequisite for the digital transformation of the medical industry is that the new experience empowered by digital has matured: the rise of the power of informants, healthy competition in the industry, increased consumer participation, and improved user experience. Of course, although the future is bright, the road is still tortuous. I recently wrote an article to analyze the current situation that the application speed of digital medical platforms is not as fast as expected, and discusses that the reason why several digital medical products have wider coverage is that they are connected to many devices and systems to provide a more comprehensive real-time experience. This will inevitably involve interoperability and the Internet of Things. The Internet of Things enables smart devices to share data in real time, and real-time data sharing is one of the requirements for revolutionizing medical services. At present, consumer-oriented digital medical companies are facing dilemmas such as low market share and weakened venture capital interest. The focus of such companies has shifted from the B2C model to the B2B model. It goes without saying that healthcare companies will have the initiative to influence patient data-based medical solutions.