The API is comprised of three modality-specific interfaces that implement key industry-wide standards for healthcare data:
- FHIR, an emerging standard for health data interchange
- HL7v2, the most widely adopted method for health systems integration
- DICOM, the dominant standard for radiology and imaging-related disciplines
Each interface is backed by a standards-compliant data store that provides read, write, search and other operations on the data. These data stores also provide an interface into Google Cloud’s high-capacity Publish-Subscribe (Cloud Pub/Sub) product that provides a clean, secure integration point for applications. Cloud Pub/Sub integration can also be used for invoking data transformations in Cloud Dataflow, executing serverless applications using Cloud Functions, streaming data into the popular BigQuery analytics engine, or generating clinical outcome predictions by sending data to the Cloud ML Engine machine learning platform.
Edge computing in healthcare
Cloud computing has become ubiquitous over the past 10-15 years, but according to this article on edge computing in healthcare (Can Edge Computing Be A Game Changer For the Healthcare Industry?), there is a new recognition that there is a need to coordinate centralized data storage facilities or cloud storage which is distributed over a wide-spread network. The majority of this data comes from different locations such as clinics, individual hospitals, etc. and it usually comes in an unstructured form.
Edge computing, also called fog computing, is helping healthcare institutions distribute their data to make it available quickly and securely. It also improves network efficiency, as it also reduces the amount of mobile data.
What is edge computing?
Software and services which perform tasks previously requiring human analysis and interaction. Marketing applications of AI typically aim to improve business to customer communications including targeting media, personalized messaging, and customer service interactions.
A review in Healthtech Magazine summarizes these benefits:
Some of the portable IoT devices, when combined with edge computing, have a greater ability to gather, store, analyze, and distribute data remotely. Edge computing can help solve connectivity issues and can work for remotely located patients as well. As a use-case, patients with wearable IoT medical devices on them can be quickly diagnosed from anywhere, anytime, and the data gathered can be distributed to a central server whenever connectivity is available. The characteristic localized processing power of edge computing can facilitate access and medical intervention for patients that are remotely located.
Medtronic recently launched a wireless monitoring service for patients with cardiac disease, which enables them to send data from their implanted devices directly to their doctors. The latest devices can even be programmed to update and send patient data automatically. And other precedents for moving into health management exist outside pharma itself.
Now you've read about the first 3 trends, why not download your free copy of the 2021 pharma and healthcare marketing trend guide and take your next steps to a winning strategy today?