Proving the Business Case for the Internet of Things

Orion uses AWS for big data in healthcare

Steve Rogerson
October 16, 2018
 
New Zealand-based Orion Health has hosted on Amazon Web Services (AWS) Amadeus Core, the latest in its suite of data management, storage and sharing products to help healthcare organisations harness the power of big data.
 
With vast amounts of data from multiple sources to contend with, healthcare organisations struggle to deal with the complicated and expensive technology options for storing large volumes of data securely.
 
A secure health data store, Amadeus Core is hosted on AWS to provide the scalability to support organisations of any size. With HIPAA compliance and Hitrust certification, Amadeus Core provides a platform for data analytics, machine learning, value-based care and population health management.
 
Health data can be drawn upon for analysis allowing organisations the flexibility of leveraging the potential of big data now or in the future when the organisation is ready to use machine learning models to gain insights and make predictions that could improve the lives of their patients.
 
"Amadeus Core helps healthcare organisations prepare for the opportunities that lie ahead in data analytics," said Ian McCrae, CEO of Orion Health. "Healthcare organisations the world over struggle with disparate and siloed information but see the value of extracting insights from their data for better decision making and more efficient management and operation. Securely storing and enabling access to these vast volumes of health data is the first step in a data journey that healthcare organisations can take to share and unleash the potential of their data."
 
Making the shift to big data, machine learning and artificial intelligence is something 42% of professionals believe will happen in the next three to five years but, despite these expectations, many are struggling to come to grips with how to leverage big data and the AI capabilities that come with it, Deloitte's 2018 Global Human Capital Trends research recently found.
 
The analysis highlighted a readiness gap, where 72% saw AI as important but only a third of those surveyed felt ready to address it. This is especially the case in healthcare where big data are something that have been spoken about for many years but the reality of the journey to achieving the benefits of what a connected data ecosystem offers has only been achieved by a few.
 
"Health determinants in isolation are interesting; in combination, they're powerful," McCrae said. "Storing and aggregating vast volumes of different data and surfacing them via data analytics and machine learning models brings healthcare organisations a step closer to realising precision medicine, which is only possible when we have the complete picture of a person's health."
 
Amadeus Core has been designed as a platform to handle vast volumes of data from multiple sources and enable machine learning. Its rapid data model development and secure deployment lets users deliver robust cloud hosted services quickly.
 
It enables an ecosystem of apps using Restful APIs on pre-configured and custom data models. Secure APIs let developers build applications on top of the shared data. Amadeus Core uses Ansi SQL interfaces to allow easy data access for analytics, machine learning and BI reporting use cases.
 
The software provides long-term secure cloud storage of health data. Healthcare organisations can comply with long-term data retention policies as it provides a way to store any data easily in a secure, scalable and cost-effective AWS hosted environment.
 
Historical information is available for re-use without the expense of retrieving the data a second time from the source. When data are no longer required, they are easily purged. There is appropriate offsite storage for disaster recovery purposes.
 
Out-of-the-box dashboards and reports provide insights such as traffic trends, message characteristics and flow patterns to improve operational efficiency.
 
It aggregates and stores patient data to enable the exchange of health information. Data are easily queried via APIs and a BI interface to support a range of clinical applications.
 
There is a repository for new and non-traditional data types. Any data, as are, can be stored in the source data store with little pre-processing. Custom data modelling provides flexibility for storing any and all types of data, including traditional and emerging data types.
 
It enables a platform for data analytics, machine learning, value-based care and population health management. Original and modelled data can be queried via the SQL interface to support deeper understanding of data assets.