
Transforming healthcare reporting with InterSystems IRIS for Health
01/18/22 • 15 min
Within healthcare there are a multitude of reports available for organisations, providing information ranging from market-specific insights to supply chain reports, which can all be viewed through different means from dashboards to analytics. However, historically many of these reports supported break-fix models where they provided insight when problems occurred. Yet with the amount of data available, health and social care organisations need to align, capitalise and exploit the data they hold to become more preventative in the insights they produce, rather than reactive. Interoperability will be key to achieving this shift in data usage to combine data sets into one platform, in real-time.
In this episode, we discuss how better reporting of data can offer an overwhelming amount of transformation capabilities within the healthcare sector and how InterSystems IRIS for Health can support this change.
https://www.intersystems.com/migrate-to-intersystems-iris/
Within healthcare there are a multitude of reports available for organisations, providing information ranging from market-specific insights to supply chain reports, which can all be viewed through different means from dashboards to analytics. However, historically many of these reports supported break-fix models where they provided insight when problems occurred. Yet with the amount of data available, health and social care organisations need to align, capitalise and exploit the data they hold to become more preventative in the insights they produce, rather than reactive. Interoperability will be key to achieving this shift in data usage to combine data sets into one platform, in real-time.
In this episode, we discuss how better reporting of data can offer an overwhelming amount of transformation capabilities within the healthcare sector and how InterSystems IRIS for Health can support this change.
https://www.intersystems.com/migrate-to-intersystems-iris/
Previous Episode

Integrating Support for Machine Learning with InterSystems IRIS
While data wrangling is an important step for getting data into a usable state, data scientists need to have tools like machine learning (ML) available to them to make it easier to take the data once clean.
IntegratedML® is a new capability within InterSystems IRIS that enables your SQL developers to easily develop ML models with just a few SQL-like commands. ML models can be seamlessly embedded into applications and productions to execute in real time in response to events and transactions, allowing you to transform your applications into ML enabled intelligent applications.
This episode will explore how all of this functionality in InterSystems IRIS can now also be invoked via Python, as well as via ObjectScript, enabling your existing Python developers to develop and maintain sophisticated InterSystems IRIS applications with their current skills. For more information, visit https://www.intersystems.com/migrate-to-intersystems-iris/
Next Episode

The Global Fintech Landscape: Challenges, Collaboration, and Cloud
In recent years, fintechs have begun to deliver significant value to both consumers and businesses and have reshaped how some interact with financial services. Yet, while the fintech sector is going from strength to strength, these organisations still tend to face challenges.
This podcast explores the findings from InterSystems research that found an overwhelming 81% of fintechs identify data issues as their biggest technical challenge. And of this figure, 41% struggle to leverage data for analytics, machine learning, and artificial intelligence, while 40% are unable to connect to customers’ applications and data or legacy systems.
Encouragingly, most fintechs appear to be ready to take steps to overcome these challenges. Almost half (48%) plan to invest in data management technologies over the next 12 months, while 45% expect to implement AI and ML. Find out more from the research and how to overcome data barriers in this latest episode of the Data Dialogue, or for more information, visit: https://bit.ly/3HjUXnI
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