The Atmohealth project was successfully completed on March 31st 2018; and the Atmohealth version of ‘Atmolytics’, Imosphere’s data discovery and visualisation platform, is now available.
System-wide Devolved Analytics: a New Paradigm
Atmolytics enables analytic functions to distributable across whole healthcare communities, helping accelerate key elements of new models of healthcare, including:
The ‘learning health system’ – an environment in which continuous learning happens at every level, taking account of each patient intervention.
The ‘integrated care system’ – which recognises the systemic nature of a patient’s involvement and the consequent need for a ‘360-degree view’ of the patient journey in order to optimise care pathways.
‘Precision medicine and personalised care’ – in which interventions are tailored to the specific needs and attributes of individual patients, based upon both phenotypic and genotypic data.
‘Pluralistic clinical research’ – research data is combined with clinical data; self-report data; medical device data and public data, in order to identify complex cohorts and develop predictive models.
Simplifying data analytics and business intelligence
Atmolytics uses radical new technology to simplify the integration of data from multiple sources and streamline data discovery for both specialist and non-technical end users.
Supports healthcare and research improving:
Quality of care
Performance management and cost savings
Scales access across institutions supporting:
Registries on a local, regional and national basis
Simplifies research by improving the:
Integration of multiple datasets
Identification of complex cohorts
Exploration of phenotypic and genotypic data
About Horizon 2020
The Atmohealth project received funding from the European Union’s Horizon 2020 research and innovation programme.
We worked with four leading European clinical research organisations, who conducted indepth testing and evaluation of the Atmolytics platform using large-scale health datasets covering a wide spectrum of medical conditions.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 739096.
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