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Information Sharing through Digital Service Agreement (Preprint)
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BACKGROUND
Data sharing and services reuse in the health sector is a significant problem due to privacy, security issues. The European Commission has classified health data as a unique resource owing to the ability to do both prospective and retrospective research at a low cost. Similarly, the OECD encourages member nations to create and implement health data governance systems that protect individual privacy while allowing data sharing.
OBJECTIVE
This paper aimed to describe a conceptual framework to allow medical information sharing among health entities in a secure environment. A framework of shared Artificial Intelligent services is proposed to provide a safe environment for information sharing based on digital services agreements (DSA) and a shared services infrastructure for artificial intelligence (AI) and knowledge creation.
METHODS
An action research approach was used to develop a solution to enable health data sharing towards infrastructure of sharing AI services
RESULTS
We provide a framework that will allow secure information exchange between different health organisations in the future. This information will create an opportunity for AI to identify the pattern, and make disease predictions at an early stage. A framework for secure information sharing among patient information is proposed to improve health care services. This approach allows the creation of big data and enhances the quality of the service provided at a lower cost for the servicing health entity.
CONCLUSIONS
From the collaborative platform with privacy, health data can be shared, and shared analytics services will allow an easy and fast application of AI algorithms. The framework allows data prosumers (producers/consumers) to easily express their preferences on sharing their data, which analytics operations can be performed on such data and by whom the resulting data can be shared, among other relevant aspects. This entails a framework that combines several technologies for expressing and enforcing data sharing agreements and technologies to perform data analytics operations compliant. Among these technologies, we can mention data-centric policy enforcement mechanisms and data analysis operations directly performed on encrypted data provided by multiple prosumers. The framework is mainly based on an Information Sharing Infrastructure (ISI) and an Information Analysis Infrastructure (IAI) that can be deployed in several ways and on several devices (from cloud to mobile devices).
Title: Information Sharing through Digital Service Agreement (Preprint)
Description:
BACKGROUND
Data sharing and services reuse in the health sector is a significant problem due to privacy, security issues.
The European Commission has classified health data as a unique resource owing to the ability to do both prospective and retrospective research at a low cost.
Similarly, the OECD encourages member nations to create and implement health data governance systems that protect individual privacy while allowing data sharing.
OBJECTIVE
This paper aimed to describe a conceptual framework to allow medical information sharing among health entities in a secure environment.
A framework of shared Artificial Intelligent services is proposed to provide a safe environment for information sharing based on digital services agreements (DSA) and a shared services infrastructure for artificial intelligence (AI) and knowledge creation.
METHODS
An action research approach was used to develop a solution to enable health data sharing towards infrastructure of sharing AI services
RESULTS
We provide a framework that will allow secure information exchange between different health organisations in the future.
This information will create an opportunity for AI to identify the pattern, and make disease predictions at an early stage.
A framework for secure information sharing among patient information is proposed to improve health care services.
This approach allows the creation of big data and enhances the quality of the service provided at a lower cost for the servicing health entity.
CONCLUSIONS
From the collaborative platform with privacy, health data can be shared, and shared analytics services will allow an easy and fast application of AI algorithms.
The framework allows data prosumers (producers/consumers) to easily express their preferences on sharing their data, which analytics operations can be performed on such data and by whom the resulting data can be shared, among other relevant aspects.
This entails a framework that combines several technologies for expressing and enforcing data sharing agreements and technologies to perform data analytics operations compliant.
Among these technologies, we can mention data-centric policy enforcement mechanisms and data analysis operations directly performed on encrypted data provided by multiple prosumers.
The framework is mainly based on an Information Sharing Infrastructure (ISI) and an Information Analysis Infrastructure (IAI) that can be deployed in several ways and on several devices (from cloud to mobile devices).
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