Information Sharing through Digital Service Agreement
Elvas, L. B.; ferreira, j.; Helgheim, B.
Show abstract
Data sharing and services reuse in the health sector is a significant problem due to privacy, and 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. 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: 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).
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- From theoretical models to practical deployment: A perspective and case study of opportunities and challenges in AI-driven healthcare research for low-income settings 93%
- A data management system for precision medicine 93%
- From months to minutes: creating Hyperion, a novel data management system expediting data insights for oncology research and patient care 92%
Similar papers in this journal
- Artificial intelligence tool for the study of COVID-19 microdroplet spread across the human diameter and airborne space 93%
- A Model of Workflow in the Hospital During a Pandemic to Assist Management 93%
- A flexible method for optimising sharing of healthcare resources and demand in the context of the COVID-19 pandemic 92%
Similar papers in this journal
- Design and implementation of a system for automated monitoring of adherence to evidenced-based clinical guideline recommendations 94%
- Quantified Flu: an individual-centered approach to gaining sickness-related insights from wearable data 93%
- COHD-COVID: Columbia Open Health Data for COVID-19 Research 92%
Similar papers in this journal
- FHIR-DHP: A Standardized Clinical Data Harmonisation Pipeline for scalable AI application deployment 94%
- Is the quality of hospital EHR data sufficient to evidence its ICHOM outcomes performance in heart failure? A pilot evaluation 92%
- Transformative potential of Large Language Models in data mining on Electronic Health Records. 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.