Improving expressiveness of agents using openEHR to retrieve multi-institutional health data Feeding local repositories through HL7 based providers

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Paulo R Silva Ferreira (Author) Other; Jose H Patriarca Almeida (Author) Other; Pedro M Vieira Marques (Author) FMUP; Ricardo Joao Cruz Correia (Author) FMUP

Conference proceedings International

Title: INFORMATION SYSTEMS AND TECHNOLOGIES

7th Iberian Conference on Information Systems and Technologies (CISTI)

Madrid, SPAIN, JUN 20-23, 2012

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 6 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-002-FX3

Abstract (EN): In healthcare there are perceived benefits in the integration of multi-institutional patient data. The use of multi-agent systems may facilitate the discovery and retrieval of patient data from the multiple health institutions that the patient has come into contact with. The main objective of this work is to define an architecture that allows agents to seek and collect health data from an HL7 based Information Systems. A key aspect in the development of the system for the retrieval of healthcare data is the integration with local systems. This paper describes a way to integrate openEHR queries with HL7 messages to query a local repository of patient information at an external institution, enabling a multi-agent system designed for the retrieval of multi-institutional data to search for and retrieve patient data essential for the process of care delivery. With health open standards and technologies a model was developed in order to enhance the discovery and retrieval of patient health data, this model have harmonized health data source input (HL7) which is modeled through metabolic templates with the same structure of an archetype template, providing openEHR compositions. Consequently building an openEHR repository with the modeled compositions allows the agents to use the Archetype Query Language for searching and retrieving the clinical data found in archetype-based EHRs.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5