ArticleBMC medical informatics and decision making2020
Facilitating the design of HL7 domain models through a model-driven solution.
Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
0 citing papers in PubMed, 6 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
background and goalHealth information systems are increasingly sophisticated and developing them is a challenge for software developers. Software engineers usually make use of UML as a standard model language that allows defining health information system entities and their relations. However, working with health system requires learning HL7 standards, that defines and manages standards related to health information systems. HL7 standards are varied, however this work focusses on v2 and v3 since these are the most used one on the area that this work is being conducted. This works aims to allow modeling HL7 standard by using UML.
methodsSeveral techniques based on the MDE (Model-Driven Engineering) paradigm have been used to cope with it.
resultsA useful reference framework, reducing final users learning curve and allowing modeling maintainable and easy-going health information systems.
conclusionsBy using this approach, a software engineer without any previous knowledge about HL7 would be able to solve the problem of modeling HL7-based health information systems. Reducing the learning curve when working in projects that need HL7 standards.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.