Alfano, Marco ORCID: 0000-0001-7200-9547, Lenzitti, Biagio ORCID: 0000-0003-2664-7788, Lo Bosco, Giosuè ORCID: 0000-0002-1602-0693, Muriana, Cinzia ORCID: 0000-0002-9951-1761, Piazza, Tommaso ORCID: 0000-0001-5881-1410 and Vizzini, Giovanni ORCID: 0000-0002-3273-1719 (2020) Design, development and validation of a system for automatic help to medical text understanding. International Journal of Medical Informatics, 138 . ISSN 1386-5056
Abstract
Objective: The paper presents a web-based application, SIMPLE, that facilitates medical text comprehension by
identifying the health-related terms of a medical text and providing the corresponding consumer terms and
explanations.
Background: The comprehension of a medical text is often a difficult task for laypeople because it requires
semantic abilities that can differ from a person to another, depending on his/her health-literacy level. Some
systems have been developed for facilitating the comprehension of medical texts through text simplification,
either syntactical or lexical. The ones dealing with lexical simplification usually replace the original text and do
not provide additional information. We have developed a system that provides the consumer terms alongside the
original medical terms and also adds consumer explanations. Moreover, differently from other solutions, our
system works with multiple languages.
Methods: We have developed the SIMPLE application that is able to automatically: 1) identify medical terms in a
medical text by using medical vocabularies; 2) translate the medical terms into consumer terms through medicalconsumer
thesauri; 3) provide term explanations by using health-consumer dictionaries. SIMPLE can be used as a
standalone web application or can it be embedded into common health platforms for real time identification and
explanation of medical terms. At present, it works with English and Italian texts but it can be easily extended to
other languages. We have run subjective tests with both medical experts and non-experts as well as objective
tests to verify the effectiveness of SIMPLE and its simplicity of use.
Results: Non-experts found SIMPLE easy to use and responsive. The big majority of respondents confirmed they
were helped by SIMPLE in understanding medical texts and declared their willingness to continue using SIMPLE
and to recommend it to other people. The subjective tests, conducted with medical experts on a set of Italian
radiology reports, showed an agreement between SIMPLE and the experts, on the highlighted medical terms, that
ranges between 74.05 % and 81.16 % as well as an agreement of around 60 % on the consumer term translation.
The objective tests showed that the consumer terms, provided by SIMPLE, are, on average, eighteen times more
familiar than the relative medical terms so proving, once more, the effectiveness of SIMPLE in simplifying the
medical terms.
Conclusions: The performed tests demonstrate the effectiveness of SIMPLE, its simplicity of use and the willingness
of people in continuing with its use. SIMPLE provides, with a good agreement level, the same information
that medical experts would provide. Finally, the consumer terms are ‘objectively’ more familiar than
the related technical terms and as a consequence, much easier to understand.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Additional Information: | Article number 104109 |
Uncontrolled Keywords: | e-health; Patient empowerment; Lexical simplification; Consumer health vocabulary; Term familiarity; Infobutton |
Subjects: | Computer Science > Information retrieval Computer Science > World Wide Web Medical Sciences > Health |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > Lero: The Irish Software Engineering Research Centre |
Publisher: | Elsevier |
Official URL: | https://doi.org/10.1016/j.ijmedinf.2020.104109 |
Copyright Information: | © 2020 Elsevier |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 754489, Science Foundation Ireland grant 13/RC/2094, European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero, the Science Foundation Ireland Research Centre for Software |
ID Code: | 24682 |
Deposited On: | 25 Jun 2020 11:37 by Marco Alfano . Last Modified 03 Mar 2021 04:30 |
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