Design, development and validation of a system for automatic help to medical text understanding

Abstract

Objective: The paper presents a web-based application, SIMPLE, which facilitates medical text comprehension by identifying the health-related terms of a medical text and providing the corresponding consumer terms and explanations.Background: Understanding medical texts is a difficult task for laypeople. The comprehension of a medical text mainly requires semantic abilities that can differ from a person to another, depending on his/her literacy level on the subject. Some systems have been developed for facilitating the comprehension of medical texts through text simplification (syntactical or lexical). The ones dealing with lexical simplification usually replace the original text and do not provide additional information whereas our system provides the consumer terms alongside the original medical terms and also adds consumer explanations. Moreover, differently from other solutions, our system works with more languages. Methods:We have developed SIMPLE that is able to automatically: 1) identify medical terms by using medical vocabularies; 2) translate them into consumer terms through medical-consumer 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 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:The subjective tests with non-experts indicate that SIMPLE was considered easy to use and responsive. The big majority of respondents confirmed that SIMPLE helped them 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.

Tailored Retrieval of Health Information from the Web for Facilitating Communication and Empowerment of Elderly People

“…As a future work, we want to further develop the unified communication model for improving the human-to-human and human-to-machine communication processes that underlie patient empowerment. For example, we plan to improve the communication between patients and medical professionals by translating the medical terms, retrieved by FACILE, in lay terms (Alfano et al, 2020;Alfano et al, 2018;Alfano et al, 2015). Moreover, we want to create a visual framework (Alfano et al, 2016) that uses the retrieving capabilities of FACILE and allows easy creation of advanced health services for elderly people, such as virtual assistants, thus facilitating the human-tomachine communication.…”

Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities

“…These customized data displays also focused on a diverse set of application areas, including integrated dashboards [ 10 , 61 , 124 ], critical care displays [ 96 ], opioid management [ 123 ], plan of care tools [ 125 ], and patient-focused communication [ 11 , 55 , 98 ]. A smaller number of studies addressed non-EHR integrated information systems [ 9 , 65 , 68 , 83 , 112 , 120 ], and EHR training design [ 46 , 59 , 135 ].…”

Augmented EHR: Enrichment of EHR with Contents from Semantic Web Sources

“…The presented work introduces an approach in the opposite direction, aiming to bring additional contents from Semantic Web sources to the EHR of a given patient, in such a way that normalized healthcare IT systems and services can leverage these contents. Other works address methods to incorporate additional potentially relevant information into the EHR [17][18][19]33]. Nevertheless, this information (i.e., the augmentation content) is not normalized according to an EHR standard, leading to a limited degree of interoperability, in contrast to the augmented EHR approach described in this paper, in which the content from external sources is normalized and integrated as a part of the EHR.…”

“…Although the Infobuttons approach has been incorporated as part of the HL7 standard, its main limitation is the lack of interoperability of this solution with EHR standards based on the dual model representation. Similarly, M. Alfano et al [18] presented a method to obtain additional definitions of clinical terms. It starts from EHR extracts and queries a thesaurus to provide explanations of medical terms through a web service.…”