An Automatic System for Helping Health Consumers to Understand Medical Texts

Medical texts (reports, articles, etc.) are usually written by professionals (physicians, medical researchers, etc.) who use their own language and communication style. On the other hand, these texts are often read by health consumers (as in the case of medical reports) who do not have the same skills and vocabularies of the experts and can have difficulties in text comprehension. To help a health consumer in understanding a medical text, it would be desirable to have an automatic system that, given a text written with medical (technical) terms, translates them in simple or plain language and provides additional information with the same kind of language. We have designed such a system. It processes online medical documents and provides health consumers with the needed information for their understanding. To this end, we use a medical vocabulary for finding the technical terms in the medical texts, a consumer health vocabulary (CHV) for translating the technical terms into their consumer equivalents and a health-consumer dictionary for finding supplementary information on the terms. We have built a prototype that processes Italian medical reports and uses infobuttons next to the technical terms for allowing easy retrieval of the desired information

Tailored retrieval of health information from the web for facilitating communication and empowerment of elderly people

A patient, nowadays, acquires health information from the Web mainly through a “human-to-machine” communication process with a generic search engine. This, in turn, affects, positively or negatively, his/her empowerment level and the “human-to-human” communication process that occurs between a patient and a healthcare professional such as a doctor. A generic communication process can be modelled by considering its syntactic-technical, semantic-meaning, and pragmatic-effectiveness levels and an efficacious communication occurs when all the communication levels are fully addressed. In the case of retrieval of health information from the Web, although a generic search engine is able to work at the syntactic-technical level, the semantic and pragmatic aspects are left to the user and this can be challenging, especially for elderly people. This work presents a custom search engine, FACILE, that works at the three communication levels and allows to overcome the challenges confronted during the search process. A patient can specify his/her information requirements in a simple way and FACILE will retrieve the “right” amount of Web content in a language that he/she can easily understand. This facilitates the comprehension of the found information and positively affects the empowerment process and communication with healthcare professionals

Improving communication in risk management of health information technology systems by means of medical text simplification

Health Information Technology Systems (HITS) are increasingly used to improve the quality of patient care while reducing costs. These systems have been developed in response to the changing models of care to an ongoing relationship between patient and care team, supported by the use of technology due to the increased instance of chronic disease. However, the use of HITS may increase the risk to patient safety and security. While standards can be used to address and manage these risks, significant communication problems exist between experts working in different departments. These departments operate in silos often leading to communication breakdowns. For example, risk management stakeholders who are not clinicians may struggle to understand, define and manage risks associated with these systems when talking to medical professionals as they do not understand medical terminology or the associated care processes. In order to overcome this communication problem, we propose the use of the “Three Amigos” approach together with the use of the SIMPLE tool that has been developed to assist patients in understanding medical terms. This paper examines how the “Three Amigos” approach and the SIMPLE tool can be used to improve estimation of severity of risk by non-clinical risk management stakeholders and provides a practical example of their use in a ten step risk management process

Facilitating access to health web pages with different language complexity levels

The number of people looking for health information on the Internet is constantly growing. When searching for health information, different types of users, such as patients, clinicians or medical researchers, have different needs and should easily find the information they are looking for based on their specific requirements. However, generic search engines do not make any distinction among the users and, often, overload them with the provided amount of information. On the other hand, specific search engines mostly work on medical literature and specialized web sites are often not free and contain focused information built by hand. This paper presents a method to facilitate the search of health information on the web so that users can easily and quickly find information based on their specific requirements. In particular, it allows different types of users to find health web pages with required language complexity levels. To this end, we first use the structured data contained in the web to classify health web pages based on different audience types such as, patients, clinicians and medical researchers. Next, we evaluate the language complexity levels of the different web pages. Finally, we propose a mapping between the language complexity levels and the different audience types that allows us to provide different types of users, e.g., experts and non-experts with tailored web pages in terms of language complexity

Language complexity in on-line health information retrieval

The number of people searching for on-line health information has been steadily growing over the years so it is crucial to understand their specific requirements in order to help them finding easily and quickly the specific in-formation they are looking for. Although generic search engines are typically used by health information seekers as the starting point for searching information, they have been shown to be limited and unsatisfactory because they make generic searches, often overloading the user with the provided amount of results. Moreover, they are not able to provide specific information to different types of users. At the same time, specific search engines mostly work on medical literature and provide extracts from medical journals that are mainly useful for medical researchers and experts but not for non-experts. A question then arises: Is it possible to facilitate the search of on-line health/medical information based on specific user requirements? In this pa-per, after analysing the main characteristics and requirements of on-line health seeking, we provide a first answer to this question by exploiting the Web structured data for the health domain and presenting a system that allows different types of users, i.e., non-medical experts and medical experts, to retrieve Web pages with language complexity levels suitable to their expertise. Furthermore, we apply our methodology to the results of a generic search engine, such as Google, in order to re-rank them and provide different users with the proper health/medical Web pages in terms of language complexity