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BackgroundTo earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website’s HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. ObjectiveThe goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. MethodsUsing manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. ResultsFor the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more than 50% for contact details (100% precision, 69% recall), authority (85% precision, 52% recall), and reference (75% precision, 56% recall). The results also revealed issues for some criteria such as date. Changing the “document” definition (ie, using the sentence instead of whole document as a unit of classification) within the automated system resolved some but not all of them. ConclusionsStudy results indicate concordance between automated and expert manual compliance detection for authority, privacy, reference, and contact details. Results also indicate that using the same general parameters for automated detection of each criterion produces suboptimal results. Future work to configure optimal system parameters for each HONcode principle would improve results. The potential utility of integrating automated detection of HONcode conformity into future search engines is also discussed.

We are well into the 21st century and the Internet has been around long enough that there are adults who have not known a world without this wonderful tool. And just as time has gone since the beginnings of the Internet, so too has it developed, probably above and beyond the wildest dreams of its founders. These developments, though mostly positive, also have their share of the not so positive. One of these challenges is the difficulty in maintaining accuracy and quality of all the information, data gathered, aggregated or automatically generated being displayed on the Internet on Web websites or via mobile application, and this is a concern in the health domain. In this paper, we attempt to discuss in detail, some of the latest developments along with the challenges each of them entail and proposed Code of Conduct for health apps and connected objects. [ABSTRACT FROM AUTHOR]

The Health On the Net Foundation (HON) was born in 1996, during the beginning of the World Wide Web, from a collective decision by health specialists, led by the late Jean-Raoul Scherrer, who anticipated the need for online trustworthy health information. Because the Internet is a free space that everyone shares, a search for quality information is like a shot in the dark: neither will reliably hit their target. Thus, HON was created to promote deployment of useful and reliable online health information, and to enable its appropriate and efficient use. Two decades on, HON is the oldest and most valued quality marker for online health information. The organization has maintained its reputation through dynamic measures, innovative endeavors and dedication to upholding key values and goals. This paper provides an overview of the HON Foundation, and its activities, challenges, and achievements over the years. [ABSTRACT FROM AUTHOR]

The most popular mean of searching for online health content is a general search engine for all domains of interest. Being general implies on one hand that the search engine is not tailored to the needs which are particular to the medical and on another hand that health domain and health-specific queries may not always return adequate and adapted results. The aim of our study was to identify difficulties and preferences in online health information search encountered by members of the general public. The survey in four languages was online from the 9th of March until the 27th of April, 2011. 385 answers were collected, representing mostly the opinions of highly educated users, mostly from France and Spain. The most important characteristics of a search engine are relevance and trustworthiness of results. The results currently retrieved do not fulfil these requirements. The ideal representation of the information will be a categorization of the results into different groups. Medical dictionaries/thesauruses, suggested relevant topics, image searches and spelling corrections are regarded as helpful tools. There is a need to work towards better customized solutions which provide users with the trustworthy information of high quality specific to his/her case in a user-friendly environment which would eventually lead to making appropriate health decisions. [ABSTRACT FROM AUTHOR]

Question answering systems try to give precise answers to a user's question posed in natural language. It is of utmost importance that the answers returned are relevant to the user's question. For clinical QA, the trustworthiness of answers is another important issue. Limiting the document collection to certified websites helps to improve the trustworthiness of answers. On the other hand, limited document collections are known to harm the relevancy of answers. We show, however, in a comparative evaluation, that promoting trustworthiness has no negative effect on the relevance of the retrieved answers in our clinical QA system. On the contrary, the answers found are in general more relevant. [ABSTRACT FROM AUTHOR]

The Internet is increasingly being used as a means to search and communicate health information. As the mission of Health on the Net Foundation (HON) is to guide healthcare consumers and professionals to trustworthy online information, we have been interested in seeing the trend of the attitudes towards Internet use for health purposes since 1996. This article presents the results of the 10th HON survey conducted in July-August 2010 (in English and French). It was hosted on the HON site with links from Facebook and Twitter and from HONcode certified web sites. There were 524 participants coming mainly from France (28%), the UK (18%) and the USA (18%). 65% of participants represented the 'general public', while the remaining 35% were professionals. Information quality remains the main barrier users encounter while looking for health information online; at the same time, 79% believe they critically assess online content. Both patients and physicians consider the Internet to be helpful in facilitating their communication during consultations, although professionals are more sceptic than the general public. These results justify the continuing efforts of HON to raise public awareness regarding online health information and the ethical, quality and transparency issues, and to educate and guide users towards trustworthy health information. [ABSTRACT FROM AUTHOR]

The majority of the adult population in both Europe and North America have access to the internet. Over 70% state that they have used the internet to look for health information and the majority started their search at a search engine. Given that search engines list sites according to popularity and not quality, it is imperative that users have a means of discerning trustworthy and honest information from non-reliable health information. The HONcode, a set of eight quality guidelines, ensures access to standardized trustworthy health information which can be used as a tool to guide consumers. [ABSTRACT FROM AUTHOR]

Many attempts have been made in the QA domain but no system applicable to the field of health is currently available on the Internet. This paper describes a bilingual French/English question answering system adapted to the health domain and more particularly the detection of the question's model. Indeed, the Question Analyzer module for identifying the question's model has a greater effect on the rest of the QA system. Our original hypothesis for the QA is that a question can be defined by two criteria: type of answer expected and medical type. These two must appear in the step of detection of the model in order to better define the type of question and thus, the corresponding answer. For this, questions were searched on the Internet and then given to experts in order to obtain classifications according to criteria such as type of question and type of medical context as mentioned above. In addition, tests of supervised and non-supervised classification were made to determine features of questions. The result of this first step was that algorithms of classification were chosen. The results obtained showed that categorizers giving the best results were the SVM. Currently, for a set of 100 questions, 84 are well categorized in English and 68 in French according to the type of answer expected. This figures fall to less than 50% for the medical type. Evaluations have showed that the system was good to identify the type of answer expected and could be enhanced for the medical type. It leads us to use an external source of knowledge: UMLS. A future improvement will be the usage of UMLS semantic network to better categorize a query according to the medical domain. [ABSTRACT FROM AUTHOR]

Legal and technologic trends are making medical records progressively more patient-accessible. In the near future, information technology may make it even easier to provide patients a chance to review their records. One may wonder, however, about the practical use of this technology by patients. Understanding his/her own health record will certainly be one of the main concerns of patients. WRAPIN has been designed to provide patients and citizens with trusted health information. It will help to determine the reliability of documents by checking the ideas contained against established benchmarks, and enable users to determine the relevance of a given document from a page of search results. First, we present what is, in our opinion, the most original and important patient-centred WRAPIN characteristics and functionalities. Then, we compare these characteristics with those of representatives of two main trends in information retrieval: systems based on the popularity of web sites, and on the clustering of web sites. This comparison shows that, even though patients are tempted to use popular search engines, these are not sufficiently specialized in the medical domain to help them understand their own HER.. Finally, we discuss the complexity of medical readings over the Internet and the efforts that are still required in this domain. [ABSTRACT FROM AUTHOR]

The number of medical websites is constantly growing [1]. Owing to the open nature of the Web, the reliability of information available on the Web is uneven. Internet users are overwhelmed by the quantity of information available on the Web. The situation is even more critical in the medical area, as the content proposed by health websites can have a direct impact on the users' well being. One way to control the reliability of health websites is to assess their quality and to make this assessment available to users. The HON Foundation has defined a set of eight ethical principles. HON's experts are working in order to manually define whether a given website complies with s the required principles. As the number of medical websites is constantly growing, manual expertise becomes insufficient and automatic systems should be used in order to help medical experts. In this paper we present the design and the evaluation of an automatic system conceived for the categorisation of medical and health documents according to he HONcode ethical principles. A first evaluation shows promising results. Currently the system shows 0.78 micro precision and 0.73 F-measure, with 0.06 errors. [ABSTRACT FROM AUTHOR]

The Internet provides a great amount of information and has become one of the communication media which is most widely used [1]. However, the problem is no longer finding information but assessing the credibility of the publishers as well as the relevance and accuracy of the documents retrieved from the web. This problem is particularly relevant in the medical area which has a direct impact on the well-being of citizens. In this paper, we assume that the quality of web pages can be controlled, even when a huge amount of documents has to be reviewed. But this must be supported by both specific automatic tools and human expertise. In this context, we present various initiatives of the Health on the Net Foundation informing the citizens about the reliability of the medical content on the web. [ABSTRACT FROM AUTHOR]

Medical institutions produce ever-increasing amount of diverse information. The digital form makes these data available for the use on more than a single patient. Images are no exception to this. However, less is known about how medical professionals search for visual medical information and how they want to use it outside of the context of a single patient. This article analyzes ten months of usage log files of the Health on the Net (HON) medical media search engine. Key words were extracted from all queries and the most frequent terms and subjects were identified. The dataset required much pre-treatment. Problems included national character sets, spelling errors and the use of terms in several languages. The results show that media search, particularly for images, was frequently used. The most common queries were for general concepts (e.g., heart, lung). To define realistic information needs for the ImageCLEFmed challenge evaluation (Cross Language Evaluation Forum medical image retrieval), we used frequent queries that were still specific enough to at least cover two of the three axes on modality, anatomic region, and pathology. Several research groups evaluated their image retrieval algorithms based on these defined topics. [ABSTRACT FROM AUTHOR]