A search tool based on 'encapsulated' MeSH thesaurus to retrieve quality health resources on the internet

Interventions to support consumer evaluation of online health information credibility: A scoping review

PURPOSE

Various interventions have been designed to help consumers better evaluate the credibility of online health information (OHI). However, assessing information credibility remained the most widely reported challenge by online health consumers. This review aims to provide an overview of major intervention approaches for improving consumer ability to evaluate OHI credibility in order to identify opportunities for future interventions.

METHODS

A scoping review was performed. Seven relevant scientific databases were searched to identify articles that report the design and/or evaluation of interventions to support, facilitate, or assist consumers in assessing the credibility of OHI. Thirty-one articles met the inclusion criteria. Relevant content was extracted from the articles and all codes were validated by second coders.

RESULTS

Three major intervention approaches for enhancing consumers' ability to evaluate OHI credibility were identified: educational program, algorithm, and interactive interface. The design of most interventions (particularly the credibility evaluation component) lacked the guidance of theories, and very few studies systematically evaluated their effectiveness in real online search contexts. Few interventions can provide spontaneous support to consumers while they search online.

CONCLUSION

Our understanding of what theoretical constructs contribute to effective OHI credibility evaluation interventions and how intervention outcomes should be measured remained limited. Future efforts need to focus on the design, development, test, and evaluation of theory-guided OHI credibility evaluation interventions that are scalable, sustainable, and can provide real-time support to consumers.

Building a Semantic Health Data Warehouse in the Context of Clinical Trials: Development and Usability Study

Background

The huge amount of clinical, administrative, and demographic data recorded and maintained by hospitals can be consistently aggregated into health data warehouses with a uniform data model. In 2017, Rouen University Hospital (RUH) initiated the design of a semantic health data warehouse enabling both semantic description and retrieval of health information.

Objective

This study aimed to present a proof of concept of this semantic health data warehouse, based on the data of 250,000 patients from RUH, and to assess its ability to assist health professionals in prescreening eligible patients in a clinical trials context.

Methods

The semantic health data warehouse relies on 3 distinct semantic layers: (1) a terminology and ontology portal, (2) a semantic annotator, and (3) a semantic search engine and NoSQL (not only structured query language) layer to enhance data access performances. The system adopts an entity-centered vision that provides generic search capabilities able to express data requirements in terms of the whole set of interconnected conceptual entities that compose health information.

Results

We assessed the ability of the system to assist the search for 95 inclusion and exclusion criteria originating from 5 randomly chosen clinical trials from RUH. The system succeeded in fully automating 39% (29/74) of the criteria and was efficiently used as a prescreening tool for 73% (54/74) of them. Furthermore, the targeted sources of information and the search engine–related or data-related limitations that could explain the results for each criterion were also observed.

Conclusions

The entity-centered vision contrasts with the usual patient-centered vision adopted by existing systems. It enables more genericity in the information retrieval process. It also allows to fully exploit the semantic description of health information. Despite their semantic annotation, searching within clinical narratives remained the major challenge of the system. A finer annotation of the clinical texts and the addition of specific functionalities would significantly improve the results. The semantic aspect of the system combined with its generic entity-centered vision enables the processing of a large range of clinical questions. However, an important part of health information remains in clinical narratives, and we are currently investigating novel approaches (deep learning) to enhance the semantic annotation of those unstructured data.

Combining different standards and different approaches for health information retrieval in a quality-controlled gateway

Internet as source of information is increasing in preeminence in numerous fields, including health. We describe in this paper the CISMeF project (acronym of Catalogue and Index of French-speaking Medical Sites) which has been designed to help the health information consumers and health professionals to find what they are looking for among the numerous health documents available online. The catalogue is founded on two standards: a set of metadata and a terminology based on the MeSH thesaurus which has the same structure and use as an ontology of the medical domain. The structure of the catalogue allows us to place the project at an overlap between the present Web, which is informal, and the forthcoming Semantic Web. Many features of information retrieval and navigation through the catalogue were developed. These features take into account the kind of the end-user (health professional, medical student, patient). The CISMeF-patients catalogue is a sub-catalogue of CISMeF and is dedicated to the patients and the general public. It shares the same model as CISMeF whereas MEDLINE and MedlinePlus do not. We also propose to couple two approaches (morphological processing and data mining) to help the users by correcting and refining their queries.

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality-controlled gateway

The amount of health information available on the Internet is considerable. In this context, several health gateways have been developed. Among them, CISMeF (Catalogue and Index of Health Resources in French) was designed to catalogue and index health resources in French. The goal of this article is to describe the various enhancements to the MeSH thesaurus developed by the CISMeF team to adapt this terminology to the broader field of health Internet resources instead of scientific articles for the medline bibliographic database. CISMeF uses two standard tools for organizing information: the MeSH thesaurus and several metadata element sets, in particular the Dublin Core metadata format. The heterogeneity of Internet health resources led the CISMeF team to enhance the MeSH thesaurus with the introduction of two new concepts, respectively, resource types and metaterms. CISMeF resource types are a generalization of the publication types of medline. A resource type describes the nature of the resource and MeSH keyword/qualifier pairs describe the subject of the resource. A metaterm is generally a medical specialty or a biological science, which has semantic links with one or more MeSH keywords, qualifiers and resource types. The CISMeF terminology is exploited for several tasks: resource indexing performed manually, resource categorization performed automatically, visualization and navigation through the concept hierarchies and information retrieval using the Doc'CISMeF search engine. The CISMeF health gateway uses several MeSH thesaurus enhancements to optimize information retrieval, hierarchy navigation and automatic indexing.

Seal of transparency heritage in the CISMeF quality-controlled health gateway

Background

It is an absolute necessity to continually assess the quality of health information on the Internet. Quality-controlled subject gateways are Internet services which apply a selected set of targeted measures to support systematic resource discovery.

Methods

The CISMeF health gateway became a contributor to the MedCIRCLE project to evaluate 270 health information providers. The transparency heritage consists of using the evaluation performed on providers that are referenced in the CISMeF catalogue for evaluating the documents they publish, thus passing on the transparency label from the publishers to their documents.

Results

Each site rated in CISMeF has a record in the CISMeF database that generates an RDF into HTML file. The search tool Doc'CISMeF displays information originating from every publisher evaluated with a specific MedCIRCLE button, which is linked to the MedCIRCLE central repository. Starting with 270 websites, this trust heritage has led to 6,480 evaluated resources in CISMeF (49.8% of the 13,012 resources included in CISMeF).

Conclusion

With the MedCIRCLE project and transparency heritage, CISMeF became an explicit third party.