Dataset Information

Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.

ABSTRACT: The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between professional language and consumer friendly language. To keep up with the constantly evolving medical knowledge and language use, new terms need to be identified and added to the OAC CHV. User-generated content on social media, including social question and answer (social Q&A) sites, afford us an enormous opportunity in mining consumer health terms. Existing methods of identifying new consumer terms from text typically use ad-hoc lexical syntactic patterns and human review. Our study extends an existing method by extracting n-grams from a social Q&A textual corpus and representing them with a rich set of contextual and syntactic features. Using K-means clustering, our method, simiTerm, was able to identify terms that are both contextually and syntactically similar to the existing OAC CHV terms. We tested our method on social Q&A corpora on two disease domains: diabetes and cancer. Our method outperformed three baseline ranking methods. A post-hoc qualitative evaluation by human experts further validated that our method can effectively identify meaningful new consumer terms on social Q&A.

SUBMITTER: He Z

PROVIDER: S-EPMC5488691 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.

He Zhe Z Chen Zhiwei Z Oh Sanghee S Hou Jinghui J Bian Jiang J

Journal of biomedical informatics 20170327

The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between pro ...[more]

PMID: 28359728

Similar Datasets

Project description:BackgroundHealth professionals and consumers use different terms to express medical events or concerns, which makes the communication barriers between the professionals and consumers. This may lead to bias in the diagnosis or treatment due to the misunderstanding or incomplete understanding. To solve the issue, a consumer health vocabulary was developed to map the consumer-used health terms to professional-used medical terms.MethodsIn this study, we extracted Chinese consumer health terms from both online health forum and patient education monographs, and manually mapped them to medical terms used by professionals (terms in medical thesauri or in medical books). To ensure the above annotation quality, we developed annotation guidelines.ResultsWe applied our method to extract consumer-used disease terms in endocrinology, cardiology, gastroenterology and dermatology. In this study, we identified 1349 medical mentions from 8436 questions posted in an online health forum and 1428 articles for patient education monographs. After manual annotation and review, we released 1036 Chinese consumer health terms with mapping to 480 medical terms. Four annotators worked on the manual annotation work following the Chinese consumer health term annotation guidelines. Their average inter-annotator agreement (IAA) score was 93.91% ensuring high consistency of the released terms.ConclusionsWe extracted Chinese consumer health terms from online forum and patient education monographs, and mapped them to medical terms used by professionals. Manual annotation efforts have been made for term annotating and mapping. Our study may contribute to the Chinese consumer health vocabulary construction. In addition, our annotated corpus, both the contexts of consumer health terms and consumer-professional term mapping, would be a useful resource for automatic methodology development. The dataset of the Chinese consumer health terms (CHT) is publicly available at http://www.phoc.org.cn/cht/ .

Project description:BackgroundRadiology reporting is a clinically oriented form of documentation that reflects critical information for patients about their health care processes. Realizing its importance, many medical institutions have started providing radiology reports in patient portals. The gain, however, can be limited because of medical language barriers, which require a way for customizing these reports for patients. The open-access, collaborative consumer health vocabulary (CHV) is a terminology system created for such purposes and can be the basis of lexical simplification processes for clinical notes.ObjectiveThe aim of this study was to examine the comprehensibility and suitability of CHV in simplifying radiology reports for consumers. This was done by characterizing the content coverage and the lexical similarity between the terms in the reports and the CHV-preferred terms.MethodsThe overall procedure was divided into the following two main stages: (1) translation and (2) evaluation. The translation process involved using MetaMap to link terms in the reports to CHV concepts. This is followed by replacing the terms with CHV-preferred terms using the concept names and sources table (MRCONSO) in the Unified Medical Language System (UMLS) Metathesaurus. In the second stage, medical terms in the reports and general terms that are used to describe medical phenomena were selected and evaluated by comparing the words in the original reports with the translated ones. The evaluation includes measuring the content coverage, investigating lexical similarity, and finding trends in missing concepts.ResultsOf the 792 terms selected from the radiology reports, 695 of them could be mapped directly to CHV concepts, indicating a content coverage of 88.5%. A total of 51 of the concepts (53%, 51/97) that could not be mapped are names of human anatomical structures and regions, followed by 28 anatomical descriptions and pathological variations (29%, 28/97). In addition, 12 radiology techniques and projections represented 12% of the unmapped concepts, whereas the remaining six concepts (6%, 12/97) were physiological descriptions. The rate of lexical similarity between the CHV-preferred terms and the terms in the radiology reports was approximately 72.6%.ConclusionsThe CHV covered a high percentage of concepts found in the radiology reports, but unmapped concepts are associated with areas that are commonly found in radiology reporting. CHV terms also showed a high percentage of lexical similarity with terms in the reports, which contain a myriad of medical jargon. This suggests that many CHV terms might not be suitable for lay consumers who would not be facile with radiology-specific vocabulary. Therefore, further patient-centered content changes are needed of the CHV to increase its usefulness and facilitate its integration into consumer-oriented applications.

Project description:BACKGROUND:Although a number of studies have investigated how consumers use social media for health-related purposes, there is a paucity of studies in the Australian context. OBJECTIVE:This study aimed to explore how Australian consumers used social media for health-related purposes, specifically how they identified social media platforms, which were used, and which health-related activities commonly took place. METHODS:A total of 5 focus groups (n=36 participants), each lasting 60 to 90 minutes, were conducted in the Sydney metropolitan area. The group discussions were audiorecorded and transcribed verbatim. The transcripts were coded line-by-line and thematically analyzed. RESULTS:Participants used general search engines to locate health-related social media platforms. They accessed a wide range of social media on a daily basis, using several electronic devices (in particular, mobile phones). Although privacy was a concern, it did not prevent consumers from fully engaging in social media for health-related purposes. Blogs were used to learn from other people's experiences with the same condition. Facebook allowed consumers to follow health-related pages and to participate in disease-specific group discussions. Wikipedia was used for factual information about diseases and treatments. YouTube was accessed to learn about medical procedures such as surgery. No participant reported editing or contributing to Wikipedia or posting YouTube videos related to health topics. Twitter was rarely used for health-related purposes. Social media allowed consumers to obtain and provide disease and treatment-related information and social and emotional support for those living with the same condition. Most considered their participation as observational, but some also contributed (eg, responded to people's questions). CONCLUSIONS:Participants used a wide range of social media for health-related purposes. Medical information exchange (eg, disease and treatment) and social and emotional support were the cornerstones of their online activities. Social media appears to be used as a key tool to support disease self-management.

Project description:ImportanceLittle is known about how discrimination in health care relates to inequities in hospital-based care because of limitations in the ability to measure discrimination. Consumer reviews offer a novel source of data to capture experiences of discrimination in health care settings.ObjectiveTo examine how health care consumers perceive and report discrimination through public consumer reviews.Design, setting, and participantsThis qualitative study assessed Yelp online reviews from January 1, 2011, to December 31, 2020, of 100 randomly selected acute care hospitals in the US. Word filtering was used to identify reviews potentially related to discrimination by using keywords abstracted from the Everyday Discrimination Scale, a commonly used questionnaire to measure discrimination. A codebook was developed through a modified grounded theory and qualitative content analysis approach to categorize recurrent themes of discrimination, which was then applied to the hospital reviews.ExposuresReported experiences of discrimination within a health care setting.Main outcomes and measuresPerceptions of how discrimination in health care is experienced and reported by consumers.ResultsA total of 10 535 reviews were collected. Reviews were filtered by words commonly associated with discriminatory experiences, which identified 2986 reviews potentially related to discrimination. Using the codebook, the team manually identified 182 reviews that described at least 1 instance of discrimination. Acts of discrimination were categorized by actors of discrimination (individual vs institution), setting (clinical vs nonclinical), and directionality (whether consumers expressed discriminatory beliefs toward health care staff). A total of 53 reviews (29.1%) were coded as examples of institutional racism; 89 reviews (48.9%) mentioned acts of discrimination that occurred in clinical spaces as consumers were waiting for or actively receiving care; 25 reviews (13.7%) mentioned acts of discrimination that occurred in nonclinical spaces, such as lobbies; and 66 reviews (36.3%) documented discrimination by the consumer directed at the health care workforce. Acts of discrimination are described through 6 recurrent themes, including acts of commission, omission, unprofessionalism, disrespect, stereotyping, and dehumanizing.Conclusions and relevanceIn this qualitative study, consumer reviews were found to highlight recurrent patterns of discrimination within health care settings. Applying quality improvement tools, such as the Plan-Do-Study-Act cycle, to this source of data and this study's findings may help inform assessments and initiatives directed at reducing discrimination within the health care setting.

Dataset Information

Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.

Publications

Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets