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

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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

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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.

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