Answering diabetic patients' questions using expert-vetted online resources: A case study

Yuqun Zeng, Xusheng Liu, Liwei Wang, Hongfang D Liu, Yanshan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As an increasing number of patients seek medical information online, it is crucial to bring expert-vetted information to patients. Multiple expert-vetted online resources exist for their accuracy and authority of medical knowledge. However, it is not clear which resource is better in meeting the information needs of the patients. Utilizing a collection of questions raised by patients with diabetes retrieved from an online forum, we manually evaluated three widely used expert-vetted online resources (WebMD, MedlinePlus, and UpToDate) in terms of content coverage and time spent to find answers. The results indicated that WebMD had slightly better content coverage with less time spent in finding answers. Leveraging the Natural Language Processing (NLP) techniques and a clinical terminology resource, the Unified Medical Language System (UMLS), we demonstrated that WebMD had a higher mapping rate of clinical concepts comparing to other resources.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages525-528
Number of pages4
ISBN (Electronic)9781509016105
DOIs
StatePublished - Jan 17 2017
Event2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China
Duration: Dec 15 2016Dec 18 2016

Other

Other2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
CountryChina
CityShenzhen
Period12/15/1612/18/16

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Keywords

  • Diabetes
  • Expert-vetted online resources
  • Natural language processing

ASJC Scopus subject areas

  • Genetics
  • Medicine (miscellaneous)
  • Genetics(clinical)
  • Biochemistry, medical
  • Biochemistry
  • Molecular Medicine
  • Health Informatics

Cite this

Zeng, Y., Liu, X., Wang, L., Liu, H. D., & Wang, Y. (2017). Answering diabetic patients' questions using expert-vetted online resources: A case study. In Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 (pp. 525-528). [7822575] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2016.7822575