Fulfilling information needs of patients in online health communities

被引：15
作者：
Chen, Donghua [1 ]
Zhang, Runtong [1 ]
Feng, Jiayi [1 ]
Liu, Kecheng [2 ]
机构：
[1] Beijing Jiaotong Univ, Sch Econ & Management, Dept Informat Management, Beijing 100044, Peoples R China
[2] Univ Reading, Henley Business Sch, Informat Res Ctr, Reading, Berks, England
来源：
HEALTH INFORMATION AND LIBRARIES JOURNAL | 2020年 / 37卷 / 01期
基金：
中国国家自然科学基金;
关键词：
China; consumer health information; health information needs; health literacy; information seeking behaviour; SOCIAL MEDIA; EXTRACTION; KNOWLEDGE; SUPPORT;
D O I：
10.1111/hir.12253
中图分类号：
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号：
1205 ; 120501 ;
摘要：
Background Online health communities (OHCs) experience difficulties in utilising patient reported posts to fulfil the information needs of online patients concerning health related issues. Objectives We aim to propose a comprehensive method that leverages medical domain knowledge to extract useful information from posts to fulfil information needs of online patients. Methods A knowledge representation framework based on authoritative knowledge sources in the medical field for the OHC is proposed. On the basis of the framework, a health related information extraction process for analysing the posts in the OHC is proposed. Then, knowledge support rate (KSR) and effective information rate (EIR) are introduced as metrics to evaluate changes in knowledge extracted from the knowledge sources in terms of fulfilling the information needs of patients in the OHC. Results On the basis of a data set with 372 343 posts in an OHC, experimental results indicate that our method effectively extracts relevant knowledge for online patients. Moreover, KSR and EIR are feasible metrics of changes in knowledge in terms of fulfilling the information needs. Conclusions The OHCs effectively fulfil the information needs of patients by utilising authoritative domain knowledge in the medical field. Knowledge based services for online patients facilitate an intelligent OHC in the future.
引用
收藏
页码：48 / 59
页数：12
相关论文
共 35 条
  • [1] Next Generation Phenotyping Using the Unified Medical Language System
    Adamusiak, Tomasz
    Shimoyama, Naoki
    Shimoyama, Mary
    [J]. JMIR MEDICAL INFORMATICS, 2014, 2 (01) : 20 - 33
  • [2] Network-Based Modeling and Intelligent Data Mining of Social Media for Improving Care
    Akay, Altug
    Dragomir, Andrei
    Erlandsson, Bjorn-Erik
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2015, 19 (01) : 210 - 218
  • [3] Enabling Online Studies of Conceptual Relationships Between Medical Terms: Developing an Efficient Web Platform
    Albin, Aaron
    Ji, Xiaonan
    Borlawsky, Tara B.
    Ye, Zhan
    Lin, Simon
    Payne, Philip R. O.
    Huang, Kun
    Xiang, Yang
    [J]. JMIR MEDICAL INFORMATICS, 2014, 2 (02) : 221 - 232
  • [4] Evaluation of semantic similarity metrics applied to the automatic retrieval of medical documents: An UMLS approach
    Alonso, Israel
    Contreras, David
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2016, 44 : 386 - 399
  • [5] Chen YS, 2014, IEEE ICC, P1825, DOI 10.1109/ICC.2014.6883588
  • [6] Use of "off-the-shelf" information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes
    Chiaramello, Emma
    Pinciroli, Francesco
    Bonalumi, Alberico
    Caroli, Angelo
    Tognola, Gabriella
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2016, 63 : 22 - 32
  • [7] Forty years of SNOMED: a literature review
    Cornet, Ronald
    de Keizer, Nicolette
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2008, 8 (Suppl 1)
  • [8] Organizing health services for patients with chronic pain: When there is a will there is a way
    Dobkin, Patricia L.
    Boothroyd, Lucy J.
    [J]. PAIN MEDICINE, 2008, 9 (07) : 881 - 889
  • [9] 'Keep complaining til someone listens': Exchanges of tacit healthcare knowledge in online illness communities
    Foster, Drew
    [J]. SOCIAL SCIENCE & MEDICINE, 2016, 166 : 25 - 32
  • [10] Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online
    Greaves, Felix
    Ramirez-Cano, Daniel
    Millett, Christopher
    Darzi, Ara
    Donaldson, Liam
    [J]. JOURNAL OF MEDICAL INTERNET RESEARCH, 2013, 15 (11)
1234