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Identifying Oncological Patient Information Needs to Improve e‐Health Communication: a preliminary text‐mining analysis
Author(s) -
Falotico Rosa,
Liberati Caterina,
Zappa Paola
Publication year - 2015
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1853
Subject(s) - health care , content analysis , knowledge management , extant taxon , computer science , psychology , medicine , sociology , social science , evolutionary biology , economics , biology , economic growth
Extant healthcare literature has demonstrated that providing oncological patients with detailed, continuous, and diversified information on their pathology positively affects patient empowerment and care continuum effectiveness. Medical information is traditionally conveyed by physicians and professional care givers. In the latest years, however, there has been a rapid rise in the use of web media as a source of health information. Improving cancer care continuum requires also the implementation of a reliable and high‐quality oncological web communication system, as well as a deeper understanding of patients' requirements in this respect. To the best of our knowledge, however, no papers have investigated the importance and role of web communication, and of websites, in particular. This work aims to address these aspects explicitly, proposing the use of text mining as a tool for identifying oncological patient communication needs. For this purpose, we conducted an exploratory study on a sample of rare cancer patients. Text mining techniques were applied on transcriptions of semi‐structured interviews on patients' information requirements, and the text content was synthetized. By means of correspondence analysis, the main concepts expressed by patients were identified, and the association between patients and concepts was represented in an appropriate metric space. Although our study is at an early stage, the findings highlighted by this preliminary text mining analysis could support the design of a patient‐centered e‐health communication system and be the basis for further analysis. Copyright © 2015 John Wiley & Sons, Ltd.