Intest Res  
What’s app? Electronic health technology in inflammatory bowel disease
Alissa Walsh, Simon Travis
Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, UK
Correspondence to: Alissa Walsh, Translational Gastroenterology Unit, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK. Tel: +44-7495920267, E-mail: alissa.walsh@ndm.ox.ac.uk
Received: March 13, 2018; Revised: May 9, 2018; Accepted: May 10, 2018; Published online: July 11, 2018.
© Korean Association for the Study of Intestinal Diseases. All rights reserved.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Electronic health (eHealth) data collection is increasingly used in many chronic illnesses, to track pattern of disease. eHealth systems have the potential to revolutionize care. Inflammatory bowel disease (IBD) is a paradigm for such an approach: this is a chronic disease that usually affects young and technologically literate patient population, who are motivated to be involved in their own care. A range of eHealth technologies are available for IBD. This review considers the strengths and weaknesses of 7 platforms that focus on patient-provider interaction. These have been developed in Denmark, United States, the Netherlands, and the United Kingdom, demonstrating an international interest in this form of technology and interaction. Not only do these technologies aim to improve care but they also have the potential to collect large amounts of information. Information includes demographics and patient reported outcomes (symptoms, quality of life), quality of care (steroid use, among other metrics) and outcomes such as hospitalization. These data could inform quality improvement programmes to improve their focus. eHealth technology is also open to machine learning to analyze large data sets, through which personalized algorithms may be developed.
Keywords: Mobile applications; Electronic health records; Inflammatory bowel disease


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