Chronic disease in a digital health environment. Issue 1 (1st February 2018)

• Record Type: Journal Article
• Authors: Pearce, Christopher
• Is Part Of: Family medicine and community health. Volume 6:Issue 1(2018)
• Page Start: 20
• Page End: 25
• Publication Date: 2018-02-01
• Subjects: Ehealth -- digital health -- chronic disease -- patient centred medicine -- health systems; Family medicine -- Periodicals; Public health -- Periodicals; Family medicine; Public health; Family Practice; Community Health Services; General Practice; Electronic journals; Periodicals; Periodical; 610.5
• DOI: 10.15212/FMCH.2017.0144
• Languages: English
• ISSNs: 2305-6983

Abstract

Abstract : Although we know that there are benefits to individual patients from electronic data, the next potential, and potentially the biggest, benefit will come from the technologies known as big data, machine learning, and artificial intelligence . Harnessing the potential of computers to sift through large amounts of data will result in the possibility of generating insights into individual patients, and into whole populations, predicting the risk of hospital admission for an individual, or tracking influenza epidemics to prepare adequate responses. Once the data are reliable, recorded in a computer-interpretable way, new horizons will open. Significance statement: The health care of individual patients and communities is being affected by two distinct changes: the increase in chronic disease (with emphasis on continuing management and preventive care) and the development of digital health using electronic tools to manage and improve care. Caring for patients with chronic disease requires regular monitoring of progress, the involvement of multiple health professionals who are often not in the same institution, and the involvement of the patient and the patient's family. Thus care becomes as much about managing information. Digital health is crucial to this process, with the ability to share information across institutions and with the patient. But to do so the information must be structured in such a way as to be machine interpretable, as well and human interpretable.