Digital health is a cultural transformation of traditional healthcare.
By Bertalan Meskó, Z. Drobni, E. Benyei, Bence Gergely, Z. Győrffy. mHealth, 2017
546 citations recorded by the source corpus.
Under the term "digital health", advanced medical technologies, disruptive innovations and digital communication have gradually become inseparable from providing best practice healthcare. While the cost of treating chronic conditions is increasing and doctor shortages are imminent worldwide, the needed transformation in the structure of healthcare and medicine fails to catch up with the rapid progress of the medical technology industry. This transition is slowed down by strict regulations; the reluctance of stakeholders in healthcare to change; and ignoring the importance of cultural changes and the human factor in an increasingly technological world. With access and adoption of technology getting higher, the risk of patients primarily turning to an accessible, but unregulated technological solution for their health problem is likely to increase. In this paper, we discuss how the old paradigm of the paternalistic model of medicine is transforming into an equal level partnership between patients and professionals and how it is aided and augmented by disruptive technologies. We attempt to define what digital health means and how it affects the status quo of care and also the study design in implementing technological innovations into the practice of medicine.
Subfields: Applied Psychology, Psychiatry and Mental health, Philosophy
View Paper: https://www.semanticscholar.org/paper/ed4e71df01d07c6ff1e87107853fc22a37350cfd
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Citations in the corpus
- A framework for digital health equity (2022, background): “For example, the digitization of healthcare may democratize the relationship between the individual and clinician, transforming the paternalistic paradigm of medicine into an equal partnership through data access and transparency 26 .”
- Remote patient monitoring using artificial intelligence: Current state, applications, and challenges (2023, background): “Although AI can transform healthcare with its potential to analyze, predict and classify data efficiently, there remains a hesitancy to adopt the technology (Mesk (cid:2) o et al., 2017).”