Researchers such as MIT Szymon Fedor and Mintu P. Turakhia of Stanford University recently published a review in The New England Journal of Medicine, illustrating the applications, challenges, and future of wearable digital health technologies in two scenarios: depressive disorders and cardiovascular diseases [1], [2].
The authors believe that the objective, high-frequency, longitudinal, and dimensionally rich information provided by wearable digital health technology in normal life scenarios has high clinical value, which is a good supplement to routine clinical information, and can help better track patient status for more timely adjustments/interventions [1], [2].
However, there are still some problems in this technology, such as the heterogeneity of data in different populations (the same data has different meanings for different populations), the difficulty of data integration and interpretation, the low transparency (the original data and processing algorithms are rarely provided), the relative difficulty of insisting on use, privacy concerns, the need for adjustment of medical staffing and medical insurance policy support, and the need to confirm its medical value with rigorous clinical trials [1], [2].
Data provided by wearable digital health technologies and their potential interpretable information [1].
Combined with wearable digital health technology to monitor the rehabilitation mode of cardiovascular patients[2].
The authors believe that the key to the future is to combine large-scale clinical trials to help people better understand the data generated by these wearable digital health technologies and their potential for clinical applications [1], [2].
These two works were published in The New England Journal of Medicine on December 28, 2023 and January 24, 2024, respectively[1], [2].
Comment(s):
A very vivid and multi-dimensional review.
Perhaps in the future, the data generated by the massive amount of naturally occurring wearable digital health technology can be used to guide the design or prioritization of relevant clinical trials by combining it with preliminary analysis such as machine learning.
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Bibliography:
[1] S. Fedor, R. Lewis, P. Pedrelli, D. Mischoulon, J. Curtiss, and R. W. Picard, “Wearable Technology in Clinical Practice for Depressive Disorder,” N. Engl. J. Med., vol. 389, no. 26, pp. 2457–2466, Dec. 2023, doi: 10.1056/NEJMra2215898.
[2] E. S. Spatz, G. S. Ginsburg, J. S. Rumsfeld, and M. P. Turakhia, “Wearable Digital Health Technologies for Monitoring in Cardiovascular Medicine,” N. Engl. J. Med., vol. 390, no. 4, pp. 346–356, Jan. 2024, doi: 10.1056/NEJMra2301903.
Original link:
https://www.nejm.org/doi/full/10.1056/NEJMra2215898
https://www.nejm.org/doi/full/10.1056/NEJMra2301903