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Evaluating passive physiological data collection during Spravato treatment.

Authors :
Solomon TM
Hajduk M
Majernik M
Jemison J
Deschamps A
Scoggins J
Kolar A
Pinheiro MA
Dubec P
Skala O
Muir O
Tinkelman A
Karlin DR
Barrow R
Source :
Frontiers in digital health [Front Digit Health] 2023 Nov 29; Vol. 5, pp. 1281529. Date of Electronic Publication: 2023 Nov 29 (Print Publication: 2023).
Publication Year :
2023

Abstract

Spravato and other drugs with consciousness-altering effects show significant promise for treating various mental health disorders. However, the effects of these treatments necessitate a substantial degree of patient monitoring which can be burdensome to healthcare providers and may make these treatments less accessible for prospective patients. Continuous passive monitoring via digital devices may be useful in reducing this burden. This proof-of-concept study tested the MindMed Session Monitoring System™ (MSMS™), a continuous passive monitoring system intended for use during treatment sessions involving pharmaceutical products with consciousness-altering effects. Participants completed 129 Spravato sessions with MSMS at an outpatient psychiatry clinic specializing in Spravato treatment. Results indicated high rates of data quality and self-reported usability among participants and health care providers (HCPs). These findings demonstrate the potential for systems such as MSMS to be used in consciousness-altering treatment sessions to assist with patient monitoring.<br />Competing Interests: TS, JJ, MH, MM, AD, PD, AK, MP, OS, DK and RB are employed by Mind Medicine, Inc., the Sponsor of this research. OM and AT were employed by Brooklyn Minds Psychiatry, the research site, during this study. All funding for this research was provided by the study sponsor, Mind Medicine, Inc.<br /> (© 2023 Solomon, Hajduk, Majernik, Jemison, Deschamps, Scoggins, Kolar, Pinheiro, Dubec, Skala, Muir, Tinkelman, Karlin and Barrow.)

Details

Language :
English
ISSN :
2673-253X
Volume :
5
Database :
MEDLINE
Journal :
Frontiers in digital health
Publication Type :
Academic Journal
Accession number :
38094111
Full Text :
https://doi.org/10.3389/fdgth.2023.1281529