JMIR Research Protocols (Sep 2024)

Overdose Detection Among High-Risk Opioid Users Via a Wearable Chest Sensor in a Supervised Injecting Facility: Protocol for an Observational Study

  • Basak Tas,
  • Will Lawn,
  • Marianne Jauncey,
  • Mark Bartlett,
  • Paul Dietze,
  • Daniel O'Keefe,
  • Nico Clark,
  • Bruce Henderson,
  • Catriona Cowan,
  • Osian Meredith,
  • John Strang

DOI
https://doi.org/10.2196/57367
Journal volume & issue
Vol. 13
p. e57367

Abstract

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BackgroundOpioid overdose is a global health crisis, affecting over 27 million individuals worldwide, with more than 100,000 drug overdose deaths in the United States in 2022-2023. This protocol outlines the development of the PneumoWave chest biosensor, a wearable device being designed to detect respiratory depression in real time through chest motion measurement, intending to enhance early intervention and thereby reduce fatalities. ObjectiveThe study aims to (1) differentiate opioid-induced respiratory depression (OIRD) from nonfatal opioid use patterns to develop and refine an overdose detection algorithm and (2) examine participants’ acceptability of the chest biosensor. MethodsThe study adopts an observational design over a 6-month period. The biosensor, a small device, will be worn by consenting participants during injecting events to capture chest motion data. Safe injecting facilities (SIF) in Melbourne, Victoria (site 1), and Sydney, New South Wales (site 2), which are legally sanctioned spaces where individuals can use preobtained illicit drugs under medical supervision. Each site is anticipated to recruit up to 100 participants who inject opioids and attend the SIF. Participants will wear the biosensor during supervised injecting events at both sites. The biosensor will attempt to capture data on an anticipated 40 adverse drug events. The biosensor’s ability to detect OIRD will be compared to the staff-identified events that use standard protocols for managing overdoses. Measurements will include (1) chest wall movement measured by the biosensor, securely streamed to a cloud, and analyzed to refine an overdose detection algorithm and (2) acute events or potential overdose identified by site staff. Acceptability will be measured by a feedback questionnaire as many times as the participant is willing to throughout the study. ResultsAs of April 2024, a total of 47 participants have been enrolled and data from 1145 injecting events have already been collected, including 10 overdose events. This consists of 17 females and 30 males with an average age of 45 years. Data analysis is ongoing. ConclusionsThis protocol establishes a foundation for advancing wearable technology in opioid overdose prevention within SIFs. The study will provide chest wall movement data and associated overdose data that will be used to train an algorithm that allows the biosensor to detect an overdose. The study will contribute crucial insights into OIRD, emphasizing the biosensor’s potential step forward in real-time intervention strategies. International Registered Report Identifier (IRRID)DERR1-10.2196/57367