Rapid opioid overdose response system technologies

Joseph Tay Wee Teck*, Alberto Oteo Perez, Alexander Mario Baldacchino

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)
10 Downloads (Pure)

Abstract

Purpose of review 

Opioid overdose events are a time sensitive medical emergency, which is often reversible with naloxone administration if detected in time. Many countries are facing rising opioid overdose deaths and have been implementing rapid opioid overdose response Systems (ROORS). We describe how technology is increasingly being used in ROORS design, implementation and delivery.

Recent findings 

Technology can contribute in significant ways to ROORS design, implementation, and delivery. Artificial intelligence-based modelling and simulations alongside wastewater-based epidemiology can be used to inform policy decisions around naloxone access laws and effective naloxone distribution strategies. Data linkage and machine learning projects can support service delivery organizations to mobilize and distribute community resources in support of ROORS. Digital phenotyping is an advancement in data linkage and machine learning projects, potentially leading to precision overdose responses. At the coalface, opioid overdose detection devices through fixed location or wearable sensors, improved connectivity, smartphone applications and drone-based emergency naloxone delivery all have a role in improving outcomes from opioid overdose. Data driven technologies also have an important role in empowering community responses to opioid overdose.

Summary 

This review highlights the importance of technology applied to every aspect of ROORS. Key areas of development include the need to protect marginalized groups from algorithmic bias, a better understanding of individual overdose trajectories and new reversal agents and improved drug delivery methods.

Original languageEnglish
Pages (from-to)308-315
Number of pages8
JournalCurrent Opinion in Psychiatry
Volume36
Issue number4
Early online date26 Apr 2023
DOIs
Publication statusPublished - 1 Jul 2023

Keywords

  • Technology
  • Opioid overdose
  • Naloxone
  • Artificial Intelligence
  • Big data analytics

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