A fundamental challenge of the opioid epidemic is that overdose victims die because they are alone or among untrained or impaired bystanders. Yet opioid deaths are readily preventable with early detection and appropriate supportive care. As mortality continues to rise, new approaches are needed to prevent deaths from opioid overdose. The long-term goal of this research program is to develop low-cost, mobile overdose detection and signaling modalities to optimize outcomes in patients at high risk for opioid overdose. The overall objective of this specific proposal is to evaluate whether two existing, clinically validated, low-cost respiratory sensing systems can be modified to reliably detect overdose events. The central hypotheses are that: (1) existing, portable respiratory sensing systems can be modified to accurately detect the entire spectrum of abnormal respiratory mechanics arising from overdose events; and (2) high-risk individuals will use such a sensing system as a low-cost life-saving intervention. This K23 award is an essential element of my evolution as an independent physician scientist, as it will allow me to obtain new training in patient-oriented research and enable me to collect key preliminary data for a future, larger scale intervention. Guided by strong preliminary data on two existing mobile respiratory sensing systems, the central hypotheses will be investigated in 3 specific aims:
Aim 1. Determine the feasibility of mobile, low-cost, non-invasive respiratory sensing systems to accurately identify rapid and prolonged apnea events in a safe, controlled, operating room setting, using induction of general anesthesia during elective surgery as an acute, fentanyl-induced overdose model;
Aim 2. Determine the feasibility and preliminary efficacy of mobile sensing systems to detect opioid-induced respiratory depression and overdose events in a real-world opioid using population, in a pilot diagnostic study of participants self-injecting opioids in a supervised injection facility (SIF) in nearby Vancouver, BC;
Aim 3. Measure stakeholder acceptance of using and disseminating mobile overdose detection technologies, using a qualitative approach involving structured interviews with opioid prescribers, chronic pain patients and people who inject opioids. The approach is innovative because it will utilize existing, low-cost mobile sensing systems to identify potentially lethal prolonged apnea events in humans, using induction of general anesthesia as a physiologic overdose model. The study will also be the first to utilize a SIF to measure the continuum of respiratory physiology generated from real-world opioid self-injection events. The proposed research is significant, because at the completion of the 3 Aims, the team will have obtained user feedback and generated the necessary data to implement a low-cost, truly ubiquitous system capable of identifying (and eventually signaling to EMS and bystanders) acute overdose events.
The proposed research is relevant to public health as it directly attempts to reduce morbidity and mortality associated with opioid overdose through the development of low-cost, mobile systems capable of detecting acute overdose events. Thus, the proposed research is relevant to the NIH mission by applying knowledge to enhance health, lengthen life, and reduce illness and disability. !