The Digital Medicine Society (DiMe) announced it is partnering with Alcohol and Drug Services (ADS), Duke University, Google Fitbit, Morse Clinics, North Carolina Central University, Ōura, ProofPilot, Triangle CERSI and the University of North Carolina at Chapel Hill (UNC).
The partnership aims to use data collected from consumer wearables to lower opioid use disorder (OUD) fatalities by creating interventions to help prevent relapse.
According to a 2023 National Survey on Drug Use and Health by the Substance Abuse and Mental Health Services Administration (SAMHSA), among people aged 12 or older in 2023, 2.0 percent (or 5.7 million people) had an opioid use disorder in the past year.
The partners will collaborate to describe and gather physiological signals and behavior traits, including heart rate, insomnia, physical inactivity and physiological stress, that can forecast relapse and be measured by wearable technologies.
Researchers will use smartphones to collect mental health characteristics such as social isolation, patient-reported anxiety and depression. The data points train a tool to prevent opioid relapse.
The team will proceed with research jointly led by Duke University’s BIG IDEAs Lab and enlist patients for a pilot study to test the approach and ensure that their methods obtain optimal-quality data to develop the relapse prevention tool.
“OUD is a complex challenge, and complex challenges require innovative collaboration and solutions,” Candice Taguibo, associate program director of DiMe, said in a statement.
“Our team is working to incorporate the many issues at play for those facing OUD – mental health, social support, treatment options, finances, access to technology, social stigma, and more – and build a tool that can meaningfully change the arc of OUD relapse and save thousands of lives.”
Shyamal Patel, senior vice president of science at Oura, asserted that leveraging technological advancements to develop evidence-based protocols for people living with OUD will position these interventions for success.
“We’re proud to support this study by providing continuous health monitoring and personalized, data-driven insights. This can empower individuals to take proactive steps in their recovery, potentially reducing the burden on our overstretched public health systems and offering a crucial tool in the fight against the opioid epidemic,” Patel said in a statement.
THE LARGER TREND
In March, DiMe and Google Health introduced a free online course for medical professionals, researchers, administrators and innovators to learn the fundamentals of generative AI, large language models (LLMs) and the technologies’ use cases in healthcare.
The Generative AI for Healthcare course provides stakeholders with an understanding of LLMs and their applications in healthcare. In addition, participants will gain insights into generative AI technology, develop prompt engineering skills and explore how AI can support decision-making in clinical settings.
In 2024, Researchers from South Korea built machine learning-based models that can predict mood episodes using only sleep and circadian rhythm data from wearable devices.
The team comprised researchers from the Institute for Basic Sciences (IBS), Korea Advanced Institute of Science and Technology (KAIST) and Korea University College of Medicine.
In a study published in Nature’s Digital Medicine journal, the research team first collected and analyzed 429 days’ worth of sleep-wake data generated from Fitbit of 168 Korean patients with mood disorders, including major depression and bipolar disorders.
The research team extracted 36 sleep and circadian rhythm features from this dataset, which were then applied to train models based on the machine learning library XGBoost to predict mood episodes.
The findings revealed that the predictive models achieved 80%, 98% and 95% accuracy in predicting depressive, manic and hypomanic episodes, respectively.
That same year, Oura closed a $200 million Series D funding round led by Fidelity Management & Research Company and Dexcom. The investment raised the company’s valuation to $5.2 billion.
In November 2024, Dexcom made a $75 million strategic investment in Oura and established a strategic partnership that enabled two-way data flow between Dexcom’s continuous glucose monitor (CGM) and the Oura Ring. The investment at the time brought Oura’s valuation to more than $5 billion.
The Digital Medicine Society (DiMe) announced it is partnering with Alcohol and Drug Services (ADS), Duke University, Google Fitbit, Morse Clinics, North Carolina Central University, Ōura, ProofPilot, Triangle CERSI and the University of North Carolina at Chapel Hill (UNC). The partnership aims to use data collected from consumer wearables to lower opioid use disorder (OUD) fatalities by creating interventions to help prevent relapse. According to a 2023 National Survey on Drug Use and Health by the Substance Abuse and Mental Health Services Administration (SAMHSA), among people aged 12 or older in 2023, 2.0 percent (or 5.7 million people) had an opioid use disorder in the past year. The partners will collaborate to describe and gather physiological signals and behavior traits, including heart rate, insomnia, physical inactivity and physiological stress, that can forecast relapse and be measured by wearable technologies. Researchers will use smartphones to collect mental health characteristics such as social isolation, patient-reported anxiety and depression. The data points train a tool to prevent opioid relapse. The team will proceed with research jointly led by Duke University’s BIG IDEAs Lab and enlist patients for a pilot study to test the approach and ensure that their methods obtain optimal-quality data to develop the relapse prevention tool. “OUD is a complex challenge, and complex challenges require innovative collaboration and solutions,” Candice Taguibo, associate program director of DiMe, said in a statement. “Our team is working to incorporate the many issues at play for those facing OUD – mental health, social support, treatment options, finances, access to technology, social stigma, and more – and build a tool that can meaningfully change the arc of OUD relapse and save thousands of lives.” Shyamal Patel, senior vice president of science at Oura, asserted that leveraging technological advancements to develop evidence-based protocols for people living with OUD will position these interventions for success. “We’re proud to support this study by providing continuous health monitoring and personalized, data-driven insights. This can empower individuals to take proactive steps in their recovery, potentially reducing the burden on our overstretched public health systems and offering a crucial tool in the fight against the opioid epidemic,” Patel said in a statement. THE LARGER TREND In March, DiMe and Google Health introduced a free online course for medical professionals, researchers, administrators and innovators to learn the fundamentals of generative AI, large language models (LLMs) and the technologies’ use cases in healthcare. The Generative AI for Healthcare course provides stakeholders with an understanding of LLMs and their applications in healthcare. In addition, participants will gain insights into generative AI technology, develop prompt engineering skills and explore how AI can support decision-making in clinical settings. In 2024, Researchers from South Korea built machine learning-based models that can predict mood episodes using only sleep and circadian rhythm data from wearable devices. The team comprised researchers from the Institute for Basic Sciences (IBS), Korea Advanced Institute of Science and Technology (KAIST) and Korea University College of Medicine. In a study published in Nature’s Digital Medicine journal, the research team first collected and analyzed 429 days’ worth of sleep-wake data generated from Fitbit of 168 Korean patients with mood disorders, including major depression and bipolar disorders. The research team extracted 36 sleep and circadian rhythm features from this dataset, which were then applied to train models based on the machine learning library XGBoost to predict mood episodes. The findings revealed that the predictive models achieved 80%, 98% and 95% accuracy in predicting depressive, manic and hypomanic episodes, respectively. That same year, Oura closed a $200 million Series D funding round led by Fidelity Management & Research Company and Dexcom. The investment raised the company’s valuation to $5.2 billion. In November 2024, Dexcom made a $75 million strategic investment in Oura and established a strategic partnership that enabled two-way data flow between Dexcom’s continuous glucose monitor (CGM) and the Oura Ring. The investment at the time brought Oura’s valuation to more than $5 billion.
