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Leveraging digital measurement to potentially support treatment retention of opioid use disorder (OUD) to provide better care and prevent life-threatening situations

OUD is a public health epidemic. With an estimated 3 million U.S. citizens and 16 million individuals worldwide suffering from OUD, the relapse rate is devastatingly high, leading to unacceptably high death rates.

The Digital Health Measurement Collaborative Community (DATAcc) by the Digital Medicine Society (DiMe) and Duke BIG IDEAs Lab are collaborating on a project funded by FDA through the Triangle CERSI to inform the development of an equitable, scalable, and person-focused risk prediction tool for opioid relapse.

What are risk prediction engines, and how can they be used to support people living with OUD?

Risk prediction engines can predict specific outcomes by using algorithms to analyze patterns in data and are examples of machine learning (ML), a subset of artificial intelligence (AI).

Advances in sensor-based digital health technologies (sDHTs) – like smartphones, smartwatches, and smart rings – now allow for continuous tracking of health data, such as physical activity, sleep, heart rate, and breathing rate.

In a condition like OUD, risk prediction engines can use data collected from sDHTs to flag when a person is likely experiencing a trigger for opioid relapse and might need support during recovery.

The study

Through a mixed methods study, we will identify the perspectives of a representative sample of clinicians and patients affected by OUD on factors associated with relapse that can be measured by acceptable consumer technologies.

Informed by the mixed methods study and a systematic literature review, we will develop a scientific protocol, including ethical oversight, for developing and validating a risk prediction engine to supply valuable information to clinicians, trusted support networks, and individuals with opioid use disorder to prevent relapse, ultimately aiding in the prevention of 120,000 annual deaths caused by opioid abuse and misuse.

The impact

The maturity of sDHTs has reached a critical point, offering unprecedented opportunities to revolutionize healthcare.

DATAcc’s leadership is poised to deploy these sDHTs in the most impactful and powerful ways, leveraging digital tools to predict clinical events and proactively prevent adverse outcomes. We are committed to saving lives and improving patient care by fearlessly tackling the most impactful healthcare challenges.

Our partners

DATAcc is thrilled to collaborate with Duke BIG IDEAs Lab on this project, funded by FDA through the Triangle CERSI.

Join us for the launch of our Core Measures of Sleep Resources

On Wed., Apr. 24 at 11 a.m. ET., DATAcc’s Core Measures of Sleep project team will launch a new core set of sleep measures and resources to facilitate their implementation for the research and care community. These resources aim to transform research and care to advance overall population health and multiple diseases, the use of self-monitored health, and early intervention.

Join us and be among the first in the field to access the new resources.