AWS Public Sector Blog

Open Data, Data Analytics, and Artificial Intelligence: How the Cloud is Taking on the Opioid Epidemic

The recent Winter Innovation Summit in Salt Lake City, Utah, showcased a breakthrough Sundance documentary, Dying in Vein. Its filmmaker, Jenny Mackenzie, joined a panel of public health and technology leaders, including Dr. Bill Hazel, former Secretary of Health and Human Resources for the Commonwealth of Virginia, and Alex Chan, CEO of the Clinton Foundation Health Initiative, to discuss opiate and heroin addiction, which, as the film highlights, claims an average of 90 lives in the U.S. daily. A prevailing theme that emerged cast the opioid epidemic as an issue of public health – rather than one of criminal justice – and pressed the role of technology in mitigating its risks.

(left to right: Dr. Jenny Mackenzie, filmmaker; Brad Bostic,; Rob Cohen, Appriss Health; Alex Chan, Clinton Foundation Health Matters Initiative; Secretary Bill Hazel, Commonwealth of Virginia; Michael Jackson, AWS)

Since the epidemic became a U.S. national emergency last August, technology companies have increasingly turned to the cloud to enhance the accessibility and analysis of opioid data. Through open data initiatives, data analytics, and artificial intelligence, AWS customers are building solutions to help underscore the issue to healthcare providers, agencies, and insurers, and make them a part of the solution.

Here are a few ways AWS customers and collaborators are striving to combat the epidemic:

  • The hc1 Opioid Dashboard, built on AWS, is a cloud-based information service that applies artificial intelligence to healthcare data. Designed for state, local, and federal governments, hc1’s dashboard allows drug-screening labs, healthcare providers and payers, pharmacists, and distributors to report opioid data to help uncover cases of misuse, abuse, and addiction. It also enables governments to measure the effectiveness of drug diversion programs and formulate strategies that could ultimately lead to earlier intervention and prevention.
  • OpenLattice, responsible for the underlying datasets powering the Data-Driven Justice initiative, has created a multi-sector data platform that provides members of the Greater Portland Addiction Collaborative with real-time information to track the success of its programs. The platform, formerly a White House initiative and now managed under the Laura and John Arnold Foundation, offers a holistic view of how resources are being used by the public. It does so by aggregating data from local hospitals, the City of Portland, the Portland Police Department, a community detox center, treatment providers, the recovery community, crisis providers, housing and employment providers, and peer recovery centers.
  • Appriss is another innovator working to mitigate the opioid crisis through the accessibility of quality data. It built a comprehensive prescription drug monitoring program using AWS, which is now host to 42 participating states. With the appropriate interstate agreements in place, the tool makes it possible to examine opioid records any time a doctor prescribes, or a pharmacist dispenses, an opioid drug. By linking information across states, medical doctors can quickly identify signs of misuse and abuse before writing prescriptions.

While there is no quick fix to the opioid epidemic, the availability of data to address each stage of addiction remains a critical gap. Should collaboration become the norm among the stakeholders in this mission, results could promise richer data from which to derive deeper insights in a secure and efficient way. And with cloud technology as the host for these efforts, there will be more opportunity to serve solutions to the public at scale.

Watch this video featuring the City of Iowa City, who is working with the Data-Driven Justice Initiative to identify high utilizers of law enforcement, emergency medical services, emergency rooms, and jail services in order to provide proactive mental health and substance abuse treatment and reduce recidivism.