A landmark settlement between state governments and several large pharmaceutical companies could help states exponentially expand their response to the opioid epidemic. The settlement alone would funnel up to $26 billion to states and communities struggling to respond to the crisis.

With the settlement’s strict guidelines defining how funds can be used and millions of families eager to see the settlement create lasting change in their communities, it’s critical that state leaders understand how to leverage data analytics to create the most positive resident outcomes for their programs.

Earlier this month, Voyatek’s VP of Analytics Adam Roy and Jodi Manz, Project Director at the National Academy for State Health Policy, hosted a webinar to discuss how states can create evidence-based opioid responses by leveraging data analytics and cross-agency data sharing. Here are some key takeaways from the session:

Maximizing the ROI of Settlement Funding

Because states have broad authority to determine how this funding will be used, it’s critical that states leverage this opportunity and invest in initiatives that can’t be done with other funding sources like State Opioid Response (SOR) dollars or Medicaid reimbursement.

It’s also important to keep in mind the historical context at play – this settlement is constantly being compared to the tobacco settlement of the 1990’s, and, unfortunately, the reality that many of those dollars ultimately went to causes unrelated to tobacco use prevention. Over the last 20 years, states have received over $157 billion from tobacco settlements, but studies have shown that only a fraction of that funding went toward programs focused on preventing tobacco use. The health community sees this as a missed opportunity given that tobacco use is still one of the leading causes of death 20 years later.

State and local leaders must learn from the mistakes made during that era. Data and analytics are key to ensuring that these investments deliver outcomes.

The Importance of Data and Analytics in a Statewide Response to the Opioid Epidemic

From a policymaker perspective, data is critical to building an effective statewide response. But there are also some big challenges to extracting value from that data. Many different state agencies and organizations play a role in combatting the opioid epidemic: state health departments, treatment centers, courts, social services – the list goes and on and on. Each of those entities has their own view of the crisis, but how do we see the full picture? This is where data comes in. Data is the key to understanding the on-the-ground reality as well as which programs and initiatives are successful.

For instance, without comprehensive data from a variety of sources, even obtaining an accurate count of the number of overdoses in a community is very challenging – and understanding overdose numbers is a core KPI of opioid response. States need to have a framework in place to bring data sets together so we can get the complete picture, make better decisions, and be more proactive and preventative in our activities.

Core Elements of a Substance Use Disorders (SUD) Data & Analytics Program

Every state is different, but there are universally important components of SUD data and analytics programs that will set states up for success.

The first is a data governance model and a data trust that will define how organizations and agencies share data with each other. Unlike typical data sharing agreements, which are usually static documents governing one-to-one sharing, a data trust is a master data sharing agreement that allows for growth. Instead of having to invest money in updating legal documents every time an organization wants access to data, the data trust allows for datasets and trust participants to be easily added, without risk to privacy or security.

Secondly, states need a scalable and secure data sharing platform that can be customized for different user types. We also recommend establishing a well-defined strategy to fully document all data and the metadata around it, so users of all types can easily find and use data that’s relevant to them.

This is where the final component, self-service analytics, comes in. Most people involved in the opioid response are not data scientists. Access to the raw data is not helpful. Self-service analytics – prebuilt dashboards, visualizations, reports – can help them quickly access what they need and have a bigger impact the epidemic.

The Virginia Case Study

The Commonwealth of Virginia is an example of how an investment in a data and analytics solution aided in the development and implementation of opioid policy priorities. Virginia’s Framework for Addiction Analysis and Community Transformation (FAACT) put data in the hands of policy makers and leaders, as well as law enforcement, healthcare, social services treatment facilities, community coalitions, faith-based, and nonfaith-based organizations.

FAACT enables policymakers to better understand the impact of the opioid epidemic at the local level and use that understanding to make more data-driven policy decisions. For example, FAACT revealed that one Virginia region had a higher than usual number of arrests for violent crimes that also involved the use of stimulants. Because the arrests were for violent crimes, the individuals were sent through criminal court instead of drug court. FAACT’s analysis showed that these individuals were often becoming repeat offenders, cycling through criminal court again and again – potentially because they were not able to access the treatment programs that they would have via drug court.  This led to policy changes around eligibility for drug court programs.

Other states can follow suit by using data and analytics to make key decisions around the use of state settlement funds in response to the current opioid epidemic. Understanding the data and building a plan that provides a holistic story of the community and the effects of opioids and other drugs within the community is key to developing an effective response and combatting substance use disorders.

Voyatek Leadership