Tackling the Opioid Epidemic: Leveraging Linked Datasets for Insights and Informed Action

Communities across the country share a common sense of urgency to take action against rapidly escalating rates of preventable deaths associated with opioid use. While an increase in clinical opioid prescriptions and the introduction of synthetic opioids into the drug supply partially explain the national uptick in overdose and addiction rates, knowledge gaps surrounding more localized factors related to opioid use, addiction, overdose, and treatment makes developing responsive and evidence-based interventions a challenge for states and communities.

The linking of de-identified datasets from across health and social sectors presents a great opportunity for states and communities to build understanding of the opioid crisis as it manifests at a more local level, which can help to inform preventative interventions. Public agencies are often well positioned to organize such data sharing efforts, but developing a multi-sector dataset that allows for meaningful analytics and is legally compliant is no small feat, especially given the sensitive nature of data related to substance use, the legal structures governing such data sharing, and administrative and technical resources required for maintaining these efforts.

In a recent webinar, All In heard from experts from two health departments who have successfully developed de-identified linked datasets to better understand local opioid risk and to inform evidence-based state and community intervention efforts.

Example 1: Massachusetts Department of Public Health

Presenters from the Massachusetts Department of Public Health discussed their innovative project to link cross sector, state-level with the express purpose of informing the state’s response the opioid epidemic in Massachusetts. This effort is unique in part because it arose from a specific legislative mandate. In 2015, Massachusetts passed a new law calling for a comprehensive, aggregate, de-identified report on trends related to opioid use related deaths. This law expressly required cross-agency collaboration and specified that data sources would include the All Payer Claims Database, Medicaid, the Prescription Monitoring Program, substance use disorder treatment records, and public safety data.

While the legislation removed state barriers to data sharing, the health department still had to navigate federal laws related to data sharing, including HIPAA, the Medicaid Rules, and 42 CFR Part 2, which regulates the confidentiality of patient records associated with substance use disorders. In addition, the development of the aggregate, de-identified, comprehensive dataset involved overcoming challenges associated with data-related considerations like variations in structure, consistency, and storage across data sources, as well as decisions surrounding technical infrastructure that would allow for securely linking, storing, and accessing the database.

The health department leveraged a third-party linkage agent to match raw data files and produce a completely de-identified dataset. The end result included data from 22 different sources and from nine agencies. Keys to success included strong collaboration and a clear vision for the final project.

Increased understanding of the population at risk for opioid-related harms in Massachusetts has informed evidence-based policy change, including the allocation of resources to opioid prevention, treatment, and recovery services, changes in the medical school curriculum, and a pilot that aims to address opioid risk associated with the Massachusetts criminal justice system.

Example 2: Allegheny County, Pennsylvania Department of Human Services

The Allegheny County Department of Human Services has developed a county-wide data warehouse that lends insight into factors related to opioid use related deaths in the county. Unlike in Massachusetts, there is no All Payer Claims Database. However, Allegheny County’s uniquely comprehensive data warehouse integrates an array of data systems falling under the County umbrella, including vital records, supportive services, child and education services, juvenile and criminal justice, and physical and behavioral health data including Medicaid, substance use, and mental health data.

This impressive effort was championed by the director of Allegheny County Department of Human Services, and the sharing of data across sectors is supported and facilitated by Allegheny County, which is the legal covered entity managing the records.

While Allegheny County does leverage the data warehouse in a platform that allows front-line direct service professionals to access data for improved care, strict privacy laws surrounding substance use data limit the sharing of information relevant to opioid use disorder at the client level.

However, analyses of the integrated data have helped Allegheny County to better understand overdose deaths in the context of individual engagement with public systems and services, including the criminal justice system, behavioral health services, child welfare, and housing services. Discernable items include time between overdose death and last encounter with a public system, housing system encounters prior to an overdose, and prescriptions filled within 90 days of a fatal overdose. These data also help to illuminate the ripple effects of deaths associated with opioid use, such as adverse impacts on children who have been affected by an opioid-related death of a parent. Efforts are underway to use this data to predict overdose risk in Allegheny County, and altogether the integrated data warehouse has potential to inform the improvement of county-wide public services.

Visit alleghenycountyanalytics.us for more information, and to view a report enumerating risks and opportunities for intervention related to opiate-related overdose deaths in Allegheny County.

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