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To effectively monitor, evaluate, and continuously improve local opioid crisis response efforts, cities and counties should implement a coordinated strategy for the systematic collection, integration, and use of data. This article outlines key data domains, common data sources and analytical strategies that will support evidence-based decision-making and help to design more informed strategies for community opioid response.

Introduction

Recent evidence indicates meaningful declines in U.S. opioid and overall drug overdose mortality rates after years of steady increases. CDC provisional data show that overdose deaths fell by roughly 24–27% between 2023 and 2024, representing the largest one-year decline on record and returning mortality to levels last seen around 2020. 

Generally, declining rates are consistent with a changing landscape in local government community response strategies. Many have attributed the reversal to programs like naloxone distribution, broader access to medications for opioid use disorder, therapeutic and peer-based supports, as well as improved public-health surveillance. However, larger trends point to a victorious outcome, regional and demographic sub-group risk patterns remain distinct and will require more tailored strategies. For many, this involves breaking down barriers to reach marginalized, ESL and/or underserved communities. These efforts can now be supported with state and federal settlement funds. One common barrier to effective use of these funds; however, is the knowledge needed around evidence-driven data collection systems and practices.  

Setting Goals

A comprehensive community opioid response begins with clearly defined, shared goals that reflect the complex nature of substance use and overdose. For communities seeking to implement new or enhanced strategies, the collection of socio-ecological data is an important overall consideration. With improved data use, cities and counties can begin identifying the precursors to fatal overdoses and invest in community assets that establish protective factors and improve determinants of health in affected communities.

Community-Level Indicators

To effectively monitor and evaluate the opioid crisis, a set of regularly observed and benchmarked community-wide indicators is crucial.  Data can be gathered across three broad community needs domains: 1) Opioid Risks; 2) Harm Prevention and Reduction; 3) Community Assets. The following indicators can help track trends, measure the effectiveness of interventions, and identify areas that need additional resources.

Opioid Risk Indicators. This domain captures data related to factors that increase the likelihood of opioid misuse, overdose, or opioid-related harm at both the individual and community levels. Indicators may include mental health calls for service, SUD-related deaths and arrests as well as prescription rates.

Harm Prevention and Reduction. This domain focuses on interventions and services designed to prevent overdose, reduce morbidity and mortality, and mitigate negative consequences associated with opioid use. Data may include naloxone distribution and administration, access to medications for opioid use disorder (MOUD), utilization of treatment and recovery services, crisis response encounters, and diversion and deflection activities. 

Community Assets. This domain reflects the protective resources and systemic capacities that support prevention, recovery, and long-term resilience. Community asset data may include availability of behavioral health providers, peer recovery supports, housing and employment services. Asset data help communities assess readiness, identify strengths, and strategically align resources to sustain recovery-oriented systems of care.

Individual-Level Opioid Response Indicators

Traditional community health needs assessments (CHNAs) rely on a single-shot surveys and/or focus groups from a small number of constituents. This is a limited way of capturing local health concerns and patterns of substance use that occur at the individual level. While surveys provide a snapshot of community needs, they fall short in capturing real-time and context-specific data necessary for meaningful intervention planning. Moreover, one-shot community surveys that can suffer from low participation rates, self-selection bias, and social desirability bias, leading to incomplete or skewed findings outside of the target sampling frame. 

A better measurement framework for community needs assessment, particularly in the context of substance use and opioid response, must integrate real-time data, multi-agency data, cross-sector/cross-intercept partnership information, and integration of program-level processes and outcomes. Table 2 focuses on individual and program-level data collection sources that fall within similar domains (e.g. Opioid Risks, Harm Prevention and Reduction, Community Assets) and also covers factors affecting access to referral and care. 

Access to Screening, Referral, and Treatment Services. This domain focuses on the availability, accessibility, and utilization of services that identify opioid-related risk and connect individuals to appropriate care. Data may include screening activity (e.g., SBIRT), referral pathways and completion rates, wait times for assessment or treatment, access to medications for opioid use disorder (MOUD), and continuity of care following emergency or justice-system contact. Data collection within this domain, involve a deep dive into consumer needs, risks and outcomes. 

To learn more about how to support data sharing and collection at the individual and program-level, access our website. And, when looking for the right data systems for collection and management of community response data, contact ARETGroup Co-Responder. 

Consideration for Data Use and Analysis 

Collaboration and Data Sharing. Collaborative data sharing agreements are essential tools that enable the secure and responsible exchange of individual-level identifiable information to be collected systematically across community opioid response partners. The goal of data sharing among ECS, EMS, Law Enforcement is to create an integrated system where information from multiple touch points in a community is collated and analyzed frequently or in real-time. This is an important goal to achieve when addressing opioid misuse, overdose prevention, and recovery efforts.

Tracking High-Risk Cases. One of the most critical advantages of collaborative data sharing for community needs and outcome tracking is the ability to identify high-risk individuals who are engaging with multiple service providers. A person who has frequent contacts with emergency services, rehab centers, and law enforcement may have underlying issues that need targeted intervention. Data sharing agreements enable agencies to identify individuals who might be slipping through the cracks or whose needs aren’t being fully addressed because their data is siloed. This could include individuals with a history of multiple opioid overdoses, arrests related to substance abuse, or recurring treatment failures.

Aggregate Data for Improved Services. Beyond individual case management, data sharing agreements also facilitate the collection of aggregate data across agencies. This can be useful for identifying broader trends (e.g., geographic areas with high rates of opioid overdoses, or demographics most at risk for relapse) and informing public health initiatives. By aggregating individual-level data in a de-identified form, agencies can better understand the scope of the problem and develop evidence-based policies and interventions.

Conclusion

ARETGroup provides premium enterprise SaaS applications for human services data management. Our vision is to combine day-to-day data collection needs with ‘first principle’ concepts for ethical research and evaluation. ARETGroup technology solutions meet rigorous national compliance standards. We offer specific solutions for justice & public safety, youth & education, and community health settings.