As state policymakers confront the substance use disorder (SUD) epidemic, they require a wide range of data – often found in disparate systems – to understand its impact and craft more effective treatment programs and interventions. This report explores best practices and sources for data gathering and describes how states can help communities access and use data to support local efforts.
The nation’s substance use disorder (SUD) epidemic poses unique challenges for policymakers working to understand and apply data – which often exists in disparate systems – to guide their treatment and interventions. States, localities, and organizations need to access and generate reliable data, not just in health and behavioral health care, but in workforce, criminal justice, social services, and other systems to design successful SUD interventions.
This report describes the uses and limitations of commonly available data sets that can stand alone or be used in conjunction with other data to answer common questions posed by state and local leaders. The report reviews common data sources that can help state leaders address key issues, such as preventing SUD and diversion of controlled substances, supporting harm reduction, increasing treatment capacity and service delivery, and understanding the needs of vulnerable populations. The report also highlights best practices at the state level, and notes where state strategies can also assist communities in accessing and using data to support local efforts.
The State SUD Data Landscape
Policymakers have access to data sets that are collected, compiled, analyzed, and maintained by state and federal agencies and other entities responsible for providing or overseeing services related to the prevention, reduction, or treatment of SUD. The following highlights data sets that are commonly used by state policymakers in their efforts to analyze key SUD indicators.
Individual claims and administrative and programmatic data collected by states: Individual-level data sets that tie to the unique experiences of one person through a system can help illuminate the ways that individuals and populations seek and use services. This data is often personally identifiable, which requires either consent, legally authorized use, or systematic anonymization that removes identifying characteristics.
|Medicaid claims and encounter data||State Medicaid agency
Medicaid managed care organization
|· Patient demographic data
· Diagnostic/service codes
· Service utilization data
|Prescription drug monitoring programs (PDMPs)||State licensing boards, public health agencies, or free-standing PDMP agency||Patient and prescriber data related to scheduled prescription drugs|
|Vital statistics, forensic epidemiology, or medical examiner/coroner reports||State public health or vital statistics agencies||· Deceased demographic data
· International Classification of Diseases 9-10 codes identifying causes of death
· Toxicology reports
|Homeless management information systems||State housing or social service agencies||Housing program services and client data, including self-reported diagnoses|
|Infectious disease data||State public health agencies||Surveillance data on hepatitis B/C and HIV infections|
|Behavioral health services data||State behavioral health agencies||· Non-Medicaid-funded services for SUD delivered by community behavioral health systems or state hospitals
· Provider licensure information
|Emergency medical systems data||State public health agencies||Overdose response data, including naloxone deployment|
|Hospital admissions and discharge data||State public health agencies||Overdoses treated in hospital settings and/or discharges coded as overdose-related|
|Corrections||State and local corrections agencies||Health and behavioral health assessment and treatment data for incarcerated individuals|
De-identified state/federal data sets available to researchers, organizations, and the public: Aggregate data sets can also be helpful to understand system interactions and population trends. These kinds of data are valuable in gauging systemwide behaviors as well as shifts in services, demographics, or activities that indicate the needs of a given region or population.
|All-payer claims databases (APCD)||Independent state or quasi-governmental organizations||Insurance claims from across payer sources|
|Behavioral Risk Factor Surveillance System (BRFSS)||Centers for Disease Control and Prevention (CDC)||Self-reported health risk factor and health condition data|
|Census data||US Census Bureau||Self-reported demographic data|
|National Overdose Report||CDC||Overdose deaths by demographics, states/regions, and substances present|
|Annual HIV Surveillance Report||CDC||HIV infections by demographics, states/regions, and transmission factors|
|National Survey on Drug use and Health (NDSUH)||Substance Abuse and Mental Health Services Administration (SAMHSA)||Self-reported substance use, mental health, and treatment services by demographics and state/region|
SUD Data Use Cases for State and Community Leaders
The following data use cases and strategies describe how available data can be used, often in innovative ways, to inform and guide state and local policy decisions.
Best Practices in Using Data to Support State and Local Policy Development
Comprehensive data – often gathered from across state, local, and federal resources – enables state and local leaders to tailor their prevention, treatment, and recovery responses and make the most of scarce resources. However, effectively using available data, matching or comparing complementary data sets, and identifying what should be the focus of analyses can be complicated. The following are key considerations for states seeking to improve data quality, explore data-sharing opportunities, and analyze existing data sets across systems.
Leadership is critical: Sharing data across state silos is challenging – many agencies generally prefer not to release data. Encouraging the sharing of health care and related data sets requires unifying leadership and a vision that can maintain momentum through many programmatic, legal, and technical hurdles. In some states, such as Pennsylvania, the governor used a disaster declaration to bring agencies to the table to create and sustain that state’s multi-agency data capacity. Other states, such as Massachusetts, made significant progress in cross-agency data sharing through legislation. That state’s Chapter 55 public law, passed in 2015, provided the impetus and structure needed for that state’s many SUD data innovations.
Engage both technical and policy expertise to make the most of existing data: While technical expertise in essential, policy and programmatic expertise is also a critical factor in successfully using data to support SUD prevention, treatment, and recovery. Data insights help state policymakers understand and explain variances in eligibility groups, interactions between specialty programs, and flag anomalies in the data due to program idiosyncrasies. Data also helps guide analysts in shaping metrics that will have value for policy decision-making.
Allow time and resources to address data governance: How substance use data is stored and shared is covered by both the Health Insurance Portability and Accountability Act (HIPAA) and 42 CFR Part 2 – the latter is specific to SUD data and imposes privacy standards that are often more stringent than those found in HIPAA. With few exceptions, providers and stewards of SUD data must obtain consent before sharing personally identifiable information that is protected by 42 CR Part 2. States can make the most of sharing data across agencies by building in time and resources to manage data governance issues:
- Data use agreements help to clearly articulate how organizations will use data, and specifically how it supports policy development. This Centers for Medicare & Medicaid Services fact sheet on DUAs outlines necessary components, helpful tips, and includes state example documents. Recognizing the limitations of all data sets included in a DUA also helps to expedite work. Confidentiality issues can be addressed clearly and completely, eliminating onerous approaches to de-identification or aggregation that may not ultimately be necessary. State agencies may have existing DUAs in place that can support new/emerging uses.
- Massachusetts was able to combine protected data from across ten disparate state agencies through a project-specific de-identification process that assigned random identifiers to each record. The state also developed a series of legal agreements that covered how data would be linked, shared, hosted, and accessed.
- Timeliness of data in a rapidly shifting substance use epidemic can be a challenge for virtually all data sets, as very few reporting systems offer real-time data. Longer lags, however, particularly those that pass more than a year from collecting data to reporting, make some data sets better used for understanding the landscape in retrospect rather than as a planning tool. Some states use unconfirmed data when necessary to track particularly urgent indicators, such as drug overdose deaths.
- Completeness of data sets – and the lack thereof – can also pose limitations for policymakers and is a major factor in data quality. State Medicaid enrollees, for instance, may move on and off the program as individual eligibility fluctuates, creating gaps in coverage and in key data points, such as current addresses. Encounter data from Medicaid managed care plans can also be problematic – states can improve encounter data quality through contract incentives, regular communication, and guidance. State-level guidance to providers and/or managed care organizations may be required to improve completeness of data
Many data sets produced by state and federal agencies have value when used individually, but when data can be shared and presented in new ways, it begins to tell a more comprehensive story of the particular and highly localized impact of SUD across systems and populations. There has been unprecedented activity at the state level in recent years to identify and use data sources to better understand and address state and local needs to prevent SUD, reduce the harms caused by SUD, and promote treatment and recovery. While states adopt indicators and metrics that meet specific state needs, there is an increasingly innovative menu of options to support their efforts.
Acknowledgements: The National Academy for State Health Policy provided this report with the ongoing support of JBS International and the federal Health Resources and Services Administration (HRSA). The authors would like to thank Lisa Patton, PhD, Vice President of Health Optimization Program and RCORP-TA Project Director at JBS International, and Marcia Colburn, MSW, Program Analyst in the Federal Office of Rural Health Policy at HRSA, for their continued guidance and expertise in supporting this work.