Data on drug overdose death rates, by drug type and selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Vital Statistics System, numerator data from annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics.2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

We collect data and report statistics on opioid, stimulant, and other substance use and their impact on health and well-being.

A. SUMMARY This dataset includes unintentional drug overdose death rates by race/ethnicity by year. This dataset is created using data from the California Electronic Death Registration System (CA-EDRS) via the Vital Records Business Intelligence System (VRBIS). Substance-related deaths are identified by reviewing the cause of death. Deaths caused by opioids, methamphetamine, and cocaine are included. Homicides and suicides are excluded. Ethnic and racial groups with fewer than 10 events are not tallied separately for privacy reasons but are included in the “all races” total.

Unintentional drug overdose death rates are calculated by dividing the total number of overdose deaths by race/ethnicity by the total population size for that demographic group and year and then multiplying by 100,000. The total population size is based on estimates from the US Census Bureau County Population Characteristics for San Francisco, 2022 Vintage by age, sex, race, and Hispanic origin.

These data differ from the data shared in the Preliminary Unintentional Drug Overdose Death by Year dataset since this dataset uses finalized counts of overdose deaths associated with cocaine, methamphetamine, and opioids only.

B. HOW THE DATASET IS CREATED This dataset is created by copying data from the Annual Substance Use Trends in San Francisco report from the San Francisco Department of Public Health Center on Substance Use and Health.

C. UPDATE PROCESS This dataset will be updated annually, typically at the end of the year.

D. HOW TO USE THIS DATASET N/A

E. RELATED DATASETS Overdose-Related 911 Responses by Emergency Medical Services Preliminary Unintentional Drug Overdose Deaths San Francisco Department of Public Health Substance Use Services

F. CHANGE LOG

• 12/16/2024 - Updated with 2023 data. Asian/Pacific Islander race/ethnicity group was changed to Asian.
• 12/16/2024 - Past year totals by race/ethnicity were revised after obtaining accurate race/ethnicity for some decedents that were previously marked as “unknown” race/ethnicity.

Data Source: DC Office of the Chief Medical Examiner (OCME) and American Community Survey (ACS) 1-Year Estimates

Why This Matters

Opioid-related overdoses have been continuously rising since the late 1990s, with synthetic opioids (such as Tramadol or Fentanyl) being responsible for a sharp rise in opioid-related deaths since 2013.

Opioid Use Disorder (OUD) is treatable, and recovery is possible. Accessing treatment can help people regain their health and continue avoid the dangers associated with opioid misuse.

Several systemic inequities, including disparities in the treatment of mental health disorders, have led to Black individuals dying from opioid overdoses at a higher rate than white individuals.

The District Response

LIVE.LONG.DC (LLDC) is the District’s strategic plan to reduce opioid use, misuse, and related deaths. The plan provides a strategic framework that guides opioid work and investments.

The District does work to prevent, reduce the harm of, treat, and aid in the recovery of opioid use. This includes educational efforts, supplying Naloxone, no-cost rides to initial treatment appointments, and recovery support services.

The Interactive, Ward-specific map provides information about opioid use disorder and substance us disorder-related resources and services available in the District.

A. SUMMARY This dataset includes data on a variety of substance use services funded by the San Francisco Department of Public Health (SFDPH). This dataset only includes Drug MediCal-certified residential treatment, withdrawal management, and methadone treatment. Other private non-Drug Medi-Cal treatment providers may operate in the city. Withdrawal management discharges are inclusive of anyone who left withdrawal management after admission and may include someone who left before completing withdrawal management.

This dataset also includes naloxone distribution from the SFDPH Behavioral Health Services Naloxone Clearinghouse and the SFDPH-funded Drug Overdose Prevention and Education program. Both programs distribute naloxone to various community-based organizations who then distribute naloxone to their program participants. Programs may also receive naloxone from other sources. Data from these other sources is not included in this dataset.

Finally, this dataset includes the number of clients on medications for opioid use disorder (MOUD).

The number of people who were treated with methadone at a Drug Medi-Cal certified Opioid Treatment Program (OTP) by year is populated by the San Francisco Department of Public Health (SFDPH) Behavioral Health Services Quality Management (BHSQM) program. OTPs in San Francisco are required to submit patient billing data in an electronic medical record system called Avatar. BHSQM calculates the number of people who received methadone annually based on Avatar data. Data only from Drug MediCal certified OTPs were included in this dataset.

The number of people who receive buprenorphine by year is populated from the Controlled Substance Utilization Review and Evaluation System (CURES), administered by the California Department of Justice. All licensed prescribers in California are required to document controlled substance prescriptions in CURES. The Center on Substance Use and Health calculates the total number of people who received a buprenorphine prescription annually based on CURES data. Formulations of buprenorphine that are prescribed only for pain management are excluded.

People may receive buprenorphine and methadone in the same year, so you cannot add the Buprenorphine Clients by Year, and Methadone Clients by Year data together to get the total number of unique people receiving medications for opioid use disorder.

For more information on where to find treatment in San Francisco, visit findtreatment-sf.org. 

B. HOW THE DATASET IS CREATED This dataset is created by copying the data into this dataset from the SFDPH Behavioral Health Services Quality Management Program, the California Controlled Substance Utilization Review and Evaluation System (CURES), and the Office of Overdose Prevention.

C. UPDATE PROCESS Residential Substance Use Treatment, Withdrawal Management, Methadone, and Naloxone data are updated quarterly with a 45-day delay. Buprenorphine data are updated quarterly and when the state makes this data available, usually at a 5-month delay.

D. HOW TO USE THIS DATASET Throughout the year this dataset may include partial year data for methadone and buprenorphine treatment. As both methadone and buprenorphine are used as long-term treatments for opioid use disorder, many people on treatment at the end of one calendar year will continue into the next. For this reason, doubling (methadone), or quadrupling (buprenorphine) partial year data will not accurately project year-end totals.

E. RELATED DATASETS Overdose-Related 911 Responses by Emergency Medical Services Unintentional Overdose Death Rates by Race/Ethnicity Preliminary Unintentional Drug Overdose Deaths

U.S. Opiate Prescriptions

Accidental death by fatal drug overdose is a rising trend in the United States. What can you do to help?

This dataset contains summaries of prescription records for 250 common opioid and non-opioid drugs written by 25,000 unique licensed medical professionals in 2014 in the United States for citizens covered under Class D Medicare as well as some metadata about the doctors themselves. This is a small subset of data that was sourced from cms.gov. The full dataset contains almost 24 million prescription instances in long format. I have cleaned and compiled this data here in a format with 1 row per prescriber and limited the approximately 1 million total unique prescribers down to 25,000 to keep it manageable. If you are interested in more data, you can get the script I used to assemble the dataset here and run it yourself. The main data is in prescriber-info.csv. There is also opioids.csv that contains the names of all opioid drugs included in the data and overdoses.csv that contains information on opioid related drug overdose fatalities.

The increase in overdose fatalities is a well-known problem, and the search for possible solutions is an ongoing effort. My primary interest in this dataset is detecting sources of significant quantities of opiate prescriptions. However, there is plenty of other studies to perform, and I am interested to see what other Kagglers will come up with, or if they can improve the model I have already built.

The data consists of the following characteristics for each prescriber

• NPI – unique National Provider Identifier number
• Gender - (M/F)
• State - U.S. State by abbreviation
• Credentials - set of initials indicative of medical degree
• Specialty - description of type of medicinal practice
• A long list of drugs with numeric values indicating the total number of prescriptions written for the year by that individual
• Opioid.Prescriber - a boolean label indicating whether or not that individual prescribed opiate drugs more than 10 times in the year

Injury from poisoning exists under several Injury Intents: unintentional (accidental), intentional self-harm, assault, undetermined and adverse effect and underdosing. Only injuries in the first four categories are reported here combined. The data show rates per 100,000 people in order to standardize between areas with different population levels. Except for age specific rates, we use age-adjusted rates because they take into account where one age group dominates a population and thus are more representative. We use diagnosis by hospital records for non-fatal injury and cause of death from death certificates for fatal injury information.

Annual number of deaths registered related to drug poisoning, by local authority, England and Wales.

BackgroundWorldwide opioid-related overdose has become a major public health crisis. People with opioid use disorder (OUD) are overrepresented in the criminal justice system and at higher risk for opioid-related mortality. However, correctional facilities frequently adopt an abstinence-only approach, seldom offering the gold standard opioid agonist treatment (OAT) to incarcerated persons with OUD. In an attempt to inform adequate management of OUD among incarcerated persons, we conducted a systematic review of opioid-related interventions delivered before, during, and after incarceration.Methods and findingsWe systematically reviewed 8 electronic databases for original, peer-reviewed literature published between January 2008 and October 2019. Our review included studies conducted among adult participants with OUD who were incarcerated or recently released into the community (≤90 days post-incarceration). The search identified 2,356 articles, 46 of which met the inclusion criteria based on assessments by 2 independent reviewers. Thirty studies were conducted in North America, 9 in Europe, and 7 in Asia/Oceania. The systematic review included 22 randomized control trials (RCTs), 3 non-randomized clinical trials, and 21 observational studies. Eight observational studies utilized administrative data and included large sample sizes (median of 10,419 [range 2273–131,472] participants), and 13 observational studies utilized primary data, with a median of 140 (range 27–960) participants. RCTs and non-randomized clinical trials included a median of 198 (range 15–1,557) and 44 (range 27–382) participants, respectively. Twelve studies included only men, 1 study included only women, and in the remaining 33 studies, the percentage of women was below 30%. The majority of study participants were middle-aged adults (36–55 years). Participants treated at a correctional facility with methadone maintenance treatment (MMT) or buprenorphine (BPN)/naloxone (NLX) had lower rates of illicit opioid use, had higher adherence to OUD treatment, were less likely to be re-incarcerated, and were more likely to be working 1 year post-incarceration. Participants who received MMT or BPN/NLX while incarcerated had fewer nonfatal overdoses and lower mortality. The main limitation of our systematic review is the high heterogeneity of studies (different designs, settings, populations, treatments, and outcomes), precluding a meta-analysis. Other study limitations include the insufficient data about incarcerated women with OUD, and the lack of information about incarcerated populations with OUD who are not included in published research.ConclusionsIn this carefully conducted systematic review, we found that correctional facilities should scale up OAT among incarcerated persons with OUD. The strategy is likely to decrease opioid-related overdose and mortality, reduce opioid use and other risky behaviors during and after incarceration, and improve retention in addiction treatment after prison release. Immediate OAT after prison release and additional preventive strategies such as the distribution of NLX kits to at-risk individuals upon release greatly decrease the occurrence of opioid-related overdose and mortality. In an effort to mitigate the impact of the opioid-related overdose crisis, it is crucial to scale up OAT and opioid-related overdose prevention strategies (e.g., NLX) within a continuum of treatment before, during, and after incarceration.

Data from surveillance reports provide information on opioid- and stimulant-related harms (deaths, hospitalizations, emergency department visits, and responses by emergency medical services) in Canada. The Public Health Agency of Canada (PHAC) works closely with the provinces and territories to collect and share accurate information about the overdose crisis in order to provide a national picture of the public health impact of opioids and other drugs in Canada and to help guide efforts to reduce substance-related harms.

This dataset contains frequencies, rates, and proportions that describe drug toxicity deaths in Nova Scotia over time and space and by certain demographic and contextual characteristics. See usage considerations for further details on these data.

This CBHSQ Data Brief presents findings from the evaluation of the State Targeted Response to the Opioid Crisis Grants (Opioid STR) that describe how funding was used to support peer services for people with or recovering from opioid use disorder (OUD). The evaluation revealed that most Opioid STR grantees used funds to implement, expand, or enhance peer services. The peer services most commonly provided were coaching, mentoring, and providing information and referrals to relevant services.The Opioid STR was the predecessor of the State Opioid Response (SOR) grant program and informed its development. At the start of SOR, grantees were expected to provide an array of services based on needs identified in their STR strategic plan. SOR addresses the opioid overdose crisis by providing resources to states and territories for increasing access to FDA-approved medications for the treatment of opioid use disorder (MOUD), and for supporting the continuum of prevention, harm reduction, treatment, and recovery support services.

Medi-Cal claims for persons receiving medication-assisted treatment for opioid use disorders are unduplicated by medication. Methadone program participation is identified from claims submitted by the counties. Buprenorphine and naltrexone pharmacy claims are those used for treating opioid use disorders. Naloxone pharmacy claims are those dispensed as a first aid item (injectables and nasal sprays). The county source is taken from submitted claims.

Age adjusted rate of deaths from heroin overdoses among residents of Santa Clara County by total population and sex; trends if available. Source: California Department of Public Health. California Opioid Overdose Surveillance Dashboard. California Department of Public Health. https://discovery.cdph.ca.gov/CDIC/ODdash/METADATA:Notes (String): Lists table title, note and sourceYear (Numeric): Year of dataRate per 100,000 people (Numeric): Age adjusted rate of deaths from heroin overdoses among residents of Santa Clara County (rate per 100,000 people)

A listing of each accidental death associated with drug overdose in Connecticut from 2012 to 2021. A "Y" value under the different substance columns indicates that particular substance was detected.

Data are derived from an investigation by the Office of the Chief Medical Examiner which includes the toxicity report, death certificate, as well as a scene investigation.

The “Morphine (Not Heroin)” values are related to the differences between how Morphine and Heroin are metabolized and therefor detected in the toxicity results. Heroin metabolizes to 6-MAM which then metabolizes to morphine. 6-MAM is unique to heroin, and has a short half-life (as does heroin itself). Thus, in some heroin deaths, the toxicity results will not indicate whether the morphine is from heroin or prescription morphine. In these cases the Medical Examiner may be able to determine the cause based on the scene investigation (such as finding heroin needles). If they find prescription morphine at the scene it is certified as “Morphine (not heroin).” Therefor, the Cause of Death may indicate Morphine, but the Heroin or Morphine (Not Heroin) may not be indicated.

“Any Opioid” – If the Medical Examiner cannot conclude whether it’s RX Morphine or heroin based morphine in the toxicity results, that column may be checked.

This dataset includes:1. Search terms used to identify codes that may represent a history of illicit opioid use 2. Codelist for identifying people with a history of illicit opioid use 3. Age- and sex-distribution of patients by product and clinical codes 4. Number of patients currently in the cohort5. Age of patients at cohort entry6. Internal validation based on hospital admissions for opioid dependence

ObjectivePrescription opioid misuse has led to a new cohort of opioid use disorder (OUD) patients who were introduced to opioids through a legitimate prescription. This change has caused a shift in the demographic profile of OUD patients from predominantly young men to middle age and older people. The management of OUD includes medication-assisted treatment (MAT), which produces varying rates of treatment response. In this study, we will examine whether the source of first opioid use has an effect on treatment outcomes in OUD. Using a systematic review of the literature, we will investigate the association between source of first opioid introduction and treatment outcomes defined as continuing illicit opioid use and poly-substance use while in MAT.MethodsMedline, EMBASE, CINHAL, and PsycInfo were searched from inception to December 31st, 2019 inclusive using a comprehensive search strategy. Five pairs of reviewers conducted screening and data extraction independently in duplicate. The review is conducted and reported according to the PRISMA guidelines. A random-effects model was used for meta analyses assuming heterogeneity among the included studies.ResultsThe initial search results in 27,345 articles that were screened, and five observational studies were included in the qualitative and quantitative analyses. Our results found that those who were introduced to opioids through a legitimate prescription were significantly less likely to have illicit opioid use (0.70, 95% CI 0.50, 0.99) while on MAT. They were also less likely to use cannabis (0.54, 95% CI 0.32, 0.89), alcohol (0.75, 95% CI 0.59, 0.95), cocaine (0.50, 95% CI 0.29, 0.85), and injection drug use (0.25, 95% CI 0.14, 0.43) than those introduced to opioids through recreational means.ConclusionThis study shows that the first exposure to opioids, whether through a prescription or recreationally, influences prognosis and treatment outcomes of opioid use disorder. Although the increased pattern of prescribing opioids may have led to increased OUD in a new cohort of patients, these patients are less likely to continue to use illicit drugs and have a different prognostic and clinical profile that requires a tailored approach to treatment.Systematic Review RegistrationPROSPERO CRD42017058143.

EMSIndicators:The number of individual patients administered naloxone by EMSThe number of naloxone administrations by EMSThe rate of EMS calls involving naloxone administrations per 10,000 residentsData Source:The Vermont Statewide Incident Reporting Network (SIREN) is a comprehensive electronic prehospital patient care data collection, analysis, and reporting system. EMS reporting serves several important functions, including legal documentation, quality improvement initiatives, billing, and evaluation of individual and agency performance measures.Law Enforcement Indicators:The Number of law enforcement responses to accidental opioid-related non-fatal overdosesData Source:The Drug Monitoring Initiative (DMI) was established by the Vermont Intelligence Center (VIC) in an effort to combat the opioid epidemic in Vermont. It serves as a repository of drug data for Vermont and manages overdose and seizure databases. Notes:Overdose data provided in this dashboard are derived from multiple sources and should be considered preliminary and therefore subject to change. Overdoses included are those that Vermont law enforcement responded to. Law enforcement personnel do not respond to every overdose, and therefore, the numbers in this report are not representative of all overdoses in the state. The overdoses included are limited to those that are suspected to have been caused, at least in part, by opioids. Inclusion is based on law enforcement's perception and representation in Records Management Systems (RMS). All Vermont law enforcement agencies are represented, with the exception of Norwich Police Department, Hartford Police Department, and Windsor Police Department, due to RMS access. Questions regarding this dataset can be directed to the Vermont Intelligence Center at dps.vicdrugs@vermont.gov.Overdoses Indicators:The number of accidental and undetermined opioid-related deathsThe number of accidental and undetermined opioid-related deaths with cocaine involvementThe percent of accidental and undetermined opioid-related deaths with cocaine involvementThe rate of accidental and undetermined opioid-related deathsThe rate of heroin nonfatal overdose per 10,000 ED visitsThe rate of opioid nonfatal overdose per 10,000 ED visitsThe rate of stimulant nonfatal overdose per 10,000 ED visitsData Source:Vermont requires towns to report all births, marriages, and deaths. These records, particularly birth and death records are used to study and monitor the health of a population. Deaths are reported via the Electronic Death Registration System. Vermont publishes annual Vital Statistics reports.The Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) captures and analyzes recent Emergency Department visit data for trends and signals of abnormal activity that may indicate the occurrence of significant public health events.Population Health Indicators:The percent of adolescents in grades 6-8 who used marijuana in the past 30 daysThe percent of adolescents in grades 9-12 who used marijuana in the past 30 daysThe percent of adolescents in grades 9-12 who drank any alcohol in the past 30 daysThe percent of adolescents in grades 9-12 who binge drank in the past 30 daysThe percent of adolescents in grades 9-12 who misused any prescription medications in the past 30 daysThe percent of adults who consumed alcohol in the past 30 daysThe percent of adults who binge drank in the past 30 daysThe percent of adults who used marijuana in the past 30 daysData Sources:The Vermont Youth Risk Behavior Survey (YRBS) is part of a national school-based surveillance system conducted by the Centers for Disease Control and Prevention (CDC). The YRBS monitors health risk behaviors that contribute to the leading causes of death and disability among youth and young adults.The Behavioral Risk Factor Surveillance System (BRFSS) is a telephone survey conducted annually among adults 18 and older. The Vermont BRFSS is completed by the Vermont Department of Health in collaboration with the Centers for Disease Control and Prevention (CDC).Notes:Prevalence estimates and trends for the 2021 Vermont YRBS were likely impacted by significant factors unique to 2021, including the COVID-19 pandemic and the delay of the survey administration period resulting in a younger population completing the survey. Students who participated in the 2021 YRBS may have had a different educational and social experience compared to previous participants. Disruptions, including remote learning, lack of social interactions, and extracurricular activities, are likely reflected in the survey results. As a result, no trend data is included in the 2021 report and caution should be used when interpreting and comparing the 2021 results to other years.The Vermont Department of Health (VDH) seeks to promote destigmatizing and equitable language. While the VDH uses the term "cannabis" to reflect updated terminology, the data sources referenced in this data brief use the term "marijuana" to refer to cannabis. Prescription Drugs Indicators:The average daily MMEThe average day's supplyThe average day's supply for opioid analgesic prescriptionsThe number of prescriptionsThe percent of the population receiving at least one prescriptionThe percent of prescriptionsThe proportion of opioid analgesic prescriptionsThe rate of prescriptions per 100 residentsData Source:The Vermont Prescription Monitoring System (VPMS) is an electronic data system that collects information on Schedule II-IV controlled substance prescriptions dispensed by pharmacies. VPMS proactively safeguards public health and safety while supporting the appropriate use of controlled substances. The program helps healthcare providers improve patient care. VPMS data is also a health statistics tool that is used to monitor statewide trends in the dispensing of prescriptions.Treatment Indicators:The number of times a new substance use disorder is diagnosed (Medicaid recipients index events)The number of times substance use disorder treatment is started within 14 days of diagnosis (Medicaid recipients initiation events)The number of times two or more treatment services are provided within 34 days of starting treatment (Medicaid recipients engagement events)The percent of times substance use disorder treatment is started within 14 days of diagnosis (Medicaid recipients initiation rate)The percent of times two or more treatment services are provided within 34 days of starting treatment (Medicaid recipients engagement rate)The MOUD treatment rate per 10,000 peopleThe number of people who received MOUD treatmentData Source:Vermont Medicaid ClaimsThe Vermont Prescription Monitoring System (VPMS)Substance Abuse Treatment Information System (SATIS)

Chronic obstructive pulmonary disease (COPD) is common among people who use illicit opioids. This study will estimate the incidence of diagnosed COPD and the rate of death due to COPD among patients in primary care in England with previous records of illicit opioid use, and compare this to patients without records of illicit opioid use. Among patients with a new COPD diagnosis, we estimate the association between illicit opioid use and the probability of preventative healthcare such as flu and pneumococcal vaccines or support with smoking cessation, and the association between illicit opioid use and adverse outcomes such as acute exacerbations and death. Data will be drawn from the Clinical Practice Research Datalink (CPRD), using a validated method to identify patients with a history of illicit opioid use. Patients without a history of illicit opioid use will be selected using a process called ‘exposure density sampling’ to create a cohort matched on age, sex, GP practice, and date of cohort entry.

The COVID-19 pandemic is adding to the ongoing public health crisis related to high rates of opioid overdose and deaths, as well as acute substance use harms. These crises are made worse in communities where there is chronic overcrowding, including a shortage of housing or other shelters.