U.S. Prescribing Rate Maps

About the Maps

The data in the maps show the geographic distribution in the United States, at both state and county levels, of retail opioid prescriptions dispensed per 100 persons from 2006–2016. ^a,b,c

Data are displayed within two types of interactive maps that show the estimated rate of opioid prescriptions per 100 U.S. residents. The state maps portray these rates for each of the 50 states plus the District of Columbia.  The county maps portray these rates for 87.6% to 93.4% of U.S. counties for a given year from 2006-2016.^d

Rates are classified by the Jenks^e natural breaks classification method into 4 groups using the 11-year range of data to determine the class breaks. Hover over a county or state to reveal its prescription rate or view the corresponding data table for additional information.

Key Highlights

• After a steady increase in the overall national opioid prescribing rate from 2006, the total number of prescriptions dispensed peaked in 2012 at more than 255 million and a prescribing rate of 81.3 prescriptions per 100 persons.
• The overall national opioid prescribing rate declined from 2012 to 2016, and in 2016, the prescribing rate had fallen to the lowest it had been in more than 10 years at 66.5 prescriptions per 100 persons (over 214 million total opioid prescriptions).
• However, in 2016, prescribing rates continue to remain very high in areas across the country.
  • In about a quarter of U.S. counties, enough opioid prescriptions were dispensed for every person to have one.
  • While the overall opioid prescribing rate in 2016 was 66.5 prescriptions per 100 people, some counties had rates that were seven times higher than that.
• Prescribing rates for opioids vary widely across different states and counties. Emerging hotspot areas are identified by the darker colors on the maps.

Table 1. Total number and rate of opioid prescriptions dispensed, United States, 2006–2016

Table 2. Total number and percentage of counties with available opioid prescribing data, United States, 2006–2016

Sources and Footnotes

1. Source for all prescribing data: QuintilesIMS Transactional Data Warehouse (TDW) 2006–2016.
   QuintilesIMS TDW is based on a sample of approximately 59,000 retail (non-hospital) pharmacies, which dispense nearly 88% of all retail prescriptions in the U.S. For this database, a prescription is an initial or refill prescription dispensed at a retail pharmacy in the sample, and paid for by commercial insurance, Medicaid, Medicare, or cash or its equivalent. Does not include mail order pharmacy data.
2. For the calculation of prescribing rates, numerators are the total number of opioid prescriptions dispensed in a given year, state, or county, as appropriate.  Annual resident population denominator estimates were obtained from the Population Estimates Program, U.S. Census Bureau. For population data, 2000–2010 Intercensal Estimates of the Resident Population for Counties and States were used for 2006–2010 rate calculations; 2010–2016 Postcensal Estimates of the Resident Population for Counties and National were used for 2011–2016.
3. Opioid prescriptions, including butrans (buprenorphine), codeine, fentanyl, hydrocodone, hydromorphone, methadone, morphine, oxycodone, oxymorphone, propoxyphene, tapentadol, and tramadol were identified using the National Drug Code. Cough and cold formulations containing opioids and buprenorphine, an opioid partial agonist used for treatment of opioid use disorder as well as for pain, were not included. In addition, methadone dispensed through methadone maintenance treatment programs is not included in QuintilesIMS TDW data.
4. Table 2 displays the percentage of counties in the U.S that have opioid prescribing rates available for a given year. A lack of available data may indicate that the county had no retail pharmacies, the county had no retail pharmacies sampled, or the prescription volume was erroneously attributed to an adjacent, more populous county according to the sampling rules used.
5. Jenks, George F. 1967. “The Data Model Concept in Statistical Mapping,” International Yearbook of Cartography 7: 186–190.