1. Prescription Opioid Use Disorders: Trends and Correlates
Martin J. Dennis, Michael L. Dennis & Rodney R. Funk, Chestnut Health Systems, Normal, IL
Aims of Research
Methods
Results
Discussion
The aims of this research are to 1) explore the trends in opioid use disorders overall, by age and geography and 2) examine differences based on age.
Trends for people in the community are based on the 2012 National Survey on Drug Use and Heath (NSDUH; SAMHSA, 2012). Since 2002, the NSDUH has based on the same multistage area probability sample for each of the 50 states and the District of Columbia. Within each area census tracts (or groups of census tracks in rural areas) were randomly sampled; within those tracks census blocks were sampled; and within those blocks, households were listed and sampled. Within the sampled household all members were listed and sampled in to achieve a stratified sample by age that slightly over represented adolescents and young adults so that they could be broken out better. Respondents were given an incentive of $30 to complete the survey and 73% agreed to do so.. The graphs here are based on subsetting to just interviews were the respondents self-reported sufficient past year symptoms of the criteria to suggest an opioid use disorder. Data were weighted to represent the U.S. household population and adjusted to correct for non-response
Trends in treatment admissions are based on the Treatment Episode Data Set (TEDS; SAMHSA 2012). TEDS is based on a census of initial intake administrative records from public substance use disorder treatment programs as reported to state substance abuse agencies and then SAMHSA. Based on the NSDUH data on treatment participation, this is estimated to be about 88% of the admissions for adolescents and young adults and over 60% of those over age 25. The graphs here are based on subsetting to records where clients were reported as having any kind of opioid as a primary, secondary, and tertiary substance for treatment and/or in states that collect it a formal diagnosis. Records were also divided by substance (heroin vs. prescription opioid), year of admission, and age (under 18, 18-24, and 25 or more) Since it is a census, there is no need to weight the data.
Figure 1. Trends in Opioid Use Disorders in the
Community by Type of Substance
Figure 3. Trends in Opioid Treatment
Admissions by Substance
Early concerns about the rapid rise of prescription opioid use leading to increasing rates of prescription opioid misuse and the development of opioid use disorders appear to be founded. The rapid growth in opioid use disorders is clearly being driven by prescription opioid use disorders. While most people with opioid use disorders continue to be over the age of 25, the rate of growth among young adults (and adolescents in treatment) cohorts is growing much faster and will continue to fuel further growth among adults in the years ahead. Across age groups the economics of tolerance will also likely lead to further increases in heroin use and the associated risks of HIV and hepatitis C as well.
There are several limitations to this analysis that should be briefly discussed. While this is only an observational analysis, it is looking at trends over a long period of time. While the NSDUH data are based only on self report, but past year criteria are actually likely to be conservative (e.g, clinicians would also typically consider more than a year ago and course and other symptoms that the client might not self-identify). While the TEDS data vary by states in the scope of their public treatment system, degree of relying on mandates from the justice system, and quality/completeness of their data processing – yet these patterns are robust across all regions and most of the states. Thus, the consistent and long term nature of the pattern makes it important to address.
There are several implications of this analysis for funders and practices. Increased rates of opioid use disorders suggest the need to restore the availability of detoxification services that were widely cut during the recession. They also suggest the need for further investment in medication assisted treatment as there are now multiple medications that are FDA approved to help address withdrawal, reduce cravings, and block the ability to get the effects of opioids. Though not shown here, geographic variation in the rates of disorders are also correlated with local prescribing practices of medical and dental staff and suggest the ability of education to help as well. Several pharmaceutical companies are also working on medications that are more difficult to abuse. The growing rates among youth and young adults suggest the need for further prevention, screening and early intervention in school, and college and work settings where they are typically found.
Background
The increasing rates of prescribing prescription opioids in the past 20 years has been associated with increasing numbers of opioid related emergency room admissions and deaths. (Paulozzi et al 2011). From 2004 to 2010, there has been a 42% rise in drug related emergency room admissions, with the rates particularly high for prescription opioid alone (132%), prescription opioid + other illicit drugs (139%), prescription opioid + alcohol (+63%) or prescription opioid + illicit drugs + Alcohol (+94%) (Dennis, 2014).
In areas where prescription opioid misuse first starting rising, this has also led to a subsequent increase in opioid use disorders and a shift to lower cost heroin use driven by the economics of “tolerance” requiring increasingly more drugs to get the same effect; this in turn has led to increased needle use, risk of HIV and Hepatitis C (Hadland, 2013).
Earlier ages of on set and increasing prevalence of both prescription opioid misuse and heroin use has led to increasing rates opioid use disorders, which have now risen to be the third most common substance use disorder (after alcohol and marijuana) among both people in the community and entering treatment (O’Grady, Surratt, & Kurtz, 2014).
There is also evidenced that the demographic composition of opioid users is also shifting. Over the past 50 years, they are increasingly more likely to be white, female, over the age of 25 and from outside of large urban area (Cicero, Ellis, Surratt, & Kurtz, 2014).
Source: SAMHSA 2012 NSDUH data
Source: Treatment Episode Data Set A (primary, secondary or tertiary)
Figure 2. Trends in Prescription Opioid Use
Disorders in the Community by Age
Figure 4. Trends in Prescription Opioid
Treatment Admissions by Age
Source: SAMHSA 2012 NSDUH data
Source: Treatment Episode Data Set A (primary, secondary or tertiary)
Figure 1 shows that from 2002 to 2011 the number of people with opioid use disorders (OUD) rose 38%, with OUD being primarily driven by prescription opioid misuse. The number of people with prescription opioid use disorders is 3 times higher than heroin use disorders, but the increase of heroin use disorders was actually faster (104%). Figure 2 shows that over half the people with prescription opioid use disorders were over the age of 25, but that the rate of growth was highest (+55%) among those age
Figure 3 reveals that from 1992 to 2010, there has been a 127% increase in opioid related treatment admissions overall, including a 676% increase in treatment admission for prescription opioids. Figure 4 shows that over half of these prescription opioid use admission were for adults over the age of 24. But like in the community, the rate of growth of prescription Opioid Treatment admissions are growing even more rapidly for young adults ages 18 to 24 (+2717%).and adolescents (2288%) than adults (+484%).
Contact Information
Poster 156 at the College of Problems on Drug Dependence (CPDD), San Juan, PR, June 18, 2014 available from Supported by NIDA grant no. R37 DA Questions and comments can be directed to Martin J. Dennis, Chestnut Health Systems, 448 Wylie Drive, Normal, IL 61761, Phone: , or .

2. References:
Cicero, T. J., Ellis, M. S., Surratt, H. L., & Kurtz, S. P. (2014). The changing face of heroin us in the United States: A retrospective analysis of the past 50 years. JAMA Psychiatry.
Hadland, S. E. (2013). Risk of Hepatitis C among heroin and prescription opioid-injecting youth. Journal of Adolescent Health, 52(2 Supplement 1), S1-S2.
O’Grady, C. L., Surratt, H. L., Kurtz, S. P., & Levi-Minzi, M. A. (2014). Nonmdical prescription users in private vs. public substance abuse treatment: a cross sectional comparison of demographic and HIV risk behavior profiles. Substance Abuse Treatment, Prevention, and Policy, 2014, 9:9.
Paulozzi L, Mack K, Rudd R, Jones C. Vital signs: Overdoses of prescription opioid pain relievers—United States, 1999–2008. MMWR, vol 60, 1487–
Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality (SAMHSA/CBHSQ, 2012National Survey on Drug Use and Health: 2-Year R-DAS (2002 to 2003, 2004 to 2005, 2006 to 2007, 2008 to 2009, and 2010 to 2011). ICPSR34482-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor],
Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality (SAMHSA/CBHSQ, 2012). Treatment Episode Data Set -- Admissions (TEDS-A) --Concatenated, 1992 to ICPSR25221-v5. Ann Arbor, MI:Inter-university Consortium for Political and Social Research [distributor], doi: /ICPSR25221.v5