Abstract
Introduction:
Opioid use disorder (OUD) has grown rapidly over the years and is a public health crisis in the U.S. Though OUD is widely studied, relatively little is known about OUD among older adults. The goal of this study is to gain a better understanding of OUD among older Medicare beneficiaries over time and across several sociodemographic dimensions.
Methods:
Data from the 2013–2018 Centers for Medicare & Medicaid Services Master Beneficiary Summary Files were analyzed in 2020 to examine trends in OUD prevalence among Fee-for-Service Medicare beneficiaries aged ≥65 years. Utilizing the overarching opioid use disorder flag, trends in OUD prevalence were examined for the following sociodemographic dimensions: age, sex, race/ethnicity, and dual eligibility status (i.e., enrolled in both Medicare and Medicaid owing to low income). Chi-square tests were used to compare OUD prevalence across groups.
Results:
Since 2013, estimated rates of OUD among older adults have increased >3-fold overall in the U.S. Estimated OUD is more prevalent among the “young—old” (i.e., ages 65–69 years) beneficiaries than other older adults, and dually eligible beneficiaries have consistently shared a heavier burden of OUD compared with Medicare-only beneficiaries. Regarding race/ethnicity, Blacks and American Indians/Alaskan Natives are more vulnerable to OUD than other groups.
Conclusions:
The descriptive trends between 2013 and 2018 indicate that estimated OUD prevalence has increased greatly over the study period in all sociodemographic subgroups of older adults, highlighting an urgent challenge for public health professionals and gerontologists.
INTRODUCTION
The current opioid epidemic in the U.S. can be traced back to the 1990s, when opioid utilization started to rise.1 Individuals with opioid use disorder (OUD), the problematic use of opioids (e.g., narcotic prescriptions and illicit fentanyl) leading to clinical impairment or distress, are at high risk of death, morbidity, or other adverse health conditions.2,3 Recent longitudinal studies find that the mortality rate among OUD patients is at least twice as high as that of the general public.4,5 OUD patients also demonstrate a high prevalence of morbidity, such as infectious and cardiovascular diseases, which burden healthcare systems.6
Though the aforementioned studies improved understanding of the role of OUD in the opioid epidemic, older adults (i.e., aged ≥65 years) have been largely left out of previous research. Instead, researchers have focused on young and middle-aged adults,6,7 among whom the prevalence of opioid misuse is particularly high.8 As such, little is known about how older adults are affected by OUD. Some research, however, suggests that over the past decade, several opioid-related outcomes have been worsening among older adults, including prescription opioid misuse, opioid-related hospital stays, and emergency department (ED) visits.9–11 Importantly, between 2016 and 2017, older adults experienced the highest increases in the overall opioid-related mortality rate (17.2% increase) and prescription opioid mortality rate (10.5% increase).12 To gain a better understanding of OUD among older adults, this research brief examines the trend in OUD prevalence among older Medicare beneficiaries from 2013 to 2018 across several sociodemographic dimensions.
METHODS
Study Sample
This study used data from the following 2013–2018 Centers for Medicare & Medicaid Services Master Beneficiary Summary File segments: Base, Chronic Conditions, Other Chronic or Potentially Disabling Conditions, and Cost and Utilization. To be included in this analysis, Medicare beneficiaries had to be aged ≥65 years and continuously enrolled in Fee-for-Service Parts A, B, and D for all 12 months of the current year and previous year. Previous year enrollment was required because of the 1-year lookback period used in the OUD measure. Beneficiaries with cancer or in hospice care were excluded from the analysis owing to their high use of opioids.
Measures
Investigators defined OUD using the Master Beneficiary Summary File overarching opioid use disorder flag that is composed of 3 sub-indicators: (1) diagnosis and procedure basis for OUD,a (2) opioid-related hospitalization or ED visits,b and (3) use of medication-assisted treatment.c When any of the three criteria were met, the beneficiary was defined as having OUD.
Statistical Analysis
This study examined 2013–2018 trends in OUD prevalence across the following sociodemographic dimensions: age, sex, race/ethnicity, and dual eligibility (i.e., enrolled in both Medicare and Medicaid owing to low income). Chi-square tests were used to compare estimated OUD prevalence rates across groups. The chi-square statistic values can be found in Appendix Table 1.
RESULTS
All differences discussed were statistically significant (p<0.001) with 1 exception noted in this section. Estimated OUD prevalence (per 1,000 Medicare beneficiaries) is displayed in Table 1. The estimated OUD prevalence rate increased from 4.6 OUD cases per 1,000 beneficiaries in 2013 to 15.7 in 2018. Younger beneficiaries experienced higher estimated rates of OUD prevalence compared with older beneficiaries. Female beneficiaries had higher estimated rates of OUD compared with male beneficiaries and these differences increased over time. American Indian/Alaskan Native beneficiaries had the highest rates of estimated OUD prevalence, followed by Black, White, Hispanic, other race, and Asian/Pacific Islander beneficiaries. Dually eligible beneficiaries had significantly higher estimated OUD prevalence rates (8.4 in 2013) compared with Medicare-only beneficiaries (3.3 in 2013). Differences between these groups grew each year to an estimated rate of 29.2 for dually eligible beneficiaries and 12.9 for Medicare-only beneficiaries in 2018.
Table 1.
Estimated Opioid Use Disorder Prevalence per 1,000 Medicare Beneficiaries by Demographic Characteristics, 2013–2018
| Variable | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 |
|---|---|---|---|---|---|---|
| Opioid use disorder | 4.6 | 5.4 | 7.4 | 11.9 | 15.0 | 15.7 |
| Age, years | ||||||
| 65–69 | 8.6 | 9.6 | 12.1 | 17.3 | 21.0 | 22.1 |
| 70–74 | 4.9 | 5.8 | 7.8 | 12.0 | 14.8 | 15.5 |
| 75–79 | 3.6 | 4.3 | 6.2 | 10.5 | 13.3 | 14.0 |
| 80–84 | 2.9 | 3.4 | 5.2 | 9.5 | 12.6 | 13.0 |
| ≥85 | 2.1 | 2.5 | 4.0 | 8.1 | 11.2 | 11.7 |
| Sex | ||||||
| Male | 4.4 | 5.1 | 6.8 | 10.7 | 13.4 | 14.3 |
| Female | 4.7 | 5.6 | 7.8 | 12.6 | 16.0 | 16.7 |
| Race | ||||||
| White | 4.6 | 5.4 | 7.5 | 12.0 | 15.2 | 15.9 |
| Black | 6.3 | 7.5 | 9.9 | 15.6 | 19.6 | 20.9 |
| Asian/Pacific Islander | 1.2 | 1.4 | 2.1 | 3.7 | 5.0 | 5.3 |
| Hispanic | 3.9 | 4.5 | 6.4 | 10.2 | 13.2 | 13.7 |
| American Indian/Alaskan Native | 9.0 | 11.2 | 15.8 | 24.9 | 29.4 | 31.8 |
| Other race | 3.2 | 3.8 | 5.4 | 8.5 | 11.5 | 11.7 |
| Dual eligibility status | ||||||
| Medicare-only | 3.3 | 4.0 | 5.7 | 9.6 | 12.2 | 12.9 |
| Dual Medicare and Medicaid | 8.4 | 10.5 | 14.5 | 22.2 | 27.5 | 29.2 |
| Number of beneficiaries (in millions) | 10.7 | 12.2 | 12.7 | 13.3 | 13.7 | 13.9 |
Figure 1 shows the estimated OUD prevalence rate by age and dual eligibility status. As in Table 1, younger beneficiaries experienced higher estimated rates compared with older beneficiaries. Dually eligible beneficiaries also experienced significantly higher estimated prevalence rates of OUD compared with Medicare-only beneficiaries in each age group.
Figure 1.
Estimated opioid use disorder prevalence per 1,000 Medicare beneficiaries by age and dual eligibility status, 2013–2018. Note: All differences are statistically significant (p≤0.001).
Estimated OUD prevalence rates by sex and dual eligibility status are displayed in Figure 2. For both male and female beneficiaries, dually eligible beneficiaries had higher estimated OUD prevalence rates compared with Medicare-only beneficiaries and these differences increased over time. Although female beneficiaries experienced higher estimated rates of OUD prevalence in the bivariate case, when examining these differences by dual eligibility status, among dually eligible beneficiaries, male beneficiaries had higher estimated rates of OUD prevalence than female beneficiaries. Among Medicare-only beneficiaries, however, female beneficiaries had higher estimated rates than male beneficiaries.
Figure 2.
Estimated opioid use disorder prevalence per 1,000 Medicare beneficiaries by sex and dual eligibility status, 2013–2018. Note: All differences are statistically significant (p≤0.001).
Figure 3 shows the estimated OUD prevalence rate by race and dual eligibility status. Once dual eligibility status was considered, the findings were slightly different from the bivariate results. Among dually eligible beneficiaries, American Indians/Alaskan Natives continued to have the highest estimated OUD prevalence rates across all study years with the exception of 2013, when White beneficiaries had the highest estimated rates of OUD. Following American Indian/Alaskan Native beneficiaries, dually eligible beneficiaries with the highest estimated rates of OUD prevalence were White, Black, Hispanic, other race, and Asian/Pacific Islander beneficiaries. Hispanic beneficiaries switched rank with other race beneficiaries in 2018. A similar order was found for Medicare-only beneficiaries, but both White and Black beneficiaries and other race and Hispanic beneficiaries changed rank in some years. As was true in all other analyses, dually eligible beneficiaries had significantly higher estimated rates of OUD prevalence compared with Medicare-only beneficiaries for each racial group.
Figure 3.
Estimated opioid use disorder prevalence per 1,000 Medicare beneficiaries by race and dual eligibility status, 2013–2018. Note: All differences are statistically significant (p≤0.001) with the exception of Asian/Pacific Islander in 2013.
DISCUSSION
Since 2013, estimated rates of OUD have been increasing precipitously among older adults. Also, estimated prevalence of OUD has been consistently higher among dually eligible beneficiaries compared with Medicare-only beneficiaries. The risk for OUD that is associated with dual eligibility may be particularly strong among the “young—old” (e.g., ages 65–69 years) and among male beneficiaries. More research is needed to determine whether OUD among older adults, particularly dually eligible beneficiaries, develops later in life or rather represents a continuation of OUD experienced earlier in life. Additionally, more research is needed to determine whether the risk for OUD associated with dual eligibility is purely a function of beneficiary-level factors (e.g., lower SES among dually eligible beneficiaries), or whether provider-level factors also play a role (e.g., differences in prescription patterns for dually eligible beneficiaries).
Limitations
Although this study uses a multifaceted indicator of OUD, OUD prevalence among older adults may be underestimated, as this condition is often underdiagnosed and undercounted because of stigma. There are also reasons to believe OUD may be overestimated in this analysis. Older adults are particularly susceptible to opioid related hospitalizations and ED visits due to opioid adverse reactions that are not evidence of OUD.15 This could occur when they took an opioid pain reliever for pain management, but they experienced a bad drug interaction and thus an ED visit. To address this concern, a sensitivity analysis was performed (Appendix). It should be noted that marginalized populations (e.g., racial/ethnic minorities or the impoverished) may be more likely to be suspected of OUD owing to systematic discrimination,13,14 which may increase the rates of OUD among these groups.
CONCLUSIONS
In the U.S., OUD is a growing public health threat among older adults. Risk for OUD is particularly high among dually eligible beneficiaries, pointing to the urgent need for more research into the causes of this elevated risk.
Supplementary Material
ACKNOWLEDGMENTS
The views expressed in this article are those of the authors, and no official endorsement by HHS or the Centers for Medicare & Medicaid Services is intended or should be inferred. We acknowledge the support from the National Institute on Aging—funded Interdisciplinary Network on Rural Population Health and Aging group (R24-AG065159). This research benefited from grant P30AG066583, Center for Aging and Policy Studies, awarded to Syracuse University, in consortium with Cornell University and the University at Albany, by the National Institute of Aging. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Footnotes
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Beneficiaries must have at least 1 Medicare inpatient claim or 2 other non-drug claims of any service type with a related code in any position during the 2-year period. When 2 claims are required, they must occur at least 1 day apart.
Beneficiaries must have at least 1 Medicare inpatient claim or 1 ED claim with a related code in any position during the 2-year period.
Beneficiaries must have ≥1 drug claim with a national drug code for opioid medication-assisted treatment or ≥1 non-drug claim with a Healthcare Common Procedure Coding System code during the 2-year period.
No financial disclosures were reported by the authors of this paper.
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