Abstract
Context:
Older adults are less likely than younger adults to receive naloxone therapy. Given high rates of prescription opioid use/misuse and increasing illicit opioid use among older adults, factors associated with naloxone administration for older opioid poisoning cases need examination.
Methods:
We analyzed the 83,135 opioid-involved cases aged 50+ from the 2015–2020 National Poison Data System. Single-variable logistic regression was used to examine associations of naloxone administration with demographic factors, exposure site/reason, medical outcomes, management site/level of care, clinical effects, and other interventions. Multivariable logistic regression models were fit to examine associations of naloxone administration with different types of opioids.
Results:
Over the six years, the proportion of prescription opioid cases that received naloxone therapy increased steadily from 21.9% to 28.4%. The proportion of illicit opioid cases that received naloxone therapy was 51.9% in 2015 and 59.8% in 2020 with a high of 64.4% in 2019. In 2020, the death rate for illicit opioid cases without naloxone therapy was 31.4% compared to 2.3% for those with the therapy. Cases managed at healthcare facilities (HCF) had higher odds of receiving naloxone therapy. Among prescription opioid cases, naloxone therapy rates among older and female cases and those managed at non-HCF settings were especially low even for major medical outcomes. Cases involving oxycodone, morphine, methadone, prescription fentanyl, hydromorphone, oxymorphone, and other/unknown opioids had higher odds of naloxone administration.
Discussion:
Rates of naloxone therapy for older prescription opioid poisoning cases need improvement. While rates were higher among illicit opioid cases, the drop in 2020 and the sharp increase in deaths among illicit opioid cases without naloxone therapy confirm the importance of access to this life-saving intervention.
Conclusions:
Increased naloxone co-prescribing and other means of facilitating access to naloxone are needed to prevent opioid poisoning deaths among older adults who use prescription opioids.
Keywords: Poison control centers, older adults, prescription opioids, illicit opioids, opioid poisoning, naloxone, CNS depression
Introduction
Naloxone is a safe and effective opioid receptor antagonist for rapidly reversing or blocking opioids’ effects [1]. Naloxone therapy has increased over the past decade in the face of growing opioid overdose mortality. Data from the National Emergency Medical System (EMS) Information System showed that between 2013 and 2016, EMS naloxone administrations per capita rose at a faster rate than opioid-related overdose deaths across urban, suburban, and rural counties, with the highest rate in the suburban South [2]. EMS data also show that naloxone administrations increasingly involved young adults (aged 20–39) followed by those aged 40–49 and occurred in public settings with significant increases in the percentage of individuals requiring multiple doses and refusing subsequent care [2]. Analysis of the National Poison Data System (NPDS) also showed that the frequency of naloxone administration and recommendations (by poison control centers) increased from 9,498 in 2000 to 26,826 in 2016, with cases aged 20–39 being the largest share of those with naloxone reports [3].
Despite expanding naloxone therapy, studies, including those cited above, show that older adults (aged 50+), people with chronic illnesses, women, and those without signs of potential illicit drug abuse, such as drug paraphernalia or track marks, were less likely to be administered naloxone [4]. Even after the Centers for Disease Control and Prevention’s (CDC) March 2016 release of a category A recommendation for naloxone co-prescribing for adults at high-risk of opioid overdose (e.g., high dosage [≥ 50 morphine mg equivalent/day], concurrent benzodiazepine use), older internal medicine patients had lower rates of naloxone prescription (e.g., 3.9% and 1.9% in the 55–64 and 65+ age groups, respectively) than younger patients (e.g., 14.8% in the 25–34 age group) between April 2016 and December 2018 [5].
Lower rates of naloxone administration and prescription for older adults are concerning given that prescription opioids are involved in more than a third of opioid-involved overdose deaths in the United States, and older adults have the highest rate of prescription opioid use [6]. In 2018, 23.4 million patients aged 55+ filled an average of four opioid prescriptions [6]. Older adults also have the highest rate of long-term opioid use [7], which puts them at high risk of opioid misuse and dependence.
Although prescription opioid use rates among older adults have decreased in recent years, especially since publication of the CDC’s opioid prescription guideline in 2016 [8–10], prescription opioid misuse and overdose among this group remain significant. Our analysis of 2015–2019 National Survey on Drug Use and Health data showed that despite decreases in past-year prescription opioid use rates in the 50+ age group (noninstitutionalized) from 40.0% in 2015 to 34.2% in 2019, rates of misuse among users remained unchanged at an average of 6.4% during the 5-year period. According to the Office of Inspector General, about 5,000 Medicare Part D beneficiaries per month suffered an opioid overdose during the first eight months of 2020 [11]. Moreover, late-onset (age≥30) heroin use is increasing among those aged 50+ [12]. With rapid increases in fentanyl overdose deaths since 2015 (NIDA, 2021), the likelihood of unintentional exposure to fentanyl among older-adult heroin and other illicit substance users is also increasing given their limited ability to identify fentanyl in the drugs they use [13].
In this paper, using the NPDS, we first examined changes in naloxone administration among prescription and illicit opioid poisoning cases aged 50+ during the six year period from 2015 to 2020. We then examined naloxone administration’s associations with: (1) exposure year, census region, age, gender, medical outcomes, and management site; (2) clinical effects (poisoning signs and symptoms) and other therapeutic interventions; and (3) types of opioids--prescription vs. illicit opioids, with or without prescription opioids, and then specific types of prescription opioids, controlling for year, census region, age, gender, and select clinical effects. Study hypotheses were: (H1) compared to prescription opioid poisoning cases, illicit opioid cases will have higher odds of receiving naloxone therapy; and (H2) among prescription opioid cases, those involving oxycodone, morphine, methadone, prescription fentanyl, hydromorphone, oxymorphone, and hydrocodone will have higher odds of receiving naloxone therapy given previous research findings showing their high abuse liability and effects on the central nervous system (CNS) and respiratory depression [14–16]. As the first study focusing on naloxone administration among opioid poisoning cases aged 50+, the findings will add insight into demographic characteristics, clinical effects, and types of opioids associated with increased or decreased likelihood of naloxone administration among this age group.
Methods
Data source
We used the American Association of Poison Control Centers’ NPDS for January 2015 through December 2020 (see the NPDS website [https://aapcc.org/data-system] or Gummin et al. [17] for detailed NPDS descriptions). Given fentanyl’s increased presence in illicit drug markets since the latter part of the 2010s, we focused on the 2015–2020 NPDS in order to examine heroin and fentanyl cases along with prescription opioid cases. Of all cases from the 55 poison control centers reporting, 83,153 cases aged 50+ had any opioid involvement. Although the NPDS lists cases, not individuals, the extent to which these cases include duplicate individuals is minimal as poison center specialists are trained to detect duplication and correct it as soon as it is discovered. Based on the authors’ institutional IRB guidelines, IRB exemption was assumed for analysis of these de-identified, existing data.
Measures
Types of opioids
Prescription opioids in the NPDS included 23 types of narcotics (e.g., tramadol, oxycodone and hydrocodone alone or combination products [other than with acetaminophen or acetylsalicylic acid], morphine, methadone, buprenorphine, prescription fentanyl) as well as acetaminophen and acetylsalicylic acid combined with opioids. Illicit opioids included heroin, non-prescription fentanyl, and other synthetic, nonpharmaceutical opioids. We also present the number of opioids since multiple opioids were involved in some cases. We were unable to examine substance quantity (mg or tabs/pills/capsules) due to large amounts of missing data.
Demographics, exposure-related factors, medical outcomes, and management site/level of care
In addition to exposure year (2015–2020), census region of residence, age, and gender, we report exposure site (at own or other’s home vs. all other locations), exposure reason, medical outcomes, management site/level of care, and medical outcomes. For exposure reasons, we used four categories: unintentional poisoning (adverse reaction or unintentional therapeutic error, misuse, general, occupational, environmental, or unintentional but unknown reason); intentional misuse/abuse without suicidal intent; suspected suicide; and unknown or other reasons (e.g., withdrawal and malice). Medical outcomes from opioid poisoning included: no/minimal effect, moderate effect, major effect/potential toxic exposure, and death. Management sites/levels of care included: managed at exposure site (non-healthcare facility [HCF]); treated/evaluated and released from HCF; admitted to a critical care unit; admitted to a noncritical care unit; admitted to a psychiatric facility; refused referral/did not arrive at HCF; lost to follow-up/left against medical advice; and other/unknown management site/level of care.
Clinical effects
The NPDS allows up to 169 individual clinical effects (signs, symptoms, or laboratory abnormalities) for each case [17]. Each clinical effect is further defined as related, not related, or unknown if related. In this study, we focused on “related” effects that are common signs/symptoms of opioid poisoning.
Naloxone administration and other therapeutic interventions
In the NPDS, naloxone administration is recorded as performed; recommended (by poison control centers) and performed; recommended but not known if performed; recommended but not performed; or missing. In this study, we categorized “performed” and “recommended and performed” as administered and all the other categories as not administered. The other two “recommended” categories (unknown administration status and known non-administration status) were 1.0% of prescription opioid only and 0.6% of illicit opioid cases. We categorized other interventions in the same manner. According to the 2019 NPDS annual report [17], data on administration of all therapeutic interventions should be interpreted as underestimates because of the limitations of telephone data gathering. The NPDS does not provide data on single versus multiple administrations.
Analysis
All analyses were conducted with Stata 17/MP (Stata Corp, College Station, TX). We first calculated the numbers of prescription and illicit opioid poisoning cases aged 50+ by year (2015–2020) and used χ2 to examine changes in the proportions of naloxone administrations during the six years. Then, we used single-variable logistic regression analyses to examine the associations of naloxone administration with (1) year, census region, age group, gender, number of opioids involved, exposure site and reason, medical outcomes, and management site/level of care, and (2) clinical effects and other therapeutic interventions. To test H1 (associations of naloxone administration with prescription vs. illicit opioids) and H2 (associations of naloxone administration with different types of prescription opioids), we used multivariable logistic regression models controlling for year, census region, age group, gender, number of opioids involved, and the following clinical effects: CNS depression, respiratory problems, miosis, hypotension, bradycardia, acidosis, and cyanosis. Selection of these clinical effects was based on their significant odds of naloxone administration in single-variable logistic regression analyses. Single-variable and multivariable logistic regression results are reported as odds ratios (ORs) and 95% confidence intervals (CIs) and adjusted ORs (AORs) with 95% CIs, respectively. Statistical significance was set at p <.05.
Results
Changes in opioid poisoning cases and naloxone administration
Table 1 shows a gradual decrease in prescription opioid-only poisoning cases and a sharp increase in illicit opioid poisoning cases over the six-year study period. As a result, shares of illicit opioid cases among all opioid poisoning cases increased from 3.5% in 2015 to 11.2% in 2020. Among illicit opioid cases, 11.2% also involved prescription opioids. Over the six years, the proportion of prescription opioid cases administered naloxone gradually increased from 21.9% to 28.4%. The proportion of illicit opioid cases administered naloxone increased from 51.9% in 2015 to 59.8% in 2020 with a high of 64.4% in 2019. See Figure 1 for a graphic presentation of the changes.
Table 1.
Prescription and illicit opioid cases aged 50+ and the proportion administered naloxone by year, 2015–2020
| Prescription opioids (PO) only | Illicit opioids with or without PO | |||||
|---|---|---|---|---|---|---|
| N | No naloxone | Naloxone | N | No naloxone | Naloxone | |
| 2015 | 13,631 | 78.14 | 21.86 | 497 | 48.09 | 51.91 |
| 2016 | 13,926 | 77.38 | 22.62 | 792 | 37.75 | 62.25 |
| 2017 | 13,263 | 75.46 | 24.54 | 945 | 40.11 | 59.89 |
| 2018 | 12,460 | 75.24 | 24.76 | 985 | 42.84 | 57.16 |
| 2019 | 12,308 | 73.20 | 26.80 | 1,175 | 35.57 | 64.43 |
| 2020 | 11,678 | 71.61 | 28.39 | 1,473 | 40.19 | 59.81 |
| 2015–2020 | 77,286 | 75.30 | 24.70 | 5,867 | 40.04 | 59.96 |
| Significancea (2015–2020) | χ2(5)=206.48, p <.001 | χ2(5)=28.13, p <.001 | ||||
Significance in changes in the proportions of naloxone administration during 2015–2020
Figure 1.
Proportion (%) of cases with naloxone therapy, 2015–2020
Associations of naloxone administration with year, demographics, and exposure-related factors
Single-variable logistic regression results in Table 2 show that among prescription opioid-only cases, compared to cases in 2015, those in 2017 through 2020 had progressively higher odds of naloxone administration. Compared to cases age 50–59 and male cases, older and female cases, respectively, had lower odds. Compared to cases in the South, those in the Northeast had higher odds while those in other regions had lower odds. Cases exposed to opioids at a location other than their own or another’s home, all intentional and other exposure cases than unintentional exposure cases, and cases with medical outcomes that were moderate, major, and death, compared to no/minimal effect had higher odds of naloxone administration. Additional analysis showed death rates of 2.2% and 1.5% among those with and without naloxone therapy, respectively. Cases managed at healthcare facilities and other/unknown settings/level of care as well as those who refused referral and did not arrive at a HCF and those who were lost to follow-up/left against medical advice had higher odds. Additional analysis showed that naloxone administration rates for cases managed at non-HCF settings were low even for major medical outcomes (i.e., 6.1% or 20 of 327 cases).
Table 2.
Associations of naloxone administration with demographic and exposure-related factors: Single-variablea logistic regression results
| Prescription opioids (PO) only N=77,286 (92.94%) | Illicit opioids (IO) with or without PO N=5.867 (7.06%) | ||||
|---|---|---|---|---|---|
| % of all PO cases | Naloxone administered vs. not administered OR (95% CI) | % of all IO cases | Naloxone administered vs. not administered OR (95% CI) | ||
| Year | |||||
| 2015 (ref) | 17.66 | -- | 8.47 | -- | |
| 2016 | 18.02 | 1.04 (0.99–1.11) | 13.50 | 1.53 (1.22–1.92) | |
| 2017 | 17.16 | 1.16 (1.10–1.23) | 16.11 | 1.38 (1.11–1.72) | |
| 2018 | 16.12 | 1.18 (1.11–1.25) | 16.79 | 1.24 (1.00–1.53) | |
| 2019 | 15.93 | 1.31 (1.24–1.39) | 20.03 | 1.68 (1.36–2.08) | |
| 2020 | 15.11 | 1.42 (1.34–1.50) | 25.11 | 1.38 (1.12–1.69) | |
| Census region | |||||
| South (ref) | 38.84 | -- | 26.27 | -- | |
| Northeast | 15.87 | 1.47 (1.41–1.54) | 40.33 | 0.98 (0.85–1.12) | |
| Midwest | 19.17 | 0.93 (0.88–0.97) | 18.0 | 0.71 (0.60–0.83) | |
| West | 25.72 | 0.80 (0.77–0.83) | 15.20 | 0.18 (0.15–0.21) | |
| Puerto Rico/other US territories | 0.39 | 0.09 (0.05–0.18) | 0.20 | n/a | |
| Age | |||||
| 50–59 (ref) | 44.81 | -- | 72.23 | -- | |
| 60–69 | 31.41 | 0.85 (0.82–0.88) | 25.07 | 1.09 (0.96–1.23) | |
| 70+ | 2.69 | 1.12 (0.81–1.55) | |||
| 70–79 | 15.52 | 0.54 (0.51–0.57) | |||
| 80+ | 8.25 | 0.37 (0.34–0.40) | |||
| Gender | |||||
| Male (ref) | 39.31 | -- | 73.41 | -- | |
| Female | 60.63 | 0.85 (0.82–0.88) | 26.50 | 0.97 (0.86–1.09) | |
| Missing | 0.06 | 0.35 (0.14–0.90) | 0.09 | n/a | |
| No. of opioids involved | |||||
| One (ref) | 92.69 | -- | 88.46 | -- | |
| 2+ | 7.31 | 1.78 (1.68–1.88) | 11.54 | 0.50 (0.43–0.59) | |
| Exposure site | |||||
| Own/other’s residence (ref) | 93.82 | -- | 72.20 | -- | |
| Other/unknownb | 6.18 | 2.29 (2.15–2.43) | 27.80 | 1.20 (1.06–1.34) | |
| Exposure reason | |||||
| Unintentionalc (ref) | 40.42 | -- | 3.14 | -- | |
| Intentional misuse/abuse | 18.62 | 9.24 (8.75–9.77) | 79.90 | 4.39 (3.19–6.03) | |
| Suspected suicide | 35.44 | 7.75 (7.36–8.15) | 11.44 | 1.47 (1.04–2.09) | |
| Other/unknown | 5.52 | 6.73 (6.22–7.27) | 2.47 | 0.82 (0.55–1.22) | |
| Medical outcomes | |||||
| No/minimal (ref) | 54.54 | -- | 22.14 | -- | |
| Moderate | 26.30 | 10.47 (9.99–10.96) | 30.97 | 6.24 (5.32–7.32) | |
| Major | 17.51 | 12.56 (11.95–13.21) | 39.32 | 14.51 (12.29–17.12) | |
| Death | 1.65 | 6.61 (5.86–7.47) | 7.57 | 0.74 (0.57–0.97) | |
| Management site/level of care | |||||
| On site (non-healthcare facility [HCF]) (ref) | 25.78 | -- | 2.93 | -- | |
| HCF treated/evaluated & released | 19.07 | 226.74 (156.22–329.11) | 45.63 | 4.45 (3.22–6.15) | |
| Admitted to a critical care unit | 24.14 | 810.79 (559.05–1175.89) | 17.74 | 3.05 (2.18–4.27) | |
| Admitted to a noncritical care unit | 13.73 | 367.05 (253.05–533.39) | 12.44 | 1.92 (1.36–2.71) | |
| Admitted to a psychiatric facility | 7.45 | 157.42 (108.01–229.43) | 4.99 | 1.00 (0.68–1.48) | |
| Refused referral/did not arrive at HCF | 2.21 | 39.08 (25.48–59.94) | 1.93 | 6.41 (3.72–11.02) | |
| Lost to follow-up/left AMAd | 5.38 | 141.55 (96.87–206.82) | 8.25 | 2.70 (1.88–3.87) | |
| Other/unknown management site and level of care | 2.05 | 40.68 (26.47–62.52) | 6.08 | 0.29 (0.19–0.45) | |
In the case of variables with more than two levels (e.g., census region), variables were represented with dummy variables coded for each level of the variable except for the reference group.
Public area, healthcare facility, workplace, other, unknown
Adverse reaction; unintentional therapeutic error, misuse, or unintentional general; occupational or environmental exposure; or unintentional but unknown reason
Against medical advice
Table 2 also shows that among illicit opioid cases, compared to 2015, cases in 2016, 2017, 2019, and 2020 had higher odds of naloxone administration. Age and gender were not significantly associated with naloxone administration. Compared to cases in the South, those in the Midwest and the West had lower odds. Exposures at a location other than one’s own or another’s home, intentional misuse/abuse and suspected suicide cases compared to unintentional exposure cases, and cases with moderate and major medical outcomes compared to no/minimal effect had higher odds of naloxone administration. However, cases that resulted in death had lower odds. Additional analyses showed six-year average death rates of 15.2% and 2.4% among those without and with naloxone therapy, respectively; however, in 2020, the death rate for those without naloxone therapy was 31.4% compared to 2.3% for those with the therapy. Cases managed at healthcare settings (but not those admitted to a psychiatric facility) as well as those who refused referral and did not arrive at a HCF and those who were lost to follow-up/left against medical advice had higher odds of naloxone administration.
Associations of naloxone administration with clinical effects and other therapeutic interventions
Table 3 shows that CNS and respiratory depression were the most common effects among both prescription and illicit opioid cases followed by confusion, nausea/vomiting, tachycardia, and hypotension in prescription opioid cases, and miosis, bradycardia, tachycardia, and agitation in illicit opioid cases. In prescription opioid cases, most clinical effects except nausea/vomiting, dizziness/vertigo, and diaphoresis were associated with higher odds of naloxone administration, with the highest odds in cases with cyanosis, CNS depression, and respiratory problems. In illicit opioid cases, in addition to these same three clinical effects, hypotension, bradycardia, and acidosis were associated with higher odds, but nausea/vomiting, agitation, dizziness/vertigo, hypertension, and tachycardia were associated with lower odds of naloxone administration.
Table 3.
Associations of naloxone administration with clinical effects and other therapeutic interventions: Single-variable logistic regression results
| Prescription opioids (PO) only 77,286 (92.94%) | Illicit opioids (IO) with or without PO 5,867 (7.06%) | |||
|---|---|---|---|---|
| % of all PO cases | Naloxone vs. no naloxone OR (95% CI) | % of all IO cases | Naloxone vs. no naloxone OR (95% CI) | |
| Clinical effects | ||||
| Central nervous system (CNS) depression | 44.78 | 16.91 (16.13–17.73) | 66.22 | 19.47 (16.93–22.39) |
| Respiratory problems | 13.12 | 15.32 (14.58–16.10) | 36.92 | 14.46 (12.30–17.01) |
| Confusion | 8.24 | 2.23 (2.12–2.35) | 5.86 | 0.98 (0.79–1.23) |
| Nausea/vomiting | 8.24 | 0.72 (0.68–0.77) | 5.73 | 0.57 (0.45–0.71) |
| Miosis | 5.28 | 7.73 (7.22–8.28) | 13.67 | 3.25 (2.70–3.91) |
| Agitation | 4.95 | 1.83 (1.71–1.96) | 6.68 | 0.47 (0.38–0.57) |
| Hypotension | 7.47 | 4.36 (4.13–4.60) | 4.79 | 1.37 (1.06–1.77) |
| Hypertension | 3.31 | 1.78 (1.64–1.93) | 4.45 | 0.64 (0.50–0.82) |
| Bradycardia | 3.84 | 3.42 (3.18–3.68) | 2.18 | 1.48 (1.02–2.16) |
| Tachycardia | 7.82 | 2.39 (2.37–2.53) | 8.88 | 0.82 (0.68–0.98) |
| Cardiac arrest/asystole | 1.56 | 1.54 (1.36–1.74) | 8.27 | 0.20 (0.16–0.25) |
| Acidosis | 3.41 | 5.15 (4.75–5.58) | 3.44 | 1.53 (1.13–2.07) |
| Slurred speech | 3.88 | 1.39 (1.28–1.50) | 1.64 | 0.89 (0.59–1.34) |
| Dizziness/vertigo | 3.32 | 0.24 (0.21–0.28) | 0.87 | 0.36 (0.20–0.64) |
| Electrolyte imbalance | 3.08 | 2.98 (2.74–3.23) | 2.52 | 0.85 (0.61–1.18) |
| Creatinine increase | 2.27 | 4.00 (3.63–4.40) | 2.45 | 1.19 (0.84–1.67) |
| AST, ALTa >100 <=1,000 | 2.18 | 2.47 (2.24–2.73) | 1.14 | 1.05 (0.64–1.73) |
| AST, ALTa >1000 | 1.03 | 2.05 (1.78–2.36) | 0.73 | 1.55 (0.80–2.97) |
| Conduction disturbance | 2.15 | 2.57 (2.32–2.80) | 1.40 | 0.85 (0.55–1.32) |
| Cyanosis | 0.52 | 17.18 (13.07–22.58) | 3.29 | 21.92 (9.70–49.50) |
| Diaphoresis | 1.24 | 1.03 (0.89–1.19) | 2.15 | 0.71 (0.50–1.01) |
| Therapeutic interventions other than naloxone | ||||
| Fluid, intravenous | 29.64 | 4.06 (3.92–4.20) | 25.0 | 1.11 (0.99–1.26) |
| Oxygen | 21.34 | 7.76 (7.47–8.06) | 24.88 | 3.54 (3.07–4.08) |
| Intubation | 7.46 | 3.99 (3.78–4.22) | 6.60 | 1.27 (1.02–1.57) |
| N-acetylcysteine (NAC) intravenous or oral formulations | 7.71 | 2.61 (2.48–2.76) | 1.94 | 0.79 (0.55–1.15) |
| Ventilator | 7.22 | 4.05 (3.83–4.28) | 6.34 | 1.29 (1.04–1.61) |
| Noninvasive ventilationb | 0.94 | 24.29 (19.31–30.55) | 6.92 | 28.66 (15.26–53.82) |
| Benzodiazepine | 6.09 | 1.77 (1.67–1.89) | 8.18 | 0.49 (0.41–0.60) |
| Sedation | 5.49 | 3.06 (2.87–3.26) | 5.66 | 0.91 (0.73–1.14) |
| Antibiotics | 3.88 | 3.99 (3.71–4.30) | 4.74 | 1.16 (0.90–1.49) |
| Vasopressor | 3.43 | 4.32 (4.00=4.68) | 2.66 | 1.31 (0.93–1.83) |
| Antiemetic | 2.92 | 1.62 (1.48–1.77) | 4.04 | 1.04 (0.79–1.35) |
| Cardiopulmonary resuscitation (CPR) | 0.82 | 7.80 (6.56–9.28) | 4.07 | 4.70 (3.21–6.88) |
AST (aspartate aminotransferase); ALT (alanine aminotransferase)
CPAP (continuous positive airway pressure), BiPAP (bi-level positive airway pressure)
Table 3 also shows that in terms of other therapeutic interventions in both prescription and illicit opioid cases, noninvasive ventilation (involving continuous positive airway pressure [CPAP] or bi-level positive airway pressure [BiPAP]) was associated with the highest odds of naloxone administration, followed by oxygen, CPR, intubation, and ventilator. In prescription opioid cases, fluid IV, N-acetylcysteine (NAC) intravenous or oral formulations, benzodiazepines, sedation, antibiotics, and antiemetics were also positively associated with naloxone administration. In illicit opioid cases, benzodiazepines were negatively associated with naloxone administration while the other interventions were not significantly associated.
Associations of naloxone administration with types of opioids
Table 4 shows the odds of naloxone administration for different types of opioids, controlling for year, census region, age group, gender, number of opioids used, and select clinical effects. Compared to cases involving prescription opioids only, those involving both prescription opioids and heroin (AOR=2.08, 95% CI=1.68–2.58), heroin only (AOR=3.19, 95% CI=2.94–3.46), and fentanyl and other synthetic nonpharmaceutical opioids (AOR=1.68, 95% CI=1.15–2.45) had higher odds of naloxone administration.
Table 4.
Odds of naloxone administration by types of prescription and illicit opioids: Multivariable logistic regression results
| N | % | Naloxone vs. no naloxone AOR (95% CI) | ||
|---|---|---|---|---|
| Opioid type (N=82,788a) | ||||
| Prescription opioid only (ref) | 76,938 | 92.93 | -- | |
| Prescription opioid and heroin | 610 | 0.74 | 2.08 (1.68–2.58)*** | |
| Heroin without prescription opioid | 4,981 | 6.02 | 3.19 (2.94–3.46)*** | |
| Fentanyl and other synthetic, non-pharmaceutical opioid | 213 | 0.31 | 1.68 (1.15–2.45)** | |
| Prescription opioid-only cases (N=76,938b) | ||||
| Acetaminophen with opioids | 18,853 | 24.50 | 0.91 (0.87–0.96)*** | |
| Tramadol | 18,217 | 23.68 | 0.31 (0.29–0.33)*** | |
| Oxycodone alone or in combinationc | 15,139 | 19.68 | 1.33 (1.27–1.40)*** | |
| Morphine | 7,832 | 10.18 | 1.60 (1.50–1.71)*** | |
| Methadone | 4,521 | 5.88 | 1.76 (1.62–1.91)*** | |
| Buprenorphine | 3,069 | 3.99 | 0.70 (0.63–0.79)*** | |
| Prescription fentanyl | 2,727 | 3.54 | 2.15 (1.94–2.38)*** | |
| Hydromorphone | 2,609 | 3.39 | 1.15 (1.03–1.28)* | |
| Hydrocodone alone or in combinationc | 2,561 | 3.33 | 0.77 (0.68–0.87)*** | |
| Codeine | 1,362 | 1.77 | 0.46 (0.37–0.58)*** | |
| Tapentadol | 622 | 0.81 | 0.83 (0.65–1.07) | |
| Oxymorphone | 552 | 0.72 | 1.54 (1.22–1.95)*** | |
| Acetylsalicylic acid with opioids | 106 | 0.14 | 0.54 (0.31–0.94)* | |
| Other or unknown prescription narcotics | 3,733 | 4.85 | 2.93 (2.68–3.21)*** | |
Excluded cases with unknown gender (n=49) and in Puerto Rico and other US territories (n=316)
Excluded cases with unknown gender (n=44) and in Puerto Rico and other US territories (n=304)
Excluding combination products with acetaminophen or acetylsalicylic acid
AOR: Adjusted odds ratio. The odds ratio in each cell was adjusted for year, census region, age group, gender, number of opioids used, and the following clinical effects: CNS depression, respiratory problems, miosis, hypotension, bradycardia, acidosis, and cyanosis.
p<.05
p<.01
p<.001
Among prescription opioids only cases, cases involving oxycodone, morphine, methadone, prescription fentanyl, hydromorphone, oxymorphone, and other/unknown opioids had higher odds of naloxone administration, but cases involving acetaminophen with opioid, tramadol, buprenorphine, hydrocodone, codeine, and acetylsalicylic acid with opioid had lower odds.
Discussion
This study shows that during the six-year period from 2015 to 2020, naloxone therapy rates increased in both prescription and illicit opioid cases aged 50+ reported to the NPDS. Though the steady increase in naloxone administration among prescription opioid poisoning cases from 21.9% in 2015 to 28.4% in 2020, despite the COVID-19 pandemic in 2020, is a positive development, many more lives could be saved by increasing these rates. Data also show that naloxone administration for cases managed at non-HCF settings (most often one’s home), especially those with major medical outcomes, needs improvement. The very low rates of naloxone therapy among these cases suggest that they (as well as their relatives or friends) either lacked knowledge of or access to naloxone [18–20]. In many states, monthly prescription fill limits for Medicaid beneficiaries are also likely to be significant barriers to obtaining naloxone [21]. In addition, our findings indicate that women are less likely than men and those aged 60+ are less likely than those aged 50–59 to receive naloxone therapy, suggesting that age and gender differences persist in receiving this life-saving treatment. Naloxone co-prescribing for those at risk of opioid overdose and exempting naloxone from Medicaid prescription limit restrictions or providing it free without prescription are needed to expand access [21,22].
As expected, naloxone administration rates were higher for illicit than prescription opioid cases; however, the rates for illicit opioid cases decreased in 2020 from 2019, despite the increased number of these cases. This may be due to stay-at-home orders and other social distancing measures during the COVID-19 pandemic that resulted in the lack of bystanders or other support systems to administer naloxone [23,24], delays in EMS and other healthcare services that were overburdened due to COVID-19 patients, and discouragement and prohibition of intranasal naloxone due to concerns about COVD-19 infection [25]. The spike in the death rate (31.4%) in 2020 among illicit opioid cases without naloxone therapy may also reflect individual patients’ reluctance and delay in seeking healthcare services due to concerns about COVID-19 infection. A study of an EMS system found more than a two-fold increase in the rate of transport refusal after non-fatal opioid overdose following the COVID-19 outbreak [26]. The death rate among illicit opioid cases who received naloxone therapy remained low (2.3%) in 2020, confirming naloxone’s life-saving effect.
Our findings also show that, as expected, CNS depression and respiratory problems were the most common opioid poisoning symptoms associated with increased odds of naloxone administration. Cyanosis was not common, but it notably increased the odds of naloxone administration. In terms of the types of opioids associated with naloxone administration, H1 (higher odds for illicit opioids) was fully supported. H2 was almost fully supported since, as hypothesized, cases involving oxycodone, morphine, methadone, prescription fentanyl, hydromorphone, and oxymorphone (but not hydrocodone) were associated with higher odds of naloxone administration. The findings underscore the importance of naloxone co-prescription when these opioids are prescribed. Hydrocodone was associated with lower odds of naloxone administration as were cases involving acetaminophen with opioid, tramadol, buprenorphine, codeine, and acetylsalicylic acid with opioid. While exposure doses are likely to be the most important factor in naloxone administration [27], hydrocodone and these other analgesics tend to be less potent and may cause less sedative effects than fentanyl, hydromorphone, oxymorphone, oxycodone, or morphine [28–32].
Study limitations are: First, the lack of accurate NPDS data on opioid doses and the number of times naloxone was administered prevented more detailed analyses. Second, we included only clinical effects related to opioids. However, as most older adults utilize polypharmacy, combinations of opioids and other CNS depressant medications may have had additive adverse CNS effects [32] that may have increased naloxone therapy odds. Third, the NPDS does not provide data on the timing or duration of specific clinical effects and therapeutic interventions; pre-existing health conditions; and substance use history that would allow more detailed analyses of factors and circumstances associated with cases. Fourth, given the spike in fentanyl poisoning deaths from adulterated heroin and psychostimulants in all age groups in recent years [33], the NPDS appears to underreport fentanyl poisoning cases likely because poison centers record what the caller reports, i.e., without clinical toxicology data. Finally, since the NPDS contains only exposures that are reported (usually by phone) to PCCs, it likely underestimates the number of overdose cases and naloxone administrations and other therapeutic interventions and may not be representative of all exposures among the population, limiting the findings’ generalizability [17].
Conclusions
Naloxone administration in prescription opioid poisoning cases aged 50+ was significantly lower than in illicit opioid cases, although rates increased over the six-year study period. Rates among older and female cases and those managed at non-HCF settings were especially low. The findings also highlight the types of prescription opioids associated with higher odds of naloxone administration. Although naloxone administration rates were higher among illicit than prescription opioid cases, the rate for illicit opioid cases dropped in 2020. A sharp increase in deaths among illicit opioid cases without naloxone therapy in 2020 confirms the importance of access to this life-saving intervention.
Acknowledgements
The American Association of Poison Control Centers made the National Poison Data System (NPDS) available to the authors for this study. This study’s findings and conclusions are those of the authors alone and do not necessarily represent the official position of the American Association of Poison Control Centers or participating poison control centers.
Funding
This research was supported by grant P30AG066614, awarded to the Center on Aging and Population Sciences at The University of Texas at Austin by the National Institute on Aging. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Disclosure statement
The authors report no potential conflict of interest.
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