Medicaid

1. Patterns of Opioid Use and Risk of Opioid Overdose
Death Among Medicaid Patients
Renu K. Garg, PhD,* Deborah Fulton-Kehoe, PhD,w and Gary M. Franklin, MD, MPHwzy8
Background: The Centers for Disease Control and Prevention
recognizes Medicaid as a high-risk population for fatal opioid
overdose. Further research is needed to identify factors that put
Medicaid patients at increased risk.
Objective: To determine whether patterns of opioid use are asso-
ciated with risk of opioid-related mortality among opioid users.
Design: This is a retrospective cohort study.
Patients: In total, 150,821 noncancer pain patients aged 18–64
years with Z1 opioid prescription, April 2006 to December 2010,
Washington Medicaid.
Measures: Average daily dose (morphine equivalents), opioid
schedule/duration of action, sedative-hypnotic use.
Results: Compared with patients at 1–19 mg/d, risk of opioid
overdose death significantly increased at 50–89 mg/d [adjusted
hazard ratio (aHR), 2.3; 95% confidence interval (CI), 1.4–4.1],
90–119 mg/d (aHR, 4.0; 95% CI, 2.2–7.3), 120–199 mg/d (aHR,
3.8; 95% CI, 2.1–6.9), and Z200 mg/d (aHR, 4.9; 95% CI,
2.9–8.1). Patients using long-acting plus short-acting Schedule II
opioids had 4.7 times the risk of opioid overdose death than non-
Schedule II opioids alone (aHR, 4.7; 95% CI, 3.3–6.9). Sedative-
hypnotic use compared with nonuse was associated with 6.4 times
the risk of opioid overdose death (aHR, 6.4; 95% CI, 5.0–8.4). Risk
was particularly high for opioids combined with benzodiazepines
and skeletal muscle relaxants (aHR, 12.6; 95% CI, 8.9–17.9). Even
at opioid doses 1–19 mg/d, patients using sedative-hypnotics con-
currently had 5.6 times the risk than patients without sedative-
hypnotics (aHR, 5.6; 95% CI, 1.6–19.3).
Conclusions: Our findings support Federal guideline-recommended
dosing thresholds in opioid prescribing. Concurrent sedative-hypnotic
use even at low opioid doses poses substantially greater risk of opioid
overdose.
Key Words: opioid, overdose, Medicaid, chronic pain
(Med Care 2017;55: 661–668)
Adramatic increase in fatal opioid overdose has paralleled
a rise in use of prescription opioids.1–5 Prescriptions for
opioids soared6 following changes to governmental regu-
lations in the late 1990s to liberalize opioid use for the
treatment of chronic noncancer pain.7,8 By 2012, the national
rate of opioid-related mortality was 5.1 per 100,000, >3.5
times the rate in 1999 (1.4/100,000).9 Accidental poisonings
became the country’s leading cause of unintentional injury
death, largely due to deaths associated with prescription
opioids.1 The Centers for Disease Control and Prevention
(CDC) has declared opioid overdose deaths a national epi-
demic.10,11 However, risk factors for opioid overdose are not
fully understood and research gaps still exist in quantifying
the risks posed by opioid use.12–14
Medicaid has been recognized by CDC as a high-risk
population for fatal opioid overdose.10,15,16 Nationally, pre-
scriptions for opioids in Medicaid nearly doubled between
1998 and 2003 to >27.5 million, an estimated 4% of the
program’s prescription drug expenditures.3 The 2004–2007
rate of opioid overdose death among Washington (WA)
Medicaid enrollees was 30.8 per 100,000 person-years, al-
most 6 times the rate in the non-Medicaid population [age-
adjusted relative risk, 5.7; 95% confidence interval (CI),
5.3–6.1].15
Prescription opioid studies in Medicaid populations
have focused on drug utilization,17–20 opioid use patterns,16,21
opioid dependence/abuse,19 or long-acting opioids.22,23 Others
reported opioid-related death by opioid dosage but were
restricted to specific generic forms of opioids23–25 or did not
distinguish between fatal and nonfatal events.21,26,27 Although
dose-response relationships between opioids and overdose
risk were identified in non-Medicaid populations,28–32 only
1 Medicaid study has assessed dose and opioid-related
overdose.33
Previous research has shown that sedative-hypnotic
use is common among opioid users28,31,34,35 and increases
opioid overdose risk.28,31,35,36 Little is known about the
combined risk of opioids and specific types of sedative-
hypnotics, including skeletal muscle relaxants. One study
explored the relationship of opioid overdose with benzo-
diazepine use by level of opioid dose; however, the analysis
was limited to benzodiazepines ever used in the previous
From the Departments of *Epidemiology; wEnvironmental and Occupational
Health Sciences; zHealth Services; 8Neurology, University of
Washington, Seattle; and yWashington State Department of Labor and
Industries, Olympia, WA.
Supported by the Centers for Disease Control and Prevention (grant number
5R21CE001850-01).
The authors declare no conflict of interest.
Reprints: Renu K. Garg, PhD, Department of Epidemiology, University of
Washington, 130 Nickerson Street, Suite 212, Seattle, WA 98109.
E-mail: rkgarg@uw.edu.
Supplemental Digital Content is available for this article. Direct URL cita-
tions appear in the printed text and are provided in the HTML and PDF
versions of this article on the journal’s Website, www.lww-medical
care.com.
Copyright r 2017 Wolters Kluwer Health, Inc. All rights reserved.
ISSN: 0025-7079/17/5507-0661
ORIGINAL ARTICLE
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2. year.31 Long-acting opioids pose an increased risk as
well,11,23,32,37 but as emphasized in the recently released
CDC opioid prescribing guideline, evidence is lacking on
overdose risk for long-acting versus short-acting opioids.11
To address the need for more evidence on determinants
for fatal opioid overdose, we conducted a population-based
retrospective cohort study among opioid users in WA Med-
icaid to determine whether various patterns of opioid use are
associated with the risk of opioid-related mortality. We
evaluated the risk of opioid-related mortality associated with
opioid dose, long-acting and short-acting opioids, duration of
use, recent use of sedative-hypnotics by drug class, and
concurrent sedative-hypnotic use by opioid dose.
METHODS
Study Setting and Population
We obtained WA Medicaid data for medical, hospital,
and pharmacy claims, cause of death, and enrollment.
Patient-level data were available for claims under the fee-
for-service program beginning in April 2006. There were
328,445 patients in WA Medicaid aged 18–64 years with
Z1 paid fee-for-service claims for oral or transdermal opioid
prescriptions dispensed between April 1, 2006 and December
31, 2010. The study was approved by the University of
Washington and Washington State Institutional Review
Boards. Because the research involved no more than minimal
risk and included a large number of individuals, the
requirement for informed consent was waived.
The first paid opioid prescription dispensed during the
study period for each patient was defined as the index pre-
scription. The index prescription was the first available paid
opioid prescription in the data and reflects first opioid use
during the study period. Follow-up began on the index pre-
scription date. Patients were excluded (Table 1) if they had:
(1) history of cancer (except nonmelanoma skin cancer)
based on International Classification of Diseases, Ninth
Revision, Clinical Modification (ICD-9) codes or prescriptions
for cancer treatment up to 1 year after the index prescription
(5.3%); (2) history of methadone maintenance treatment
(outpatient procedure code H0020) up to 90 days after the index
prescription (0.9%); (3) comprehensive managed care only or at
first opioid use (6.8%); (4) dual-eligible coverage (benefits
through both Medicaid and Medicare) only or before first
use (10.9%); (5) no clinic visits within 1 month of the index
prescription (4.3%); or (6) limited fee-for-service enrollment for
follow-up at first opioid use because of switching to managed
care/dual-eligible coverage (24.0%) or having 90 days of
continuous fee-for-service enrollment (2.0%). We required the
minimum follow-up of 90 continuous days of fee-for-service
enrollment from the index prescription due to the instability
of enrollment in Medicaid. Patients with sporadic fee-for-service
enrollment at first use had incomplete data on opioid use and
health outcomes during that time. The final sample consisted of
150,821 patients.
Follow-up continued until disenrollment from Medic-
aid, switch in enrollment to managed care or dual-eligible
coverage, diagnosis of cancer, admission into methadone
maintenance treatment, date of 65th birthday, death, or end
of the study (December 31, 2010). Mean (SD) follow-up was
20.0 (16.3) months, with more than half of patients having
Z1 year of continuous enrollment (median, 13.0 mo)
(Table 2).
Opioid Prescription Use and Dosing
The WA Medicaid pharmacy database contains records
for each medication dispensed with information on drug
name, strength, quantity, days’ supply, and dispense date.
For each prescription, we defined the end date as the
date dispensed plus the days’ supply minus 1 day. The dates
encompassed by a prescription were counted as the days
covered by opioids. If an individual had Z2 prescriptions
with days’ supply covering the same dates, the overlapping
dates were counted as 1 covered day.
We grouped opioids by generic name, short-acting
versus long-acting properties, and Drug Enforcement
Administration schedule (Appendix 1, Supplemental Digital
Content 1, http://links.lww.com/MLR/B382). We further
categorized opioids as short-acting Schedule II, long-acting
Schedule II, or non-Schedule II.38 Various combinations of
opioid types used in the past 30 days were defined for each
day of follow-up: non-Schedule II opioids only, Schedule II
short-acting opioids only, Schedule II long-acting opioids
only, and both Schedule II long-acting and short-acting
opioids.
We calculated daily dose for each opioid prescription
as the number of pills dispensed multiplied by the drug
strength, divided by the days’ supply. For fentanyl, daily
dose was equivalent to the drug strength delivered by 1
patch. Daily doses were then converted to morphine equiv-
alent doses using published conversion factors.38–40 If
individuals had prescriptions with overlapping dates, the
daily dose was defined as the sum of the doses from the
different prescriptions for the same day. We used the daily
doses to measure the average daily dose in the past 30 days.
Average daily dose [morphine equivalent dose (mg)/d] was
TABLE 1. Study Exclusions Among Washington State
Medicaid Enrollees Aged 18–64 Years Who Had Z1 Paid
Opioid Prescriptions* During April 2006 to December 2010
Patients With Z1 Paid Opioid
Prescriptions* (N = 328,445)
[n (%)]
Exclusions
History of cancer 12,662 (3.9)
Cancer diagnosis within 1st year of
opioid use
4546 (1.4)
History of methadone maintenance
treatment (up to 3 mo after 1st
opioid use)
2958 (0.9)
Comprehensive managed care only
or at 1st opioid use
22,293 (6.8)
Dual-eligible coverage only or by 1st
opioid use
35,706 (10.9)
No paid office visits 13,966 (4.3)
Limited enrollment 85,493 (26.0)
Total no. subjects eligible for study
inclusion
150,821 (45.9)
*Oral or transdermal prescription opioid.
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3. computed for each follow-up day as the sum of the daily
doses over the past 30 days, divided by the number of days in
that interval covered by an opioid prescription.
An individual’s overall duration of use was the total
number of days covered by opioid prescriptions. Cumulative
duration of use was determined on each day of follow-up as
the sum of days covered by opioid prescriptions since the
index prescription through that point in time.
Opioid Overdose Death
Fatal prescription opioid overdoses were identified
by WA Department of Health through a review of death
certificates for accidental deaths with ICD 10 codes (T40.0-
T40.6 and F11) for poisoning by narcotics or opioid abuse,
dependence, or misuse.15 They classified deaths as related to
prescription opioids if the death certificate reported a pre-
scription opioid and contained terms indicating overdose or
acute drug intoxication. On the basis of the study criteria,
316 prescription opioid-related deaths occurred among the
included enrollees during study follow-up. Overdose deaths
TABLE 2. Characteristics of the Study Population Among
Washington State Medicaid Enrollees Aged 18–64 Years With
Z1 Opioid Prescriptions During April 2006 to December 2010
Total Population
(N = 150,821) [n (%)]
Age at first use (y)
18–24 34,934 (23.2)
25–34 39,661 (26.3)
35–44 28,283 (18.8)
45–54 29,510 (19.6)
55–64 18,433 (12.2)
Sex
Female 102,134 (67.7)
Male 48,686 (32.3)
Race
Non-Hispanic white 84,442 (56.0)
Non-Hispanic black 9439 (6.3)
Non-Hispanic Asian, Hawaiian/Pacific
Islander
5343 (3.5)
Hispanic 15,778 (10.5)
Non-Hispanic Native American/Alaskan
Native
11,512 (7.6)
Other 10,656 (7.1)
Unknown 13,651 (9.1)
Area of residence*
Urban 119,171 (79.0)
Large, rural city/town 15,263 (10.1)
Small/isolated, rural town 15,830 (10.5)
Follow-up time (mean = 20.0, median = 13.0) (mo)
3–5 25,778 (17.1)
6–12 34,624 (23.0)
13–24 46,699 (31.0)
25–36 15,187 (10.1)
37–48 11,076 (7.3)
49–57 17,457 (11.6)
Average daily dose in last 30 d of use (mg/d)
1–19 18,165 (12.0)
20–49 78,907 (52.3)
50–89 34,446 (22.8)
90–119 7762 (5.2)
120–199 4811 (3.2)
Z200 6730 (4.5)
Overall duration of use (total days) (d)
1–30 97,873 (64.9)
31–90 17,805 (11.8)
91–180 9915 (6.6)
181–365 8533 (5.7)
366–730 7269 (4.8)
730 9426 (6.3)
Time since last opioid prescription at
last follow-up (d)
Same day 22,762 (15.1)
1–30 15,724 (10.4)
31–90 17,467 (11.6)
91–180 25,078 (16.6)
181–365 32,449 (21.5)
365 37,341 (24.8)
No. opioid prescriptions in first year of use
1–2 79,191 (52.5)
3–5 28,833 (19.1)
6–10 16,750 (11.1)
11–20 16,603 (11.0)
20 9444 (6.3)
Total days’ supply in first year of use
1–30 106,813 (70.8)
31–90 16,669 (11.1)
91–180 10,024 (6.7)
180 17,315 (11.5)
(Continued)
TABLE 2. Characteristics of the Study Population Among
Washington State Medicaid Enrollees Aged 18–64 Years With Z1
Opioid Prescriptions During April 2006 to December 2010
(continued)
Total Population
(N = 150,821) [n (%)]
Drug type in last 30 d of use
Non-Schedule II only 95,832 (63.5)
Schedule II short-acting onlyw
44,931 (30.0)
Schedule II long-acting onlyw
5244 (3.5)
Schedule II short-acting and long-actingw
4814 (3.2)
No. prescribing providers in first year of use
1–2 104,180 (69.1)
3–5 34,274 (22.7)
Z6 12,367 (8.2)
Diagnosis of opioid dependence/abusez
Before first use 1594 (1.1)
Within 2 y after first use 4760 (3.2)
Any sedative-hypnotic use during follow-up 66,104 (43.8)
Benzodiazepines 38,069 (25.2)
Skeletal muscle relaxants 44,644 (29.6)
Barbiturates 4289 (2.8)
Nonbarbiturate hypnotics 15,981 (10.6)
Sedative-hypnotic use at last follow-up 28,877 (19.1)
Benzodiazepines 16,688 (11.0)
Skeletal muscle relaxants 13,740 (9.1)
Barbiturates 1016 (0.7)
Nonbarbiturate hypnotics 4224 (2.8)
Concurrent opioid and sedative-hypnotic
use at last follow-up
Opioids only 20,095 (13.3)
Sedative-hypnotics only 10,486 (7.0)
Both opioids and sedative-hypnotics 18,391 (12.2)
No opioids or sedative-hypnotics 101,849 (67.5)
*Defined using the 2005 classification system for rural-urban commuting area
(RUCA) codes by the University of Washington Rural Health Research Center.
w
With or without non-Schedule II opioids.
z
Does not include Medicaid recipients who were receiving opioid dependence
treatment before or up to 3 months after their first opioid use, as they were excluded
from the study.
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4. with heroin mentioned on the death certificate were not
included in this definition of opioid overdose fatalities.
Comorbidities
For each day of follow-up, we ascertained whether
or not patients had prescriptions for sedative-hypnotics
(benzodiazepines, skeletal muscle relaxants, barbiturates,
and nonbarbiturate hypnotics) in the past 30 days. Appendix
2 (Supplemental Digital Content 2, http://links.lww.com/
MLR/B383) contains a table of medications in each sedative-
hypnotic category. A diagnosis of opioid dependence/abuse
was defined as ICD-9 codes 304.0, 304.7, or 305.5.41,42
We considered the first visit date with these codes to be the
diagnosis date. We calculated the Charlson Comorbidity
Index at baseline as an adjustor for comorbidity severity.43
Statistical Analysis
Descriptive statistics were used to characterize opioid
users, prescription history, dosing patterns, and duration of
use. The overall rate of opioid-related deaths per 100,000
person-years was calculated, and rates were stratified by
demographics, average daily dose, opioid drug type, duration
of use, and sedative-hypnotic use. We also present rates of
opioid-related death by average daily dose stratified by
sedative-hypnotic users and nonusers.
Cox proportional hazards models were used to assess
the associations between the various factors and risk of
opioid-related death. Time-varying variables included aver-
age daily dose, opioid drug type, cumulative duration of
opioid use, and sedative-hypnotic use (as yes/no). Because of
correlation between opioid use variables, each measure was
analyzed in separate models rather than as covariates to
calculate hazard ratios (HRs). We adjusted HRs for demo-
graphics and continuous Charlson Comorbidity Index. We
assessed proportional hazards assumptions based on plots
and tests of Schoenfeld residuals, which all had P 0.05
indicating the proportional hazards assumption was met. All
analyses were conducted using Stata Statistical Software
Release 12 (College Station, TX).44
RESULTS
Opioid Prescription Use and Dosing
Of the eligible enrollees, approximately three quarters
of patients received Z1 prescriptions for hydrocodone
(74.1%) and half received Z1 prescriptions for oxycodone
(49.0%) (Appendix 3, Supplemental Digital Content 3,
http://links.lww.com/MLR/B384). Other opioids that pa-
tients ever used included tramadol (18.3%), codeine (16.6%),
propoxyphene napsylate (9.1%), and morphine (5.8%). Less
than 5% of patients had ever received prescriptions for
methadone (4.9%) or hydromorphone (4.4%). Fentanyl was
rarely used (1.2%). Almost two thirds of patients (64.3%)
had average daily doses 50 mg/d at last opioid use
(Table 2). However, the distribution of average daily doses
was skewed with a median (interquartile range) of 40.0
(23.3–80.0) mg/d and mean (SD) of 127.1 (336.6) mg/d. Less
than 8% of patients were receiving high doses of opioids at
the time of last use (3.2% with 120–199 mg/d and 4.5% with
Z200 mg/d).
Patients were predominantly short-term users with
3 months of opioid use overall (76.7%). Over half of pa-
tients had only 1–2 opioid prescriptions in the first year of
use (52.5%). The majority of patients had r30 days’ supply
in the first year of use (70.8%). Almost two thirds had only
non-Schedule II opioids at last use (63.5%). Two thirds had
1–2 prescribing providers in the first year of use (69.1%) and
8.2% had Z6 providers. A fraction of patients received a
diagnosis of opioid dependence/abuse before their index
prescription (1.1%) or within the following 1–2 years (3.2%).
During study follow-up, 43.8% of patients had any sedative-
hypnotic use, most commonly benzodiazepines (25.2%) and
skeletal muscle relaxants (29.6%). At last follow-up, 19.1%
of patients received sedative-hypnotics.
Opioid Overdose Death
Overall, the rate of opioid-related death in the WA
Medicaid population was 125.8 per 100,000 person-years
(Table 3). Patients aged 45–54 years had twice the risk of
fatal opioid overdose as patients aged 25–34 years [adjusted
HR (aHR), 2.1; 95% CI, 1.5–3.0]. Males were 70% more
likely than females to have an opioid overdose death (aHR,
1.7; 95% CI, 1.3–2.1). Non-Hispanic blacks and Native
Americans/Alaskan Natives were at least 50% less likely
than non-Hispanic whites to have a fatal opioid overdose
(aHR, 0.4; 95% CI, 0.2–0.7 and aHR, 0.5; 95% CI, 0.3–0.9,
respectively).
Compared with patients at doses 1–19 mg/d, the risk of
opioid overdose death significantly increased at 50–89 mg/d
(aHR, 2.3; 95% CI, 1.4–4.1), 90–119mg/d (aHR, 4.0; 95% CI,
2.2–7.3), 120–199 mg/d (aHR, 3.8; 95% CI, 2.1–6.9), and
Z200mg/d (aHR, 4.9; 95% CI, 2.9–8.1). Overdose risk also
increased with cumulative duration of use during the study
period. Users with 31–89 cumulative days of opioid use were
4 times more likely to have an opioid-related death than users
with r30 cumulative days of use (aHR, 4.3; 95% CI, 2.7–6.9).
At 730 cumulative days of use, the risk of opioid overdose
death was over 20 times the risk in users with r30 cumulative
days of use (aHR, 23.7; 95% CI, 13.9–40.5).
Opioid schedule and duration of action were also as-
sociated with risk of opioid overdose death. Patients with
prescriptions for Schedule II short-acting opioids alone had
more than double the risk compared with patients with non-
Schedule II opioids alone (aHR, 2.3; 95% CI, 1.6–3.3). The
greatest risk was among patients with both Schedule II long-
acting and short-acting opioids compared with patients with
non-Schedule II opioids alone (aHR, 4.7; 95% CI, 3.3–6.9).
The risk was almost as high for patients with Schedule II
long-acting opioids alone compared with non-Schedule II
opioids only (aHR, 4.5; 95% CI, 3.1–6.4).
Recent sedative-hypnotic use compared with nonuse
was associated with 6 times the risk of opioid overdose
death (aHR, 6.4; 95% CI, 5.0–8.4) (Table 4). Significant
increases in opioid mortality risk were seen with benzodia-
zepines alone (aHR, 7.5; 95% CI, 5.5–10.0) or with a
combination of benzodiazepines and skeletal muscle relax-
ants (aHR, 12.6; 95% CI, 8.9–17.9). Patients simultaneously
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5. receiving all types of sedative-hypnotics had the highest risk
compared with no recent use of sedative-hypnotics (aHR,
16.7; 95% CI, 9.4–29.6). When sedative-hypnotics were used
concurrently with opioids, risk increased substantially with
increasing opioid doses. Compared with patients receiving
no sedative-hypnotics and opioid doses 1–19 mg/d, patients
using sedative-hypnotics at similarly low opioid doses had
5 times the risk of overdose death (aHR, 5.6; 95% CI,
1.6–19.3). Concomitant sedative-hypnotic use also increased
risk substantially at opioid doses 20–49 mg/d (aHR, 6.2; 95%
CI, 1.9–20.0), 50–89 mg/d (aHR, 11.9; 95% CI, 3.7–38.8),
90–119mg/d (aHR, 15.8; 95% CI, 4.6–53.9), and Z120mg/d
(aHR, 20.3; 95% CI, 6.4–64.3). Among patients without
sedative-hypnotic use, risk of opioid overdose death increased
significantly at opioid doses Z90 mg/d, with 8.6 times the
risk at 90–119 mg/d and 5.8 times the risk at Z120 mg/d
(aHR, 8.6; 95% CI, 2.2–33.2 and 5.8; 95% CI, 1.7–20.0,
respectively).
TABLE 3. Risk Factors for Opioid-related Death Among WA Medicaid Enrollees Who Had Z1 Opioid Prescriptions During April
2006 to December 2010
Unadjusted Adjusted*
Deaths Person-Years Rate/100,000 HR (95% CI) P HR (95% CI) P
Total 316 251,204.1 125.8 — — — —
Age (y)
18–24 6 38,451.8 15.6 0.2 (0.1–0.5) 0.001 0.2 (0.1–0.5) 0.001
25–34 41 55,012.7 74.5 1.0 (Ref) — 1.0 (Ref) —
35–44 76 46,893.9 162.1 2.1 (1.4–3.0) 0.001 1.7 (1.2–2.6) 0.004
45–54 140 62,735.8 223.2 2.7 (1.9–3.9) 0.001 2.1 (1.5–3.0) 0.001
55–64 53 48,110.0 110.2 1.3 (0.9–2.0) 0.213 1.0 (0.7–1.6) 0.90
Sex
Female 163 169,022.0 96.4 1.0 (Ref) 1.0 (Ref) —
Male 153 82,181.8 186.2 1.9 (1.5–2.4) 0.001 1.7 (1.3–2.1) 0.001
Race/ethnicity
Non-Hispanic white 267 155,506.2 171.7 1.0 (Ref) — 1.0 (Ref) —
Non-Hispanic black 12 17,195.2 69.8 0.4 (0.2–0.7) 0.002 0.4 (0.2–0.7) 0.001
Native American/Alaskan native 14 18,967.6 73.8 0.4 (0.3–0.8) 0.003 0.5 (0.3–0.9) 0.016
Otherw
11 43,871.7 25.1 0.2 (0.1–0.3) 0.001 0.2 (0.1–0.4) 0.001
Unknown 12 15,663.4 76.6 0.5 (0.3–0.9) 0.03 0.7 (0.4–1.3) 0.27
Area of residence at first usez
Urban 248 198,094.5 125.2 1.0 (Ref) — 1.0 (Ref) —
Large, rural city/town 29 26,090.9 111.2 0.9 (0.6–1.3) 0.51 0.8 (0.6–1.2) 0.31
Small/isolated, rural town 39 26,709.9 146.0 1.2 (0.8–1.6) 0.38 1.1 (0.8–1.5) 0.67
Average daily dose (mg/d)
1–19 18 16,158.5 111.4 1.0 (Ref) — 1.0 (Ref) —
20–49 52 41,401.2 125.6 1.2 (0.7–2.1) 0.42 1.2 (0.7–2.1) 0.48
50–89 43 17,346.2 247.9 2.5 (1.4–4.3) 0.001 2.3 (1.4–4.1) 0.002
90–119 24 5228.3 459.0 4.3 (2.3–7.9) 0.001 4.0 (2.2–7.3) 0.001
120–199 25 5243.6 476.8 4.1 (2.3–7.6) 0.001 3.8 (2.1–6.9) 0.001
Z200 81 11,729.4 690.6 5.7 (3.4–9.4) 0.001 4.9 (2.9–8.1) 0.001
No current use 73 154,096.7 47.4 0.4 (0.2–0.6) 0.001 0.5 (0.3–0.8) 0.003
Duration of use (cumulative) (d)
1–30 36 153,034.9 23.5 1.0 (Ref) — 1.0 (Ref) —
31–89 37 30,907.0 119.7 5.3 (3.4–8.5) 0.001 4.3 (2.7–6.9) 0.001
90–180 45 16,999.2 264.7 9.4 (6.1–14.7) 0.001 7.2 (4.6–11.4) 0.001
181–365 74 17,455.6 423.9 18.6 (12.1–28.3) 0.001 14.0 (9.0–21.7) 0.001
366–730 61 17,189.8 354.9 18.6 (11.7–29.7) 0.001 13.9 (8.6–22.6) 0.001
730 63 15,617.6 403.4 31.8 (18.6–53.5) 0.001 23.7 (13.9–40.5) 0.001
Opioid drug type
Non-Schedule II only 54 53,304.4 101.3 1.0 (Ref) 1.0 (Ref) —
Schedule II short-acting onlyy
57 23,301.4 244.6 2.4 (1.6–3.5) 0.001 2.3 (1.6–3.3) 0.001
Schedule II long-acting onlyy
76 11,183.3 625.9 5.1 (3.6–7.3) 0.001 4.5 (3.1–6.4) 0.001
Schedule II long-acting and short-actingy
56 9318.3 665.4 5.4 (3.7–7.8) 0.001 4.7 (3.3–6.9) 0.001
None 73 154,096.7 47.4 0.4 (0.3–0.5) 0.001 0.5 (0.3–0.7) 0.001
No. prescribing providers in first year of use
1–2 80 157,308.0 50.9 1.0 (Ref) 1.0 (Ref) —
3–5 122 66,999.4 182.1 3.4 (2.5–4.5) 0.001 2.8 (2.1–3.8) 0.001
Z6 114 26,896.7 423.8 7.7 (5.8–10.3) 0.001 6.4 (4.8–8.6) 0.001
*Opioid variables were analyzed in separate models and were not included as covariates in other models. Variables used for adjustment were age, sex, race/ethnicity, area of
residence, and continuous Charlson Comorbidity Index.
w
Asian, Hawaiian/Pacific Islander, and Hispanic were combined with “Other” because there were no deaths in these categories.
z
Defined using the 2005 classification system for rural-urban commuting area (RUCA) codes by the University of Washington Rural Health Research Center.
y
With or without non-Schedule II opioids.
CI indicates confidence interval; HR, hazard ratio; Ref, reference.
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6. DISCUSSION
We report a clear dose-response relationship between
opioid dose and risk of overdose death in WA Medicaid.
Treatment with both long-acting and short-acting Schedule II
opioids had the highest risk compared with non-Schedule II
medications only. A striking increase in opioid mortality risk
was seen with recent use of benzodiazepines alone or a
combination of benzodiazepines and skeletal muscle relax-
ants. Concurrent use of sedative-hypnotics with opioids,
even at the lowest opioid doses, substantially increased risk
of opioid overdose death compared with low-dose opioid use
and no sedative-hypnotics. This risk associated with con-
current sedative-hypnotic use significantly increased with
increasing opioid doses. Still, opioids alone, without con-
current sedative-hypnotic use, had a significantly increased
risk of fatal overdose at doses Z90 mg/d.
The elevated risks of opioid overdose death that we
observed among all opioid users with higher doses of
Z120 mg/d compared with users at the lowest doses are
consistent with other studies.28–32,45,46 The risk of fatal
opioid overdose also significantly increased among patients
at doses 50–89 and 90–119 mg/d, which corroborate dosing
recommendations in the recent CDC guideline.11 A study at
a WA health maintenance organization found that, compared
with low-dose opioid users, users of 50–99 mg/d were at 3.7
(95% CI, 1.5–9.5) times greater risk for an overdose event and
users of Z100 mg/d were at 8.9 (95% CI, 3.99–19.72) times
the risk.28 Similarly, US Veterans receiving 50–99 mg/d had
4.6 (3.18–6.74) times higher risk as compared with 20 mg/d,
and those receiving 100 mg/d, had a 7-fold increased risk of
opioid overdose death (95% CI, 4.85–10.65).29
Our findings support the recent CDC opioid prescribing
guideline which underscores the need to practice caution
when treating patients with high-risk regimens, including
opioid doses Z50 mg/d and concomitant benzodiazepine
use.11 We demonstrated that not only did risk of opioid
overdose death in patients receiving both opioids and
sedative-hypnotics significantly increase with increasing
opioid doses, but risk was substantially higher even at low to
moderate opioid doses. In addition, the risk remained ele-
vated among opioid users at doses above 90 mg/d who were
not using sedative-hypnotics. We also observed higher opioid
overdose risk in patients who were not current opioid users
but were currently using sedative-hypnotics. The higher risk
of opioid overdose among patients using sedative-hypnotics
during periods of nonopioid use may reflect patients who had
unused opioids from an earlier prescription and continued
opioid use without medical supervision.
A North Carolina study observed increasing rates of
opioid overdose death with increasing opioid dose among
TABLE 4. Risk of Opioid-related Death and Recent Sedative-hypnotic Use Among WA Medicaid Enrollees Who Had Z1 Opioid
Prescriptions During April 2006 to December 2010
Unadjusted Adjusted*
Deaths Person-Years Rate/100,000 HR (95% CI) P HR (95% CI) P
Total sedative-hypnoticsw
236 65,379.9 361.0 8.0 (6.2–10.4) 0.001 6.4 (5.0–8.4) 0.001
Types of sedative-hypnotics
None 80 185,848.6 43.1 1.0 (Ref) 1.0 (Ref) —
Benzodiazepines only 106 25,381.8 417.6 9.3 (6.9–12.4) 0.001 7.5 (5.5–10.0) 0.001
Benzodiazepines and skeletal muscle relaxants 56 8075.3 693.5 15.3 (10.8–21.6) 0.001 12.6 (8.9–17.9) 0.001
Benzodiazepines and otherz
17 3176.9 535.1 11.7 (6.9–19.8) 0.001 9.8 (5.8–16.5) 0.001
Skeletal muscle relaxants only 30 19,786.5 151.6 3.5 (2.3–5.3) 0.001 2.8 (1.8–4.2) 0.001
Skeletal muscle relaxants and otherz
4 1829.5 218.6 4.8 (1.7–13.0) 0.002 3.9 (1.4–10.7) 0.008
Other onlyz
9 5591.8 161.0 3.6 (1.8–7.2) 0.001 3.1 (1.6–6.2) 0.001
All types 14 1513.7 924.9 19.8 (11.2–35.0) 0.001 16.7 (9.4–29.6) 0.001
Opioid average daily dose by sedative-hypnotic use (mg/d)
No sedative-hypnotic use
1–19 3 9165.5 32.7 1.0 (Ref) 1.0 (Ref) —
20–49 11 24,074.3 45.7 1.6 (0.5–5.9) 0.450 1.6 (0.4–5.6) 0.49
50–89 7 9716.3 72.0 2.7 (0.7–10.3) 0.155 2.5 (0.6–9.7) 0.18
90–119 7 2555.2 274.0 9.6 (2.5–37.0) 0.001 8.6 (2.2–33.2) 0.002
Z120y
17 7049.6 241.2 6.9 (2.0–23.6) 0.002 5.8 (1.7–20.0) 0.005
No current opioid use 35 133,263.5 26.3 0.7 (0.2–2.2) 0.512 0.8 (0.2–2.6) 0.68
Sedative-hypnotic use
1–19 15 6993.0 214.5 5.9 (1.7–20.4) 0.005 5.6 (1.6–19.3) 0.007
20–49 41 17,326.9 236.6 6.7 (2.1–21.7) 0.001 6.2 (1.9–20.0) 0.002
50–89 36 7629.9 471.8 13.2 (4.1–42.7) 0.001 11.9 (3.7–38.8) 0.001
90–119 17 2673.2 636.0 17.4 (5.1–59.5) 0.001 15.8 (4.6–53.9) 0.001
Z120y
89 9923.5 896.9 23.7 (7.5–75.0) 0.001 20.3 (6.4–64.3) 0.001
No current opioid use 38 20,833.2 182.4 4.6 (1.4–15.0) 0.010 4.4 (1.4–14.3) 0.013
*Variables were analyzed in separate models and were not included as covariates in other models. Variables used for adjustment were age, sex, race/ethnicity, area of residence,
and continuous Charlson Comorbidity Index.
w
Use of sedative-hypnotics compared with nonuse.
z
Because of the small number of deaths in the sedative-hypnotic categories “barbiturates” and “nonbarbiturate hypnotics,” the 2 categories were collapsed as “other” for this
analysis.
y
Because of the small number of deaths among sedative-hypnotic nonusers with doses 120–199 mg/d, the dose categories of 120–199 mg/d and Z200mg/d were collapsed for
this analysis.
CI indicates confidence interval; HR, hazard ratio; Ref, reference; WA, Washington.
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7. patients who had an opioid prescription and received a
benzodiazepine in the prior year. The overall rate of opioid
overdose death among these patients was 10 times higher
than in patients with opioid use only.31 We report increased
risk among patients with benzodiazepine use alone, but also
showed that skeletal muscle relaxants and other non-
benzodiazepines contribute to increased risk by sedative-
hypnotics. To our knowledge, this study is the first report of
substantially increased risk of opioid-related mortality with
combinations of benzodiazepines and muscle relaxants. In
our study, 10.5% of patients had used these medications
together (data not shown), suggesting that this treatment
combination may be relatively common. A recent meta-analysis
of noninvasive treatments for low back pain found only low-
quality evidence in support of use of muscle relaxants, primarily
for acute low back pain.47 However, a recent high-quality
randomized trial among patients who initially presented to the
emergency department with acute low back pain found no ef-
ficacy of a muscle relaxant compared with a nonsteroidal anti-
inflammatory medication.48 The common use of these drugs
may relate to a misconception that they directly alleviate muscle
spasm, which is common in low back pain. The substantially
added risk for prescription opioid mortality with concomitant
opioids and muscle relaxants described here should prompt
much greater caution in the routine use of this class of drugs.
Our study seems to be the first to provide evidence of an
association between treatment combinations of long-acting and
short-acting opioids and risk of fatal opioid overdose. We
found that patients using both long-acting and short-acting
Schedule II opioids had the highest risk of overdose compared
with users of non-Schedule II opioids only. The risk was
similar for use of long-acting opioids alone. Although use of
long-acting opioids with or without Schedule II short-acting
opioids posed greater risk of overdose death, users of Schedule
II short-acting opioids alone also had a smaller but sig-
nificantly increased risk compared with users of non-Schedule
II opioids only. A recent study reported increased risk of
nonfatal opioid overdose among noncancer pain patients ini-
tiating opioid therapy with long-acting opioids versus short-
acting opioids.37 Other studies have observed varying opioid
overdose risk with specific long-acting opioids.22,23,49
In a recent Medicaid study, more than half of nonfatal
opioid poisonings were in patients with acute or intermittent
opioid use.50 In our study, we found that the risk of fatal opioid
overdose significantly increased among opioid users starting at
only 31–89 cumulative days of use compared with users with
r30 cumulative days of use. Because of a study limitation of
not having information on opioid use before study eligibility,
duration of opioid use may have been underestimated. We
were also unable to distinguish between incident and chronic
opioid users. Although some studies have required an opioid-
free time interval before the index opioid prescription,28,33,37
we found that over 70% of the patients who died of opioid
overdose were already on prescription opioids at the time they
became eligible for Medicaid. Requiring an opioid-free time
period before the index prescription would have excluded these
opioid deaths and created a very limited and possibly biased
sample of Medicaid patients taking opioids. By including all
opioids users, without requiring an opioid-free interval, our
sample is more representative of all opioid users in the WA
Medicaid system.
Another limitation of our study was that data were only
available for individuals with fee-for-service (67%–75% of
Medicaid enrollees during study years) and did not include
complete data for individuals when enrolled in managed care
or dual-eligible programs. We were, however, fortunate to
have captured this fee-for-service data when available as the
vast majority of Medicaid patients in WA are now in managed
care, similar to many other states. Future studies would likely
have to use state prescription drug monitoring programs to
access detailed opioid prescription data with Medicaid as
payer. Other limitations in our study are inherent in use of
pharmacy claims data. Opioid use may be underestimated due
to prescriptions that were denied, charged to other insurance,
or paid for out-of-pocket. The prescription dispense date may
not reflect the actual timing of medication use, and we could
not determine actual medication intake or duration of use.
Finally, we could not assess changes in pain and function
without patient-reported outcomes.
Our findings support new CDC guideline-recommended
dosing thresholds in opioid prescribing and increased risk
monitoring at lower opioid doses when factors that increase
risk for harm are present. Recent use of sedative-hypnotics,
especially benzodiazepines or benzodiazepine/skeletal muscle
relaxant combinations, substantially increased opioid mortality
risk. Concurrent use of prescription opioids and sedative-
hypnotics, even at low to moderate opioid doses, poses a great
increased risk of opioid overdose.
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