Direct Costs of Opioid Abuse in an Insured Population in the United States

O R I G I N A L R E S E A R C H
Direct Costs of Opioid Abuse in an
Insured Population in the United States
ALAN G. WHITE, PhD; HOWARD G. BIRNBAUM, PhD; MILENA N. MAREVA, BA; MAHAM DAHER, BA;
SUSAN VALLOW, RPh, MBA, MA; JEFF SCHEIN, DrPH, MPH; and NATHANIEL KATZ, MD
ABSTRACT
pioid abuse can impose substantial costs on society
and to payers as well as to the users themselves.
OBJECTIVE: To (a) describe the demographics of opioid abusers; (b) compare the
OAlthough there has been some research on the overall
prevalence rates of selected comorbidities and the medical and drug utilization
patterns of opioid abusers with patients from a control group, for the period
costs of opioid abuse, few studies have undertaken systematic
from 1998 to 2002; and (c) calculate the mean annual per-patient total health
research of costs from the payer perspective and quantified the
care costs (e.g., inpatient, outpatient, emergency room, drug, other) from the
payer burden of opioid abuse. In this article, we analyzed the
perspective of a private payer.
economic burden of opioid abuse (both prescription and non-
METHODS: An administrative database of medical and pharmacy claims from
prescription) from a private payer’s perspective. The analysis
1998 to 2002 of 16 self-insured employer health plans with approximately
focused on average per-patient direct health care costs (medical
2 million lives was used to identify “opioid abusers”—patients with claims
and drug) measured in 2003 United States dollars.
associated with ICD-9-CM (International Classification of Diseases, 9th Revision,
Clinical Modification) codes for opioid abuse (304.0, 304.7, 305.5, and 965.0
A number of studies have discussed the growing prevalence
[excluding 965.01]). A control group of nonabusers was selected using a matched
of opioid abuse in the United States. The National Household
sample (by age, gender, employment status, and census region) in a 3:1 ratio.
Survey on Drug Abuse (NHSDA) estimated that more
Per-patient annual health care costs (mean total medical and drug costs) were
than 6 million Americans used prescription pain relievers
measured in 2003 U.S. dollars. Multivariate regression techniques were also used
(e.g., oxycodone) for nonmedical purposes in 1999. By 2001,
to control for comorbidities and to compare costs with a benchmark of depressed
patients.
this number had increased to 8.4 million, approximately 4 % of
the U.S. population.1-3 Findings from the National Survey on
RESULTS: 740 patients were identified as opioid abusers, a prevalence of 8 in
Drug Use and Health showed that nonmedical use of pain
10,000 persons aged 12 to 64 years continuously enrolled in health care plans
for whom 12 months of data were available for calculating costs. Opioid abusers,
relievers among persons aged 12 years and older increased from
compared with nonabusers, had significantly higher prevalence rates for a number
11.0 million to 11.7 million.4 Although these results are not
of specific comorbidities, including nonopioid poisoning, hepatitis (A, B, or C),
directly comparable with those of the NHSDA, they indicate the
psychiatric illnesses, and pancreatitis, which were approximately 78, 36, 9, and
growing prevalence of opioid abuse in the United States.
21 (P < 0.01) times higher, respectively, compared with nonabusers. Opioid
From 1999 to 2001, the number of patients admitted for the
abusers also had higher levels of medical and prescription drug utilization.
Almost 60% of opioid abusers had prescription drug claims for opioids compared
treatment of prescription opioid abuse increased from approxi-
with approximately 20% for nonabusers. Prevalence rates for hospital inpatient
mately 23,000 in 1999 to more than 38,000 in 2001.5
visits for opioid abusers were more than 12 times higher compared with
Furthermore, the number of emergency room visits related to
nonabusers (P < 0.01).
illegal drug use or nonmedical use of prescription drugs
Mean annual direct health care costs for opioid abusers were more than
increased from approximately 250,000 in the latter half of 1997
8 times higher than for nonabusers ($15,884 versus $1,830, respectively, P < 0.01).
Hospital inpatient and physician-outpatient costs accounted for 46% ($7,239) and
to more than 325,000 in the latter half of 2001.6 The growing
31% ($5,000) of opioid abusers’ health care costs, compared with 17% ($310)
prevalence of drug and opioid abuse has caused an increase in
and 50% ($906), respectively, for nonabusers. Mean drug costs for opioid abusers
were more than 5 times higher than costs for nonabusers ($2,034 vs. $386,
respectively, P < 0.01), driven by higher drug utilization (including opioids) for
opioid abusers. Even when controlling for comorbidities using a multivariate
Authors
regression model of a matched control of depressed patients, the average health
ALAN G. WHITE, PhD, is a vice president, HOWARD G. BIRNBAUM, PhD, is
care costs of opioid abusers were 1.8 times higher than the average health care
a vice president, MILENA N. MAREVA, BA, is a senior analyst, and MAHAM
costs of depressed patients.
DAHER, BA, is a senior analyst, Analysis Group, Inc., Boston, Massachusetts;
CONCLUSION: The high costs of opioid abuse were driven primarily by high
SUSAN VALLOW, RPh, MBA, MA, is associate director, primary care outcomes
prevalence rates of costly comorbidites and high utilization rates of medical
research, and JEFF SCHEIN, DrPH, MPH, is senior director, primary care
services and prescription drugs.
outcomes research, Janssen Medical Affairs, L.L.C., Raritan, New Jersey;
NATHANIEL KATZ, MD, is a vice president, medical affairs and pain research,
KEYWORDS: Opioid abuse, Prevalence rates, Direct health care costs
Inflexxion, Inc., Newton, Massachusetts.
J Manag Care Pharm. 2005;11(6):469-79
AUTHOR CORRESPONDENCE: Alan G. White, PhD, Vice President, Analysis
Group, Inc., 111 Huntington Ave., 10th Fl., Boston, MA 02199.
Tel: (617) 425-8217; Fax: (617) 425-8001; E-mail: awhite@analysisgroup.com
Copyright© 2005, Academy of Managed Care Pharmacy. All rights reserved.
www.amcp.org Vol. 11, No. 6 July/August 2005 JMCP
Journal of Managed Care Pharmacy 469

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Direct Costs of Opioid Abuse in an Insured Population in the United States
government attention devoted to this problem; in 2001, the
rates of selected comorbidities, and direct health care costs were
National Institute of Drug Abuse launched a public information
compared for opioid abusers and nonabusers.
campaign to educate patients, health care providers, and
pharmacists regarding the potential dangers of prescription drug
Data
abuse.7
The database contained deidentified administrative claims data
Several researchers have attempted to quantify the costs
for approximately 2 million insured members from 16 large
associated with drug abuse, including opioid abuse. Without
employers for the period from 1998-2002. Together these
distinguishing between legal and illegal drug use, Harwood
employers had operations nationwide in a broad array of industries
estimated that overall costs of drug abuse in 1998 were and job classifications. The data included all medical (e.g., hospital
$97.7 billion.8 His study focused on 3 major cost categories:
inpatient, physician office visits, etc.) as well as prescription
health care, criminal justice, and workplace burden costs. The
drug claims for employees, spouses, and dependents.
National Institutes of Health reported that, in 1998, the overall
Prescription drug utilization was identified using both National
cost of drug abuse was $143.4 billion, with 69% in lost Drug Codes (NDCs) for drug claims and Health Care Financing
productivity costs, 9% in health costs, and 22% in other costs
Administration Common Procedure Coding System (HCPCS)
such as criminal justice.9 There have also been a few studies that
codes for medical claims where drugs were administered as part
have focused on the costs associated with illicit drug abuse.10,11
of a medical procedure. The data allowed for disaggregation of
Only one study was found that focused on prescription opioid
costs by place of service (e.g., hospital outpatient versus hospital
abuse in particular. Birnbaum et al. found that the cost of inpatient). The data could therefore be used to compare the
prescription opioid abuse in the United States in 2001 was drivers of total payer costs across opioid abusers and
$9.2 billion; approximately 30% ($2.8 billion) was for health
nonabusers. The data also allowed comparison of medical
care, 50% ($4.6 billion) for lost productivity, and 20% and drug utilization and prevalence rates of selected pre-
($1.8 billion) for criminal justice.12 Given the trends in increasing
specified comorbidities across opioid abusers and nonabusers.
prevalence rates of prescription opioid abuse, its economic burden
The prevalence rates were compared by calculating relative risk
on society is very likely to escalate in the coming years.
ratios (i.e., the ratio of the respective prevalence rates for opioid
Furthermore, since the condition is likely to be underdiagnosed
abusers to nonabusers), and statistical differences in prevalence
because of the associated stigma, the true burden is probably
rates were assessed using a chi-squared analysis. Differences in
much greater.
averages between the 2 samples were assessed using t tests.
This article focuses on the payer burden of opioid abuse by
measuring the per-patient costs incurred by payers arising from
Identification of Research Samples
all medical and pharmacy payments made for patients The patient research samples were identified as patients
diagnosed with opioid abuse (i.e., related to opioid abuse and
between the ages of 12 and 64 years who were continuously
other comorbid conditions).
enrolled in health care plans for a 12-month period around the
index date (defined below). Patients were identified as opioid
II Methods
abusers based on having at least 1 claim with at least 1 of the
Overview
following 4 ICD-9-CM codes over the period 1998-2002:
A group of patients with a diagnosis of opioid abuse was identified
304.0 opioid type dependence
and randomly matched to a group of patients with no diagnoses
304.7 combinations of opioid abuse with any other
of opioid abuse. Medical and pharmacy claims and eligibility
305.5 opioid abuse
data were used to compare the demographic characteristics,
965.0 poisoning by opiates and related narcotics excluding
medical services and drug utilization, prevalence rates of selected
poisoning by heroin (965.01)
comorbidities, and average annual direct health care (i.e., medical
The index date in this study was defined as the first
and drug) costs for patients for both groups. Patient samples
observed date of diagnosis of opioid abuse. Patients were
were identified using ICD-9-CM (International Classification of
included if they had claims history for at least 6 months preindex
Diseases, 9th Revision, Clinical Modification) codes for opioid
date and 6 months postindex date. The index date was not
abuse. The difference in costs between these 2 groups was used
necessarily the first date of diagnosis of opioid abuse, given the
to calculate the excess burden of opioid abuse (i.e., the extent
requirement of 6 months of medical claims history prior to
to which health care costs of opioid abusers were greater than
the index date. If a patient was diagnosed with opioid abuse in
those of nonabusers). Costs were measured as payer payments
February 1998, then this patient would not be included in the
for services provided during a 12-month period for each patient
analysis, given that the patient would not have had at least
during the years 1998-2002, and were adjusted to 2003 U.S.
6 months of preindex date medical claims history (assuming
dollars using the medical consumer price subindex. Descriptive
there were no subsequent claims associated with opioid abuse).
statistics for medical services and drug utilization, prevalence
Patients were required to be continuously enrolled in health
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Direct Costs of Opioid Abuse in an Insured Population in the United States
care plans during all 12 months of the study (i.e., the 6 months
TABLE 1
Demographic Profile of Opioid Abusers
preindex and postindex date). The sample is likely to contain
and Nonabusers, 1998-2002
both prescription opioid abusers and nonprescription opioid
(Patients Aged 12-64 Years)
abusers, since ICD-9-CM codes do not distinguish between the
2 types of opioid abuse.
Opioid Abusers* (N = 740)
Nonabusers* (N = 2,220)
It is worth noting that the term “opioid abuse” is a general
N
%
N
%
term, used differently by different people in various contexts. Gender
In some cases, it means a less serious form of addiction,
Male
422
57.0
1,266
57.0
Female
318
43.0
954
43.0
i.e., someone appears to be addicted but doesn’t meet the full
Age (years)
Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)
Mean
37.6
37.4
criteria for addiction (opioid dependence).7 In fact DSM-IV has
Median
39.0
39.0
specific criteria for opioid abuse. Definitions of prescription
Standard deviation
13.3
13.5
opioid abuse span a spectrum from episodic nonmedical use of
12-17
56
7.6
168
7.6
a drug (Drug Enforcement Agency and National Institute for
18-34
222
30.0
666
30.0
Drug Abuse) to nonmedical use resulting in harm (Institute of
35-54
389
52.6
1,167
52.6
55-64
73
9.9
219
9.9
Medicine and Drug Abuse Warning Network) to very specific
Region
criteria such as those in DSM-IV.7 In 2001, The American
Midwest
105
14.2
315
14.2
Academy of Pain Medicine issued recommendations for distin-
Northeast
153
20.7
459
20.7
guishing between “physical dependence” and “addiction,”
South
388
52.4
1,164
52.4
where physical dependence referred to a condition characterized
West
94
12.7
282
12.7
by withdrawal symptoms when one stops using opioids. * Patients are required to have medical claims data 6 months preindex date and 6 months
By contrast, addiction “is characterized by behaviors that include
postindex date during which they are continuously enrolled in a health care plan. The
index date here is defined as the first date for a claim associated with an opioid abuse
one or more of the following: impaired control over drug use,
ICD-9-CM code that satisfies the above enrollment requirements.
compulsive use, continued use despite harm, and craving.”13
Given the different uses of the term opioid abuse and the
possibility for miscoding with the ICD-9-CM codes, we
TABLE 2
Comparison of Prevalence Rates of
grouped all such ICD-9-CM codes that related to opioid abuse
Selected Comorbidities 1998-2002
for the purposes of our cost calculations and analyses and
(Patients Aged 12-64 Years)
labeled these patients “opioid abusers.” However, recognizing
Opioid Abusers
Nonabusers
that abuse and dependence may not necessarily be synonymous,
(N = 740)
(N = 2,220)
Relative
P
we report some sensitivity analyses based on different cohorts
N
%
N
%
Risk Ratio Value*
defined by ICD-9-CM codes. These are discussed below.
[E] =
Comorbidities†
[A]
[B]
[C]
[D]
[B]/[D]
A random sample was also drawn from the same overall
patient population to serve as a comparison group. The same
Nonopioid poisoning
130
17.6
5
0.2
78.0
< 0.01
Hepatitis (A,B, and C)
48
6.5
4
0.2
36.0
< 0.01
basic inclusion criteria imposed on the opioid abuse sample
Other substance abuse
373
50.4
26
1.2
43.0
< 0.01
were also imposed on the matched sample: aged 12 to 64 years,
Pancreatitis
7
0.9
1
0.05
21.0
< 0.01
continuously enrolled in a health care plan during all Psychiatric diagnoses
526
71.1
186
8.4
8.5
< 0.01
12 months of the study period, and having at least 1 medical or
Cirrhosis/chronic or
33
4.5
13
0.6
7.6
< 0.01
acute liver disease
prescription drug claim during that year. The random sample
Motor vehicle traffic
10
1.4
5
0.2
6.0
< 0.01
excluded patients with opioid abuse diagnoses and was matched
accidents
with the opioid abuse sample by gender, age, employment status,
HIV/AIDS
10
1.4
6
0.3
5.0
< 0.01
and census geographic region on a 3:1 matching ratio.
Hepatitis (E and Other)
3
0.4
2
0.1
4.5
0.07
Skin infections/abscesses
75
10.1
55
2.5
4.1
< 0.01
An important feature of the analysis is that there was no
Burns
6
0.8
6
0.3
3.0
0.05
“wash-out” period before or after claims associated with the
Gastrointestinal bleeding
59
8.0
57
2.6
3.1
< 0.01
ICD-9-CM codes for the opioid abusers in the study. Studies
Trauma
270
36.5
333
15.0
2.4
< 0.01
that impose a wash-out period before the first diagnosis and
Herpes simplex
10
1.4
14
0.6
2.1
0.06
Sexually transmitted
59
8.0
96
4.3
1.8
< 0.01
after the end of a “disease episode” are generally focused on
diseases
capturing the cost of illness associated with the onset of the Hepatitis (alcoholic)
1
0.1
0
0.0
–
–
disease in question and its immediate treatment. In contrast, the
Endocarditis
5
0.7
0
0.0
–
–
goal of the current study was to capture a payer’s typical direct
* Chi-square tests were conducted to compare the prevalence rates of comorbidities for
medical cost burden for the average annual cost of illness for all
opioid abusers and nonabusers.
† For ICD-9-CM codes corresponding to each comorbidity group, see Appendix A.
patients diagnosed with opioid abuse who may have been in
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Direct Costs of Opioid Abuse in an Insured Population in the United States
FIGURE 1 Comparison of Medical Utilization Patterns,*† 1998-2002 (Patients Aged 12-64 Years)
100%
97.3%
I Opioid Abusers
I Nonabusers
80%
Medical Services Determined
Medical Services Determined
by Place of Service
by Diagnosis and Procedure Codes
isit or Claim
71.5%
71.1%
67.8%
61.5%
60%
ith at Least 1 V
45.5%
40%
36.5%
29.1%
centage of Patients W
20%
17.4%
Per
15.0%
14.6%
12.6%
9.2%
8.4%
4.1%
5.5%
4.4%
1.4%
0.2%
0.2%
0.5%
0.2%
0%
Physician’s
Mental
Hospital Emergency Mental
Other
Motor
Trauma Substance
Substance
Mental
Visit/ Health
Inpatient
Room
Health
Place
of
Vehicle
N = 270/333
Abuse
Abuse
Disorders
Outpatient Outpatient N = 502/123 N = 129/97 Inpatient Service
Traffic
Treatment
Treatment N = 526/186
N = 720/1,587 N = 337/90 N = 93/5
N = 455/645 Accident
Outpatient
Inpatient
N = 10/5
N = 68/11
N = 108/5
* The difference in prevalence rates between abusers and nonabusers for all visit or claim types was found to be statistically significant at the 1% level (P < 0.01).
† “N” denotes the number of opioid abusers/nonabusers who had at least 1 visit or claim for the corresponding medical service category. The total number of opioid abusers
and nonabusers were 740 and 2,220, respectively.
different stages of their abuse: onset, treatment, management,
ments paid by the patients (i.e., the claim field used in the
and/or recovery. In addition, the nature of opioid abuse and the
current study was net plan cost after subtraction of copayments
fact that it likely lasts for several years with associated higher
and other member cost share). The dollar amounts for all claims
prevalence rates of certain comorbidities creates difficulties in
for each patient during the 12 months including the 6-month
identifying the beginning or end of abuse and the costs preindex and 6-month postindex date were summed to arrive at
associated with it. Therefore, by taking a more general their total direct medical costs. These costs were then averaged
cross-sectional approach in calculating the average direct health
over all patients in the research samples to arrive at the average
care costs associated with opioid abuse, patients with varying
cost per patient for opioid abusers and nonabusers.
degrees of severity and in different stages of their illnesses were
captured. Thus, we selected patients on the basis of a claim for
II Results
opioid abuse, conditioned on having their medical claims The resulting sample sizes for the study were 740 opioid
history for the 6 months preindex and postindex date.
abusers and 2,220 nonabusers. Males accounted for 57% of
opioid abusers and nonabusers (Table 1). The average age of
Calculation of Direct Costs
opioid abusers was 37.6 years, and 52.6% of opioid abusers
Direct health care costs were calculated based on payments
were in the 35 to 54-year age range.
made by payers for inpatient, outpatient, physician, and
The prevalence of opioid abuse among the members in our
prescription drug claims as well as for all other medical services.
database increased from 5 per 10,000 in 1998 to 8 per 10,000
Since the focus of this study was on the payer burden of opioid
in 2002, where the denominator was the total annual number
abuse, these payments did not include deductibles or copay-
of insured members in each year, and the numerator was the
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Direct Costs of Opioid Abuse in an Insured Population in the United States
cumulative number of patients with claims associated with
TABLE 3
Prevalence Rates of Chronic Painful
ICD-9-CM codes for opioid abuse in the year. This represents a
Comorbidities,* 1998-2002
60% increase.
(Patients Aged 12-64 Years)
The prevalence rates of a number of comorbid conditions
between opioid abusers and nonabusers were identified (Table 2).
Opioid Abusers
Nonabusers
(N = 740)
(N = 2,220)
A patient was classified as having a given comorbid condition if
Relative
P
the patient had at least 1 claim associated with the ICD-9-CM
N
%
N
%
Risk Ratio Value†
codes for the conditions over the period 1998-2002 (see
[E] =
Painful Comorbidity
[A]
[B]
[C]
[D]
[B]/[D]
Appendix A for the ICD-9-CM codes associated with the
comorbid conditions). Among opioid abusers, comorbid Headache/migraine
57
7.7
22
1.0
7.8
< 0.01
Other musculoskeletal
44
5.9
23
1.0
5.7
< 0.01
conditions such as nonopioid poisoning, hepatitis (A, B, C),
pain
psychiatric illnesses, and pancreatitis were 78.0, 36.0, 8.5, and
Low-back pain
143
19.3
79
3.6
5.4
< 0.01
21.0 (P < 0.01) times, respectively, as prevalent as those for
Neuropathic pain
18
2.4
10
0.5
5.4
< 0.01
nonabusers. Similarly, an analysis of painful comorbidities
Other chronic pain
128
17.3
102
4.6
3.8
< 0.01
Arthritis
111
15.0
99
4.5
3.4
< 0.01
found that almost half of all opioid abusers had any chronic
Other back and neck
32
4.3
38
1.7
2.5
< 0.01
pain comorbidity (47.6%), with low-back pain being the most
pain
prevalent (19.3%, Table 3). The higher prevalence rates of these
Cancer
11
1.5
17
0.8
1.9
0.08
potentially costly comorbidities likely contributed to the higher
Any painful
352
47.6
384
17.3
2.8
< 0.01
comorbidity‡
health care costs for opioid abusers compared with nonabusers. * A claimant is considered to have a chronic painful comorbidity if the claimant has
Opioid abusers had higher utilization rates of various
at least 2 claims at least 90 days apart within a comorbidity group.
medical services as measured by the number of claims for † Chi-square tests were conducted to compare the prevalence rates of comorbidities
medical services (Figure 1). For example, opioid abusers were
for the opioid abusers and nonabusers.
11.2 times more likely to have had at least 1 mental health ‡ “Any painful comorbidity” includes ICD-9-CM codes from any of the painful
comorbidity groups: headache/migraine, other musculoskeletal pain, low-back pain,
outpatient visit and 12.2 times more likely to have had at least
neuropathic pain, other chronic pain, arthritis, other back and neck pain or cancer.
1 hospital inpatient stay than nonabusers (P < 0.01). Furthermore,
opioid abusers averaged 18.7 physician or outpatient visits
compared with 7 for nonabusers (P<0.01). Opioid abusers were
also 4 times more likely to have had an emergency room visit
Calculations of the average health care costs for opioid
than nonabusers (P < 0.01). The high rates of use of medical
abusers and nonabusers showed that patients who were opioid
services by opioid abusers, in combination with their comor-
abusers had health care costs that were more than 8 times higher
bidity profile, likely contributed to their higher average health
than those of nonabusers (Figure 2). The total average per-
care costs.
patient direct health care payer cost for opioid abusers was
Opioid abusers had higher utilization rates of prescription
$15,884 compared with $1,830 for nonabusers (P < 0.01).
drugs (Table 4). When one considers all prescription drug use
Statistically significant differences from the matched sample of
(including opioids and nonopioids), 86.9% of opioid abusers
nonabusers are noted in Figure 2, where applicable. These
had at least 1 prescription drug claim compared with 61.7% for
average per-patient costs included both opioid-abuse related
nonabusers, and opioid abusers had, on average, 41.6 prescription
costs (such as substance abuse treatment) in addition to other
drug claims compared with 13.8 for nonabusers (P < 0.01).
comorbidity-related costs (such as pancreatitis, hepatitis, etc.)
These drugs were identified using NDCs for drug claims and
The excess annual cost burden of opioid abuse (i.e., the differ-
HCPCS codes for medical claims in the cases of drugs adminis-
ence between the average per-patient payer costs of opioid
tered as medical procedures. About 58% of opioid abusers had
abusers and nonabusers) was $14,054 per patient.
claims for short-acting opioids (SAOs), long-acting opioids
Disaggregated direct health care costs were also calculated
(LAOs), or both, compared with about 20% of nonabusers.
(Appendix B provides a detailed breakdown of costs, by cost
More than 40% of opioid abusers had claims for SAOs, and
component, for both patient samples). Statistically significant
about 17% had claims for both SAOs and LAOs. As noted
differences in average costs between the 2 groups are noted,
above, almost 50% of opioid abusers had a diagnosis of a chron-
where applicable. For direct health care costs, hospital inpatient
ically painful condition (Table 3), similar to prevalence rates of
costs accounted for the largest percentage of costs for opioid
chronic pain among opioid abusers in another study.14 This abusers, 46% compared with 17% for nonabusers (or $7,239
suggests that the rates of opioid claims among opioid abusers
vs. $310, P<0.01, or more than 20 times higher). Physician and
coincide with high prevalence rates of chronically painful outpatient visits accounted for 31% of opioid abusers’ costs
conditions, noting that the notion of opioid abuse is not always
compared with 50 % for nonabusers. Although such visits com-
well defined.
prised a greater percentage of the costs for nonabusers, the costs
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Direct Costs of Opioid Abuse in an Insured Population in the United States
TABLE 4
Comparison of Drug Utilization Patterns, 1998-2002 (Patients Aged 12-64 Years)
Opioid Abusers
Nonabusers
(N = 740)
(N = 2,220)
Number of Claims per Patient
Number of Claims per Patient
Number (%)
Number (%)
of Patients
of Patients
Relative Risk
With at Least 1 Claim
Mean*
SD
Median
With at Least 1 Claim
Mean*
SD
Median
Ratio†
[C] =
[A]
[B]
[A]/[B]
Prescription drugs
All prescription drugs
643
86.9%
41.6a
41.9
27.0
1,369
61.7%
13.8a
19.3
7.0
1.4a
All nonopioids
637
86.1%
32.4a
32.7
23.0
1,353
60.9%
13.0a
17.5
7.0
1.4a
Prescription opioids
SAOs‡ only
304
41.1%
9.4a
11.9
4.0
421
19.0%
2.3a
3.6
1.0
2.2a
LAOs§ only
7
0.9%
6.9
5.6
9.0
3
0.1%
11.3
14.6
5.0
7.0a
Both SAOs and LAOs
127
17.2%
25.7
15.5
24.0
8
0.4%
32.1
32.4
23.0
47.6a
* t tests were conducted to compare the mean number of claims per patient between opioid abusers and nonabusers; a denotes significance at the 1% level (P < 0.01).
† Chi-square tests were conducted to compare the prevalence rates of drug claims between opioid abusers and nonabusers; a denotes significance at the 1% level (P < 0.01).
‡ Short-acting (prescription) opioids (SAOs): any prescription drug with these active ingredients: hydrocodone (308 patients), oxycodone (153), tramadol (88), codeine (110),
propoxyphene (93), and other SAOs (78, meperidine, butorphanol, fentanyl, hydromorphone, buprenorphine, morphine, pentazocine, dihydrocodeine, opium, sufentanil, nalbuphine or
drugs administered as a medical procedure with the following HCPCS codes: J0592, J0745, J1170, S0092, J2175, J2180, J2270, J2271, J2300, and J3010). “SAOs only” includes
patients with claims only for SAOs.
§ Long-acting (prescription) opioids (LAOs): oxycodone ER (97 patients), fentanyl transdermal system (38), methadone (29), extended-release morphine (16, including the claims for
brand names Kadian, Avinza, MS Contin, Oramorph, Astramorph PF, Duramorph, and Infumorph or extended-release morphine administered as a medical procedure
with the following HCPCS codes: J2275 and S0093). “LAOs only” includes patients with claims only for LAOs.
of such visits for opioid abusers were more than 5 times higher
of opioid abusers based on alternative groupings of ICD-9-CM
compared with nonabusers ($5,000 vs. $906, P < 0.01). Average
codes is $15,884 to $18,388, and $1,830 to $2,210 for our
drug costs for opioid abusers were more than 5 times higher
matched sample.
compared with those for nonabusers ($2,034 vs. $386), while
The descriptive analyses reported above do not control for
such drug costs accounted for 21% of overall costs for
comorbidities. The methodology adopted here considers direct
nonabusers compared with 13% for opioid abusers.
health care costs for opioid abusers arising from the presence of
We also conducted sensitivity analyses on direct health care
other comorbid conditions such as pancreatitis, hepatitis, etc.,
costs based on different groupings of the ICD-9-CM codes. in addition to opioid abuse-related costs. Analysis using a
In particular we divided our sample into 2 subgroups: one
multivariate regression approach (described below) would
based on ICD-9-CM codes 304.7 and 305.5, codes for “abuse”
allow for a more direct comparison of costs between opioid
(“Group A,” N = 141), and another based on the ICD-9-CM
abusers and a matched control while simultaneously controlling
codes 304.0 and 965.0, codes for “dependence” and “poisoning”
for a variety of factors such as comorbidity profiles and demo-
(excluding 965.01, “Group B,” N = 635). The subgroups are not
graphics that may drive costs. Furthermore, it would be useful
mutually exclusive since it is possible for a patient to be to have an alternative benchmark control group with which to
diagnosed with more than one ICD-9-CM code for opioid
compare the costs of opioid abuse; for this purpose, we have
abuse. Using the same methodology as above, the total average
chosen a control group of patients with a diagnosis of depression
per-patient direct health care payer cost for Group A was
(ICD-9-CM codes 296.2, 296.3, 300.4, 309.0, 309.1, and 311).
$18,388 compared with $2,210 for matched controls (P<0.01).
Depression is a mental health illness that is common and is
For Group B, the total average per-patient direct health care cost
diagnosed on a relatively consistent basis. Similar to opioid
was $16,204 compared with $2,179 for matched controls abuse, this condition is managed by primary care doctors and
(P < 0.01). In both instances, the direct health care costs of
specialists and is also a costly condition of interest to payers.15
Groups A and B were approximately 8 times as high as the
This regression allows us to compare the costs of an opioid
matched controls, consistent with the findings above for the
abuser to those of a depressed patient, holding other factors
broader group used for this study. It appears that Group A has
constant, such as age, gender, and the presence of other comorbid
costs that are higher than Group B, indicating that those
conditions. This allows for a more direct and meaningful
patients diagnosed as opioid “abusers” have higher costs than
comparison of the costs associated with opioid abuse.
those diagnosed as opioid “dependent.” This finding should be
We constructed a multivariate regression to account for this,
interpreted with caution given the different uses of the term
where the left-hand variable was the per-patient costs during
opioid abuse. Thus, the range of cost estimates for our sample
the 12-month period encompassing the 6 months preindex and
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Direct Costs of Opioid Abuse in an Insured Population in the United States
6 months postindex date. Patients were matched on a 3:1 basis
when one controls for comorbidities using a multivariate regression
(as before), and overlap between the 2 groups was controlled
analysis, we found that opioid abusers were 1.8 times as costly
for (e.g., patients who had a diagnosis of both depression and
to the payer as a matched control of depressed patients. In fact,
opioid abuse). The regression specification is as below:
much of the cost of opioid abuse is driven by such things as
3
hospitalizations and emergency room visits. This analysis has
cost =? + ? age +
1
?2age2 + ?3 female +?? r + ?4abuser +
i
?5abuser
shown that opioid abusers have higher prevalence rates of
i
i
=1
N
N
× depressed +
?
?
? ,
6 comorbid +
6
comorbid ×abuser +
certain comorbidities (such as nonopioid poisoning, hepatitis
? j j
j
k
=
?k
k
=
[A, B, C], pancreatitis, etc.) and have higher utilization rates
where female is a dummy variable taking the value 1 if the
of medical services such as hospital inpatient visits. This suggests
patient is female, 0 otherwise; ri is a dummy variable taking the
that these factors may have jointly contributed to the higher
value 1 if the patient is in region i, 0 otherwise; abuser is a
level of per-patient costs associated with opioid abusers
dummy variable taking the value 1 if the patient is an opioid
compared with nonabusers.
abuser, 0 otherwise; abuser x depressed is an interaction term
taking the value of 1 if the patient has at least 1 diagnosis for
Limitations
opioid abuse and at least 1 diagnosis for depression, 0 otherwise;
Focusing only on the direct health care costs understates the full
and comorbidj are dummy variables taking the value 1 if the cost burden imposed by indirect costs associated with disability,
patient has a given comorbid condition, 0 otherwise. The variables
absenteeism, and presenteeism (defined as the feeling that one
comorbidk x abuser are interaction terms, taking the value 1 if must go to work even if one is too ill to be productive or effective).
the patient is an opioid abuser and has a given comorbid It is important for payers to consider indirect costs in calculating
condition; ? is the error term.
the true overall burden of opioid abuse. Birnbaum et al. note
When we calculated descriptive statistics for our 2 samples,
that lost productivity costs accounted for 50% of the societal
we found that the per-patient costs of opioid abuse were
cost of prescription opioid abuse in the United States in 2001.12
3.4 times higher than the matched control of depressed
Since the diagnosis codes in medical claims do not distin-
patients, $16,722 for opioid abusers compared with $4,875 for
guish between prescription and nonprescription opioid abuse,
depressed patients. Based on the regression results that control
it was not possible in this study to examine the relationship of
for the effects of comorbid conditions, we found that the nonmedical use of nonprescription (e.g., heroin, cocaine, etc.)
incremental costs of opioid abuse relative to depressed patients
drugs to prescription opioid (e.g., morphine, hydrocodone,
was $3,040, indicating that opioid abusers were 1.8 times as
etc.) and total direct health care costs. Since 58% of opioid
costly as depressed patients ($3,040 vs. $3,619) (Table 5). abusers had claims for SAOs, LAOs, or both, 42% of opioid
The coefficient estimates on the comorbidities included in abusers (as defined here) may be abusing other prescription
the regression indicated that the incremental costs of the drugs or nonprescription (illicit) narcotics. Further research
comorbidities (i.e., the additional costs compared with patients
should seek to distinguish between abuse of prescription
without the comorbid condition) of other substance abuse, narcotics and illicit narcotics and measure indirect costs as well
psychiatric diagnoses, and trauma, were $5,169, $2,677, and
as direct costs for prescription and illicit opioids.
$3,145, respectively. The results suggested that patients who
A more thorough analysis of the comorbidity profile of
were abusers and had a psychiatric diagnosis or a trauma opioid abuse patients, including an assessment of the temporal
incident had additional psychiatric or trauma costs of pattern of such comorbidities, would be valuable in under-
$2,025 and $2,066, respectively. That is, psychiatric costs were
standing cost drivers. For example, if the onset of opioid abuse
$4,702 (i.e., $2,677 + $2,025) and $5,211 (i.e., $3,145 +
is associated with human immunodeficiency virus (HIV) or
$2,066) for opioid abusers compared with those without that
hepatitis (A, B, or C), then a cost offset may be realized by
comorbid condition.
advocating better treatment of opioid abuse; however, longitudinal
examinations of temporal patterns may not be possible in
II Discussion
administrative claims databases due to relatively limited
The analyses presented here highlight the substantial payer duration of membership of opioid abusers.
burden associated with patients who are diagnosed as opioid
Future research with Medicaid data is also necessary to shed
abusers. We are not aware of any other studies that have light on the prevalence and costs of opioid abuse among a
systematically quantified and compared the direct medical and
Medicaid population and possibly to help understand more
drug costs of opioid abusers with a cohort of nonabusers. This
clearly the causal relationship between opioid abuse and the
group of opioid abusers has direct health care costs that are
comorbidities discussed here. The costs of such patients in a
more than 8 times higher than those of nonabusers. These cost
Medicaid population could be quite different compared with
measures were the total per-patient direct health care costs and
those reported here from commercial health plan members.
included costs associated with other comorbid conditions. Even
It would also be useful to extend the multivariate regression
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Journal of Managed Care Pharmacy 475

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Direct Costs of Opioid Abuse in an Insured Population in the United States
analysis to account for additional factors that may drive costs,
FIGURE 2 Average Annual Direct Costs* of Opioid
including duration of abuse, prior medical history, and the
Abusers and Nonabusers, 1998-2002
presence of multiple substance abuse treatments.
$ 18,000
I
As was noted earlier, the concept of opioid abuse is often
Other Costs†
Total Direct Cost = $15,884
I Physician’s Visit/
interpreted differently by different people. Given the possibility
$ 16,000
$793 (5%)
Outpatient Costs
for miscoding with ICD-9-CM codes,16 we attempted to include
$ 14,000
I Hospital Inpatient
all ICD-9-CM codes that related to opioid abuse, recognizing
$5,398 (34%)
Costs
the possibility that those codes may not always capture the
$ 12,000
Drug Costs
phenomenon of opioid abuse.
$ 10,000
II Conclusion
$ 8,000
$7,659 (48%)
Opioid abuse is a costly condition that imposes a large direct
$ 6,000
cost burden on private payers. Opioid abusers have direct
Total Direct Cost = $1,830
$ 4,000
health care costs that are approximately 8 times higher than
$198 (11%)
$928 (51%)
those of nonabusers. These costs are likely driven by higher
$ 2,000
$2,034 (13%)
$318 (17%)
prevalence rates of costly comorbidities.
$ 0
$386 (21%)
Opioid Abusers
Nonabusers
ACKNOWLEDGMENTS
The authors gratefully acknowledge helpful comments and insights on this
* Costs are in 2003 dollars. The differences between all mean annual costs of opioid
paper from Vanja Sikirica, PharmD, manager, primary care outcomes research,
abusers and nonabusers are statistically significantly different at the 1% level
and Dilesh Doshi, PharmD, associate director, regional outcomes research,
(P < 0.01) except for “Other Costs” for which the “Other Place of Service”
Janssen Medical Affairs, L.L.C., Raritan, NJ, and San Diego, CA, respectively.
component is significantly different at the 5% level (P < 0.05).
† “Other Costs” include: “Other Place of Service” and “Emergency Room” costs.
DISCLOSURES
Funding for this research was provided by an unrestricted grant from Janssen
Medical Affairs, L.L.C. and was obtained by authors Susan Vallow and Jeff
Schein, who are employed by Janssen Medical Affairs, L.L.C. Nathaniel Katz is
a consultant to Janssen and numerous other pharmaceutical companies that
manufacture branded opioid products and nonopioid analgesics; authors Alan
G. White, Howard G. Birnbaum, Milena N. Mareva, and Maham Daher
disclose no potential bias or conflict of interest relating to this article.
TABLE 5
White served as principal author of the study. Study concept and design
Regression Results
were contributed primarily by White, Vallow, Schein, and Katz. Analysis and
interpretation of data were contributed by all authors. Drafting of the manu-
Parameter
Standard
script was primarily the work of White, and its critical revision was the work
Estimate
Error
P Value
of White and Vallow. Statistical expertise was contributed by White,
Intercept
3,619
2,258
0.1090
Birnbaum, and Daher, and administrative, technical, and/or material support
was provided by Analysis Group, Inc., Boston, MA.
Demographics
Age
-188
121
0.1213
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4
2
0.0121
Gender (female=1)
568
582
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Appendix A and Appendix B are on
pages 478 and 479, respectively.
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Direct Costs of Opioid Abuse in an Insured Population in the United States
APPENDIX A
ICD-9-CM Diagnosis Codes Associated With Comorbid Conditions
Diagnosis Type
ICD-9-CM Codes Diagnosis Description
Diagnosis Type
ICD-9-CM Codes Diagnosis Description
Other substance
303.XX
Alcohol dependance syndrome
070.41
Acute or unspecified hepatitis C with hepatic coma
abuse
304.1X
Barbiturate and similarly acting or hypnotic
070.42
Hepatitis delta without mention of active hepatitis B
(excluding
dependance
disease with hepatic coma
opioid 304.0,
304.2X
Cocaine dependance
070.44
Chronic hepatitis C with hepatic coma
sedative abuse
304.3X
Cannabis dependance
070.51
Acute or unspecified hepatitis C without mention of
304.7and 305.5) 304.4X
Amphetamine and other psychostimulant dependance
hepatic coma
304.5X
Hallucinogen dependance
070.52
Hepatitis delta without mention of active hepatitis B
304.6X
Other specific drug dependance
disease or hepatic coma
304.8X
Combinations of drug dependance excluding opioid
070.54
Chronic hepatitis C without mention of hepatic coma
304.9X
Unspecified drug dependance
V02.61
Hepatitis B carrier
305.0X
Alcohol abuse
V02.62
Hepatitis C carrier
305.1X
Tobacco dependance
Hepatitis
571.1
Acute alcoholic hepatitis
305.2X
Cannabis abuse
(alcoholic)
305.3X
Hallucinogen abuse
305.4X
Barbiturate and similarly acting sedative or
Hepatitis
070.43
Hepatitis E with hepatic coma
hypnotic abuse
(E and other)
070.49
Other specified viral hepatitis with hepatic coma
305.6X
Cocaine abuse
070.53
Hepatitis E without mention of hepatic coma
305.7X
Amphetamine and other psychostimulant abuse
070.59
Other specified viral hepatitis without mention of
305.8X
Antidepressant type abuse
hepatic coma
305.9X
Other, mixed, or unspecified drug abuse
070.6
Unspecified viral hepatitis with hepatic coma
V11.3
Personal history of alcoholism
070.9
Unspecified viral hepatitis without mention of
hepatic coma
Psychiatric
290.XX-302.XX
Psychoses, neurotic disorders & personality
V02.60
Viral hepatitis
diagnoses
disorders, and other nonpsychotic mental conditions
V02.69
Other viral hepatitis carrier
306.XX-319.XX
Neurotic and personality disorders, and other
nonpsychotic mental conditions, mental retardation
Pancreatitis
577.XX
Diseases of the pancreas
V11.X
Personal history of mental disorder
Sexually
090.XX-099.XX
Syphilis and other venereal diseases
(excluding V11.3)
transmitted
112.1X
Candidiasis of vulva and vagina
HIV/AIDS
042.XX
HIV disease
diseases
112.2X
Candidiasis of other urogenital sites
79.53
HIV virus type 2
483.1X
Chlamydia
V08.X
Asymptomatic HIV infection status
078.19
Other genital warts
795.71
Nonspecific serologic evidence of HIV
078.11
Genital warts: condyloma acuminatum
V02.7
Personal history of gonorrhea
Endocarditis
421.XX
Acute and subacute endocarditis
V02.8
Personal history of other venereal diseases
424.9X
Endocarditis, valve unspecified
647.0 Syphilis
424.9X
Endocarditis, valve unspecified, unspecified cause
647.1
Gonorrhea carried by the mother during pregnancy
424.91
Endocarditis in diseases classified elsewhere
647.2
Other venereal diseases carried by the mother during
424.99
Other—any condition classifiable to 424.90 with
pregnancy
specified cause, except rheumatic
614-616
Inflammatory diseases of the female pelvic organs
391.1X
Acute rheumatic endocarditis
131.00
Urogenital trichomoniasis, unspecified
036.42
Meningococcal endocarditis
131.01
Trichomonal vulvovaginitis
074.22
Coxsackie endocarditis
131.02
Trichomonal urethritis
093.2X
Syphilitic endocarditis
131.03
Trichomonal prostatitis
098.84
Gonococcal endocarditis
131.09
Other trichomoniasis
112.81
Candidal endocarditis
622.1X
Dysplasia of cervix
Skin infections
680-686
Infections of skin and subcutaneous tissue
623.0X
Dysplasia of vagina
/abscesses
681.XX
Cellulitis and abscess of finger and toe
Herpes simplex
054
Herpes simplex
693.XX
Due to drugs and medicines
693.8X
Due to other specified substances taken internally
Burns
940.XX-949.XX
693.9X
Due to unspecified substance taken internally
Trauma
800-829
Fractures
111.8X
Other specified dermatomycoses
(excluding
830-839
Dislocation
111.9X
Dermatomycosis, unspecified
motor
840-848
Sprains and strains of joints and adjacent muscles
707.9X
Chronic ulcer of unspecified site
vehicle traffic
850-854
Intracranial injury, excluding those with skull fracture
GI bleeding
578.XX
Gastrointestinal hemorrhage
accidents)
860-869
Internal injury of thorax, abdomen, and pelvis
456.XX
Esophageal varices with bleeding
870-879
Open wound of head, neck, and trunk
530.8X
Other specified disorders of esophagus
880-887
Open wound of upper limb
531.XX
Gastric ulcer—acute with hemorrhage
890-897
Open wound of lower limb
531.2X
Gastric ulcer—acute with hemorrhage and perforation
900-904
Injury to blood vessels
532.XX
Duodenal ulcer—acute with hemorrhage
905-909
Late effects of injuries, poisonings, toxic effects, and
532.2X
Duodenal ulcer—acute with hemorrhage and perforation
other external causes
533.XX
Peptic ulcer—acute with hemorrhage
910-919
Superficial injury
533.2X
Peptic ulcer—acute with hemorrhage and perforation
920-924
Contusion with intact skin surface
534.XX
Gastrojejunal ulcer—acute with hemorrhage
925-929
Crushing injury
534.2X
Gastrojejunal ulcer—acute with hemorrhage and
930-939
Effects of foreign body entering through orifice
perforation
950-957
Injury to nerves and spinal cord
958-959
Certain traumatic complications and unspecified
Cirrhosis/chronic 570.XX
Acute and subacute necrosis of liver
injuries
or acute liver
571.XX
Chronic liver disease and cirrhosis
disease
(excluding 571.1)
Motor vehicle
E810-E819
572.XX
Liver abscess and sequelae of chronic liver disease
traffic accidents
573.XX
Other disorders of liver
Poisoning
960.XX-979.XX
Poisoning by drugs, medicinal and biologic substances
Hepatitis (A,B,C) 070.0
Viral hepatitis A with hepatic coma
(excluding
980.XX-989.XX
Toxic effects of substances chiefly nonmedicinal as to
070.1
Viral hepatitis A without mention of hepatic coma
opioid abuse:
source
070.2X
Viral hepatitis B with hepatic coma
965.00, 965.02
070.3X
Viral hepatitis B without mention of hepatic coma
and 965.09)
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