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. Author manuscript; available in PMC: 2024 Feb 1.
Published in final edited form as: Psychol Serv. 2021 Dec 30;20(1):157–165. doi: 10.1037/ser0000607

Opioid Use Disorder With Chronic Pain Increases Disease Burden and Service Use

R Ross MacLean 1, Mehmet Sofuoglu 1, Elina Stefanovics 1, Robert Rosenheck 1
PMCID: PMC9358616  NIHMSID: NIHMS1824462  PMID: 34968125

Abstract

To address the ongoing opioid epidemic, there has been an increased focus on the treatment and evaluation of opioid use disorder (OUD). OUD and chronic pain (CP) frequently co-occur; however, little is known about the additional comorbidities that present when they occur together as compared to when either condition presents alone. Using data from Fiscal Year 2012 Veteran’s Health Administration, all veterans diagnosed with both OUD + CP were compared to those diagnosed with OUD or CP alone on socioenvironmental characteristics, medical and mental health diagnoses, and Veterans Affairs (VA) clinical service use. Veterans with OUD + CP (n = 33,166), compared to those with OUD only (n = 12,517), had higher numbers of medical conditions. Compared to those with CP only (n = 2,015,368), veterans with OUD + CP had higher rates of homelessness and substance use diagnoses. Most mental health diagnoses, numbers of psychotropic medication fills, opioid prescriptions, and use of all other services were higher in the OUD + CP group than in either single disorder group. Multinomial regression analysis revealed stronger effects for medical disorders and medical–surgical outpatient service use in the comparison of OUD + CP with OUD only and stronger effects for substance use and mental health disorders and use of prescription opiates in the comparison with CP only. These findings suggest that concurrent OUD + CP imposes exceptional disease and clinical service burdens that likely require the development of simultaneous, integrated approaches to treatment.

Keywords: opioid use disorder, chronic pain, multimorbidity, Veteran’s Health Administration, comorbidity

The substantial public health impact of the current opioid epidemic in the United States has resulted in increased interest in developing effective approaches to care for individuals with opioid use disorder (OUD; Bruneau et al., 2018; Korthuis et al., 2017). Annual opioid overdose deaths have been closely correlated with the number of opioid prescriptions for chronic pain (CP) in the United States, both of which have risen steadily since the early 1990s (Centers for Disease Control and Prevention [CDC], 2011). Treatment for CP has thus emerged as an area of particular relevance as a risk factor for OUD and for developing methods of improving treatment outcomes (Clark et al., 2008; Speed et al., 2018). CP is highly prevalent in individuals with OUD, even while engaged in opioid agonist treatment (OAT; i.e., methadone and buprenorphine pharmacotherapy). More specifically, 24%–68% of individuals with OUD receiving methadone or buprenorphine continue to report CP, defined as moderate to severe pain lasting at least 3 months (Barry et al., 2013; Rosenblum et al., 2003; Tsui et al., 2016).

Similar to OUD, CP is particularly common in patient populations and the burden of CP on personal health and use of clinical services is substantial (Rice et al., 2016). Recent estimates of CP in the United States suggest upwards of 50 million adults are affected, with the age-adjusted prevalence higher among veterans as compared to nonveterans (Dahlhamer et al., 2018). Of the top 10 conditions associated with prolonged disability, five are defined by the presence of CP (Vos et al., 2012). CP has well-characterized adverse impacts on mental health, interpersonal relationships, and daily activities (Froud et al., 2014; Reid et al., 2011). Therefore, CP, even in the absence of OUD, is associated with considerable adversity and medical comorbidities that can complicate treatment.

Relatively, few studies have assessed the impact of co-occurring OUD and CP relative to either diagnosis alone. One recent study reported that co-occurrence of OUD and CP in a methadone clinic population was associated with an especially high prevalence of psychiatric comorbidities including depression, anxiety, and nonopioid substance use disorders (Barry et al., 2016). Individuals with CP who are on methadone maintenance for OUD, compared to those who are on methadone but without CP, were found to have higher rates of chronic illnesses (74.5% vs. 44.7%) including gastrointestinal, muscular, urinary, heart, endocrine, and neurological problems (Peles et al., 2005). Additionally, individuals receiving OAT for OUD who also have CP (vs. no CP) report higher rates of diabetes, reproductive problems, respiratory problems, gastrointestinal problems, and greater number of physician and emergency department visits (Dunn et al., 2015). Using a matched case–control design among individuals who are on methadone maintenance with and without CP, individuals with CP were more likely to have psychiatric, substance use, and medical (e.g., infectious disease, respiratory disease) disorders as well as greater number of medical appointments, outpatient mental health contacts, emergency department visits, and hospital admissions (O’Toole et al., 2014). A recent report suggests that, among individuals with OUD, only a small minority are engaged in OAT (Leshner & Mancher, 2019) and access to other evidence-based treatment for OUD and related conditions is suboptimal (McCarty et al., 2018). Therefore, although these studies highlight the detrimental impact of co-occurring OUD and CP, it is at the exclusion of a potentially large portion of individuals with OUD that are not engaged in OAT and it is not possible to separate problems related to CP only.

To better understand the impact of concurrent OUD and CP, we examined all veterans diagnosed with OUD and/or CP in Fiscal Year (FY) 2012 who were treated nationally in the Veteran’s Health Administration (VHA). Existing research has been limited by comparison groups (e.g., only individuals with OUD engaged in OAT) and domains of interest (e.g., primarily mental health diagnoses or physical illness). Using administrative electronic health records, we sought to simultaneously compare three diagnostic groups across multiple domains: (a) veterans diagnosed with both OUD and CP (OUD + CP), (b) veterans diagnosed with OUD alone, and (c) veterans diagnosed with CP alone. Consistent with prior studies, we evaluated differences in medical and mental health diagnoses and use of clinical services but also included socioenvironmental areas often neglected in research such as homelessness and residential locale. We hypothesized that, compared to veterans in either single disorder group, veterans in the combined OUD + CP group would have a greater number of problems across all domains and would show greater use of inpatient, outpatient, and emergency services than veterans with only one of these conditions.

Method

Participants

This study uses national VHA administrative data from FY2012 (October 1, 2011–September 30, 2012) that includes information from the electronic health record of 5.4 million veterans. The sample for analysis included veterans that had at least one clinic visit or hospital admission to any VA facility in FY2012 with an active diagnosis of OUD and/or CP (Supplemental Table 1). The presence of OUD was established using documented International Classification of Diseases, 9th edition (ICD-9) codes. An equivalent Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) diagnosis of OUD was based on any of the following ICD-9 codes: 304.00, 304.01, 304.02, 304.70, 304.71, 304.72, 305.50, 305.51, or 305.52 (excluding those in remission). CP was defined by the presence of one or more ICD-9 codes for herpetic pain (053.12 or 792.2), fibromyalgia pain (729.1), musculoskeletal pain (338.xx, 719.4, 780.96), skeletal muscle spasm pain (728.85, 781.0), pain from diabetes (250.6, 357.2, 337.1), migraine and headache (346.x, 784.0), and pain and neuropathy (352.1, 350.1).

The final sample included 2,061,051 veterans who, consistent with the general veteran population, were primarily male (93.4%), White (73.7%), with an average age of 52.5 years old. A total of 45,638 (0.8% of all FY2012 VHA users) veterans were diagnosed with OUD and 2,048,534 (37.9% of all FY2012 VHA users) were diagnosed with at least one CP condition. We created three diagnostic groups for data analyses: OUD + CP (n = 33,166), OUD only (n = 12,517), and CP only (n = 2,061,368). The study was approved by the Institutional Review Board (IRB) of the VA Connecticut Healthcare System. A waiver of informed consent was granted by the IRB, as the data were de-identified VHA administrative data.

Measures

Selected variables were extracted from the electronic health record that represented four relevant domains: socioenvironmental, medical diagnoses, mental health diagnoses, and VA clinical service use. Socioenvironmental variables included age, income, sex, residence locale (urban, large rural, small rural, isolated rural), receipt of VA disability compensation (referred to as service connection) or pension, and homelessness. Residential locale was categorized based on the zip code of residence and associated Rural Urban Commuting Area (RUCA) codes (Rural Health Research Center [RHRC], 2021). Two dichotomous variables represented VA service-connected disability ratings of greater than 50% or less than/equal to 50% as contrasted to receipt of no service-connected compensation. Another dichotomous variable was used to represent receipt of VA pension, granted to disabled veterans who served during wartime but whose disability is not related to military service. Past-year homelessness was assessed by a V60 ICD-9 code or receipt of specialized homeless services within the VA during FY2012. Dichotomous variables representing clinical diagnoses including medical, mental health, and substance use disorders (excluding OUD) that were identified using corresponding ICD-9 codes from electronic health record. See Supplemental Table 1 for a list of all clinical diagnoses evaluated.

Outpatient service use was evaluated using VHA clinic stop codes. VHA stop codes are unique numerical codes that are attached to a clinical encounter in the electronic health record and identify the type of clinic at which the encounter took place (Petrakis et al., 2015). Using these codes, we identified the number of visits for each veteran in the following clinic types: outpatient primary care, specialty medical–surgical, outpatient psychiatric and substance use treatment, psychosocial rehabilitation, and emergency department visits. Bed section codes were used to identify hospitalization or residential treatment. Prescriptions for psychotropic medications were extracted from pharmacy prescription records and classified as antidepressants, antipsychotics, sedative/anxiolytics, stimulants, anticonvulsants/mood stabilizers, and lithium as well as opioid analgesics. To evaluate polypharmacy, we created a continuous variable with the number of psychotropic prescriptions and a dichotomous variable to identify individuals with more than three prescription drug classes.

Analyses

Our first step was to conduct bivariate analyses (i.e., involving two-group comparisons on one variable of interest) to identify variables in the OUD + CP group that demonstrated a clinically meaningful difference compared to the OUD or CP only groups. Given the large study sample involving many thousands of veterans, virtually all of these comparisons would meet statistical significance at the α of .05 level but may not necessarily represent a substantial or clinically meaningful difference. Therefore, we used effect sizes to identify substantial and clinically meaningful differences between groups on each variable of interest. For continuous variables (e.g., age, number of clinical visits), we used Cohen’s d calculated as the difference in means of the OUD + CP group and either single disorder group divided by the pooled standard deviation (Cohen, 1988). For binomial variables in each domain (e.g., gender, proportions with a specific diagnosis), we used risk ratios (RR) calculated as the ratio of proportions in the OUD + CP group to the proportions in either single disorder group. Minimum thresholds used to identify a substantial difference between groups were Cohen’s d ≥ 0.2 or ≤−0.2 for continuous variables (Cohen, 1988) or RR ≥ 1.5 or <0.67 for dichotomous variables (Ferguson, 2009). Thus, a RR greater than 1.5 would identify variables are substantially more frequent in the OUD + CP group than in a particular single disorder group and a RR less than 0.67 would identify a variable that is substantially less frequent in the OUD + CP group than in a particular single disorder group.

To identify variables that were robustly and independently different between the OUD + CP group and the single disorder groups, variables that met the above effect size criteria on bivariate analysis were entered together into a multinomial logistic regression model. Such models compared each of the single disorder groups to the OUD + CP group in a single analysis that yielded two coefficients, one for each paired comparison. The dependent variable was diagnostic group membership with the single disorder groups (CP only and OUD only) as the reference conditions and clinically meaningful variables from the bivariate analysis as independent variables. Since we were interested in the comparison of the OUD + CP group to each of the single disorder groups, we multiplied the coefficients in the model by −1. Results of these analyses are represented by odds ratios (OR) and standardized regression coefficients (β). The OR in this analysis reflects the likelihood that the OUD + CP group differs from the single condition group for each additional unit of the independent variable. Although there are no published cutoffs to denote a small, medium, or large relationships, the standardized regression coefficients permit a common scale to compare the effect of dichotomous and continuous variables and can help identify the strongest associations in the model. The comparison between single disorder groups (i.e., OUD only vs. CP only) was not included as this was not a focus of this study. All statistical analyses were conducted in SAS (Version 9.4; SAS Institute, Inc., Cary, NC, USA).

Results

Bivariate Analyses

Comparisons of socioenvironmental measures between the OUD + CP group and the OUD and CP only groups on bivariate analyses are displayed in Table 1. Compared to the CP only group, veterans in the OUD + CP group were younger (d = 0.47), reported lower incomes (d = 0.20), were less likely to live in isolated rural areas (RR = 0.67), were more likely to collect a VA pension (RR = 2.93), and were more likely to have been homeless in the past year (RR = 6.96). Veterans with OUD + CP, compared to the OUD only group, were more likely to have a service connection of greater than or equal to 50% (RR = 1.53).

Table 1.

Socioenvironmental Bivariate Relationships Between Multimorbid OUD + CP Versus OUD Only or CP Only

1. OUD and pain
 2. OUD only
 3. Pain only
 1 versus 2 effect size
 1 versus 3 effect size
Socioenvironmental M SD M SD M SD Cohen’s d Cohen’s d
Age     50.43     12.63     49.25     13.88     57.72     15.47 −0.08 −0.47
Income ($) 16,980 22,345 15,663 25,140 27,805 54,729  0.020 −0.20
N % N % N % Risk ratio Risk ratio
Male 30,993 93.45 12,004 95.9 1,832,084 90.91 0.97 1.03
White 23,486 74.54   8,184 70.35 1,360,474 76.29 1.06 0.98
Hispanic   1,970   9.44   854 12.70    129,783 14.99 0.74 0.63
Urban area residents 25,208 77.86 10,304 83.96 1,365,596 70.43 0.93 1.11
Large rural area residents   3,233   9.99   875   7.13    237,022 12.22 1.40 0.82
Small rural area residents   2,280   7.04   674   5.49    186,606   9.62 1.28 0.73
Isolated rural area residents   1,653   5.11   420   3.42    149,608   7.72 1.49 0.67
OIF/OEF era veterans   4,614 13.91   2,203 17.6    252,953 12.55 0.79 1.11
VA pension   2,882   8.69   1,088   8.69   59,844   2.97 1.00 2.93
Service connected 50% or more   9,602 28.95   2,366 18.90    556,459 27.61 1.53 1.05
Service connected less than 50%   5,508 16.61   1,734 13.85    448,242 22.24 1.20 0.75
Homeless in past year 10,822 32.63   3,172 25.34   94,469   4.69 1.29 6.96
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Note. OUD = opioid use disorder; CP = chronic pain; OIF/OEF = Operation Iraqi Freedom/Operation Enduring Freedom; VA = Veteran Affairs.

Bivariate comparisons between OUD + CP and single disorder groups for medical and mental health diagnoses are displayed in Table 2. With respect to medical diagnoses, veterans with OUD + CP were more likely to have seizures (RR > 2.60), insomnia (RR > 1.84), and peptic ulcer disease (RR > 1.55) than veterans in both the OUD only and CP only groups. Compared to those with CP only, veterans with OUD + CP group were more likely to have hepatic disease (RR = 4.52) and human immunodeficiency virus (HIV; RR = 3.18) but less likely to have diabetes mellitus (RR = 0.66) and its complications (RR = 0.52), and less likely to have diabetic pain (RR = 0.55) or renal disease (RR = 0.59). Individuals with OUD + CP, when compared to those with OUD only, were more likely to have a diagnosis of myocardial infarction (RR = 2.19), peripheral vascular disease (RR = 1.84), cerebrovascular accident (RR = 1.75), chronic obstructive pulmonary disease (RR = 1.61), connective tissue disease (RR = 2.01), complications from diabetes (RR = 6.27), and paraplegia (RR = 2.81).

Table 2.

Medical and Mental Health Diagnoses Bivariate Relationships Between OUD + CP Versus OUD Only or CP Only

1. OUD and pain
 2. OUD only
 3. Pain only
 1 versus 2 effect size
 1 versus 3 effect size
Medical diagnoses   N  %    N  %    N   % Risk ratio Risk ratio
Seizures 689 2.08 100 0.80 15,727 0.78 2.60 2.66
Insomnia 3,633 10.95 637 5.09 119,844 5.95 2.15 1.84
Myocardial infarction 395 1.19  68 0.54 31,862 1.58 2.19 0.75
Peripheral vascular disease 1,421 4.28 292 2.33 115,860 5.75 1.84 0.75
Cerebrovascular accident 1,278 3.85 275 2.20 108,322 5.37 1.75 0.72
Chronic obstructive pulmonary disease 6,403 19.31 1,497 11.96 301,577 14.96 1.61 1.29
Connective tissue disease 315 0.95 59 0.47 27,507 1.36 2.01 0.70
Peptic ulcer disease 484 1.46  62 0.50 18,931 0.94 2.95 1.55
Hepatic disease 4,726 14.25 1,547 12.36 63,488 3.15 1.15 4.52
Diabetes mellitus 5,653 17.04 1,426 11.39 518,931 25.75 1.50 0.66
Complications of diabetes 1,511 4.56  91 0.73 175,028 8.68 6.27 0.52
Paraplegia 432 1.3  58 0.46 18,109 0.90 2.81 1.45
Renal disease 1,084 3.27 287 2.29 112,083 5.56 1.43 0.59
HIV 486 1.47 275 2.20  9,282 0.46 0.67 3.18
  M   SD   M SD   M SD Cohen’s d Cohen’s d
Number of major medical diagnoses 2.29 1.55 0.94 1.14 2.06 1.49 0.91 0.15
Pain diagnoses   N  % N %  N % Risk ratio Risk ratio
Headache 5,096 15.37 — — 238,827 11.85 — 1.30
Diabetic pain 1,437 4.33 — — 157,363 7.81 — 0.55
Musculoskeletal pain 18,353 55.34 — — 989,001 49.07 — 1.13
Fibromyalgia 1,617 4.88 — — 69,922 3.47 — 1.41
Skeletal muscle spasm 1,368 4.12 — — 74,606 3.70 — 1.11
Herpetic pain 608 1.83 — — 25,021 1.24 — 1.48
Mental health disorders   N  %    N   %   N % Risk ratio Risk ratio
Schizophrenia 1,763 5.32 581 4.64 35,910 1.78 1.15 2.98
Bipolar disorder 4,413 13.31 1,088 8.69 60,092 2.98 1.53 4.46
Major depression 8,345 25.16 1,971 15.75 178,985 8.88 1.60 2.83
Other depression (e.g., dysthymia) 18,154 54.74 4,752 37.96 451,131 22.38 1.44 2.45
PTSD 12,403 37.40 3,418 27.31 357,066 17.72 1.37 2.11
Anxiety disorders 11,431 34.47 2,846 22.74 253,494 12.58 1.52 2.74
Adjustment disorders 4,084 12.31 985 7.87 98,936 4.91 1.56 2.51
Personality disorders 3,841 11.58 686 5.48 29,349 1.46 2.11 7.95
Other psychiatric diagnoses 9,827 29.63 2,276 18.18 242,190 12.02 1.63 2.47
 M  SD   M  SD   M SD Cohen’s d Cohen’s d
Number of psychiatric diagnoses 2.3 1.61 1.53 1.38 0.86 1.16 0.66 1.23
Substance use disorders   N  %   N %  N % Risk ratio Risk ratio
Alcohol 14,621 44.08 5,002 39.96 164,616 8.17      1.1 5.40
Amphetamines 1,781 5.37 633 5.06 6,146 0.30 1.06 17.61
Cannabis 6,798 20.50 2,295 18.34 44,632 2.21 1.12 9.26
Cocaine 9,052 27.29 3,385 27.04 39,556 1.96 1.01 13.91
Sedatives 3,274 9.87 1,026 8.20 2,934 0.15 1.20 67.81
Tobacco 16,909 50.98 5,290 42.26 386,146 19.16 1.21 2.66
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Note. OUD = opioid use disorder; CP = chronic pain; HIV = human immunodeficiency virus; PTSD = posttraumatic stress disorder.

Considering mental health diagnoses, veterans with OUD + CP were more likely than either single disorder group to be diagnosed with bipolar disorder (RR > 1.53), major depression (RR > 1.60), anxiety disorders (RR > 1.52), adjustment disorders (RR > 1.52), personality disorders (RR > 2.11), and other psychiatric disorders (RR > 1.63). Compared to the CP only group, the OUD + CP group was more likely to have schizophrenia (RR = 2.98), dysthymia (RR = 2.45), and posttraumatic stress disorder (PTSD; RR = 2.11). Veterans with OUD + CP were similarly more likely than the CP only group to have each of the illicit substance use disorders (RR > 9.26), as well as alcohol use disorder (RR = 5.40), and tobacco use disorder (RR = 2.66). There were no substantial differences in substance use diagnoses between the OUD + CP group and the OUD only group.

Finally, bivariate comparisons between OUD + CP and single disorder groups for VA clinical service use and prescription medication are displayed in Table 3. All indicators of service use were higher in the OUD + CP group as compared to both the OUD only and the CP only groups, including any medical–surgical inpatient treatment (RR > 2.45), any mental health inpatient treatment (RR > 1.84), any residential treatment (RR > 1.75), the number of emergency department visits (d > 1.01), medical and surgical clinic visits (d > 0.38), and psychiatric and substance use outpatient visits (d > 0.32).

Table 3.

VA Clinical Service Use Bivariate Relationships Between OUD + CP Versus OUD Only or CP Only

Inpatient/residential service use 1. OUD and pain
 2. OUD only
 3. Pain only
 1 versus 2 effect size
 1 versus 3 effect size
N % N % N % Risk ratio Risk ratio
Any mental health inpatient treatment 8,661 26.11 1,773 14.16 34,001 1.69 1.84 15.48
Any residential treatment 5,188 15.64 1,119   8.94 15,954 0.79 1.75 19.76
Any medical–surgical inpatient treatment 7,154 21.57 1,101  8.8 176,184 8.74 2.45 2.47
Outpatient visits M SD M SD M SD Cohen’s d Cohen’s d
Emergency room visits   2.64   4.66   0.9   1.78   0.65   1.63 1.01 1.16
Medical and surgical visits 13.61 12.95    5.42   7.55   9.66 10.46 0.78 0.38
Psychiatric or substance use outpatient visits 37.62 58.95 31.9 54.98   4.02 15.65 0.32 1.90
All outpatient visits 51.22 61.59  37.31 56.55 13.68 19.87 0.64 1.74
Prescription medications M SD M SD M SD Cohen’s d Cohen’s d
Antidepressant prescriptions 11.53 22.3 5.19 12.16 3.08   9.63 0.63 0.85
Antipsychotic prescriptions   5.25 16.75   2.51 12.22 0.87   7.57 0.35 0.56
Anxiolytic/sedative prescriptions   4.48   9.3   1.84   5.02 1.58   4.54 0.57 0.62
Stimulant prescriptions   0.22   3.11   0.16   1.62 0.07   0.92 0.06 0.15
Anticonvulsant/mood stabilizer prescriptions   5.24 15.46   1.47   6.88 1.28   6.92 0.53 0.55
Lithium prescription   0.43   4.21   0.2   2.22 0.07   1.57 0.14 0.22
Opiate prescription   8.45 11.21   4.27   8.17 2.38   5.26 0.77 1.12
Number of psychotropic medications 27.14 48.64 11.37 26.59 6.94 20.58 0.74 0.95
N % N % N % Risk ratio Risk ratio
More than three prescription drug classes 11,720 35.34 1,794 14.33 183,120 9.09 2.47 3.89
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Note. VA = Veteran Affairs; OUD = opioid use disorder; CP = chronic pain.

Veterans in the OUD + CP group when compared to both single disorder groups also received substantially more prescriptions for all psychotropic medications (d > 0.35) except stimulants and lithium. Lithium prescriptions were more numerous in the OUD + CP group compared to the CP only (d = 0.22). The OUD + CP group also received more opioid analgesic prescriptions (excluding OAT treatment) than either single disorder group (d > 0.77). Veterans with both OUD + CP filled more psychotropic prescriptions (d > 0.74) and filled prescriptions for more than three drug classes (RR > 2.47) than both single disorder groups.

Multinomial Logistic Regression

Results of multinomial logistic regression highlighted the independent associations of variables identified above on bivariate analysis with the OUD + CP as compared to the single disorder groups (Table 4). Given the large sample size, all but two comparisons were statistically significant at p < .0001; comparisons of the OUD + CP and OUD only on income and CP only on residence in isolated rural areas were both p < .01.

Table 4.

Multinomial Logistic Regression Comparison of Comorbid and Single Disorder Groups

OUD + CP versus OUD only
 OUD + CP versus CP only
Odds ratio 95% confidence intervals
 Standardized regression coefficient Odds ratio 95% confidence intervals
 Standardized regression coefficient
Variable Lower Upper Lower Upper
Socioenvironmental
  Age (10 years)  0.95 0.95 0.95   −0.04  0.81 0.81 0.81   −0.18
  Income/$1,000  1.002 1.001 1.003     0.05  0.996 0.996 0.997   −0.11
  Isolated rural  1.58 1.42 1.76     0.07  0.92 0.87 0.97   −0.01
  Pension  0.85 0.79 0.92   −0.02  2.11 2.02 2.21     0.07
  Homeless  1.17 1.10 1.23     0.02  2.11 2.05 2.18     0.09
  Service connection > 50%  1.27 1.20 1.34     0.06  1.09 1.07 1.12     0.02
Medical diagnoses
  Number of medical diagnoses (excluding pain diagnoses)  2.44 2.39 2.49     0.73  1.08 1.08 1.09     0.07
Mental health diagnoses
  Number of substance use disorders (excluding OUD)  0.86 0.84 0.88   −0.04  2.31 2.13 2.51     0.25
  Number of mental health diagnoses  1.25 1.23 1.27     0.15  1.41 1.40 1.42     0.23
Numbers of medications
  Psychotropic prescriptions (five prescriptions)  1.01 1.01 1.02     0.04  0.99 0.99 0.99   −0.02
  Opiate prescriptions  1.01 1.01 1.02     0.04  1.09 1.09 1.09     0.27
VA clinical service use
  Any mental health inpatient treatment  1.24 1.15 1.34     0.02  2.72 2.61 2.82     0.08
  Any residential treatment  1.37 1.26 1.49     0.02  1.33 1.27 1.40     0.02
  Any medical–surgical inpatient  0.74 0.68 0.80   −0.05  1.64 1.58 1.70     0.08
  Emergency department visits (five visits)  1.49 1.40 1.59     0.08  1.26 1.23 1.28   −0.05
  Medical and surgical visits (five visits)  1.49 1.46 1.52     0.46  0.98 0.97 0.98   −0.03
  Psychiatric or substance use outpatient visits (five visits)  0.98 0.98 0.98   −0.04  1.04 1.04 1.04     0.08
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Note. OUD = opioid use disorder; CP = chronic pain; VA = Veteran Affairs. All variables were significant at p < .0001 except comparisons of the OUD + CP and OUD only on income and CP only on residence in isolated rural areas were both p < .01.

The OUD + CP group when compared to the OUD only group was younger, β = −0.04, OR = 0.95, 95% confidence interval (CI) [0.95, 0.95], less likely to receive a pension, β = −0.02, OR = 0.85, 95% CI [0.79, 0.92], but more likely to have a service-connected disability >50%, β = 0.06, OR = 1.27, 95% CI [1.20, 1.34], and to have been homeless, β = 0.02, OR = 1.17, 95% CI [1.10, 1.23]. The OUD + CP group when compared to the OUD only group had more medical diagnoses, β = 0.73, OR = 2.44, 95% CI [2.39, 2.49], and more mental health diagnoses, β = 0.15, OR = 1.25, 95% CI [1.23, 1.27], but fewer substance use diagnoses, β = −0.04, OR = 0.86, 95% CI [0.84, 0.88]. With respect to VA clinical service use, the OUD + CP group was more likely to have been hospitalized for mental health problems, β = 0.02, OR = 1.24, 95% CI [1.15, 1.34], admitted to residential care, β = 0.02, OR = 1.37, 95% CI [1.26, 1.49], have had more emergency room (ER) visits, β = 0.08, OR = 1.49, 95% CI [1.40, 1.59], and more medical–surgical outpatient visits, β = 0.46, OR = 1.49, 95% CI [1.46, 1.52], but fewer mental health outpatient visits, β = −0.04, OR = 0.98, 95% CI [0.98, 0.98]. The OUD + CP group also had more psychotropic, β = 0.04, OR = 1.01, 95% CI [1.01, 1.02], and opiate prescriptions, β = 0.04, OR = 1.01, 95% CI [1.01, 1.02], compared to the OUD only group. Examination of standardized regression coefficients show the largest effects were observed for the number of medical diagnoses (β = 0.73) and medical–surgical outpatient visits (β = 0.46). That is, for each additional medical diagnosis (excluding pain), there is a 2.4 times greater likelihood of being in the OUD + CP group as compared to the OUD only group. Likewise, for every five outpatient medical and surgical visits, there is a 1.49 times greater likelihood in the odds of being in the OUD + CP group as compared to the OUD only group.

The OUD + CP group when compared to the CP only group was younger, β = −0.18, OR = 0.81, 95% CI [0.81, 0.81], had lower incomes, β = −0.11, OR = 0.996, 95% CI [0.996, 0.997], and were more likely to receive a pension, β = 0.07, OR = 2.11, 95% CI [02.02, 2.21], as well as to have a service-connected disability >50%, β = 0.02, OR = 1.09, 95% CI [1.07, 1.12], and to have been homeless, β = 0.09, OR = 2.11, 95% CI [2.05, 2.18]. Furthermore, individuals with OUD + CP as compared to the CP only group, had more medical, β = 0.07, OR = 1.08, 95% CI [1.08, 1.09], more mental health, β = 0.23, OR = 1.41, 95% CI [1.40, 1.42], and more substance use diagnoses, β = 0.25, OR = 2.31, 95% CI [2.13, 2.51], but received fewer psychotropic prescriptions, β = −0.02, OR = 0.99, 95% CI [0.99, 0.99], and more opiate prescriptions, β = 0.27, OR = 1.09, 95% CI [1.09, 1.09]. The OUD + CP group were more likely to have inpatient medical, β = 0.08, OR = 1.64, 95% CI [1.58, 1.70], inpatient mental health, β = 0.08, OR = 2.72, 95% CI [2.61, 2.82], and residential, β = 0.02, OR = 1.33, 95% CI [1.27, 1.40], admissions. The OUD + CP group also had more ER visits, β = −0.05, OR = 1.26, 95% CI [1.23, 1.28], and mental health outpatient visits, β = 0.08, OR = 1.04, 95% CI [1.04, 1.04], compared to the CP only group. Examination of standardized regression coefficients show the largest effects were for number of substance use disorder diagnoses (β = .25), psychiatric diagnoses (β = .23), and opiate prescriptions (β = .27). Therefore, for each additional substance use disorder and mental health disorder diagnosis, there is a 2.31 and 1.41 greater likelihood of being in the OUD + CP group as compared to the CP only group, respectively. Additionally, for each additional opiate prescription, there is a 9% greater likelihood of being in the OUD + CP group (vs. CP only).

Discussion

These results demonstrate in a national VHA sample, veterans with co-occurring OUD and CP appear to have greater medical diagnoses than those with OUD only and greater substance use diagnoses than those with CP only. However, compared to both single disorder groups, veterans with OUD and CP have greater mental health issues. The complex diagnostic presentation of OUD and CP is also associated with substantially higher levels of VA clinical service use. Multinomial regression analysis revealed robust independent effects for medical disorders and medical–surgical outpatient service use in the comparison of veterans with OUD and CP to those with OUD only and stronger effects for comorbid substance use and psychiatric disorders and use of prescription opiates in the comparison with the CP only group. As suggested by these findings, individuals with OUD and CP may require an integrated treatment approach that addresses both disorders. With so many distinctive features, it is thus critical to consider OUD and CP-related multimorbidity when developing new approaches to encourage long-term coping and self-management skills for individuals with both OUD and CP.

When treating individuals with OUD and CP using a traditional comorbid framework, clinicians may focus on one condition (i.e., the index disorder) at the expense of the other (Berg et al., 2009). Focusing treatment on either OUD or CP, however, may fail to account for the relationship between these conditions and the many associated comorbidities and social adversities and can result in fragmented, disorder-centric care (Stange, 2009). Fragmented care also shifts the burden of integrating treatment and management of chronic conditions onto the patient and caregivers. For many, the result is reduced treatment adherence to any of the singular treatment approaches, further erosion for understanding of their role in self-management for various conditions, and decreased engagement in either treatment or self-management for either of the chronic conditions (Mair & May, 2014). Evaluating the impact of CP on OUD treatment outcomes is hampered by inconsistent definitions and assessment of CP and lack of information on OAT retention (MacLean et al., 2021). Based on national data from the Treatment Episodes Dataset-Discharges (TEDS-D), individuals with OUD and other psychiatric disorders are more likely to stay engaged in medications for OUD (including OAT) treatment but are also more likely to be prematurely terminated by the treatment facility (Friesen & Kurdyak, 2020). These findings suggest that other chronic conditions concurrent with OUD may not be effectively managed within standard OAT clinical care. Therefore, developing a system of interventions that explicitly consider the complexity introduced by co-occurring CP may allow more effective treatment (Darnall, 2018). Adopting a more comprehensive approach can increase important treatment factors such as a strong working alliance between the clinician and patient, which is a critical element for patient satisfaction, adoption of self-management and long-term coping skills, and effective treatment outcomes (Zilcha-Mano & Errázuriz, 2017). The scope of problems associated with concurrent OUD and CP would likely benefit from an integrated approach that combines empirically supported treatments and self-management.

One barrier to providing integrated clinical care for OUD and CP is that a large proportion of clinicians may not have received training in substance use, pain assessment, or treatment. For example, in a survey of psychologists, only 11.5% reported being “very competent” to treat CP and 91% would be interested in learning more about pain treatment (Darnall et al., 2016). Training in evidence-based psychotherapies for CP may require considerable resources and expertise that may be impractical for most OAT clinics. Despite multiple efforts to train substance use clinicians in Cognitive Behavioral Therapy (CBT) or other evidence-based treatments, elements of CBT are rarely present in a clinical session and fidelity is usually poor (Santa Ana et al., 2008). Repeated assessment of pain and OUD symptoms is a simple strategy that can be used to identify individuals with co-occurring conditions and facilitate collaboration on a treatment plan. Additionally, recent treatment guidelines have attempted to better define the diagnostic gray area between CP and OUD in pain clinics (Manhapra et al., 2020). Including a short pain assessment, such as the three-item pain intensity (P), interference with enjoyment of life (E), and interference with general activity (G) or PEG (Krebs et al., 2009), into regular OUD care can help identify patients who may benefit from adjunctive treatment related to pain. Likewise, repeatedly assessing symptoms of OUD in CP samples may help with referrals for early intervention or possible tapering (Rosenberg et al., 2018). Finally, assessment of other co-occurring medical, psychiatric, and socioenvironmental conditions will help inform treatment planning that is tailored to the individual. Deepening our understanding of the problems faced by these patients may help in the development of service models that can address the totality of their numerous health conditions.

In addition to repeated assessment, a multimorbid approach advocates for an integrated treatment that considers the relationship between conditions in planning a course of treatment. Accordingly, treatment plans that address multimorbidity should include informed discussions to prioritize treatment goals, patient education about health conditions (such as pain or addiction) that are associated with multimorbidity, evaluation of trade-offs between elements of the treatment plan and quality of life, and continuous examination of prescribed medications to consolidate regimens (Bayliss et al., 2008; Salisbury, 2013). Very few studies have explicitly evaluated integrated treatment for multimorbidity in CP and OUD (Haibach et al., 2014). Over the counter medication and prayer are the two most frequently used pain coping strategies reported by a sample of individuals with OUD receiving OAT (Dunn et al., 2015). Only a handful of studies have reported evidence-based practices that are intended to integrate the OUD and CP treatment by increasing self-management and coping skills. There is some evidence for CBT as a treatment for co-occurring substance use disorders and CP (Ilgen et al., 2016; Morasco et al., 2016), but these findings are not specific to OUD. A recent study reported that a 12-week integrated CBT for substance use and CP program in a methadone maintenance clinic reduced illicit substance use but had no effect on pain (Barry et al., 2019). It is possible that a standard 12-session course of behavioral treatment may be insufficient to address the complex clinical presentation of co-occurring OUD and CP. Instead, an interdisciplinary approach that utilizes evidence-based treatment in both psychology and medicine is not only cost-effective, but associated with better outcomes (Gatchel et al., 2014). To facilitate self-management and address specific barriers to treatment (e.g., transportation issues, rural area), technology-assisted interventions such as the Cooperative Pain Education and Self-management (COPES) program can help patients learn skills to better manage pain while keeping burdens of treatment engagement low (Heapy et al., 2017). Another option is to integrate brief pain-focused treatments with a low provider-training burden into OAT clinical care. Researchers and clinicians should continue to develop evidence-based interventions that minimize patient burden and enhance self-management of pain and substance use.

Limitations

The present study has several limitations. The use of administrative data is based on clinician diagnosed disorders in an active health care setting that were not confirmed independently. Furthermore, we defined CP by an active diagnosis of a number of conditions that are commonly indicative of CP; however, since the data is administrative, we are unable to confirm the duration of these diagnoses. This leaves open the possibility that veterans with acute (i.e., less than 3-month duration) pain were categorized as having CP. Since the data is observational, cause and effect relationships cannot be assumed between study variables, and we are also unable to control for unmeasured variables that could influence associations between diagnostic groups. However, the objective of this study was to describe clinical presentations associated with multimorbidity of OUD and CP and thus determining causal relationships was not critically important. Additional longitudinal studies would be necessary to establish such causal relationships. Since the study relied on VHA administrative data, the population is overwhelmingly male and older than most clinical populations. As such, these results may not be generalizable to nonveteran men, women, and younger age groups.

These results strongly suggest that veterans with co-occurring OUD and CP are at greater risk for clinical complexity across multiple domains as compared to those with OUD or CP alone. The increased health burden associated with the presence of both conditions suggests that an integrated treatment approach is needed. Effective treatment will likely entail evidence-based behavioral interventions that highlight effective coping strategies and self-management of pain and substance use and adopt an interdisciplinary approach within OAT clinical care. Clinicians should be aware of the increased complexity of comorbid OUD and CP when developing treatment plans and resist the tendency to treat one disorder to the exclusion of the other.

Supplementary Material

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Impact Statement.

Few studies have comprehensively evaluated the impact of concurrent OUD and CP. Using national Veteran’s Health Administration data, veterans with a diagnosis of both OUD and CP, compared to those with OUD or CP only, had more medical and mental health comorbidities and greater service use. Results underscore the need to develop integrated treatment options that consider the clinical complexity of concurrent OUD and CP.

Acknowledgments

The research is supported by IK2CX002286 (R. Ross MacLean) and the Department of VA New England Mental Illness Research, Education, and Clinical Center (MIRECC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Department of Veterans Affairs.

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