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. 2020 Jan 31;20:40. doi: 10.1186/s12888-020-2456-1

Chronic pain diagnoses and opioid dispensings among insured individuals with serious mental illness

Ashli Owen-Smith 1,2,✉, Christine Stewart 3, Musu M Sesay 2, Sheryl M Strasser 1, Bobbi Jo Yarborough 4, Brian Ahmedani 5,6, Lisa R Miller-Matero 5,6, Stephen C Waring 7, Irina V Haller 7, Beth E Waitzfelder 8, Stacy A Sterling 9, Cynthia I Campbell 10, Rulin C Hechter 10, John E Zeber 11, Laurel A Copeland 12, Jeffrey F Scherrer 13, Rebecca Rossom 14, Greg Simon 3
PMCID: PMC6995196  PMID: 32005200

Abstract

Background

Individuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia.

Methods

Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N = 65,750), BD (N = 38,117) or schizophrenia or schizoaffective disorder (N = 12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses.

Results

Multivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85–1.95) or BD (OR = 1.71; 95% CI = 1.66–1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR = 0.86; 95% CI = 0.82–0.90). Having a MDD (OR = 2.59; 95% CI = 2.44–2.75) or BD (OR = 2.12; 95% CI = 1.97–2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications.

Conclusions

Individuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients. Future research is needed to evaluate the effectiveness of involving mental health clinicians in these efforts.

Keywords: Chronic non-cancer pain, Opioids, Serious mental illness

Background

Chronic non-cancer pain (CNCP) affects an estimated 25.3 million Americans [1] at a cost of $600 billion [2]. The use of long-term opioid therapy as a treatment for CNCP has quadrupled in the last 15 years [3–5] despite little empirical evidence that opioids are effective for treating CNCP long-term [6, 7] and has instead resulted in dramatic increases in opioid abuse and overdose deaths [8, 9]. In order to more effectively address this epidemic, we need to better understand which populations are most burdened by CNCP and which populations are at the greatest risk of opioid use/abuse in order to guide both clinical and policy-related decisions.

Evidence suggests that individuals with mental illness may be one population with particularly high rates of CNCP and may also be more likely to receive prescription opioids for their pain. Several studies have reported that individuals with depression and bipolar disorder, for example, have more frequent pain complaints, higher pain intensity and more pain chronicity and are also significantly more likely to receive long-term opioids, at a higher daily dose, and with greater days supplied compared with patients without mental illness [10–16]. By contrast, evidence suggests that CNCP is less prevalent among individuals with schizophrenia compared to individuals without mental illness [17]; to our knowledge, there have been no studies published to date that have examined opioid treatment patterns specifically among individuals with schizophrenia compared to controls.

This gap in the literature, in addition to other methodological limitations inherent in many prior studies – including small sample sizes [13, 18] and limited generalizability (e.g., examining only military veterans) [11, 15, 19] – prompted the present study. Specifically, we investigated (1) whether individuals with major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia are more or less likely to receive a chronic pain diagnosis compared to individuals with no psychiatric diagnoses and (2) whether individuals with MDD, BD and schizophrenia are more or less likely to receive chronic prescription opioid medications compared to individuals with no psychiatric diagnoses using data from health care systems in the Mental Health Research Network (MHRN) that are representative of a large, geographically and racially/ethnically diverse population across the U.S.

Methods

Data source

The MHRN consists of 13 research centers located within large integrated health care delivery systems, serving over 12.5 million individuals across 15 states; most of these delivery systems also have affiliated health insurance plans. All MHRN sites maintain a Virtual Data Warehouse consisting of electronic health record (EHR) and insurance claim data for all enrolled members or patients. Data on encounters, pharmacy fills, diagnoses, laboratory tests and demographics are organized using standardized definitions across sites and are quality checked locally [20].

The current study involved 10 MHRN systems. These sites were 6 Kaiser Permanente sites (Georgia, Washington, Northwest, Hawaii, Northern California, Southern California), Henry Ford Health System, Essentia Health, Baylor Scott and White Healthcare and Health Partners. Institutional Review Boards at each site approved the study protocol for this project.

Study population

Individuals were included if they met the following criteria: adults aged 18–70 years (as of January 1, 2016) with a diagnosis of MDD (ICD-9296.2–296.39/ICD-10 F32-F33.9), BD (ICD-9296.0x, 296.1x, 29.40–296.89/ICD-10 F30-F31.9) or schizophrenia including schizoaffective disorder (ICD-9295.x/ICD-10 F20.x, F25.x) documented at least two times by mental healthcare provider in 2015 or 2016 (cases had to “start” 2016, the 12-month study period, with a diagnosis so at least 1 diagnosis had to occur in 2015). Patients who had diagnoses in more than 1 of these categories were categorized hierarchically: schizophrenia>BD > MDD. For example a patient with schizophrenia and MDD would be classified in the schizophrenia group and a patient with only MDD would be classified in the MDD group. This is an approach used in prior studies that have similarly employed a hierarchy of non-overlapping categories [21, 22]. Eligible individuals had to have continuous health plan membership throughout 2015 and 2016 (but could have a gap in enrollment records of ≤30 days, as administrative gaps can occur as a result of delays in membership data processing and thus are not indicative of membership interruptions/disenrollment). Individuals with any cancer or metastatic cancer diagnoses (ICD-9140–165, 170–172, 174–176, 179–199, 200–208, 238.6/ ICD-10 C00–26.9, C30.x, C37-C41.9, C43.x, C45-C45.7, C45.9, C46-C58, C60-C76.8, C7A.x, C7B,x, C80.x, C81-C85.99, C86.x, C88.x, C90-C96.9, D03.x, D45, D47.Z9,) during this same time period were excluded.

Controls were identified using the same criteria as described above except that they had no documented mental illness diagnoses during 2015 or 2016 (they could not “start” 2016, the 12-month study period, with a diagnosis nor receive one during 2016). Matching was done separately for each group (e.g., schizophrenia controls were selected and removed from the pool of controls, then BD controls, followed by MDD controls). Controls for each group were matched on age (in 4-year bands), sex and Medicare status using stratified random sampling. Matching cases to controls was 1:2 for schizophrenia diagnosis and 1:1 each for BP and MDD diagnoses. These ratios were based on what numbers were required to find an adequate number of controls for each group.

Measures

Non-cancer chronic pain diagnoses documented on at least 2 dates in 2016 were extracted for the matched samples. The chronic pain conditions extracted included: back pain, neck pain, limb/extremity pain, arthritis, fibromyalgia/widespread muscle pain, headache, orofacial/ear/temporomandibular pain, abdominal/bowel pain, chest pain, urogenital/pelvic/menstrual pain, fractures/contusions/sprains/strains and other painful conditions [which included sickle cell disease, complex regional pain syndrome, systemic lupus erythematosus, acquired deformities (excluding spinal disorders), spinal cord injury and neuropathic pain]. The list of ICD codes used for identifying pain conditions are available online (https://github.com/MHResearchNetwork/MHRN-Central/blob/master/WP_MHRN_SMI_painOpioids.zip).

Prescription opioid medication dispensings were also extracted for the matched samples. We were specifically interested in chronic opioid use, defined by prescriptions dispensed that covered at least 70 days in any 90-day period or 6+ dispensings in 2016. This definition was based on prior studies conducted at one of the MHRN sites [23, 24]. The list of NDC codes used for identifying opioid medication dispensings are also available online (https://github.com/MHResearchNetwork/MHRN-Central/blob/master/WP_MHRN_SMI_painOpioids.zip).

We also examined sociodemographic (age, sex, race/ethnicity, neighborhood socioeconomic status) and clinical characteristics of the study population using data from 2016 using methods similar to prior work [25]. Overall medical comorbidity burden was calculated using the Charlson Comorbidity Index Score (CCIS). This score consists of 19 categories of comorbidity, with each category weighted based on the adjusted risk of 1-year post-discharge mortality. The overall comorbidity score reflects the cumulative increased likelihood of mortality 1 year after discharge such that higher scores are indicative of a more severe burden of comorbidity [26]. Total health care utilization (hospitalizations, ED visits and other in-person outpatient encounters) was based on summarized data from the last 6 months of 2015. This timeframe was selected so that we had a baseline measure of recent utilization history prior to the study period (which was 2016). Multiple encounters occurring on the same day were coded as a single encounter so that we were able to count utilization days. In order to investigate whether any site variation existed and ensure the accuracy of the data before aggregation, preliminary data comparisons across sites were conducted. This comparison found very little site variation, supporting the stability of the aggregated estimates.

Analyses

The primary goals of our analyses were to examine whether having a diagnosis of MDD, BD or schizophrenia/schizoaffective disorder was associated with receipt of a chronic pain diagnosis and then subsequent chronic opioid prescription dispenses. For initial bivariate models, we used t-tests for continuous variables and Pearson χ2-tests for categorical data. Multivariate analyses were conducted to evaluate (1) the odds of receiving a chronic pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses. Results of the models were reported as adjusted odds ratios (ORs) with 95% confidence intervals (CIs).

Results

The total number of patients identified was 377,927 (248,283 cases, 129,644 controls); however, only one-third of the available MDD cases were included in the final dataset (selected randomly) because there were not a sufficient number of controls available. The sample of persons with MDD and matched controls (total n = 131,488) included 72% women, 86% with a neighborhood income > $40,000 per year, was 57% White, 9% Black/African-American, 22% Hispanic/Latino, and between the ages of 18 and 70 (mean: 43.5, SD: 13.8). Individuals with MDD were more likely to have higher Charlson comorbidity scores and greater healthcare utilization than matched controls without psychiatric illness; they were also more likely to have any CNCP diagnosis (62.4% compared to 39.8% of controls) and to receive chronic opioid medications (10.1% compared to 2.4% of controls; see Table 1).

Table 1.

Patients with Major Depressive Disorder (MDD) compared to Matched Controls

Characteristic Patients with MDD
(N = 65,750)
n(%)/Mean ± SD		 Matched Controls
(N = 65,738)
n(%)/Mean ± SD		 Test Statistic p-value
Total 65,750 65,738
Age 43.5+  13.8 43.5+  13.8 t = −0.14 0.89
Sex
 Male 18,733 (28.5%) 18,731 (28.5%) χ2 = 0 0.99
 Female 47,013 (71.5%) 47,005 (71.5%)
Medicare 6329 (9.6%) 6322 (9.6%) χ2 = 0 0.96
Race
 White/Caucasian 43,647 (66.3%) 31,328 (47.7%) χ2 = 5891.77 < 0.0001
 Black/African-American 5894 (9.0%) 5940 (9.0%)
 Asian 3850 (5.9%) 8846 (13.5%)
 Pacific Islander 540 (0.8%) 791 (1.2%)
 Native American 672 (1.0%) 462 (0.7%)
 Other 180 (0.3%) 165 (0.3%)
 Unknown 10,944 (16.6%) 18,199 (27.7%)
Ethnicity (Hispanic) 14,134 (21.5%) 15,274 (23.2%) χ2 = 57.19 < 0.0001
Neighborhood Income
  < $40,000 per year 7771(11.8%) 7648 (11.6%) χ2 = 0.12 0.73
  > $40,000 per year 56,796 (86.4%) 55,566 (84.5%)
Charlson Comorbidity Index 0.56+  1.19 0.25+  0.74 t = 56.17 < 0.0001
Total healthcare utilization in last 6 mos 8.3+  10.7 2.3+  4.3 t = 132.57 < 0.0001
Pain conditions
 Any Pain 41,036 (62.4%) 26,158 (39.8%) χ2 = 6731.57 < 0.0001
 Back pain 13,419 (20.4%) 5944 (9.0%) χ2 = 3382.42 < 0.0001
 Neck pain 6877 (10.5%) 3031 (4.6%) χ2 = 1613.80 < 0.0001
 Limb/extremity pain, arthritis 21,239 (32.3%) 12,449 (18.9%) χ2 = 3081.38 < 0.0001
 Fibromyalgia/widespread muscle 4262 (6.5%) 976 (1.5%) χ2 = 2146.34 < 0.0001
 Headache 8359 (12.7%) 6261 (4.8%) χ2 = 2580.33 < 0.0001
 Orofacial/ear/temporomandibular 728 (1.1%) 409 (0.6%) χ2 = 90.22 < 0.0001
 Abdominal/bowel pain 9922 (15.1%) 4679 (7.1%) χ2 = 2116.78 < 0.0001
 Chest pain 4995 (7.6%) 2417 (3.7%) χ2 = 949.73 < 0.0001
 Urogenital/pelvic/menstrual pain 3222 (4.9%) 1638 (2.5%) χ2 = 535.78 < 0.0001
 Fractures/contusions/sprains/strains 8542 (13.0%) 4405 (6.7%) χ2 = 1465.45 < 0.0001
 Other painful conditionsa 7994 (12.2%) 3253 (5.0%) χ2 = 2184.48 < 0.0001
Chronic opioid useb 6618 (10.1%) 1553 (2.4%) χ2 = 3346.72 < 0.0001
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aIncludes sickle cell disease, complex regional pain syndrome, systemic lupus erythematosus, acquired deformities (excluding spinal disorders), spinal

cord injury, lyme disease, neuropathic pain

bChronic use defined by 70+ days supply in a 90-day period, receiving 6+ dispenses in a year

The sample of persons with BP and matched controls (total n = 76,232) included 67% women, 85% with a neighborhood income > $40,000 per year, was 60% White, 9% Black/African-American, 18% Hispanic/Latino, and between the ages of 18 and 70 (mean: 42.7, SD: 13.3). Individuals with BP were similarly more likely to have a higher Charlson comorbidity score and a greater healthcare utilization than matched controls without any psychiatric illness; they were also more likely to have any CNCP diagnosis (61.5% compared to 40.3% of controls) and receive chronic opioid medications (10.4% compared to 3.0% of controls; see Table 2).

Table 2.

Patients with Bipolar Disorder compared to Matched Controls

Characteristic Patients with Bipolar Disorder
(N = 38,117)
n(%)/Mean ± SD		 Matched Controls
(N = 38,115)
n(%)/Mean ± SD		 Test Statistic p-value
Age 42.7+  13.2 42.7+  13.3 t = −0.20 0.84
Sex
 Male 12,530(32.9%) 12,530(32.9%) χ2 = 0 0.99
 Female 25,585 (67.1%) 25,583 (67.1%)
Medicare 6386 (16.8%) 6383 (16.8%) χ2 = 0 0.98
Race
 White/Caucasian 27,348(71.8%) 18,408 (48.3%) χ2 = 5450.33 < 0.0001
 Black/African-American 3410 (9.0%) 3594 (9.4%)
 Asian 1782 (4.7%) 4993 (13.1%)
 Pacific Islander 281 (0.7%) 453 (1.2%)
 Native American 499 (1.3%) 281 (0.7%)
 Other 94 (0.3%) 117 (0.3%)
 Unknown 4694 (12.3%) 10,262 (27.0%)
Ethnicity (Hispanic) 5473 (14.4%) 8307 (21.8%) χ2 = 711.63 < 0.0001
Neighborhood Income
  < $40,000 per year 4985 (13.1%) 4835(12.7%) χ2 = 0.41 0.52
  > $40,000 per year 32,544 (85.4%) 32,006 (84.0%)
Charlson Comorbidity Index 0.55+  1.10 0.28+  0.81 t = 39.21 < 0.0001
Total healthcare utilization in last 6 mo 8.6+  11.3 2.4+  4.8 t = 99.04 < 0.0001
Pain conditions
 Any Pain 23,423(61.5%) 15,342 (40.3%) χ2 = 3426.65 < 0.0001
 Back pain 7756 (20.4%) 3650 (9.6%) χ2 = 1737.92 < 0.0001
 Neck pain 3713 (9.7%) 1805 (4.7%) χ2 = 711.12 < 0.0001
 Limb/extremity pain, arthritis 12,052(31.6%) 7401 (19.4%) χ2 = 1492.66 < 0.0001
 Fibromyalgia/widespread muscle 2384 (6.3%) 663 (1.7%) χ2 = 1012.43 < 0.0001
 Headache 5000 (13.1%) 1845 (4.8%) χ2 = 1597.48 < 0.0001
 Orofacial/ear/temporomandibular 477 (1.3%) 237 (0.6%) χ2 = 81.42 < 0.0001
 Abdominal/bowel pain 5777 (15.2%) 2821 (7.4%) χ2 = 1145.30 < 0.0001
 Chest pain 3009 (7.9%) 1348 (3.5%) χ2 = 671.51 < 0.0001
 Urogenital/pelvic/menstrual pain 1925 (5.1%) 959 (2.5%) χ2 = 336.23 < 0.0001
 Fractures/contusions/sprains/strains 5567 (14.6%) 2743(7.2%) χ2 = 1076.93 < 0.0001
 Other painful conditionsa 4137 (10.9%) 2034 (5.3%) χ2 = 779.68 < 0.0001
Chronic opioid useb 3961 (10.4%) 1156 (3.0%) χ2 = 1648.10 < 0.0001
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aIncludes sickle cell disease, complex regional pain syndrome, systemic lupus erythematosus, acquired deformities (excluding spinal disorders), spinal cord injury, lyme disease, neuropathic pain

bChronic use defined by 70+ days supply in a 90-day period, receiving 6+ dispenses in a year

The sample of persons with schizophrenia and matched controls (total n = 38,707) included 44% women, 83% with a neighborhood income > $40,000 per year, was 51% White, 13% Black/African-American, 22% Hispanic/Latino, and between the ages of 18 and 70 (mean: 42.3, SD: 13.8). Individuals with schizophrenia had lower neighborhood-level incomes, higher Charlson comorbidity scores, and greater healthcare utilization than matched controls without any psychiatric illness; they were also slightly more likely to have any CNCP diagnosis (47.2% compared to 42.0% of controls) and receive chronic opioid medications (6.5% compared to 5.0% of controls; see Table 3).

Table 3.

Patients with Schizophrenia compared to Matched Controls

Characteristic Patients with Schizophrenia
(N = 12,916)
n(%)/Mean ± SD		 Matched Controls
(N = 25,791)
n(%)/Mean ± SD		 Test Statistic p-value
Age 42.3+  13.8 42.3+  13.9 t = 0.34 0.73
Sex
 Male 7250 (56.1%) 14,459 (56.1%) χ2 = 0.02 0.90
 Female 5666 (43.9%) 11,332 (43.9%)
Medicare 5144 (39.8%) 10,247 (39.7%) χ2 = 0.03 0.86
Race
 White/Caucasian 6889 (53.3%) 12,770 (49.5%) χ2 = 1021.25 < 0.0001
 Black/African-American 2476 (19.2%) 2724 (10.6%)
 Asian 1317 (10.2%) 3008 (11.7%)
 Pacific Islander 153 (1.2%) 343 (1.3%)
 Native American 138 (1.1%) 204 (0.8%)
 Other 28 (0.2%) 44 (0.2%)
 Unknown 1907 (14.8%) 6696 (26.0%)
Ethnicity (Hispanic) 2511 (19.4%) 6045 (23.4%) χ2 = 79.87 < 0.0001
Neighborhood Income
  < $40,000 per year 2404 (18.6%) 3444 (13.4%) χ2 = 170.42 < 0.0001
  > $40,000 per year 10,345(80.1%) 21,650 (83.9%)
Charlson Comorbidity Index 0.63+  1.18 0.43+  1.07 t = −16.58 < 0.0001
Total healthcare utilization in last 6 mo 7.9+  10.9 2.6+  5.6 t = −63.60 < 0.0001
Pain conditions
 Any Pain 6092 (47.2%) 10,835(42.0%) χ2 = 92.96 < 0.0001
 Back pain 1855 (14.4%) 2687 (10.4%) χ2 = 129.23 < 0.0001
 Neck pain 754 (5.8%) 1228 (4.8%) χ2 = 20.52 < 0.0001
 Limb/extremity pain, arthritis 2942 (22.8%) 5312 (20.6%) χ2 = 24.41 < 0.0001
 Fibromyalgia/widespread muscle 386 (3.0%) 463 (1.8%) χ2 = 57.13 < 0.0001
 Headache 973 (7.5%) 1264 (4.9%) χ2 = 109.52 < 0.0001
 Orofacial/ear/temporomandibular 112 (0.9%) 150 (0.6%) χ2 = 10.44 0.0012
 Abdominal/bowel pain 1497 (11.6%) 1907 (7.4%) χ2 = 188.93 < 0.0001
 Chest pain 975 (7.6%) 1137 (4.4%) χ2 = 164.51 < 0.0001
 Urogenital/pelvic/menstrual pain 280 (2.2%) 442 (1.7%) χ2 = 9.69 0.0018
 Fractures/contusions/sprains/strains 1392 (10.8%) 1968 (7.6%) χ2 = 107.50 < 0.0001
 Other painful conditionsa 1117 (8.7%) 1884 (7.3%) χ2 = 21.71 < 0.0001
Chronic opioid useb 845 (6.5%) 1299 (5.0%) χ2 = 37.29 < 0.0001
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aIncludes sickle cell disease, Complex Regional Pain Syndrome, systemic lupus erythematosus, acquired deformities (excluding spinal disorders), spinal cord injury, Lyme disease, Neuropathic pain

bChronic use defined by 70+ days supply in a 90 day period, receiving 6+ dispenses in a year

Multivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85–1.95) or BD (OR = 1.71; 95% CI = 1.66–1.77) diagnosis was associated with increased odds of receiving a comorbid chronic pain diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis (OR = 0.86; 95% CI = 0.82–0.90) was associated with decreased odds of receiving a chronic pain diagnosis (see Table 4).

Table 4.

Odds of Receiving a Chronic Pain Diagnosis and Chronic Opioid Prescriptions among Individuals with Versus without Mental Illness

Mental Illness Diagnosis Chronic Pain Diagnosisa Opioid Prescriptionb
Adjusted OR (CI) Adjusted OR (CI)
Major Depressive Disorder 1.90 (1.85–1.95)* 2.59 (2.44–2.75)*
Bipolar Disorder 1.71 (1.66–1.77)* 2.12 (1.97–2.28)*
Schizophrenia 0.86 (0.82–0.90)* 1.00 (0.91–1.11)
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aModels adjusted for age, sex, race, income, medical comorbidities, and healthcare utilization

bModels adjusted for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis

*p < 0.001

Having a MDD (OR = 2.59; 95% CI = 2.44–2.75) or BD (OR = 2.12; 95% CI = 1.97–2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and having a chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications (see Table 4).

Discussion

The present study found that individuals with MDD and BD diagnoses were significantly more likely to receive CNCP-related diagnoses compared to matched controls; by contrast, individuals with schizophrenia or schizoaffective disorder were significantly less likely to receive CNCP-related diagnoses compared to matched controls. These findings confirm and extend those from previous studies [17, 27, 28] and suggest that the pattern of CNCP-related diagnoses may be different for individuals with MDD or BD than for individuals with schizophrenia or schizoaffective disorder. This finding is not surprising given that symptoms of MDD and BD overlap more with each other than with symptoms of schizophrenia and schizoaffective disorder [19].

Compared to the general population, individuals with schizophrenia have increased risk of experiencing multiple physical comorbidities warranting pain control [29–32] and thus it seems counterintuitive that they were less likely to receive CNCP diagnoses than controls in the present study. There are several possible explanations for the lower prevalence of CNCP diagnoses among individuals with schizophrenia. First, there is some evidence that individuals with schizophrenia have reduced sensitivity to pain compared to individuals without psychiatric illness [33–36]. Further, antipsychotics have been shown to have analgesic qualities [37]; therefore, this decreased likelihood of receiving a pain diagnosis could reflect lower levels of pain. However, results from a recent meta-analysis indicate that antipsychotic-free patients with schizophrenia also had elevated pain thresholds compared to controls [36]. An alternative explanation may be that individuals with schizophrenia are less likely to express pain rather than actually experiencing less pain, either because they are unable to adequately describe the physical symptoms due to social communication impairments [38] or they withhold this information because of concerns about how they will be treated by healthcare providers. For example, Kuritzky and colleagues reported that a large percentage of people (~ 40%) with schizophrenia who had pain-related complaints indicated that they never reported these complaints in order to avoid being perceived a burden to providers and/or to avoid hospitalization [17, 39]. However, another study with Veterans Health Administration patients found that patients with schizophrenia were twice more likely to report chronic pain in comparison to those without schizophrenia [19]. Therefore, given these conflicting findings, authors of recent systematic review suggest that it is likely more appropriate to state that pain experience in schizophrenia is disturbed or distorted rather than decreased or absent [38].

Behavioral health clinicians may be less likely to assign pain-related diagnoses for individuals with schizophrenia because many have limited training in physical symptom management [40] and are more focused on treating psychiatric than medical concerns [41–43]; primary care clinicians may be less likely to assign pain-related diagnoses because their short consultation times make it difficult to both assess mental symptoms and conduct physical assessments. Additionally, less experienced providers may be uncomfortable with serious mental illness and may avoid intensifying their interaction with a patient by asking probing questions about physical symptoms and performing a physical exam [40]. Indeed, there is ample evidence that individuals with schizophrenia are less likely than their peers without any psychiatric illnesses to receive medical procedures and treatments for a range of conditions including cancer screening and treatment [44], use of antihypertensive and lipid-lowering drugs [45] and appropriate diabetes care (including A1C and cholesterol testing, eye and feet exams, etc.) [46, 47]. Future studies are needed to better understand providers’ decision-making with respect to diagnosing and treating pain among patients with schizophrenia.

This lack of expression and/or disclosure of pain-related complaints by patients or under-diagnosis by providers may lead to the under-detection and under-treatment of CNCP among individuals with schizophrenia. This is problematic given that CNCP among individuals with mental illness is associated with worsening of psychiatric symptoms, impaired recovery/poor therapeutic response [19, 48], greater functional incapacitation [49, 50], lower quality of life [51, 52] and increased risk of suicide [53, 54]. Therefore, it is essential to systematically assess and monitor CNCP-related conditions among individuals with schizophrenia. Psychiatrists may be particularly well-suited to oversee pain management in this population and thus need adequate education and training to equip them to do so [55].

The present study also found that individuals with MDD and BD diagnoses were over two times more likely to receive chronic opioid medication prescriptions compared to matched controls. This finding is consistent with prior literature which has similarly reported that opioids are more commonly prescribed (and prescribed at higher doses) in these populations compared to those without these mental health conditions, even after controlling for a wide array of other demographic and clinical risk factors [10, 13, 15, 16]. One explanation for this is that these individuals may present with greater pain severity [56], thereby increasing the likelihood that clinicians will prescribe an opioid and at a higher dose [57]. However, the relationship between depressive symptoms and opioid use is complex and likely bidirectional in nature, as prior research indicates that chronic opioid use can increase the risk of new-onset depression [58] as well as depression recurrence [59]. Regardless of the nature of the causal relationship, there is evidence that mental illness is associated with diminished opioid analgesia [60] and, more importantly, mental illness is a known risk factor for a range of adverse opioid-related outcomes including opioid use disorder [61–65]. Therefore, individuals most at risk for developing opioid-related problems are also more likely to be prescribed opioids [11]. Healthcare providers should be especially conservative in prescribing opioids for individuals with mental illness – or avoid opioid therapy altogether for this population, consistent with the current Canadian Medical Association recommendation [66] – and instead, favor non-pharmacological alternatives [16] such as behavioral/psychosocial approaches.

The present study has several limitations. First, opioid prescription data is based on dispensings, and thus may not accurately represent patients’ actual medication use. Second, we categorized patients who had more than 1 mental health diagnosis hierarchically; therefore, a patient with schizophrenia could also have had depression but he/she would not have been included in the analyses on individuals with depression. Thus our findings should be interpreted accordingly – e.g., depression is associated with an increased odds of a pain diagnosis and receipt of opioid prescriptions when not comorbid with schizophrenia. However, consistent with diagnostic criteria [67], we applied a hierarchy with diagnosis of schizophrenia superseding a diagnosis of mood disorder and bipolar disorder superseding a diagnosis of unipolar depression. Third, study results were derived from a sample of members of integrated payer–provider systems. There is some evidence to suggest that individuals who are more economically and socially disadvantaged may be more severely ill [68]. Therefore, our largely insured sample may underrepresent the most impaired patients. Thus, caution is urged in generalizing the findings to uninsured populations. This study’s strengths include a large, geographically and racially/ethnically diverse study population, the comparison of 3 populations with serious mental illness to matched controls, and the inclusion of important statistical confounders such as healthcare utilization in multivariate models.

Conclusions

The presence of pain significantly impacts individuals’ engagement in and adherence to their mental health treatment and is an important moderator of treatment-related outcomes with respect to both pharmacotherapy and psychotherapy [69, 70]. Therefore, the systematic assessment and treatment of pain among individuals with mental illness is critical to short- and long-term improvements in quality of life. Given the lack of evidence about efficacy of long-term opioid treatment for CNCP and risks of drug interactions and/or use disorders, specifically among individuals with serious mental illness, non-pharmacological (e.g., behavioral/psychosocial) treatments are needed for this population. Unfortunately, barriers to accessing these types of interventions exist, such as limited patient and clinician awareness, stigma, limited capacity and reimbursement issues [69]. Consequently, there have been recent calls for engaging mental health clinicians in pain treatment for this population, as they may be particularly well-suited to assess pain symptoms, incorporate pain into treatment plans and encourage self-management activities and participation in behavioral/psychosocial treatments for pain [69]. Future research is needed to evaluate the effectiveness of involving mental health clinicians in pain management.

Acknowledgements

The authors would like to thank all members of the Health Care Systems and Mental Health Research Networks, whose contributions to building the Virtual Data Warehouse and to the integrity of the data have made this study possible.

Abbreviations

BD

Bipolar disorder

CNCP

Chronic non-cancer pain

MDD

Major depressive disorder

MHRN

Mental Health Research Network

Authors’ contributions

AOS, CS and MS had full access to all of the data and take responsibility for the integrity of the data and accuracy of the data analysis. AOS, CS and MS made substantial contributions to the conception of the work, the data analysis and interpretation of the results and drafted and revised the work. SMS, BJY, BA, LMM, SW, IH, BW, SAS, CC, RH, JZ, LC, JS, RR and GS made substantial contributions to the conception of the work, the interpretation of the results and contributed substantively to the revision of the work. All authors read and approved the final version of the manuscript.

Funding

This project was supported by Award Number U19MH092201 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health.

Availability of data and materials

All SAS code is provided on the MHRN GitHub site: see https://github.com/MHResearchNetwork/MHRN-Central/blob/master/WP_MHRN_SMI_painOpioids.zip

Individual-level data cannot not be shared because individual patients could be re-identified; aggregated and de-identified data can be requested by contacting the first author, Dr. Ashli Owen-Smith (aowensmith@gsu.edu).

Ethics approval and consent to participate

Institutional Review Boards at each of the following sites approved the study protocol for this project: Kaiser Permanente Georgia, Kaiser Permanente Washington, Kaiser Permanente Northwest, Kaiser Permanente Hawaii, Kaiser Permanente Northern California, Kaiser Permanente Southern California, Henry Ford Health System, Essentia Institute of Rural Health, Baylor Scott and White Healthcare and Health Partners Institute.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

All SAS code is provided on the MHRN GitHub site: see https://github.com/MHResearchNetwork/MHRN-Central/blob/master/WP_MHRN_SMI_painOpioids.zip

Individual-level data cannot not be shared because individual patients could be re-identified; aggregated and de-identified data can be requested by contacting the first author, Dr. Ashli Owen-Smith (aowensmith@gsu.edu).

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