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. 2025 Dec 24;4(12):102346. doi: 10.1016/j.jacadv.2025.102346

Association Between Congenital Heart Disease Complexity, Mental Health Conditions and Opioid Use Disorder

Felicia Y Ho a, Asif Padiyath b,c, Susan C Nicolson b, Michael L O’Byrne c,d,e, Bonnie L Milas f, Craig W Newcomb g, Tori N Sutherland b,d,e,∗
PMCID: PMC12834073  PMID: 41447281

Abstract

Background

As patients with congenital heart disease (CHD) survive into adulthood, there is concern that more complex diagnoses, with possible repeat perioperative opioid exposures, may be associated with increased risk of opioid-related harms, including development of an opioid use disorder (OUD).

Objectives

The purpose of this study was to determine if OUD prevalence is higher among patients with more surgically complex CHD diagnoses.

Methods

We conducted a national retrospective cohort study among CHD patients aged 15 to 64 years between 2012 and 2022. Using clinical consensus, diagnoses were categorized as simple biventricular, complex biventricular, and single ventricle physiology conditions. Our primary outcome was OUD prevalence. Secondary outcomes included history of overdose, substance use disorders (SUD), and mental health diagnoses. Outcomes were captured in medical claims using International Classification of Diseases (Ninth Revision and Tenth Revision) diagnosis codes. We utilized multivariable logistic regression models to assess the association between CHD complexity, patient characteristics, and outcomes.

Results

Among 73,046 CHD patients, the median age was 43.0 (Q1-Q3: 29.0-56.0) years, and 39,795 (54.5%) were female. OUD prevalence was 3.6% (n = 1,994 of 55,335) among simple biventricular patients, 1.9% (n = 269 of 14,077) among complex biventricular patients, and 3.5% (n = 126 of 3,634) among single ventricle physiology patients. Trends in overdose and SUD prevalence were similar. Simple biventricular and single ventricle patients had increased anxiety and mood disorder prevalence.

Conclusions

Patients with more complex diagnoses had the lowest OUD/SUD prevalence. Comorbid mood and anxiety disorders were strongly associated with these outcomes. Findings support the need for additional research and routine mental health and OUD/SUD screening for CHD patients.

Key words: substance use disorder, overdose events, mental health

Central Illustration

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Congenital heart disease (CHD) is the most common congenital disorder, affecting 0.8% of live births.1 Advances in diagnosis, surgical repair, and perioperative management have significantly improved survival, leading to increased prevalence among children and adults. Studies in Sweden have identified survivorship plateaus around 97% for children born with CHD from 2010 to 2017,2 with many living into their 60s.3 In the United States, the estimated prevalence of adults with CHD is 3.23 per 1,000 individuals.4 Patients with simple biventricular diagnoses, such as an atrial septal defect or ventricular septal defect, may be managed with one surgical repair or transcatheter intervention early in childhood.5,6 More complex biventricular diagnoses like tetralogy of Fallot often require multistage surgeries7 with interventions later in life, such as a pulmonary valve replacement.8 Patients with single ventricle physiology require multiple procedures prior to the age of 5, culminating in Fontan completion and surveillance with other interventions later in life.9,10

Adolescents and young adults, defined hereafter as youth, are believed to be at increased risk of adverse outcomes after surgery, including new persistent opioid use.11 A sentinel study identified 4.8% of youth refilled opioid prescriptions at least once 90 to 180 days after common procedures compared to 0.1% of the control population, a new opioid use disorder (OUD).12 Despite recent declines in postsurgical opioid dispensing13, 14, 15 and increased societal awareness, youth continue to be at increased risk of developing persistent opioid use after surgery.16,17 Patients with persistent opioid use are at increased risk of developing an OUD,18 which is distinguished as developing over a 12-month period and causing clinically significant impairment or distress for the individual. This is concerning for CHD patients, who may undergo repeat procedures with opioid exposures.

With lifelong cardiac and metabolic complications,19, 20, 21 chronic pain,22,23 mobility challenges,24 and other chronic medical conditions, youth with CHD, particularly more complex diagnoses, are known to be at elevated risk for anxiety, depression, impaired psychosocial functioning, and neurodevelopmental disorders.25, 26, 27, 28, 29 Considering these challenges, CHD patients may be predisposed to developing OUD and substance use disorders (SUDs): many studies demonstrate a high proportion of adolescents with SUDs have comorbid psychiatric problems and a higher likelihood of developing substance dependence.30 Indeed, even in the general population, it is well-documented that mental health disorders place individuals at an increased risk for the development of OUD/SUD.31, 32, 33, 34 Because of challenges in conducting population-level research, prior studies examining these outcomes among CHD patients have been limited to a single state or non-U.S. countries. Between 2014 and 2017, a study of adults with CHD in Oregon identified 4.9% had an OUD diagnosis.35,36 One study using self-reported general population data estimated 2.5% of the overall U.S. population had an OUD diagnosis.35,36

To address these knowledge gaps, we planned an analysis using a national claims database to study OUD/SUD prevalence among CHD patients with simple biventricular (eg, atrial septal defect and ventricular septal defect), complex biventricular (eg, tetralogy of Fallot), and single ventricle physiology diagnoses (eg, hypoplastic left heart syndrome). The primary objective was to compare OUD prevalence, while the secondary objectives analyzed overdose events, SUD prevalence, and mental health diagnoses across the 3 cohorts. Although we could not capture postoperative opioid dispensing or use for patients, we hypothesized that those with more complex diagnoses likely had more repeat opioid exposures following multistep procedures as youth and thus higher OUD prevalence.

Methods

Study design

Using a national insurance database, we conducted a retrospective cohort study between January 1, 2012 and May 31, 2022, to measure OUD prevalence among youth and adults with a CHD diagnosis that typically requires at least one procedure via sternotomy. We followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for observational studies.37 All data were deidentified, and the study was determined to be exempt from human subject research review by the University of Pennsylvania Institutional Review Board.

Data source and population

We used data from Optum’s deidentified Clinformatics Data Mart Database (CDM or Clinformatics), derived from a database of administrative health claims for members of large commercial insurances. Clinformatics utilizes medical and pharmacy claims to derive patient-level enrollment information, health care costs, and resource utilization information. The population is geographically diverse, spanning all 50 states, and is statistically deidentified under the Expert Determination method consistent with Health Insurance Portability and Accountability Act and managed according to Optum customer data use agreements.38 Claims data have previously been used to characterize OUD/SUD prevalence in youth; while it may be an underestimate, the alternative is national self-reported data, which are expensive and challenging to collect.39

All medical claims between January 1, 2012 and May 31, 2022 were assessed to identify the study sample. Patients who had at least one medical claim with an associated CHD diagnosis typically requiring at least one sternotomy repair with anticipated opioid exposure were identified. Patients were included if they were between 15 and 64 years at the time of this claim, and they were required to have 360 days of continuous insurance enrollment around this claim. We were unable to capture procedural opioid dispensing due to the limited continuous enrollment window.

Diagnostic groups

Diagnoses were selected and assigned to groups by an experienced dual-trained pediatric cardiologist/cardiac anesthesiologist (A.P.) and a senior pediatric cardiac anesthesiologist (S.N.) and identified using International Classification of Diseases (ICD)-Ninth Revision and ICD-Tenth Revision diagnosis codes (Supplemental Table 1). Common comorbidity codes are displayed in Supplemental Table 2. Codes were also cross-referenced against existing literature.40, 41, 42 Patients with multiple diagnoses were classified by the condition most likely to require repair into adulthood, determined by expert consensus. CHD diagnoses were segregated into 3 groups based on procedural needs: simple biventricular, complex biventricular, and single ventricle physiology (Supplemental Table 3). We initially planned to directly compare patients with simple and complex biventricular diagnoses, but we recognized that it was also important to capture patients with single ventricle physiology given their unique trajectory with complex multisystem care needs. We chose to classify single ventricle diagnoses separately due to these unique medical comorbidities and health concerns.

Outcome measures

Our primary outcome was OUD prevalence39,43, 44, 45, 46 among youth and adults with simple biventricular, complex biventricular, and single ventricle physiology diagnoses. Secondary outcomes included the prevalence of overdose events, comorbid SUD diagnoses,44 and mental health diagnoses.47,48 All outcomes were captured within medical claims using the ICD-Ninth Revision and ICD-10th Revision diagnosis codes (Supplemental Table 4). These could represent either new or historic diagnoses. No prescription claims were utilized.

Statistical analysis

Primary analysis

Patient characteristics and outcomes in the 3 CHD groups are presented using the median with 25th-75th percentiles (Q1-Q3) or count (percentage). All outcomes with a submitted claim were captured in Optum, with any appropriate percent missingness for specific characteristics documented. We examined the proportion of individuals with OUD, overdose events, comorbid SUD diagnoses, and mental health diagnoses by cohort. We conducted 2 sensitivity analyses. In the first, patients with isolated double outlet right ventricle or double outlet left ventricle diagnoses were excluded from the analysis. In the second sensitivity analysis, we eased our inclusion criteria to patients with 180 days of continuous enrollment instead of 360 days.

Regression models

Univariable and multivariable logistic regression models were used to estimate the unadjusted and adjusted association, respectively, between CHD diagnoses, patient characteristics, and OUD or one or more SUD diagnoses. Results are presented as the unadjusted OR and adjusted OR (aOR) with corresponding 95% CI and P values. Other variables included were age group (15-24 years as reference), female sex, income (<$40,000 as reference), race (Asian as reference), and mental health diagnoses (no mental health disorder diagnosis as reference). Asian race was used as the reference race/ethnicity as this group had the lowest prevalence of OUD (0.84%) in the cohort, as has also been observed in previous studies using self-reported data.49 Due to visible trend changes by year, the year the outcome diagnosis was first captured was considered a categorical variable (2012 as reference). Analyses were conducted in SAS version 9.4 (SAS Institute, Inc) from June 2024 to June 2025. All tests were 2-sided, and statistical significance was set at the 5% level. We also performed chi-squared tests to evaluate differences in mental health conditions by diagnostic group.

Results

Baseline characteristics

The cohort, described in Table 1, included 73,046 youth and adults with a CHD diagnosis requiring one or more surgical repairs between 2012 and 2022. The median (Q1-Q3) age was 43.0 (29.0-56.0) years. Among participants, 39,795 (54.5%) were female, 6,714 (9.2%) were African American or Black, 2,502 (3.4%) were Asian, 7,583 (10.4%) had Hispanic/Latino ethnicity, 50,923 (69.7%) were White, and 5,324 (7.3%) were identified as other/unknown race and ethnicity. Most patients had simple biventricular diagnoses (75.8%, n = 55,335), while 14,077 (19.2%) had complex biventricular and 3,634 (5.0%) had single ventricle physiology diagnoses.

Table 1.

Characteristics of Congenital Heart Disease Patients by Surgical Repair Group

Simple Biventricular (n = 55,335) Complex Biventricular (n = 14,077) Single Ventricle Physiology (n = 3,634) Total (N = 73,046)
Age (y), median (Q1-Q3) 46.0 (31.0-57.0) 35.0 (23.0-51.0) 39.0 (25.0-56.0) 43.0 (29.0-56.0)
Age (n, %)
 15-24 7,811 (14.1) 3,961 (28.1) 847 (23.3) 12,619 (17.3)
 25-34 9,231 (16.7) 2,976 (21.1) 721 (19.8) 12,928 (17.7)
 35-44 9,468 (17.1) 2,218 (15.8) 506 (13.9) 12,192 (16.7)
 45-54 11,684 (21.1) 2,118 (15.0) 545 (15.0) 14,347 (19.6)
 55-64 17,141 (31.0) 2,804 (19.9) 1,015 (27.9) 20,960 (28.7)
Female, n (%) 30,997 (56.0) 6,819 (48.4) 1,979 (54.5) 39,795 (54.5)
Race and ethnicitya (n, %)
 Asian 1,908 (3.4) 474 (3.4) 120 (3.3) 2,502 (3.4)
 Black/African American 5,303 (9.6) 1,082 (7.7) 329 (9.1) 6,714 (9.2)
 Hispanic 5,839 (10.6) 1,394 (9.9) 350 (9.6) 7,583 (10.4)
 Non-Hispanic White 38,365 (69.3) 9,973 (70.8) 2,585 (71.1) 50,923 (69.7)
 Other/Unknown 3,920 (7.1) 1,154 (8.2) 250 (6.9) 5,324 (7.3)
Geographic region, n (%)
 East North Central 8,285 (15.0) 2,170 (15.4) 599 (16.5) 11,054 (15.1)
 East South Central 2,667 (4.8) 531 (3.8) 136 (3.7) 3,334 (4.6)
 Middle Atlantic 4,285 (7.7) 1,159 (8.2) 277 (7.6) 5,721 (7.8)
 Mountain 5,930 (10.7) 1,319 (9.4) 377 (10.4) 7,626 (10.4)
 New England 2,149 (3.9) 582 (4.1) 135 (3.7) 2,866 (3.9)
 Pacific 4,608 (8.3) 1,510 (10.7) 337 (9.3) 6,455 (8.8)
 South Atlantic 12,902 (23.3) 3,138 (22.3) 806 (22.2) 16,846 (23.1)
 West North Central 6,082 (11.0) 1,398 (9.9) 408 (11.2) 7,888 (10.8)
 West South Central 8,262 (14.9) 2,234 (15.9) 550 (15.1) 11,046 (15.1)
 Unknown 165 (0.3) 36 (0.3) 9 (0.2) 210 (0.3)
Annual household income, n (%)
 <$40,000 11,032 (21.0) 2,326 (17.6) 710 (20.5) 14,068 (20.3)
 $40,000-$59,999 6,492 (12.4) 1,531 (11.6) 420 (12.1) 8,443 (12.2)
 $60,000-$74,999 4,656 (8.9) 1,213 (9.2) 320 (9.3) 6,189 (8.9)
 $75,000-$99,999 7,252 (13.8) 1,783 (13.5) 480 (13.9) 9,515 (13.7)
 >100,000 19,534 (37.2) 5,273 (39.9) 1,175 (34.0) 25,982 (37.5)
 Unknown 3,597 (6.8) 1,100 (8.3) 353 (10.2) 5,050 (7.3)
Most common CHD diagnoses, n/N (%) ASD (69.6) Aortic valve stenosis (37.7) Aortic atresia (27.7) ASD (52.7)
VSD (20.9) Tetralogy of Fallot (24.6) Mitral valve stenosis (22.2) VSD (15.8)
Coarctation of aorta (5.4) Atrioventricular defect (16.5) Hypoplastic left heart syndrome (13.5) Aortic valve stenosis (7.3)
Common comorbidities, n (%)
 Hypertension 28,155 (50.9) 5,801 (41.2) 1,764 (48.5) 35,720 (48.9)
 Obesity 19,202 (34.7) 3,949 (28.1) 1,074 (29.6) 24,225 (33.2)
 Coronary artery disease 12,182 (22.0) 3,027 (21.5) 922 (25.4) 16,131 (22.1)
 Liver disease 16,714 (30.2) 3,241 (23.0) 1,137 (31.3) 21,092 (28.9)
 Renal disease 14,383 (26.0) 2,885 (20.5) 1,072 (29.5) 18,340 (25.1)
Months of insurance eligibility, median (Q1-Q3) 55.7 (30.4-96.1) 53.6 (30.3-91.3) 60.8 (31.8-106.4) 54.8 (30.4-95.7)
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ASD = atrial septal defect; CHD = congenital heart disease; VSD = ventricular septal defect.

a

The definition of other race is defined internally by Optum Clinformatics using a proprietary unpublished algorithm.

Substance use disorder

Table 2 displays the prevalence of OUD and SUD for substances including alcohol, amphetamine, cannabis, and nicotine. Overall OUD prevalence was 3.3% (n = 2,389). Overall nonopioid SUD prevalence was 35.9% (n = 26,228), and overdose prevalence was 0.5% (n = 391). Among the 3 cohorts, 3.6% (n = 1,994) of the simple biventricular, 1.9% (n = 269) of the complex biventricular, and 3.5% (n = 126) of the single ventricle physiology had an OUD diagnosis. Within each of these diagnostic groups, older adults (25-64 years) had higher OUD prevalence than youth (15-24 years). Similar trends were observed for nonopioid SUD diagnoses except for cannabis use disorder, where youth had a higher prevalence. We did not identify meaningful differences when excluding patients with isolated diagnoses of double outlet right ventricle or double outlet left ventricle, when study sample decreased by 96 (n = 72,950), or using 180 days of continuous enrollment, when study sample size increased by 6% (n = 77,515).

Table 2.

OUD/SUD Prevalence in CHD Patients by Surgical Repair

Simple Biventricular (n = 55,335)
 Complex Biventricular (n = 14,077)
 Single Ventricle Physiology (n = 3,634)
 Overall (N = 73,046)∗
Age 15-24 y (n = 7,811) Age 25-64 y (n = 47,524) Age 15-24 y (n = 3,961) Age 25-64 y (n = 10,116) Age 15-24 y (n = 847) Age 25-64 y (n = 2,787) Age 15-24 y (n = 12,619) Age 25-64 y (n = 60,427)
Opioid use disorder (OUD) 68 (0.9) 1,926 (4.1) 29 (0.7) 240 (2.4) 8 (0.9) 118 (4.2) 105 (0.8) 2,284 (3.8)
Proportion of OUD cohort with at least 1 additional nonopioid SUD diagnosis 57 (83.8) 1,605 (83.3) 23 (79.3) 196 (81.7) 7 (87.5) 96 (81.4) 87 (82.9) 1,897 (83.1)
OUD overdose 18 (0.2) 308 (0.6) 2 (0.1) 47 (0.5) 0 (0) 16 (0.6) 20 (0.2) 371 (0.6)
Remission from OUD 12 (0.2) 189 (0.4) 5 (0.1) 31 (0.3) 0 (0) 5 (0.2) 17 (0.1) 225 (0.4)
Nonopioid SUD 1,381 (17.7) 19,722 (41.5) 531 (13.4) 3,357 (33.2) 117 (13.8) 1,120 (40.2) 2,029 (16.1) 24,199 (40.0)
Alcohol use disorder 337 (4.3) 4,183 (8.8) 128 (3.2) 701 (6.9) 39 (4.6) 197 (7.1) 504 (4.0) 5,081 (8.4)
Amphetamine use disorder 41 (0.5) 402 (0.8) 15 (0.4) 57 (0.6) 2 (0.2) 9 (0.3) 58 (0.5) 468 (0.8)
Cannabis use disorder 248 (3.2) 838 (1.8) 91 (2.3) 134 (1.3) 19 (2.2) 56 (2.0) 358 (2.8) 1,028 (1.7)
Nicotine use disorder 624 (8.0) 16,142 (34.0) 258 (6.5) 2,737 (27.1) 49 (5.8) 949 (34.1) 931 (7.4) 19,828 (32.8)
Other SUD 765 (9.8) 5,206 (11) 293 (7.5) 764 (7.5) 58 (6.8) 260 (9.3) 1,116 (8.8) 6,230 (10.4)
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Values are n (%).

∗Unable to display total value for each diagnostic group due to cell size.

OUD = opioid use disorder; SUD = substance use disorder; other abbreviation as in Table 1.

Changes in OUD prevalence by year for each CHD diagnostic group between 2012 and 2022 are depicted in Figure 1. OUD prevalence increased between 2012 and 2017 and decreased between 2017 and 2022. For patients with complex biventricular diagnoses, OUD prevalence declined continuously.

Figure 1.

Figure 1

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Trends in OUD Prevalence by Year and Surgical Repair Group, 2012 to 2022

Trends in OUD prevalence from 2012 to 2022 for each diagnostic group (simple biventricular, complex biventricular, and single ventricle physiology) are compared. The median prevalence of OUD in each year was plotted. Overall OUD prevalence increased from 2012 to 2022, first rising from 2012 to 2017 and then falling from 2017 to 2022. For patients with repairs through adulthood, however, the prevalence of OUD declined from 2012 to 2022. Since 2015, the simple biventricular group exhibited the highest prevalence of OUD among all groups. OUD = opioid use disorder.

Mental health diagnoses

The overall prevalence of mental health comorbidities among CHD patients is compared in Table 3 by diagnostic group. The 3 most common mental health conditions in the overall cohort were mood disorders (31.5%, n = 23,004), trauma and stress-related disorders (16.4%, n = 12,005), and attention-deficient/hyperactivity disorders (6.5%, n = 4,775). Anxiety was more prevalent among those with mood disorders (14.11% vs 1.05%). Among the 3 CHD diagnostic groups, prevalence of mental health conditions, including anxiety disorders, was similar (P = 0.13), with several notable exceptions. Simple biventricular and single ventricle physiology patients had increased mood, sleep-wake, trauma and stress-related disorders, and suicidal ideation (P < 0.001). Additionally, patients with an OUD had over 2 times the prevalence of anxiety, mood, neurocognitive, schizophrenia, sleep-wake, suicide ideation, and personality disorders compared to patients with a nonopioid SUD diagnosis or neither (Supplemental Table 5).

Table 3.

Mental Health Diagnoses in CHD Patients by Surgical Repair

Simple Biventricular (n = 55,335) Complex Biventricular (n = 14,077) Single Ventricle Physiology (n = 3,634) Total (N = 73,046)
Anxiety disorders/obsessive compulsive disorder 1,274 (2.3) 286 (2.0) 76 (2.1) 1,636 (2.2)
Attention-deficient/hyperactivity disorder 3,594 (6.5) 931 (6.6) 250 (6.9) 4,775 (6.5)
Autism spectrum disorder 658 (1.2) 203 (1.4) 44 (1.2) 905 (1.2)
Communication disorders 342 (0.6) 119 (0.8) 25 (0.7) 486 (0.7)
Developmental delay/intellectual disability/learning disorders 957 (1.7) 452 (3.2) 87 (2.4) 1,496 (2.0)
Mood disorders (depression, bipolar/related) 18,233 (33) 3,554 (25.2) 1,217 (33.5) 23,004 (31.5)
Motor disorders 250 (0.5) 82 (0.6) 24 (0.7) 356 (0.5)
Neurocognitive disorders 3,014 (5.4) 566 (4.0) 243 (6.7) 3,823 (5.2)
Schizophrenia 1,631 (2.9) 312 (2.2) 122 (3.4) 2,065 (2.8)
Sexuality/gender identity disorders 865 (1.6) 172 (1.2) 57 (1.6) 1,094 (1.5)
Sleep-wake disorders 3,347 (6.0) 507 (3.6) 153 (4.2) 4,007 (5.5)
Suicidal ideation/attempt 1,495 (2.7) 295 (2.1) 100 (2.8) 1,890 (2.6)
Trauma- and stress-related disorders 9,483 (17.1) 1,935 (13.7) 587 (16.2) 12,005 (16.4)
Personality disorders 744 (1.3) 129 (0.9) 35 (1.0) 908 (1.2)
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Values are n (%).

Abbreviation as in Table 1.

Predictors of substance use disorder

The results of the univariable and multivariable analysis studying the association between patient factors and the odds of OUD or at least one SUD diagnosis are presented in Table 4 and Supplemental Table 6, respectively. Characteristics most strongly associated with OUD included mood disorders (aOR: 4.62; 95% CI: 4.11-5.13), anxiety disorders/OCD (aOR: 4.42; 95% CI: 3.82-5.13), and increasing age (aOR: for 54-64 vs 15-24: 5.75; 95% CI: 4.64-7.14). Factors strongly associated with SUD followed similar trends, with the addition of suicidal ideation/attempt (aOR: 4.18; 95% CI: 3.69-4.75). Simple biventricular diagnoses were most commonly associated with OUD (aOR: 1.31; 95% CI: 1.13-1.51), while single ventricle diagnoses were most commonly associated with SUD (aOR: 1.22; 95% CI: 1.11-1.33).

Table 4.

Predictors of OUDa in CHD Patients

Unadjusted OR 95% CI P Value Adjusted OR 95% CI P Value
Age (y) <0.001 <0.001
 15-24 (ref.)
 25-34 1.616 (1.267-2.062) 1.885 (1.457-2.438)
 35-44 3.006 (2.404-3.760) 3.176 (2.504-4.028)
 45-54 5.247 (4.259-6.464) 4.435 (3.548-5.544)
 55-64 7.276 (5.953-8.892) 5.752 (4.635-7.138)
Female 1.083 (0.997-1.176) 0.058 0.814 (0.743-0.892) <0.001
Diagnosis <0.001 <0.001
 Simple biventricular 1.919 (1.687-2.182) 1.307 (1.133-1.508)
 Complex biventricular (ref.)
 Single ventricle physiology 1.844 (1.487-2.285) 1.230 (0.968-1.561)
Income <0.0001 <0.001
 <40,000 (ref.)
 40,000-59,999 0.634 (0.559-0.719) 0.817 (0.714-0.934)
 60,000-74,999 0.427 (0.362-0.503) 0.531 (0.447-0.632)
 75,000-99,999 0.452 (0.395-0.518) 0.603 (0.522-0.698)
 >100,000 0.225 (0.200-0.254) 0.370 (0.324-0.422)
 Unknown 0.465 (0.391-0.553) 0.720 (0.598-0.868)
Race and ethnicityb <0.001 <0.0001
 Asian (ref.)
 Black/African American 5.835 (3.742-9.097) 2.356 (1.490-3.727)
 Hispanic 2.856 (1.813-4.499) 1.691 (1.059-2.698)
 Non-Hispanic White 4.137 (2.685-6.374) 2.201 (1.412-3.431)
 Other/Unknown 3.425 (2.164-5.421) 2.389 (1.384-4.125)
Year <0.001 <0.0001
 2012 (ref.)
 2013 1.227 (0.869-1.731) 1.239 (0.862-1.782)
 2014 1.351 (0.959-1.902) 1.273 (0.884-1.832)
 2015 1.549 (1.151-2.084) 1.211 (0.880-1.665)
 2016 2.016 (1.538-2.643) 1.362 (1.014-1.830)
 2017 1.982 (1.509-2.603) 1.360 (1.010-1.830)
 2018 1.742 (1.324-2.292) 1.149 (0.851-1.551)
 2019 1.831 (1.393-2.406) 1.183 (0.877-1.596)
 2020 1.567 (1.185-2.073) 0.928 (0.683-1.262)
 2021 1.428 (1.079-1.890) 0.918 (0.675-1.249)
 2022 1.354 (0.964-1.903) 0.818 (0.562-1.192)
Mental health diagnosis <0.001 <0.0001
 Anxiety disorders/OCD 9.726 (8.585-11.02) 4.424 (3.817-5.128)
 Mood disorders 9.547 (8.622-10.57) 4.615 (4.111-5.182)
 Schizophrenia 7.428 (6.581-8.383) 1.497 (1.287-1.742)
 Suicidal ideation/attempt 8.335 (7.378-9.416) 2.438 (2.110-2.818)
 Trauma- and stress-related disorder 3.044 (2.794-3.317) 1.328 (1.201-1.469)
 Other mental health diagnoses 3.884 (3.576-4.219) 1.799 (1.635-1.981)
Months of insurance eligibility 1.003 (1.002-1.004) <0.001 1.001 (1.000-1.002) 0.058
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OCD = obsessive compulsive disorder; Ref. = reference group; other abbreviations as in Tables 1 and 2.

a

Number of OUD cases and cohort size: simple biventricular (1,994/55,335), complex biventricular (269/14,077), single ventricle physiology (127/3,634).

b

The definition of other race is defined internally by Optum Clinformatics using a proprietary unpublished algorithm.

Discussion

Using a national claims database, we identified 73,046 patients aged 15 to 64 years with a CHD diagnosis and ≥360 days continuous enrollment who received care between 2012 and 2022. We observed a high prevalence of OUD, overdose events, and SUD, in addition to comorbid mental health conditions. We hypothesized that CHD patients with complex biventricular diagnoses would have the highest prevalence of OUD, possibly related to repeat periprocedural opioid exposure.50,51 As such, we anticipated similar trends for overdoses and prevalence of nonopioid SUD. Interestingly, our data do not support our hypothesis: those with simple biventricular CHD diagnoses had the highest prevalence of OUD, overdoses, and nonopioid SUD. We noted that the simple biventricular and single ventricle physiology cohorts with increased OUD and SUD prevalence also had increased prevalence of mood, sleep-wake, trauma disorders, and suicidal ideation (Central Illustration). These mental health conditions, along with anxiety disorders, have previously been associated with increased risk of OUD/SUD development in the general population.52, 53, 54, 55, 56, 57, 58

Central Illustration.

Central Illustration

Open in a new tab

OUD and Mood Disorder Prevalence by CHD Diagnostic Group

The composition of the patient cohort into named diagnostic groups (simple biventricular, complex biventricular, and single ventricle physiology) is described. OUD diagnosis and mood disorder diagnosis prevalence in each of these groups is compared, highlighting that mental health diagnoses may be stronger predictors than CHD diagnosis for OUD. CHD = congenital heart disease; other abbreviation as in Figure 1.

While OUD prevalence similarly increases with age for CHD patients as in the general population, study findings suggest they may be a uniquely at-risk population. Among U.S. adults aged 26 or older, OUD prevalence (2.5%) was lower compared to this study’s CHD population (3.3%).36 Although this U.S. adult population data are from a self-reported 2022 national survey and may be an underestimate,59 it is also important to note findings of this study are also likely underestimates: the data source does not include publicly insured or uninsured CHD patients, populations that have previously been identified as having a higher OUD prevalence. 49 35 CHD patients in this study had an increased prevalence of fatal and nonfatal opioid overdoses (0.5%) compared to combined 2023 data of fatal (0.025%) and nonfatal opioid overdoses (0.17%) from the National Vital Statistics System60 and national Emergency Medical Service data,61 respectively. Similarly, CHD patients also had an increased prevalence of one or more SUD diagnoses (35.9%) compared to self-reported data in the U.S. population (17.3%).36 The decline in diagnoses that persisted through 2022 reflected national trends and may be related to COVID-era decreased access to care or avoidance of medical settings.62 It is notable that in the international literature, CHD has been considered a protective factor against SUD development.63, 64, 65 Differences may reflect variation in cultural beliefs, perioperative opioid dispensing, regulations on substances use, and access to preventative care.

Our adjusted regression models suggest mental health diagnoses are strongly associated with OUD and may provide insight into diagnosis-specific OUD trends. The association between mental health diagnoses and OUD is well-documented in the general population53, 54, 55, 56, 57, 58,66 including among U.S. youth aged 18 to 25 years.52 This may explain why patients with simple biventricular or single ventricle physiology had the highest prevalence of OUD, nonopioid SUDs, and overdoses. Both groups had higher proportions of mental health diagnoses, including mood disorders, compared to patients with more complex CHD. While we did adjust for neurodevelopmental disorders, it should be noted that prevalence is increased with single ventricle physiology and some complex biventricular conditions and may increase individual risk.67 These findings align with previous findings of increased mental health disorder diagnosis prevalence in the CHD population, both from insurance data and self-reported interview analyses.68, 69, 70 Taken together, mental health diagnosis, not procedural need and perioperative opioid exposure, may be more strongly associated with OUD.

Another reason for differences in OUD/SUD prevalence across diagnostic groups may be differences in interaction with health care. Patients with complex CHD diagnoses anticipating repeat surgeries may have a greater disease awareness and have developed positive preventative behaviors in avoiding substances or seeking earlier treatment for mental health symptoms. Additionally, frequent appointments with a cardiologist may serve as critical opportunities to screen and provide guidance to prevent OUD/SUD. Taken together, additional research is needed to elucidate potential protective factors for CHD patients in preventing OUD/SUD.

Study limitations

This study has limitations. First, elements of this study were limited by the data available. Use of claims data did not allow for adjustment of potential confounding variables, including survivor bias among those with complex diagnoses, family support, marital status, employment, and educational level. It was beyond the scope of this study to perform a secondary analysis comparing outcomes among patients with and without CHD diagnoses, and it remains unknown if adolescents and adults with CHD have an elevated risk of developing OUD/SUD compared to the general U.S. population. Second, patient data were obtained from a private insurance claims database, and findings may not be generalizable to low-income patients with public insurance coverage or those without insurance. In fact, our findings may be an underestimate of the true prevalence of OUD among CHD patients. The referenced adult CHD study utilizing the Oregon All Payer All Claims database identified Medicaid insurance as an independent risk factor for OUD.35 Using an insurance claims database also introduces social desirability bias of patients interacting with providers, resulting in further under-reporting of OUD. It is also possible that we did not capture CHD survivors who did not submit a claim in our study timeline or those without 360 days of continuous enrollment. It is notable, however, that a sensitivity analysis of patients with 180 days of continuous enrollment yielded similar results. Another limitation is that we were unable to capture the patient’s exact surgical history, including opioid dispensing intended for postprocedural pain management. In our analysis, we were only able to capture patients as adults who received care during the study period, missing claims for cardiac procedures from infancy and early childhood. However, we recognize that complex biventricular and single ventricle physiology diagnoses often require one or more major procedures into adulthood that are often associated with opioid prescriptions. Ultimately, our findings suggest that mental health conditions are more strongly associated with OUD/SUD outcomes than hypothesized repeat opioid exposures and medical complexity. We acknowledge that using ICD diagnostic categories sacrifices granularity and precision and is a limitation of this analysis. It was also possible that the CHD diagnosis may not be accurately captured in claims. This is unlikely, however, considering most patients likely had one or more procedures, and coding accuracy is critical for proper insurance reimbursement. Finally, there is concern that a patient who consumes a chronic opioid prescription as prescribed may be labeled as having an OUD diagnosis. However, we identified elevated opioid overdose trends that were also increased in relation to OUD diagnoses, making this possibility less likely.

Conclusions

CHD youth and adults with simple biventricular disease had an increased OUD/SUD prevalence compared to those anticipated to have opioid exposures for adulthood repairs for complex biventricular disease. Our analysis supports that some mental health diagnoses may be stronger predictors for OUD/SUD development and overdose events than hypothesized perioperative opioid exposure and merits additional research. In addition, unique consideration should be given to preventing adverse outcomes among patients with single ventricle physiology in the context of their complex medical trajectories. Because CHD patients may be at elevated risk of developing OUD/SUDs, it is especially important for cardiologists and primary care providers to screen and follow evidence-based interventions to prevent and/or treat these conditions.71,72 In addition, families of CHD patients should be made aware of these concerns and provided appropriate resources. With an increasing number of CHD patients surviving into adulthood, more research is needed to understand why those with simple biventricular and single ventricle physiology diagnoses may have an elevated risk of OUD/SUD and to design effective interventions.

Perspectives.

COMPETENCY IN PATIENT CARE: As patients with CHD have elevated odds of developing OUD/SUD and many have a comorbid mental health diagnosis, it is important to regularly screen and treat these patients.

TRANSLATIONAL OUTLOOK 1: As this is the first detailed large-scale study of OUD/SUD in CHD patients in the United States, additional national studies are needed to further explore these findings.

TRANSLATIONAL OUTLOOK 2: A higher mental health diagnosis burden may explain the increased OUD/SUD prevalence among diagnostic groups in the United States. However, medical needs and outcomes specific to CHD patients merit additional study to better understand these trends.

Funding support and author disclosures

This study was supported by a Foundation for Anesthesia Education and Research (FAER) Medical Student Research Fellow grant. The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Footnotes

The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.

Appendix

For supplemental tables, please see the online version of this paper.

Supplemental material

Supplemental Tables 1-6
mmc1.docx (38.5KB, docx)

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Supplementary Materials

Supplemental Tables 1-6
mmc1.docx (38.5KB, docx)

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