Association between Social Determinants of Health and Deliberate Self-Harm Among Youth with Mental Illness

Abstract

Objective:

This study examines the association between social determinants of health (SDoH) and self-harm risk among youths.

Methods:

A retrospective longitudinal analysis was performed using Ohio Medicaid claims data for 244,958 youths (aged 10–17 years) with a primary mental health diagnosis between April 1, 2016 and December 31, 2018. SDoH were identified using ICD-10 codes and classified into fourteen categories: abuse and neglect, child welfare placement, educational, financial problems, exposure to violence, housing instability, legal issues, disappearance or death of a family member, family disruption by separation or divorce, family alcohol or drug use, parent-child conflict, other family problems, social and environmental problems, and nonspecific psychosocial needs. Cox proportional hazard analysis was used to examine the association between SDoH and self-harm, controlling for demographic characteristics and psychiatric and medical comorbidities.

Results:

During follow-up, 51,796 youths (21.1%) had at least one SDoH indicator, and 3,262 youths (1.3%) had at least one self-harm event. Abuse and neglect (HR = 1.90; 99% CI: 1.70–2.12), child welfare placement (HR=1.32; 99% CI: 1.04–1.67), parent-child conflict (HR=1.52; 99% CI: 1.23–1.87), other family problems (HR=1.25; 99% CI: 1.01–1.54), and nonspecific psychosocial needs (HR=1.41; 99% CI: 1.06–1.89) were associated with an increased hazard of self-harm.

Conclusions:

SDoH are significantly associated with self-harm even after controlling for demographic and clinical characteristics. These findings underscore the need to develop effective methods to capture SDoH information in medical records to identify youths at elevated risk for suicide to inform targeted interventions in healthcare settings.

Introduction

Research has consistently recognized the critical role social determinants have on health concerns and disparities. The U.S. Department of Health and Human Services defines social determinants of health (SDoH) as “the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.”(1) Approximately 80 to 90% of health outcomes in the United States are influenced by a combination of SDoH and health behaviors.(2,3) Healthy People 2030 underscores the importance of these conditions by focusing on SDoH as one of its overarching goals to promote health and wellbeing.(1) One important health outcome influenced by SDoH includes self-harm, defined here as encompassing both non-suicidal self-injury and suicide attempts.(4) Self-harm is a key risk factor for suicide in youth and a major public health concern.(5) Between 7% and 31% of youth may have exhibited self-injurious behaviors,(6–9) while 2019 national surveillance data indicate 8.9% of high school students in the U.S. reported at least one suicide attempt in the last 12 months.(10)

Consistent with the social-ecological model(11) that incorporates individual, relationship, community, and societal factors, evidence suggests that SDoH including economic stability, healthcare, education, family and other interpersonal relationships, and social connectedness are associated with increased risk of self-harm and suicide in youth. A study examining the association between parental socioeconomic status and youth self-harm, found youths whose parents had repeatedly low income levels had about 1.5 times greater self-harm risk compared to youths whose parents reported high income levels.(12) Another study found youth aged 10–19 living in disadvantaged neighborhoods were twice as likely to report suicidal thoughts and four times as likely to have a suicide attempt compared to controls.(13) Poor parental relations and family discord including childhood maltreatment have also been linked to increased suicide risk in youth. In a study of youth aged 9–10 years, high family conflict was significantly associated with suicidal ideation even after controlling for demographic and psychosocial variables.(14). Gomez et al.(15) also examined whether child maltreatment significantly increased suicide risk in adolescents aged 13–18 years and found youth with physical or sexual abuse had 5.8 and 4.2 times greater odds of reporting suicide attempts respectively.

Knowledge of the association between SDoH and youth self-harm and suicidal behavior is limited given the lack of standardized, population-level data linking SDoH to these outcomes. Capturing SDoH information in medical records may assist in identifying individuals in healthcare settings impacted by adverse SDoH to prevent self-harm. This can be especially critical for youth at risk for suicide, who frequently have contact with healthcare professionals prior to a suicide attempt or death.

Approximately 80% of youth who die by suicide are seen by their primary care clinicians in the year prior to death, while only 20% saw a mental health provider.(16,17) A 2019 survey by the American Academy of Pediatrics found that over 75% of pediatricians reported having a patient who attempted or died by suicide, and 48% said this had occurred in the past year.(18) To address this gap, the primary aims of the current study are to: 1) quantify the prevalence of adverse SDoH captured in medical claims data and 2) examine the association between SDoH and self-harm among Medicaid-enrolled youths with primary mental health disorders. A better understanding of SDoH and suicide risk in pediatric primary care and other healthcare settings can inform targeted suicide prevention strategies to reduce youth suicide.

Methods

Study Design and Cohort

We examined the association between SDoH and nonfatal self-harm using a retrospective longitudinal cohort design. The study population included all youths aged 10–17 years with at least one claim with a primary mental health disorder diagnosis (International Classification of Diseases, 10^th revision (ICD-10) codes F00-F99) between April 1, 2016 and December 31, 2018, who were continuously enrolled in Medicaid during the 180-day period prior to the index claim. Excluded were youth who were missing data on sex (n=4) or area of residence (n=35), leaving a final sample of 244,958. Youths were followed until the first occurrence of self-harm, age 25, the end of Medicaid enrollment, death, or December 31, 2018, whichever occurred first. Follow-up time ranged from 1.0 days to 1,004.0 days (mean: 600.5 days; SD: 330.4 days). The Ohio State University Institutional Review Board approved all procedures, and we followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.(19)

Data Sources

We extracted data from Ohio Medicaid claims and eligibility data. Medicaid claims data include information such as service dates, Current Procedural Terminology (CPT)/Healthcare Common Procedure Coding System (HCPCS) procedure codes, and up to 16 ICD-10 diagnosis codes for paid inpatient and outpatient services claims. Monthly Medicaid enrollment status and youth demographic information (e.g., age, sex, race/ethnicity) were obtained from Medicaid eligibility files.

Measures

Dependent Variable

The primary outcome of interest was time (measured in days) to first nonfatal self-harm event during the follow-up period (see online supplement for ICD-10 codes).(20) Our operationalization of self-harm included both non-suicidal self-injury and suicide attempts.(4)

Social Determinants of Health

The primary exposures of interest were adverse SDoH, identified using ICD-10 codes and classified into fourteen categories (see online supplement for the specific ICD-10). These categories, modified from previous research to better capture SDoH of interest in youth populations,(21) included abuse and neglect, child welfare placement, educational, employment, or financial problems, exposure to violence, housing instability, legal issues, disappearance or death of a family member, family disruption by separation or divorce, family alcohol or drug use, parent-child conflict, other family problems (e.g., inadequate parent supervision, parental overprotection, excessive parental pressure, needing to care for a dependent relative), social and environmental problems (e.g., discord with neighbors or landlord, problems related to living in a residential institution, acculturation difficulty, social exclusion and rejection), and nonspecific psychosocial needs, or psychosocial issues not directly defined by the ICD-10 code used (e.g., other specified problems related to psychosocial circumstances, problems related to unspecified psychosocial circumstances). Each category was treated as a time-varying variable. Youths were considered as experiencing a given SDoH for 365 days following a claim with a diagnosis code in that category.

Covariates

Covariates included demographic and clinical characteristics. Demographic variables included age on the index date, sex (male or female), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or other including American Indian/Alaskan Native, Asian American/Native Hawaiians/Other Pacific Islanders, more than 1 race, and unknown), area of residence (metropolitan or non-metropolitan), and Medicaid eligibility status (disability, foster care, poverty, or other). Clinical comorbidities, including both psychiatric and medical conditions, were identified based on medical claims during the 180 days preceding the index claim with a primary mental health diagnosis or during the follow-up period and were treated as time-varying covariates. Evidence of a psychiatric comorbidity, including attention deficit/hyperactivity disorder (ADHD), anxiety disorders, conduct/oppositional defiant disorders, bipolar disorders, major depression, intellectual disability, personality disorders, schizophrenia, and substance use disorders, was based on the presence of at least one inpatient claim and/or at least two outpatient claims with a diagnosis code for that disorder (see online supplement for ICD-10 codes). We identified complex chronic conditions (e.g., cancer, cystic fibrosis) based on the presence of at least one relevant diagnosis code using a system previously utilized in administrative data (22, 23) and non-complex chronic conditions (e.g., asthma, obesity) based on at least one claim with a relevant diagnosis code as identified using the HCUP chronic condition indicator.(22,24) Psychiatric conditions were not considered chronic medical conditions. Prior self-harm and prior suicidal ideation, as defined in previous research,(25,26) included any claim with a relevant diagnosis code during the 180 days preceding or including the index primary mental health diagnosis claim. Any inpatient, emergency room, or outpatient mental healthcare during the 180 days before the index claim were included as measures of prior healthcare utilization.

Statistical Analysis

Descriptive statistics were used to examine the distribution of demographic and clinical characteristics, service history, and SDoH prevalence. Cox proportional hazards analysis was used to examine the association between each SDoH category and time to first nonfatal self-harm event.(27) Unadjusted and adjusted hazard ratios (HRs) and 99% confidence intervals (CI) were calculated for each SDoH category. To determine the independent contribution of adverse SDoH on risk of self-harm, we estimated two Cox proportional hazards models. Model 1 included the demographic and clinical covariates. Model 2 added the adverse SDoH. A likelihood ratio test was utilized to determine whether Model 2 had significantly improved fit compared to Model 1. All analyses were completed using SAS version 9.4 and R version 4.0.3.(28,29)

Results

The final sample (n=244,958) was predominately male (54.4%) and non-Hispanic White (64.6%), with a mean age of 12.9 years (SD: 2.4 years) (Table 1). Most youths were eligible for Medicaid due to poverty (86.9%) and lived in a metropolitan area (78.8%). Approximately two-thirds (64.8%) had a chronic medical condition. Common mental health diagnoses in the cohort included ADHD (39.7%), depression (26.2%), and anxiety disorders (23.9%).

Table 1.

Demographic and clinical characteristics of youth with a primary mental health diagnosis (n=244,958)

Demographic Characteristics	N	%
Age at index date (years) (M±SD)	12.9±2.4
Sex
Male	133,167	54.4
Female	111,791	45.6
Race/ethnicity
Non-Hispanic White	158,244	64.6
Non-Hispanic Black	63,490	25.9
Hispanic	10,434	4.3
Othera	12,790	5.2
Eligibility status at index date
Poverty	212,892	86.9
Disabled	18,766	7.7
Foster care	12,415	5.1
Otherb	885	0.4
County of residence
Metro	192,937	78.8
Non-Metro	52,021	21.2
Clinical Characteristics
Psychiatric conditionsc,d
ADHD	97,257	39.7
Anxiety	58,624	23.9
Bipolar disorder	10,949	4.5
Conduct disorder/ODD	47,464	19.4
Depression	64,214	26.2
Intellectual disability	21,838	8.9
Personality disorder	2,067	0.8
Schizophrenia	3,556	1.5
Substance use disorder	20,705	8.5
Chronic medical conditiond
No chronic medical condition	86,245	35.2
Noncomplex, chronic medical condition	126,236	51.5
Complex, chronic medical condition	32,477	13.3
Prior history of suicidal ideation	8,833	3.6
Prior history of self-harm	3,004	1.2
Prior inpatient mental healthcare	3,567	1.5
Prior emergency room mental healthcare	5,615	2.3
Prior outpatient mental healthcare	124,754	50.9
Incident self-harm	3,262	1.3

^aOther race/ethnicity included Asian Americans, Native Hawaiians, or other Pacific Islanders (n=1,373; 0.6%), Native Americans/Alaska Natives (n=473; 0.2%), more than one race (n=2,391; 1.0%), and other/unknown (n=8,553; 3.5%);

^bOther eligibility included incarceration and unknown Medicaid eligibility categories

^c)Youths could have more than one condition.

^d)Prevalence for the full study period (from the index date until age 25, death, end of Medicaid enrollment, or December 31, 2018)

Prevalence of Adverse Social Determinants of Health

Adverse SDoH were documented for 51,796 youths (21.1%) in the period between the index date and the earliest of age 25, death, end of Medicaid enrollment, or December 31, 2018 (the full study period). The most prevalent adverse determinant category was abuse and neglect (13.3%), followed by other family problems (3.1%), educational problems (2.7%), parent-child conflict (2.2%), and child welfare placement (2.2%) (Table 2). Only 153 youths (0.1%) had a diagnosis code related to legal issues during follow-up, with no youths experiencing legal issues at the time of the first self-harm event. Due to the small sample size, we did not investigate the association between legal issues and self-harm.

Table 2.

Social determinant of health (SDoH) prevalence among youth with a primary mental health diagnosis

	Overalla (n=244,958)		Nonfatal Self-Harmb (n=3,262)		Unadjusted Hazard Ratio	99% CI
Social determinant of health category	n	%a	n	%b
Abuse and neglect	32,556	13.3	1,061	32.5	5.03	4.57–5.54
Child welfare placement	5,300	2.2	146	4.5	3.93	3.16–4.89
Disappearance/death of family member	2,387	1.0	62	1.9	4.35	3.13–6.05
Educational problems	6,667	2.7	79	2.4	1.95	1.46–2.62
Employment or financial problems	1,557	0.6	28	0.9	3.81	2.33–6.21
Exposure to violence	4,490	1.8	76	2.3	3.02	2.24–4.07
Family alcohol/drug use	343	0.1	8	0.3	3.99	1.60–9.94
Family disruption by separation/divorce	908	0.4	12	0.4	2.27	1.08–4.79
Housing instability	672	0.3	21	0.6	6.98	3.97–12.27
Parent-child conflict	5,464	2.2	188	5.8	5.91	4.87–7.17
Other family problems	7,703	3.1	206	6.3	4.97	4.13–5.98
Social environmental problem	2,817	1.1	100	3.1	6.49	4.99–8.43
Nonspecific psychosocial needs	2,736	1.1	91	2.8	6.29	4.78–8.27

^aPrevalence for the full study period (from the index date until age 25, death, end of Medicaid enrollment, or December 31, 2018)

^bPrevalence at the time of the first nonfatal self-harm claim

Associations between Social Determinants of Health and Nonfatal Self-Harm

Self-harm occurred in 3,262 youths (1.3%) during follow-up. The mean follow-up time before first self-harm event was 352.5 days (minimum: 1.0 days; maximum: 1,000.0 days; SD: 274.3 days). At the time of first self-harm event, one-third of youths (32.5%) had documented abuse and neglect, while 6.3% had other family problems and 5.8% had parent-child conflict. 4.5% had a child welfare placement documented within the past 365 days (Table 2).

Table 3 shows the estimated HRs and 99% CI from the multivariable Cox proportional hazards models. In Model 1, demographic characteristics associated with increased hazard for self-harm included older age (HR=1.07 [99% CI: 1.04–1.09]) and female sex (HR=2.23 [99% CI: 2.00–2.49]). Medicaid eligibility due to disability was associated with decreased hazard of self-harm compared to poverty (HR=0.77 [99% CI: 0.61–0.97]). In terms of clinical factors, the following psychiatric mental health disorders were associated with an increased hazard of self-harm: anxiety (HR=1.44 [99% CI: 1.30–1.60]), bipolar (HR=1.92 [99% CI: 1.66–2.21]), conduct/oppositional defiant disorder (HR=1.63 [99% CI: 1.46–1.82]), depression (HR=3.91 [99% CI: 3.50–4.38]), personality disorder (HR=1.60 [99% CI: 1.28–2.01]), schizophrenia (HR=1.75 [99% CI: 1.44–2.13]), or substance use disorder (HR=1.37 [99% CI: 1.20–1.56]). Compared to no chronic medical conditions, the presence of a non-complex, chronic medical condition (HR=1.30 [99% 1.16–1.45]) or complex, chronic medical condition (HR=1.30 [99% CI: 1.12–1.51]) was also associated with increased hazard of self-harm, as was prior suicidal ideation (HR=1.81 [99% CI: 1.55–2.10]) and prior self-harm (HR=2.02 [99% CI: 1.71–2.38]). Prior inpatient mental healthcare (HR=0.76 [99% CI: 0.62–0.93]) and outpatient mental healthcare (HR=0.77 [99% CI: 0.69–0.86]) were associated with a decreased hazard of self-harm.

Table 3.

Estimated hazard ratios of the association between social determinants of health and deliberate self-harm among youth with a primary mental health diagnosis (n=244,958)

	Model 1a		Model 2b
Variable	Hazard ratio	99% CI	Hazard ratio	99% CI
Age at index date	1.07	1.04–1.09	1.08	1.05–1.10
Female (reference: male)	2.23	2.00–2.49	2.09	1.87–2.34
Race/ethnicity (reference: non-Hispanic White)
Non-Hispanic Black	0.97	0.87–1.09	0.96	0.86–1.07
Hispanic	0.94	0.73–1.20	0.96	0.75–1.23
Otherc	0.88	0.71–1.09	0.86	0.70–1.07
Eligibility status at index date (reference: Poverty)
Disabled	0.77	0.61–0.97	0.78	0.61–0.98
Foster care	1.15	0.97–1.35	0.97	0.82–1.16
Otherd	0.79	0.25–2.51	0.57	0.18–1.82
Non-Metro residence (reference: Metro residence)	0.91	0.81–1.03	0.94	0.84–1.06
Psychiatric conditions
ADHD	1.08	0.97–1.21	1.05	0.94–1.17
Anxiety	1.44	1.30–1.60	1.32	1.19–1.47
Bipolar disorder	1.92	1.66–2.21	1.72	1.49–1.98
Conduct disorder/ODD	1.63	1.46–1.82	1.50	1.34–1.68
Depression	3.91	3.50–4.38	3.61	3.22–4.05
Intellectual disability	0.94	0.77–1.15	0.94	0.77–1.14
Personality disorder	1.60	1.28–2.01	1.45	1.15–1.82
Schizophrenia	1.75	1.44–2.13	1.60	1.32–1.95
Substance use disorder	1.37	1.20–1.56	1.26	1.11–1.44
Chronic medical condition (reference: no chronic medical condition)
Noncomplex, chronic medical condition	1.30	1.16–1.45	1.26	1.12–1.41
Complex, chronic medical condition	1.30	1.12–1.51	1.25	1.07–1.45
Prior history of suicidal ideation	1.81	1.55–2.10	1.68	1.44–1.96
Prior history of self-harm	2.02	1.71–2.38	1.99	1.69–2.34
Prior inpatient mental healthcare	0.76	0.62–0.93	0.73	0.59–0.89
Prior emergency room mental healthcare	1.01	0.84–1.20	0.98	0.82–1.18
Prior outpatient mental healthcare	0.77	0.69–0.86	0.77	0.70–0.86
Social determinants of health
Abuse and neglect			1.90	1.70–2.12
Child welfare placement			1.32	1.04–1.67
Disappearance/death of family member			1.17	0.83–1.65
Educational problems			1.17	0.86–1.59
Employment or financial problems			0.83	0.50–1.38
Exposure to violence			1.18	0.87–1.60
Family alcohol/drug use			1.46	0.58–3.67
Family disruption by separation/divorce			0.90	0.42–1.94
Housing instability			0.87	0.49–1.55
Parent-child conflict			1.52	1.23–1.87
Other family problems			1.25	1.01–1.54
Social environmental problem			1.24	0.93–1.66
Nonspecific psychosocial needs			1.41	1.06–1.89

^aLikelihood ratio test: χ²=5,512, df=25, p<0.001

^bLikelihood ratio test: χ²=5,848, df=38, p<0.001. Significant difference between Model 1 and Model 2 (χ²=335.6, df=13, p<0.001)

^cOther race/ethnicity included Asian Americans, Native Hawaiians, or other Pacific Islanders (n=1,373; 0.6%), Native Americans/Alaska Natives (n=473; 0.2%), more than one race (n=2,391; 1.0%), and other/unknown (n=8,553; 3.5%)

^dOther eligibility included incarceration and unknown Medicaid eligibility categories

In Model 2, inclusion of adverse SDoH significantly improved model fit compared to Model 1, which included only demographic and clinical characteristics (χ²=335.6, df=13, p<0.001). After controlling for demographic and clinical characteristics, abuse and neglect (HR=1.90 [99% CI: 1.70–2.12]), child welfare placement (HR=1.32 [99% CI: 1.04–1.67]), parent-child conflict (HR=1.52 [99% CI: 1.23–1.87]), other family problems (HR=1.25 [99% CI: 1.01–1.54]), and nonspecific psychosocial needs (HR=1.41 [99% CI: 1.06–1.89]) were associated with increased hazard of self-harm.

Discussion

Our study’s primary purpose was to identify the association between adverse SDoH and risk of self-harm. We built upon the previous literature by examining a broad range of SDoH using data applicable to real-world clinical settings, allowing the broad application of our results into daily clinical practice settings, including primary care. In this statewide, population-based sample of youths enrolled in Medicaid with a primary mental health disorder, 21.1% had at least one documented adverse SDoH, and 1.3% had at least one self-harm event during the follow-up period. Several adverse SdoH were associated with increased self-harm risk, including abuse and neglect, child welfare placement, parent-child conflict, other family problems, and nonspecific psychosocial needs. Findings suggest that adverse SdoH provide vital information beyond demographic and clinical factors in understanding the risk for self-harm, and universal identification of SDoH in healthcare settings can improve youth suicide prevention strategies that integrate medical and social service needs. In the U.S., four main screening tools have been designed for identification of SDoH in primary care: “(1) the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) tool by the National Association of Community Health Centers, (2) the Accountable Health Communities Screening Tool, (3) the Health Leads Screening Tool, and (4) HealthBegins Upstream Risks Screening Tool.”(30) Future research should investigate how to most effectively increase SDoH documentation in medical records using methods such as these screening tools, perhaps through quality improvement studies (e.g., Plan-Do-Study-Act cycles) coupled with educational initiatives or standardized protocols.

Abuse and neglect was strongly associated with increased risk for self-harm. After controlling for demographic and clinical factors, the risk of self-harm among youths who had experienced reported abuse and neglect within the past 365 days was nearly 2 times greater than those without such histories. Previous research has identified abuse and neglect as key risk factors for self-harm and suicide among adolescents.(4,31) The association between abuse and neglect and self-harm has been reported in both males and females and across race/ethnicity groups.(31) Identification of youths who have experienced abuse and neglect in medical records, including through use of SDoH ICD-10 codes, will help to ensure that these high-risk youths receive targeted screening and interventions to prevent nonfatal self-harm. For example, youths who self-report abuse or neglect using a screening tool embedded within an electronic health record or youths whose healthcare provider enters an ICD-10 code for abuse or neglect could receive an automatic referral to community or counseling services that could help support that youth.

Several factors related to family issues were also associated with increased self-harm risk, even after controlling for demographic and clinical factors. Family issues, including poor parent-child attachment, family support and cohesion, parental psychiatric symptoms, and frequent arguing with adult authority figures, have been identified as key risk factors for self-harm and suicide among youths.(31) We found that parent-child conflict and other family problems were significantly associated with increased self-harm risk. Child welfare placement, likely a proxy of poor family functioning, history of child abuse or neglect, and other previous stressors, was also associated with elevated self-harm risk, which is consistent with previous research. In a nationally representative sample of United States adolescents, risk of suicide attempt in the past 12 months was about four times greater among those with a history of foster care involvement.(32) Addressing underlying family and related social issues may help to reduce risk of self-harm. For example, multisystemic family-based therapy, a family-focused intervention that targets the multiple systems encompassing a youth and their support network, has demonstrated promising evidence of being more successful in reducing attempted suicide rates than psychiatric hospitalization for adolescents with psychiatric emergencies.(33) Identification of issues related to child welfare placement or other family-related issues may increase the chance that youths experiencing such problems receive appropriate interventions to prevent self-harm and other negative health outcomes.

Strengths of this study include: 1) a large, diverse, population-based sample of youths with primary mental health diagnoses enrolled in Medicaid; 2) one of the first examinations, to the best of our knowledge, of the association between SDoH reported using ICD-10 codes and nonfatal self-harm among youth; and 3) a longitudinal observational study design rather than cross-sectional analysis. However, this study has several limitations. First, our study included data from one state Medicaid population for youth with mental health conditions, therefore, our findings may not be generalizable to other Medicaid programs, populations without mental health conditions, or privately insured or uninsured populations. It should also be noted that Medicaid populations with mental health conditions have higher rates of medical comorbidities compared to the general population (34). Second, another significant limitation is that suicidal intent of self-harm injuries is not distinguished in claims data such that non-suicidal self-injury and suicide attempts cannot be differentiated. Third, diagnoses obtained from claims data are not validated or obtained using standardized methods. Fourth, SDoH are likely underreported in claims records,(35) and the degree of underreporting may differ by clinical setting and diagnosis. This limitation underscores the importance of increasing standardized documentation of SDoH in medical records. Finally, self-harm that does not result in medical care is not captured in medical claims.

Conclusions

SDoH are significantly associated with nonfatal self-harm among youth with primary mental health disorders even after controlling for demographic and clinical characteristics. Ultimately, our findings underscore the importance of addressing both medical and social factors in prevention of self-harm. This is particularly important in Medicaid populations who disproportionately experience suicide risk factors (e.g., mental illness) and adverse SDoH. Use of ICD-10 codes to identify both clinical and social factors related to self-harm risk in medical records can help to target youth for appropriate prevention efforts and also allows the potential for healthcare providers to bill for efforts to address SDoH in a clinical setting.(36) Although reporting of information related to SDoH in electronic medical records has been championed in recent years,(36–38) use of ICD codes to document SDoH remains underutilized despite its potential helpfulness in tracking social needs of patients using standardized definitions that can be easily translated into population-level studies and interventions. Future research should focus on effective methods to increase recording of information on SDoH in medical records and how to best translate the availability of that information into meaningful interventions.

Highlights:

• Study findings document the importance of highlighting social determinants of health in medical records as a keyway to inform targeted suicide prevention efforts, particularly in primary care settings

• Among youth with primary mental health disorders, several adverse social determinants of health documented through ICD-10 codes were positively associated with deliberate self-harm risk, including abuse and neglect, child welfare placement, parent-child conflict, other family problems, and nonspecific psychosocial needs

• Inclusion of information about adverse social determinants of health improved the fit of a model for self-harm risk beyond inclusion of demographic and clinical factors only