Racial and Ethnic Inequities in Inpatient Psychiatric Civil Commitment
Abstract
Objective:
Involuntary psychiatric treatment may parallel ethnoracial inequities present in the larger society. Prior studies have focused on restraint and seclusion, but less attention has been paid to the civil commitment system because of its diversity across jurisdictions. Using a generalizable framework, this study investigated inequities in psychiatric commitment.
Methods:
A prospective cohort was assembled of all patients admitted to an inpatient psychiatric unit over 6 years (2012–2018). Patients were followed longitudinally throughout their admission; raters recorded legal status each day. Sociodemographic and clinical data were collected to adjust for confounding variables by using multivariate logistic regression.
Results:
Of the 4,393 patients with an initial admission during the study period, 73% self-identified as White, 11% as Black, 10% as primarily Hispanic or Latinx, 4% as Asian, and 3% as another race or multiracial. In the sample, 28% were involuntarily admitted, and court commitment petitions were filed for 7%. Compared with White patients, all non-White groups were more likely to be involuntarily admitted, and Black and Asian patients were more likely to have court commitment petitions filed. After adjustment for confounding variables, Black patients remained more likely than White patients to be admitted involuntarily (adjusted odds ratio [aOR]=1.57, 95% confidence interval [CI]=1.26–1.95), as were patients who identified as other race or multiracial (aOR=2.12, 95% CI=1.44–3.11).
Conclusions:
Patients of color were significantly more likely than White patients to be subjected to involuntary psychiatric hospitalization, and Black patients and patients who identified as other race or multiracial were particularly vulnerable, even after adjustment for confounding variables.
HIGHLIGHTS
•
On an inpatient psychiatric unit in a general hospital, patients of color were more likely than White patients to be involuntarily admitted.
•
Black patients and those who identified as other race or multiracial were most likely to be involuntarily admitted, and this finding held even when the analysis controlled for several demographic and clinical variables.
•
Interventions intended to reduce the need for civil commitment must attend to these ethnoracial inequities.
Involuntary psychiatric hospitalization is accepted by many clinicians as a part of clinical practice that is sometimes necessary, yet it remains controversial (1–4). Arguments in favor cite the duty to protect patients and society from foreseeable harm and the potential for involuntary care to preserve the right to treatment for patients who lack insight (parens patriae) ( 1, 2). Arguments against cite the imprecision of risk prediction, the unethical nature of linking detention to mental illness, the adverse impact on help-seeking behavior, the risk of iatrogenic traumatization, and the incompatibility with a recovery model (3–5).
Given extensive data showing that Black patients are more often subjected to coercive treatments, including restraint and seclusion, discussions of coercive practices in psychiatry must attend to race and racism (6 –12). Further, characterization of racial and ethnic inequities is particularly relevant at a time when there is significant energy to address structural racism in mental health care (13).
Compared with studies examining inequities in restraint and seclusion, there are few such investigations related to civil commitment (14). Most studies come from the United Kingdom, with very few tracking legal status from admission through discharge (6, 15). Although the literature consistently shows ethnoracial inequities in involuntary hospitalization, it is unclear whether these findings are driven primarily by interpersonal bias, clinical differences between ethnoracial groups, or differential exposure to social determinants of health. A better understanding of the determinants of commitment would inform interventions to ensure that involuntary commitment is employed only as a last resort and in an equitable fashion.
The Bias In Acute Services project used data collected prospectively over a 6-year period on all admissions to a general inpatient psychiatric unit in a large general hospital in Boston. This data set was designed to investigate clinical, demographic, and treatment-related predictors of various outcomes, including restraint and involuntary hospitalization, to support quality improvement work. This project focused on patient ethnoracial identity and involuntary hospitalization. The inpatient unit serves a sociodemographically and clinically diverse patient population and is thus well suited to examine determinants of involuntary hospitalization. We hypothesized that patients of color (defined in this study as all non-White patients) would be overrepresented among those involuntarily held in the hospital at measured time points and that such inequities would not be fully explained by other demographic and clinical factors.
Methods
Data Collection
The study was conducted on a 24-bed adult psychiatry unit in a large academic medical center. The unit admits patients with psychiatric and substance use disorders and often manages patients with significant medical comorbid conditions. All admissions were longitudinally followed to the point of discharge between August 1, 2012, and December 31, 2018. For patients with multiple admissions during the study, only initial admissions were included. This resulted in a sample of 4,489 unique patients from a total of 5,832 admissions during the study period. All individuals who declined to provide a self-identified race were excluded, leaving a final sample of 4,393 patients.
Information regarding racial and ethnic identity was obtained by patient self-report at hospital registration. Patients could identify as White, Black, Hispanic or Latinx, Asian, or other (which included patients identifying as two or more races). Notably, prior to 2015, the hospital’s registration policies allowed patients to select Hispanic or Latinx as their primary race. After 2015, the hospital added a separate question about Hispanic or Latinx ethnicity to be consistent with the approach used by the U.S. Census Bureau. For the purposes of this study, after 2015, when a patient’s race was listed as other or unknown but ethnicity was reported as Hispanic or Latinx, that patient was grouped with patients who before 2015 identified their race as Hispanic or Latinx. During the same time frame, if patients chose to identify with one of the available options for race (White, Black, Asian, or other or multiracial) and selected Hispanic or Latinx as their ethnicity, they were grouped with the race they selected (White, Black, Asian, or other or multiracial).
Trained administrative staff used a standardized data collection tool to prospectively record demographic and clinical data via chart review. They supplemented their data collection as needed with conversations with the clinical team during daily multidisciplinary meetings. In preparation for the final data analysis, we used additional retrospective chart reviews to identify missing data. Less than 5% of data were missing for any variable in the final analysis.
Prior to analysis of the relationship between ethnoracial identity and legal outcomes, research staff a priori identified a list of potentially relevant confounders. The following sociodemographic variables were selected: age, gender, housing status, and insurance status. The following clinical variables were selected: admission day of week, referral source, treatment care team, and psychiatric diagnoses (both the primary billing diagnosis and secondary psychiatric diagnoses listed on the discharge summary).
This study was reviewed by the Partners Healthcare (now known as Mass General Brigham) Institutional Review Board and deemed to be a quality improvement project. It was approved by the departmental chief quality improvement officer.
Legal Procedures
In Massachusetts, patients can be involuntarily admitted to a psychiatric unit by a licensed clinician. At admission, the patient must be offered the opportunity to sign in to the hospital on a conditional voluntary legal status (hereafter referred to simply as “voluntary”). If the patient declines or lacks the capacity to sign in, then the physician must determine whether the patient meets commitment criteria on the basis of imminent danger to self or others or grave inability to care for self. The admitting physician can admit such patients for an involuntary hold for an observation period of 3 business days (equivalent to a 72-hour emergency hold in most states). During this 3-day period, patients with decisional capacity can choose to sign in and convert their legal status to voluntary. Alternatively, if a patient on a voluntary status requests discharge when the team believes that the patient may meet commitment criteria, the patient's status can be converted to a 3-day involuntary hold (hereafter referred to as a “vol-to-invol conversion”). The potential for this holding period is the reason that voluntary legal status is considered “conditional.”
At the end of the 3-day involuntary holding period (either 3 days after the involuntary admission or the end of the 3-day hold after a vol-to-invol conversion), the physician can either discharge the patient or petition the court for involuntary civil commitment of up to 6 months. The patient is assigned legal counsel, and a court date is scheduled within 5 business days, although it is often postponed. If at any point the patient agrees to sign in voluntarily, the court hearing can be canceled. While awaiting the court date, if the patient is no longer felt to meet commitment criteria, the physician may discharge the patient. If the judge does not grant longer-term commitment at the hearing, then the patient is immediately discharged.
The primary outcomes of interest were involuntary legal status at admission, filing of a formal civil commitment petition, and proceeding with a court hearing. An additional primary outcome was “discharge from a 3-day hold” (either after an involuntary admission or after a vol-to-invol conversion), because this represents a particular group of patients who declined to stay in the hospital voluntarily but were ultimately found not to meet commitment criteria. Finally, a secondary outcome of invol-to-vol conversion was derived from the primary-outcomes patients in this group who were admitted involuntarily but later signed into the hospital voluntarily.
Analysis
Statistical analyses were carried out in R. The distributions of categorical variables between groups of interest were compared by using chi-square tests of association, and continuous variables were compared by using one-way analysis of variance. Univariate analysis was performed to assess the rates of legal status–related outcomes of interest between racial groups; it was also performed on a set of a priori–defined covariates (as described above). Multivariate models for each legal outcome were derived by using backward stepwise multivariate regression, beginning with all covariates significant in univariate analysis below a threshold of p<0.2 and removing covariates until all that remained met a significance threshold of p<0.1. Sensitivity analyses were run with the full list of identified covariates, and the results were similar to those obtained from backward stepwise regression. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were determined for each variable included in the model. A significance threshold for primary and secondary outcomes of p<0.05 was selected a priori, and no adjustments were made for multiple comparisons. When calculating ORs for likelihood of the secondary outcome of invol-to-vol conversion, only patients who began the admission involuntarily were included.
Results
A flow diagram in the online supplement summarizes the legal pathways that all 4,393 patients followed from admission to discharge. At admission, 28% (N=1,240 patients) of the sample was on an involuntary legal status. Many of these patients either converted to voluntary admission and were discharged or were discharged after a 3-day hold. Therefore, the sample of patients on the commitment pathway gradually decreased: initial involuntary 3-day hold, 28% (N=1,240); petition filed for a court hearing, 7% (N=315); court hearing held, 3% (N=127); and formal civil commitment granted, 3% (N=122). The vast majority of patients admitted voluntarily left on the same legal status (89%, N=2,813 of 3,153), whereas many patients admitted involuntarily converted to voluntary status by discharge (47%, N=583 of 1,240).
Table 1 shows the demographic, clinical, and legal characteristics for the full sample in aggregate and by ethnoracial category. Overall, 52% of the sample was male, and the mean age of the sample was 43.4 years. On average, patients of color (defined in this study as all non-White patients) were younger, compared with White patients. The gender distributions for White patients and patients of color were similar. Homelessness was more common among Black patients (33% versus 18% for the overall sample). Both lack of insurance and accessing care through the emergency department were also more common among patients of color, compared with White patients. Diagnostically, the most striking differences were in the incidence of psychotic disorders, which were markedly more common among patients of color (25% for White patients versus 41%–58% for the other groups).
| Total (N=4,393) | White (N=3,187, 73%) | Black (N=486, 11%) | Hispanic or Latinx (N=430, 10%) | Asian (N=159, 4%) | Other or multiracial (N=131, 3%) | p | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Characteristic | N | % | N | % | N | % | N | % | N | % | N | % | |
| Age (M±SD) | 43.4±17.0 | 45.7±17.3 | 38.2±15 | 37.0±14 | 35.6±16 | 36.2±16.1 | <.001 | ||||||
| Gender | .843 | ||||||||||||
| Male | 2,288 | 52 | 1,654 | 52 | 248 | 51 | 226 | 53 | 84 | 53 | 76 | 58 | |
| Female | 2,095 | 48 | 1,524 | 48 | 237 | 49 | 204 | 47 | 75 | 47 | 55 | 42 | |
| Other or unknown | 10 | <1 | 9 | <1 | 1 | <1 | 0 | — | 0 | — | 0 | — | |
| Housing status | <.001 | ||||||||||||
| Housed | 3,609 | 82 | 2,661 | 84 | 327 | 67 | 378 | 88 | 142 | 89 | 101 | 77 | |
| Homeless | 784 | 18 | 526 | 17 | 159 | 33 | 52 | 12 | 17 | 11 | 30 | 23 | |
| Insurance status | <.001 | ||||||||||||
| Commercial | 1,470 | 34 | 1,171 | 37 | 105 | 22 | 91 | 2 | 71 | 45 | 32 | 24 | |
| Public | 2,237 | 51 | 1,599 | 50 | 271 | 56 | 257 | 60 | 43 | 27 | 67 | 51 | |
| Dually eligible (Medicare and Medicaid) | 64 | 2 | 48 | 2 | 10 | 2 | 2 | 1 | 3 | 2 | 1 | 1 | |
| Uninsured | 600 | 14 | 354 | 11 | 97 | 20 | 77 | 18 | 41 | 26 | 31 | 24 | |
| Unknown | 22 | 1 | 15 | 1 | 3 | 1 | 3 | 1 | 1 | 1 | 0 | — | |
| Any psychosis | 1,378 | 31 | 789 | 25 | 281 | 58 | 176 | 41 | 78 | 49 | 54 | 41 | <.001 |
| Any substance use disorder | 1,195 | 27 | 907 | 29 | 124 | 26 | 112 | 26 | 21 | 13 | 31 | 24 | <.001 |
| Primary diagnosis | <.001 | ||||||||||||
| Major depressive disorder | 1,614 | 37 | 1,247 | 39 | 115 | 24 | 160 | 37 | 43 | 27 | 49 | 37 | |
| Bipolar disorder | 593 | 14 | 465 | 15 | 49 | 10 | 48 | 11 | 15 | 9 | 16 | 12 | |
| Mood disorder, unspecified | 394 | 9 | 306 | 10 | 34 | 7 | 35 | 8 | 10 | 6 | 9 | 7 | |
| Schizophrenia spectrum disorder | 1,072 | 24 | 601 | 19 | 238 | 49 | 123 | 29 | 70 | 44 | 40 | 30 | |
| Anxiety disorder, trauma | 195 | 4 | 152 | 5 | 12 | 3 | 14 | 3 | 11 | 7 | 6 | 4 | |
| Substance use–related disorder | 203 | 4 | 152 | 5 | 11 | 2 | 33 | 8 | 2 | 11 | 5 | 3 | |
| Other | 322 | 7 | 264 | 8 | 27 | 6 | 17 | 4 | 8 | 5 | 6 | 4 | |
| Length of stay ≤3 days | 641 | 15 | 440 | 14 | 77 | 16 | 72 | 17 | 20 | 13 | 32 | 24 | .006 |
| Length of stay ≥30 days | 117 | 3 | 82 | 3 | 20 | 4 | 4 | 1 | 8 | 5 | 3 | 2 | .014 |
| Length of stay (M±SD days) | 9.0±8.6 | 9.0±8.3 | 10.0±12.7 | 7.3±5.0 | 10.4±8.8 | 7.7±7.3 | <.001 | ||||||
| Referral source | <.001 | ||||||||||||
| Admitted from emergency department | 3,305 | 75 | 2,305 | 72 | 407 | 84 | 361 | 84 | 124 | 78 | 108 | 82 | |
| Admitted from medical floor | 901 | 21 | 713 | 22 | 69 | 14 | 66 | 15 | 31 | 20 | 22 | 17 | |
| Admitted from other source | 187 | 4 | 169 | 5 | 10 | 2 | 3 | 1 | 4 | 3 | 1 | 1 | |
a
Analysis of variance was used to generate p values for continuous variables (age and length of stay). Chi-square tests were used to generate p values for categorical variables (all other than age and length of stay).
Table 2 shows the univariate logistic regression analysis of legal outcomes by the covariates used in our analysis, many of which were significantly associated with legal status. Patients who were experiencing homelessness were more likely than those who were housed to be involuntarily admitted. Patients who were commercially insured were less likely than those without commercial insurance to be involuntarily admitted. Patients with a primary diagnosis of bipolar disorder, schizophrenia spectrum disorder, or unspecified mood disorder were more likely than patients with depression to be on an involuntary status. Patients with substance use–related diagnoses were less likely than those without such diagnoses to be involuntarily admitted. In general, many of the same covariates that predicted involuntary admission were predictive of the outcomes discharged from 3-day hold and filed for commitment (Table 2).
| Involuntary admission | Discharged from 3-day hold | Filed for commitment | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Covariate | OR | 95% CI | p | OR | 95% CI | p | OR | 95% CI | p |
| Gender (reference: male) | |||||||||
| Female | 1.02 | .89–1.16 | .775 | 1.0 | .85–1.18 | .97 | 1.1 | .87–1.38 | .42 |
| Other | .64 | .097–2.56 | .574 | .61 | .037–3.60 | .63 | 1.51 | .082–8.10 | .70 |
| Experiencing homelessness (reference: housed) | 1.43 | 1.21–1.68 | <.001 | 1.24 | 1.01–1.52 | .04 | 1.98 | 1.53–2.56 | <.001 |
| Insurance (reference: commercial) | |||||||||
| Public insurance | 1.57 | 1.35–1.84 | <.001 | .91 | .76–1.10 | .34 | 1.43 | 1.09–1.90 | .011 |
| Dually eligible (Medicare and Medicaid) | 2.90 | 1.73–4.81 | <.001 | .69 | .28–1.44 | .37 | 1.51 | .52–3.53 | .39 |
| Uninsured | 2.28 | 1.86–2.81 | <.001 | 1.66 | 1.3–2.10 | <.001 | 2.06 | 1.45–2.91 | <.001 |
| Unknown | 3.11 | 1.3–7.3 | .009 | 2.64 | 1.0–6.33 | .036 | 3.97 | 1.12–10.93 | .02 |
| Primary diagnosis (reference: depression) | |||||||||
| Bipolar disorder | 2.31 | 1.85–2.89 | <.001 | 1.53 | 1.18–1.98 | .001 | 6.63 | 4.14–10.90 | <.001 |
| Mood disorder, unspecified | 1.78 | 1.35–2.32 | <.001 | 1.39 | 1.01–1.88 | .038 | 2.17 | 1.07–4.21 | .03 |
| Schizophrenia spectrum disorder | 6.37 | 5.31–7.65 | <.001 | 1.64 | 1.32–2.03 | <.001 | 14.04 | 9.37–21.98 | <.001 |
| Anxiety disorder, trauma | .97 | .62–1.45 | .87 | .93 | .57–1.45 | .75 | 2.02 | .74–4.67 | .13 |
| Substance use–related disorder | 1.46 | .996–2.09 | .046 | 1.79 | 1.21–2.58 | .003 | .95 | .23–2.75 | .94 |
| Other | 2.82 | 2.15–3.69 | <.001 | 1.74 | 1.26–2.37 | .001 | 3.76 | 2.00–6.95 | <.001 |
| Referral source (reference: admitted from emergency department) | |||||||||
| Admitted from medical floor | .94 | .80–1.11 | .479 | .69 | .56–.86 | .001 | 1.17 | .88–1.53 | .27 |
| Admitted from other source | .27 | .16–.43 | <.001 | .40 | .22–.67 | .001 | 1.09 | .59–1.84 | .77 |
| Any psychosis (reference: no psychosis) | 4.40 | 3.83–5.07 | <.001 | 1.24 | 1.04–1.47 | .015 | 6.79 | 5.27–8.82 | <.001 |
| Any substance use disorder (reference: no substance use disorder) | .69 | .59–.81 | <.001 | 1.14 | .95–1.37 | .147 | .45 | .32–.61 | <.001 |
Univariate analysis of legal status outcomes by ethnoracial identity was notable for increased rates of involuntary admission among patients of color (Table 3). This finding was especially prominent for patients who identified either as Black or as other or multiracial. After adjustment for covariates, these differences were attenuated, although they remained significant for the Black patient group (aOR=1.57) and for the other or multiracial group (aOR=2.12). Black patients were also more likely than White patients to have commitment petitions filed (OR=2.90) and to be discharged from a 3-day hold (OR=1.32); however, these findings did not reach statistical significance in multivariate analysis. Similarly, Asian patients were more likely than White patients to have commitment petitions filed (OR=2.10), but this finding did not reach significance in multivariate analysis. Finally, in univariate analysis only, Black and other or multiracial patients were found to be less likely than White patients to convert from an involuntary to a voluntary legal status during their admission.
| Outcome | White (N=3,187)b | Black (N=486) | Hispanic or Latinx (N=430) | Asian (N=159) | Other or multiracial (N=131) | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N | OR | N | OR | 95% CI | p | N | OR | 95% CI | p | N | OR | 95% CI | p | N | OR | 95% CI | p | ||
| Involuntary admission | 765 | 217 | 142 | 59 | 57 | ||||||||||||||
| Univariate | 1.00 | 2.55 | 2.10–3.11 | <.001 | 1.55 | 1.25–1.92 | <.001 | 1.87 | 1.33–2.59 | <.001 | 2.51 | 1.75–3.57 | <.001 | ||||||
| Multivariate (adjusted OR) | 1.00 | 1.57 | 1.26–1.95 | <.001 | 1.23 | .97–1.56 | .081 | 1.28 | .88–1.84 | .19 | 2.12 | 1.44–3.11 | <.001 | ||||||
| Filed for commitment | 183 | 73 | 29 | 18 | 12 | ||||||||||||||
| Univariate | 1.00 | 2.90 | 2.16–3.86 | <.001 | 1.18 | .77–1.74 | .42 | 2.10 | 1.22–3.41 | .005 | 1.68 | .87–2.99 | .10 | ||||||
| Multivariate (adjusted OR) | 1.00 | 1.38 | .98–1.94 | .067 | .91 | .57–1.42 | .69 | 1.15 | .62–2.03 | .64 | 1.08 | .52–2.07 | .83 | ||||||
| Discharged from 3-day hold | 467 | 90 | 73 | 27 | 25 | ||||||||||||||
| Univariate | 1.00 | 1.32 | 1.03–1.59 | .027 | 1.18 | .90–1.52 | .22 | 1.19 | .76–1.79 | .42 | 1.4 | .88–1.15 | .14 | ||||||
| Multivariate (adjusted OR) | 1.00 | .89 | .67–1.16 | .39 | .88 | .65–1.17 | .39 | .87 | .55–1.35 | .56 | .86 | .53–1.37 | .55 | ||||||
| Involuntary-to-voluntary conversionc | 373 | 92 | 68 | 27 | 23 | ||||||||||||||
| Univariate | 1.00 | .69 | .51–.94 | .017 | .91 | .64–1.31 | .619 | .57 | .44–1.29 | .305 | .57 | .32–.98 | .043 | ||||||
| Multivariate (adjusted OR) | 1.00 | .76 | .54–1.06 | .103 | .85 | .58–1.26 | .423 | .82 | .47–1.46 | .505 | .58 | .32–1.03 | .065 | ||||||
a
The following covariates were included in each model, using backward stepwise regression as described: involuntary status at admission: insurance status, primary diagnosis, psychosis, substance use disorder, referral source; filed for commitment: housing status, insurance status, age, primary diagnosis, psychosis, substance use disorder, involuntary status at admission; discharged from 3-day hold: age, primary diagnosis, referral source, presence of psychosis, involuntary status at admission; involuntary-to-voluntary conversion: housing status, insurance, primary diagnosis, referral source, psychosis.
b
Reference group.
c
Admitted involuntarily but later signed into the hospital voluntarily.
Of the 127 patients who went to court, 122 (96%) were court committed to continued inpatient treatment. Given the small number of patients in this group who were released by the court (N=5), these patients were excluded from further analysis, and comparisons were conducted between those who were released before their court date (N=188) and those who were court committed (N=122). The number of patients from each ethnoracial group who reached this point in the commitment pathway was small. Therefore, Table 4 summarizes clinical and demographic features from this final comparison in aggregate form. Overall, few differences reached statistical significance, but patients released before their court date were younger, compared with patients who were ultimately court committed.
| Characteristic | Discharged before hearing (N=188, 61%) | Court committed (N=122, 39%) | p | |||
|---|---|---|---|---|---|---|
| N | % | N | % | |||
| Age (M±SD) | 44.2±17.8 | 48.0±18.0 | <.001 | |||
| Gender | .073 | |||||
| Male | 103 | 55 | 52 | 43 | ||
| Female | 84 | 45 | 70 | 57 | ||
| Other or unknown | 1 | 1 | 0 | — | ||
| Race-ethnicity | .143 | |||||
| White | 114 | 61 | 67 | 55 | ||
| Black | 40 | 21 | 31 | 25 | ||
| Hispanic or Latinx | 19 | 10 | 10 | 8 | ||
| Asian | 6 | 3 | 11 | 9 | ||
| Other or multiracial | 9 | 5 | 3 | 3 | ||
| Housing status | .307 | |||||
| Housed | 138 | 73 | 83 | 68 | ||
| Homeless | 50 | 27 | 39 | 32 | ||
| Insurance status | .115 | |||||
| Commercial | 46 | 25 | 31 | 25 | ||
| Public | 103 | 55 | 61 | 50 | ||
| Dually eligible (Medicare and Medicaid) | 2 | 1 | 3 | 3 | ||
| Uninsured | 37 | 20 | 23 | 19 | ||
| Unknown | 0 | — | 4 | 3 | ||
| Any psychosis | 136 | 72 | 89 | 73 | .906 | |
| Any substance use disorder | 34 | 18 | 13 | 11 | .075 | |
| Primary diagnosis | .503 | |||||
| Major depressive disorder | 15 | 8 | 9 | 7 | ||
| Bipolar disorder | 34 | 18 | 22 | 18 | ||
| Mood disorder, unspecified | 10 | 5 | 3 | 3 | ||
| Schizophrenia spectrum disorder | 110 | 59 | 80 | 66 | ||
| Anxiety disorder, trauma | 3 | 2 | 3 | 3 | ||
| Substance use–related disorder | 3 | 2 | 0 | — | ||
| Other | 13 | 7 | 5 | 4 | ||
| Referral source | .705 | |||||
| Admitted from emergency department | 138 | 73 | 88 | 72 | ||
| Admitted from medical floor | 43 | 23 | 27 | 22 | ||
| Admitted from other source | 7 | 4 | 7 | 6 | ||
Of note, over the 6-year study, no clear temporal effect on group-level differences was noted. (A table in the online supplement shows rates of involuntary hospitalization by ethnoracial group for each year in the study.)
Discussion
In this study, patients of color were more likely than White patients to be involuntarily admitted. After adjustment for confounding variables, this pattern remained significant for Black patients and for other or multiracial patients. Evidence of ethnoracial inequity was found for other legal outcomes measured, particularly for Black patients; however, some findings did not remain significant in multivariate analysis.
In describing these findings, the term “inequity” was intentionally chosen in lieu of “disparity” or “difference.” This choice was made to call attention to the “systemic, avoidable, and unjust social and economic policies” that produce differential exposure to the social determinants of mental health, access to care, and other factors that we propose are upstream of our findings (16).
To our knowledge, this is the largest U.S. study designed to investigate ethnoracial inequities in civil commitment. A similar U.S. study did not find race to be independently predictive of involuntary hospitalization, but that study’s power was limited by a smaller sample (227 patients) and one that was more clinically and racially homogeneous (84.9% Black) ( 15). Another U.S. study from 2015 had a sample size similar to our own but included fewer details on legal outcomes (17 ).
Europe has a more extensive literature on the determinants of involuntary hospitalization, particularly in the United Kingdom. Consistent with our data, a large meta-analysis of these studies showed that patients of color, and especially Black patients, were more likely than White patients to be civilly committed (6). However, this meta-analysis did not adjust for any variables that might confound or mediate the relationship between ethnoracial identity and civil commitment.
Although few studies have been designed to investigate the causes of ethnoracial inequities in commitment, many explanations have been proposed. These include interpersonal racism, implicit bias, and differences between racial groups with respect to illness severity, access to and engagement with mental health care, and distribution of upstream social determinants of health (6, 18–23). Although we cannot address all these hypotheses, our findings add to the literature regarding the impact of illness expression and social determinants of health on commitment inequities. Prior work has shown that if diagnostic factors (specifically, increased prevalence of psychosis among patients of color) and social factors are controlled for, ethnoracial inequities in commitment are no longer observed (24, 25). Our work contradicts these findings, showing that Black and other or multiracial identities predicted involuntary admission independent of diagnostic and socioeconomic covariates. Future work should interrogate the role of patient-provider–level interpersonal racism, differences in symptom severity, and prehospitalization treatment history in mediating inequities (26, 27).
The fact that some of our findings did not remain significant in multivariate analysis is notable, but it does not necessarily imply that race was unrelated to these outcomes. First, although our sample size was large, some outcomes (filed for commitment and discharged from 3-day hold) were relatively low-frequency events. Given our findings at admission, future work investigating these outcomes in larger samples is warranted. Second, because of the pervasive influence of structural racism, many of the covariates used were likely not truly independent of race. Through this lens, rather than considering all covariates as “confounders,” many of the covariates may in fact mediate the impact of structural racism on outcomes (28).
This study had several limitations. The single-site design is relevant, given variability in commitment laws and local practice patterns. We were unable to investigate information related to differences in the commitment criteria (harm to self, harm to others, or grave disability) used across groups. Further, there may have been variable classification of patients identifying as Hispanic or Latinx before and after 2015 because of institutional changes in coding of racial and ethnic identity during the study. Overall, however, any such risk was likely limited, given that the proportion of patients identifying as Hispanic or Latinx was consistent before and after 2015 and fairly closely in accord with the proportion of Hispanic or Latinx individuals both admitted to our general hospital and in our institution’s home neighborhood (data not shown). Finally, although we concluded on the basis of available data that race predicted involuntary admission independent of demographic and clinical covariates, additional data would help exclude other potential explanations. These include but are not limited to more detailed sociodemographic data, treatment history, information regarding the provider decision-making process, and more detailed data on clinical presentation and illness severity.
Conclusions
This study sought to examine determinants of civil commitment, with specific attention to the role of patient ethnoracial identity. Patients of color, and particularly Black and other or multiracial patients, were more likely than White patients to be involuntarily admitted. For Black and other or multiracial patients, these differences were not fully explained by clinical and demographic factors, including diagnosis and multiple social determinants of health. Court commitment petitions were more likely to be filed for Black and other or multiracial patients; however, this finding did not remain significant in multivariate analysis. Future studies should attempt to better characterize factors that mediate observed inequities. Such work may inform interventions designed to ensure that coercive measures are used in an equitable fashion.
Supplementary Material
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References
1.
Wynn R : Coercion in psychiatric care: clinical, legal, and ethical controversies. Int J Psychiatry Clin Pract 2006 ; 10 : 247 – 251
2.
Testa M, West SG : Civil commitment in the United States. Psychiatry 2010 ; 7 : 30 – 40
3.
Respect for self-determination and use of coercion in the treatment of mentally ill persons: an ethical position statement of the DGPPN [German Association for Psychiatry, Psychotherapy and Psychosomatics] [in German]. Nervenarzt 2014 ; 85 : 1419 – 1431
4.
Swartz MS, Swanson JW, Hannon MJ : Does fear of coercion keep people away from mental health treatment? Evidence from a survey of persons with schizophrenia and mental health professionals. Behav Sci Law 2003 ; 21 : 459 – 472
5.
Schenwar M, Law V : Prison by Any Other Name: The Harmful Consequences of Popular Reforms. New York, New Press, 2020
6.
Barnett P, Mackay E, Matthews H, et al : Ethnic variations in compulsory detention under the Mental Health Act: a systematic review and meta-analysis of international data. Lancet Psychiatry 2019 ; 6 : 305 – 317
7.
Snowden LR, Hastings JF, Alvidrez J : Overrepresentation of black Americans in psychiatric inpatient care. Psychiatr Serv 2009 ; 60 : 779 – 785
8.
Sohler NL, Bromet EJ, Lavelle J, et al : Are there racial differences in the way patients with psychotic disorders are treated at their first hospitalization? Psychol Med 2004 ; 34 : 705 – 718
9.
Swanson J, Swartz M, Van Dorn RA, et al : Racial disparities in involuntary outpatient commitment: are they real? Health Aff 2009 ; 28 : 816 – 826
10.
Cusack KJ, Grubaugh AL, Yim E, et al : Are there racial differences in the experience of harmful or traumatic events within psychiatric settings? Psychiatr Q 2007 ; 78 : 101 – 115
11.
Schnitzer K, Merideth F, Macias-Konstantopoulos W, et al : Disparities in care: the role of race on the utilization of physical restraints in the emergency setting. Acad Emerg Med 2020 ; 27 : 943 – 950
12.
Wong AH, Whitfill T, Ohuabunwa EC, et al : Association of race/ethnicity and other demographic characteristics with use of physical restraints in the emergency department. JAMA Netw Open 2021 ; 4 : e2035241
13.
Shim RS : Dismantling structural racism in psychiatry: a path to mental health equity. Am J Psychiatry 2021 ; 178 : 592 – 598
14.
Morris NP : Detention without data: public tracking of civil commitment. Psychiatr Serv 2020 ; 71 : 741 – 744
15.
Craw J, Compton MT : Characteristics associated with involuntary versus voluntary legal status at admission and discharge among psychiatric inpatients. Soc Psychiatry Psychiatr Epidemiol 2006 ; 41 : 981 – 988
16.
Shim R, Compton M (eds): Social (In)Justice and Mental Health. Washington, DC, American Psychiatric Association Publishing, 2021
17.
Hamilton JE, Heads AM, Cho RY, et al : Racial disparities during admission to an academic psychiatric hospital in a large urban area. Compr Psychiatry 2015 ; 63 : 113 – 122
18.
Davies S, Thornicroft G, Leese M, et al : Ethnic differences in risk of compulsory psychiatric admission among representative cases of psychosis in London. BMJ 1996 ; 312 : 533 – 537
19.
Walker S, Mackay E, Barnett P, et al : Clinical and social factors associated with increased risk for involuntary psychiatric hospitalisation: a systematic review, meta-analysis, and narrative synthesis. Lancet Psychiatry 2019 ; 6 : 1039 – 1053
20.
Lindsey KP, Paul GL : Involuntary commitments to public mental institutions: issues involving the overrepresentation of blacks and assessment of relevant functioning. Psychol Bull 1989 ; 106 : 171 – 183
21.
Maura J, Weisman de Mamani A : Mental health disparities, treatment engagement, and attrition among racial/ethnic minorities with severe mental illness: a review. J Clin Psychol Med Settings 2017 ; 24 : 187 – 210
22.
Whaley AL : Cross-cultural perspective on paranoia: a focus on the black American experience. Psychiatr Q 1998 ; 69 : 325 – 343
23.
Snowden LR : Bias in mental health assessment and intervention: theory and evidence. Am J Public Health 2003 ; 93 : 239 – 243
24.
Gajwani R, Parsons H, Birchwood, M, et al : Ethnicity and detention: are Black and minority ethnic (BME) groups disproportionately detained under the Mental Health Act 2007? Soc Psychiatry Psychiatr Epidemiol 2016 ; 51 : 703 – 711
25.
Singh SP, Burns T, Tyrer P, et al : Ethnicity as a predictor of detention under the Mental Health Act. Psychol Med 2014 ; 44 : 997 – 1004
26.
Hairston D, Gibbs T, Wong S, et al : Clinician bias in diagnosis and treatment ; in Racism and Psychiatry: Contemporary Issues and Interventions. Edited by Medlock M, Shtasel D, Trinh N, et al. Cham, Switzerland, Springer Nature, 2019. doi: 10.1007/978-3-319-90197-8_7
27.
Schwartz, RC, Blankenship, D : Racial disparities in psychotic disorder diagnosis: a review of empirical literature. World J Psychiatry 2014 ; 4 : 133 – 140
28.
Cook, BL, McGuire, TG, Zaslavsky, AM : Measuring racial/ethnic disparities in health care: methods and practical issues. Health Serv Res 2012 ; 47 : 1232 – 1254
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Received: 9 June 2021
Revision received: 30 October 2021
Revision received: 19 February 2022
Accepted: 25 March 2022
Published online: 12 August 2022
Published in print: December 01, 2022
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The authors report no financial relationships with commercial interests.
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