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Brief Report   |    
Predictors of Decertification From Involuntary Hospitalization for Patients With Bipolar Disorder
Glen L. Xiong, M.D.; Ana-Maria Iosif, Ph.D.; Michael Brook, M.S.; Donald M. Hilty, M.D.
Psychiatric Services 2010; doi: 10.1176/appi.ps.61.2.200
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Dr. Xiong is affiliated with the Department of Psychiatry and Behavioral Sciences and Dr. Iosif is with the Department of Public Health Sciences, both at the University of California, Davis (UC Davis). Mr. Brook is with the Department of Psychology, Rosalind Franklin University of Medicine and Science, Sacramento, California. Dr. Hilty is with the Department of Psychiatry and Behavioral Sciences, UC Davis Health System, Sacramento, California. Send correspondence to Dr. Hilty at the Department of Psychiatry and Behavioral Sciences, UC Davis Health System, 2230 Stockton Blvd., Sacramento, CA 95817 (e-mail: dmhilty@ucdavis.edu).

Objective: This study examined predictors of decertification (release from involuntary hospitalization after legal hearing) among inpatients with bipolar disorder. Methods: Records from 1992 to 1997 were examined retrospectively for 50 decertified and 48 certified patients with bipolar disorder. The relationship between demographic and clinical variables and decertification was examined using logistic regression analyses. Results: In the overall multiple logistic regression model, participants were significantly more likely to be decertified if they used a mood stabilizer before the decertification hearing (odds ratio [OR]=6.73, 95% confidence interval [CI]=1.78–25.50) or if they had a comorbid substance use disorder (OR=3.45, CI=1.15–10.34). The odds of decertification increased with the number of prior hospitalizations (OR=3.92, CI=1.73–8.87) and decreased with the length of prior hospitalization (OR=.72 per week, CI=.49–1.04) and number of emergency room visits before admission (OR=.46, CI=.28–.74). Conclusions: Predictors of decertification in bipolar disorder require further research to guide future efforts to improve inpatient treatment outcomes. (Psychiatric Services 61:200–203, 2010)

Abstract Teaser
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Patients who are admitted to psychiatric hospitals often decline treatment and leave the hospital against medical advice, resulting in adverse outcomes (1,2). Although legal statutes vary in each state, in order to safeguard the rights of individuals who are involuntarily hospitalized, a hearing is conducted by an officer of the court to determine whether further involuntary treatment is indicated or whether the patient should be decertified (that is, released from involuntary hospitalization after insufficient cause for continued involuntary stay is determined). Decertification has been inadequately researched, particularly for bipolar disorder. In our previous review of 61 studies that examined discharge against medical advice from psychiatric hospitals (3), only one study focused on patients who were discharged against medical advice after decertification (4). None of the studies focused on patients with bipolar disorder (5,6). This is particularly concerning because patients with bipolar mania may be unusually resourceful in presenting themselves so that they appear not to meet the legal criteria for involuntary treatment (7,8). This is associated with adverse outcomes and often leads to a revolving door scenario in the overall clinical course (9). The study presented here aimed to identify common demographic and clinical predictors of decertification among patients with bipolar disorder.

This is a descriptive, naturalistic study involving retrospective chart review of existing treatment records at the Sacramento County Mental Health Treatment Center, a 100-bed inpatient county mental health facility. A log contains the reason for and outcome of each decertification hearing since 1986. Records were reviewed for male and female participants aged 18 years and older with a clinical diagnosis of bipolar disorder until 50 participants were identified in each decertified and certified group. Two cases were dropped from the certified group because of missing data. In the final sample, 48 participants were identified from January 2, 1996, to August 11, 1997, in the certified group, and 50 were selected from January 15, 1992, to November 24, 1997, in the decertified group. Because of lower rates of decertification, the time span was extended retrospectively to identify a sufficient number of decertified cases. Exclusion criteria included an acute medical disorder prolonging length of stay, drug-induced mania, conservatorship, and a diagnosis of schizoaffective disorder or schizophrenia.

Medical records were reviewed in detail for the index hospitalization and clinical history within two years of the index hospitalization. Data studied included sociodemographic characteristics, comorbid psychiatric conditions, routine medications, emergency medications (for example, benzodiazepines and haloperidol), urine drug screen, seclusions before the decertification hearing, and length of time between the index admission and the decertification hearing. Past data included total number of emergency room visits, hospitalizations, medication compliance, length of prior hospitalizations (weeks), duration of illness (years), and the number of previous decertification hearings. Participants who were released from involuntary hospitalization after the decertification hearings were compared with participants who were not decertified. The study protocol was approved by the institutional review board at University of California, Davis.

Informed by previous studies, we divided, a priori, previously known and hypothesized predictive variables of discharge against medical advice into four major categories: sociodemographic characteristics, clinical characteristics in the two years before the index hospitalization, clinical characteristics during the index hospitalization, and diagnostic variables. Univariate unadjusted and multiple logistic regression models (both within each category of predictors and overall) were constructed to quantify the probability of being decertified as a function of each individual variable, by using SAS, version 9.1. Model-building strategy followed the variable selection methods of Hosmer and Lemeshow (10). After selecting as candidates all variables with unadjusted tests at p<.25, we examined a series of nested models to find the set of variables (both within category groups and overall) that best predicted decertification. Contributions of the variables in the models were assessed using maximum likelihood ratio tests, and only terms that added significantly to the previous model (p<.05) were retained. After obtaining multiple models including all of the significant variables, we added back into the models, one at a time, any variable not originally selected as a candidate, to identify whether any of them made an important contribution in the presence of other variables (even though they were not significantly related to the outcome). After refining the main-effect models, clinically meaningful interactions between predictors were also tested.

Table 1 shows the baseline characteristics of the decertified and certified groups. The mean±SD age of the entire sample was 41±12 years (range 21–69), and the mean number of years of education was 12.42±2.24. Univariate analyses revealed that of the sociodemographic characteristics, education level and insurance status predicted decertification. No clinical variable in the two years before the index hospitalization by itself predicted decertification. Mood stabilizer use and a positive urine drug screen or refusal to take a urine drug screen were the only clinical variables during the index hospitalization that predicted decertification, and comorbid substance use diagnosis was the only diagnostic variable that predicted decertification.

Category-specific models were constructed separately for sociodemographic characteristics, clinical characteristics in the two years before the index hospitalization, clinical characteristics during the index hospitalization, and diagnostic variables (Table 1). In the sociodemographic model, having no insurance increased the odds of decertification (odds ratio [OR]=2.76), whereas higher levels of education decreased the odds of decertification (OR=.80). In the model that examined clinical characteristics in the two years before the index hospitalization, prior length of hospital stay (OR=.72 per week) and number of emergency room visits (OR=.52) decreased the odds of decertification, whereas a higher number of prior hospitalizations increased the odds of decertification (OR=3.62). In the model that examined clinical characteristics during the index hospitalization, participants who used mood stabilizers (OR=5.78) and those who tested positive for drugs with a urine drug screen or refused to take a urine drug screen (OR=3.41) were more likely to be decertified. In the diagnostic model, compared with their respective comparison groups, participants with personality disorders were less likely to be decertified (OR=.26), and those with a comorbid substance use disorder were more likely to be decertified (OR=3.88).

In the overall model, which accounted for all variables regardless of category, the odds of decertification were increased by additional prior hospitalizations (OR=3.92, CI=1.73–8.87, p<.001), mood stabilizer use before the decertification hearing (OR=6.73, CI=1.78–25.50, p<.01), and comorbid substance use disorder (OR=3.45, CI=1.15–10.34, p=.02). Longer prior hospitalization (OR=.72 per week, CI=.49–1.07, p=.04) and more prior emergency room visits (OR=.46, CI=.28–.74, p<.001) were associated with decreased odds of decertification. None of the sociodemographic variables were significant in the overall model, although there was a trend for higher education to be associated with a lower likelihood of decertification (p=.07) (data not shown in table).

This is the first study that systematically examined predictive factors for decertification among persons with bipolar disorder. The findings are consistent with previous studies showing that gender and socioeconomic variables did not consistently predict discharge against medical advice (3). In the study presented here, several variables involving previous treatments predicted decertification. Of most interest, the number of past hospitalizations was positively predictive of decertification, and the duration of the hospitalization was negatively predictive. This suggests that patients who have frequent hospitalizations may be more functional in noninstitutionalized settings and therefore appear less severely ill to the hearing officer. The odds of decertification were reduced by each additional emergency room visit. This is consistent with clinical experience because the hearing officer is less likely to decertify a patient who frequents the psychiatric emergency room. Also, the treatment team is more likely to gain experience with the patient given the higher number of clinical contacts and thereby builds a stronger case for certification.

Patients who were not taking medications or who were not taking enough medications have been shown to have increased risk of discharge against medical advice (11,12). In this study, the odds of decertification were higher for those taking mood stabilizers before the decertification hearing, which is likely related to symptom reduction after prompt mood stabilizer treatment (as opposed to delays caused by unwillingness to take medication). There is evidence that inpatients who take mood stabilizers may have better outpatient treatment adherence compared with those who are not taking mood stabilizers (13). To the hearing officer, knowing that the patient is taking medication before the hearing is sometimes used in favor of decertification because it demonstrates that the individual is adherent to treatment. In addition, those with substance use disorders were more likely to be decertified, presumably because of the more rapid resolution of substance-exacerbated bipolar symptoms. Patients with comorbid substance use disorders are less likely to be interested in or need inpatient treatment. It is unclear why antipsychotic use was not predictive of decertification; however, antipsychotic medication was not as commonly used for bipolar mania during the study period.

The main limitation of this study is the retrospective design, which was unable to control for unmeasured confounding variables. Because various temporal, sociopolitical, and economic factors influence regional policies regarding certification hearings (for example, background of hearing officers and role of consumer advocacy groups), the findings of this study are hypothesis generating and may not be applicable in other settings. Although there has not been any notable change in the psychiatric involuntary process for more than 20 years in California, it is important to note that the sample selected spans from 1992 to 1997. Finally, possible treatment at other facilities and severity of the bipolar disorder and other comorbidities were not directly measured in this study. Nevertheless, compared with previous studies on discharge against medical advice (and specifically decertification), the study presented here is more systematic in design and considered variables a priori, permitting adjustments for various confounders. This study has implications for policy makers and other stakeholders who are examining state and county policies concerning involuntary hospitalizations and treatment adherence (13,14). A follow-up study of this cohort, which contains subsequent inpatient and outpatient services use, is under way.

The authors thank the Sacramento County Mental Health Treatment Center and Department of Health and Human Services, Division of Mental Health; the Department of Psychiatry and Behavioral Sciences, University of California, Davis; and Robert E. Hales, M.D., Sally Ozonoff, Ph.D., Mark Frye, M.D., and Rona Hu, M.D.

The authors report no competing interests.

McGlashan TH, Heinseen RK: Hospital discharge status and long-term outcome for patients with schizophrenia, schizoaffective disorder, borderline personality disorder, and unipolar affective disorder. Archives of General Psychiatry 45:363–368, 1988
 
Glick ID, Braff DL, Johnson G, et al: Outcome of irregularly discharged psychiatric patients. American Journal of Psychiatry 138:1472–1476, 1981
 
Brook M, Hilty DM, Liu W, et al: Discharge against medical advice from inpatient psychiatric treatment: a literature review. Psychiatric Services 57:1192–1198, 2006
 
Parry CD, Turkheimer E: Length of hospitalization and outcome of commitment and recommitment hearings. Hospital and Community Psychiatry 43:65–68, 1992
 
Heinssen RK, McGlashan TH: Predicting hospital discharge status for patients with schizophrenia, schizoaffective disorder, borderline personality disorder, and unipolar affective disorder. Archives of General Psychiatry 45:353–360, 1988
 
Pages KP, Russo JE, Wingerson DK, et al: Predictors and outcomes of discharge against medical advice from the psychiatric units of a general hospital. Psychiatric Services 49:1187–1192, 1998
 
Judd LL, Akiskal HS, Schettler PJ, Endicott J, et al: The long-term natural history of the weekly symptomatic status of bipolar disorder. Archives of General Psychiatry 59:530–537, 2002
 
Hilty DM, Brady KT, Hales RE: Bipolar disorder in adults: a review of recent literature. Psychiatric Services 50:201–213, 1999
 
Quanbeck C, Frye M, Altshuler L: Mania and the law in California: understanding the criminalization of the mentally ill. American Journal of Psychiatry 160:1245–1250, 2003
 
Hosmer DW, Lemeshow S: Applied Logistic Regression. New York, Wiley, 2000
 
Dalrymple AJ, Fata M: Cross-validating factors associated with discharges against medical advice. Canadian Journal of Psychiatry 38:285–289, 1993
 
Sajatovic M, Gerhart C, Semple W: Association between mood-stabilizing medication and mental health resource use in the management of acute mania. Psychiatric Services 48:1037–1041, 1997
 
Sajatovic M, Davies M, Hrouda DR: Enhancement of treatment adherence among patients with bipolar disorder. Psychiatric Services 55:264–269, 2004
 
Targum SD, Capodanno AE, Hoffman HA, et al: An intervention to reduce the rate of hospital discharges against medical advice. American Journal of Psychiatry 239:657–659, 1982
 
Table 1  Baseline characteristics of the decertified and certified groups and the results of the univariate and category-specific multiple logistic models predicting decertification
Table 1  Baseline characteristics of the decertified and certified groups and the results of the univariate and category-specific multiple logistic models predicting decertification
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References

McGlashan TH, Heinseen RK: Hospital discharge status and long-term outcome for patients with schizophrenia, schizoaffective disorder, borderline personality disorder, and unipolar affective disorder. Archives of General Psychiatry 45:363–368, 1988
 
Glick ID, Braff DL, Johnson G, et al: Outcome of irregularly discharged psychiatric patients. American Journal of Psychiatry 138:1472–1476, 1981
 
Brook M, Hilty DM, Liu W, et al: Discharge against medical advice from inpatient psychiatric treatment: a literature review. Psychiatric Services 57:1192–1198, 2006
 
Parry CD, Turkheimer E: Length of hospitalization and outcome of commitment and recommitment hearings. Hospital and Community Psychiatry 43:65–68, 1992
 
Heinssen RK, McGlashan TH: Predicting hospital discharge status for patients with schizophrenia, schizoaffective disorder, borderline personality disorder, and unipolar affective disorder. Archives of General Psychiatry 45:353–360, 1988
 
Pages KP, Russo JE, Wingerson DK, et al: Predictors and outcomes of discharge against medical advice from the psychiatric units of a general hospital. Psychiatric Services 49:1187–1192, 1998
 
Judd LL, Akiskal HS, Schettler PJ, Endicott J, et al: The long-term natural history of the weekly symptomatic status of bipolar disorder. Archives of General Psychiatry 59:530–537, 2002
 
Hilty DM, Brady KT, Hales RE: Bipolar disorder in adults: a review of recent literature. Psychiatric Services 50:201–213, 1999
 
Quanbeck C, Frye M, Altshuler L: Mania and the law in California: understanding the criminalization of the mentally ill. American Journal of Psychiatry 160:1245–1250, 2003
 
Hosmer DW, Lemeshow S: Applied Logistic Regression. New York, Wiley, 2000
 
Dalrymple AJ, Fata M: Cross-validating factors associated with discharges against medical advice. Canadian Journal of Psychiatry 38:285–289, 1993
 
Sajatovic M, Gerhart C, Semple W: Association between mood-stabilizing medication and mental health resource use in the management of acute mania. Psychiatric Services 48:1037–1041, 1997
 
Sajatovic M, Davies M, Hrouda DR: Enhancement of treatment adherence among patients with bipolar disorder. Psychiatric Services 55:264–269, 2004
 
Targum SD, Capodanno AE, Hoffman HA, et al: An intervention to reduce the rate of hospital discharges against medical advice. American Journal of Psychiatry 239:657–659, 1982
 
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