In many countries, the managed healthcare model has sparked concern about length of stay (LOS) in acute psychiatric hospitals relative to cost. Against strong forces aimed to reducing inpatient LOS to control psychiatric treatment costs, mental health care providers are challenged to expedite discharges while simultaneously providing optimal care. This conundrum is even more pronounced when carrying for patients with severe mental illness who do not adhere to treatment plans due to a number of reasons related to patient education, side effects, access, and outpatient support. Repeated noncompliance can lead to psychiatric breaks and recurrent return to inpatient care, adding to LOS and/or costs [1-4].

Several studies have explored patient and illness-related factors that contribute to LOS in mental health facilities. A Korean study found that male patients with schizophrenia stayed longer in psychiatric inpatient hospitals than their female counterparts [5]. Other sociodemographic variables including age, marital status, education, employment, and distance between patients' residence and hospital have also been associated with LOS [6-14]. Clinical factors such as a primary diagnosis of schizophrenia and a greater number of previous admissions predicted longer LOS [5-10]. Studies have reported that the presence of substance use disorder is related to shorter LOS, while psychotic or affective disorders are associated with longer LOS [6,7,10]. Other studies, however, suggest that psychopathological symptoms at admission only minimally explain length of inpatient stay [11,12]. On the contrary, complex medical comorbidity has been cited as a contributing factor to prolonged LOS among patients with mental illness. For example, when comorbidity was a focus of care during hospitalization, LOS was prolonged on average by more than 3 days [14]. Moreover, medical comorbidity was associated with a >10% increase in psychiatric symptoms and functional impairment at discharge, even after adjusting for clinical status at admission [14].

Some studies utilized a comprehensive set of static vs. dynamic or external vs. internal factors to better understand the mechanism of LOS [5-7,15-22]. Factors external to patients or providers such as insurance coverage, reimbursement policies, and institutional characteristics have been shown to influence LOS. Provider-level factors, regional characteristics, hospital type, service-level factors, and case-mix were also associated with variations in length of hospitalization [15-22]. An Australian study by Zhang et al. asserted that LOS at an acute psychiatric inpatient unit can be predicted using a multifactorial approach; in particular, behavioral manifestations of illness and lack of social support structures are critical. They also claimed that good clinical practice did not necessarily translate to shorter LOS, where it is not readily modifiable; thus, raising a question about the validity of using rate of readmission as an outcome or quality metric of psychiatric inpatient care, which is often considered together with LOS in health policy [21].

Research on inpatient psychiatric LOS can be further complicated by the inter-relationships between psychopathological, psychosocial, economic, and legal factors [11,23-26]. Although LOS in acute psychiatric hospitals has been extensively studied in terms of characterization, association, and prediction, few studies investigated the potential role of court-mandated interventions or legal factors, including assisted outpatient treatment (AOT), medication over objection (MOO), and retention for court. AOT is indicated for individuals with severe mental illness who meet strict legal criteria, e.g., patients with a history of medication noncompliance, violence, arrest, or two previous psychiatric hospitalizations [6,12,24-26]. Particularly as the most directly relevant and comparable study, Russ and John reported that patients who underwent court-ordered MOO had a longer average LOS that was often accompanied by additional complications throughout medical care and after discharge [24]. Their study comprised 351 patients in 3 groups of MOO, comparison, and control, wherein the principal outcome measures were successful linkage after discharge, readmission within six months of discharge, and transfer to a state hospital, while LOS was described secondarily or exploratorily, without further analyses.

In the current study, we were primarily interested in whether court-ordered interventions or legal procedures are associated with longer LOS adjusting for sociodemographic and clinical factors, with an examination of the relative magnitude of the associations and how much longer.

LOS and readmission rates in inpatient medical and psychiatric facilities have been studied for a few decades in the context of healthcare quality and policy, health outcomes, and services research. Given the current political and economic climate, there is even greater pressure to understand the causes and to contain costs [1-4]. Ensuring that patients with mental illness receive appropriate care is a particular challenge in the context of cost-benefit and efficiency, particularly since LOS is an important consideration for a variety of stakeholders: providers, hospital administrators, healthcare systems, government agencies, insurers, employers, patients, and families. Identifying factors associated with longer or prolonged LOS may help guide decisions made at time of admission, during inpatient care, and upon discharge.

Our study analyzed factors associated with LOS among 521 psychiatric inpatients. Longer LOS and legal procedures served as binary dependent and independent variables of primary interest. In contrast, most previous studies focused on patient-related factors including sociodemographic and clinical factors [5-22], hospital or regional characteristics [6,15-17,21], or provider- or service-related factors [18-22], less on legal factors. For example, some studies included legal status as a predictor of LOS but did not show the actual day information [6,21]; specifically, Compton et al. reviewed legal status at admission and at discharge, not court-ordered treatment. Zhang et al. included legal status, and it can be other than court-ordered treatments. Sood et al. evaluated characteristics that describe patients who are readmitted to an inpatient psychiatric hospital within one year of having their initial court order for treatment dropped with no subsequent mandated treatment; they reported that readmitted patients and a control group had 7.4 vs. 6.3 days, respectively, in rehospitalization for patients following release from courtordered evaluation [26]. Thus, these previous studies emphasized topics different from the court-ordered treatment.

In contrast, Russ and John can be viewed more directly relevant to the current study [24]. Their and our findings are qualitatively similar, but these two studies were based on different study designs with somewhat different focuses. LOS was studied for exploratory analyses with summary statistics only in Russ and John; they reported a mean LOS of 82 days among 130 patients with the MOO status vs. 50 days in a comparison group of 89 patients who transiently refused medication vs. 29 days in a control group of 132 patients who agreed to treatment [24]. To compare, our study performed this comparison as a prespecified primary hypothesis with a more precise estimation of LOS and associational measures with multi-variable adjustment. Then we found that older age, being unmarried, of non-Hispanic ethnicity, at risk of violence, a diagnosis of schizophrenia, and court involvement showed longer LOS in the final adjusted regression models, with broader court involvement demonstrating the most pronounced association.

Based on our more definitive or confirmatory study (after an earlier, initial report by Russ and John), the psychiatry literature and communities may consider court-ordered psychiatric intervention or other legal procedures as a key factor in hospital LOS estimation or prediction. Providers, administrators, and discharge planners might use it to inform treatment schedule, predict LOS, or build in efforts to reduce readmission and LOS in this high-risk population, who are often noncompliant with medication after discharge, refractory to treatment, or out of touch with the healthcare system. Also, legal variables may be placed in a prominent place in the “variable importance” literature on psychiatric LOS, e.g., top 3 or 10 predictors [6,21].

Some limitations of this study should be noted. First, this study was based on a retrospective chart review with well-known inherent limitations. Only variables that were recorded and available could be utilized; we had no control over incomplete or error-prone data, such as occurs in self-reported information already recorded. Although we used group consensus for data retrieval and verification, we did not formally assess consistency among the data abstractions or inter-rater reliability in our low budget study; yet we followed similar approaches used in [28]. We also could not access readmission data from facilities other than our medical center. Second, data on disease severity, age of onset of psychiatric illness, level of family or social support, living situation, and cultural characteristics were not available, but could be potential confounders or mediators. We were also unable to study clinician-level factors either. Third, as a single site study in one country, it could have limited generalizability and we could not study hospital or institutional characteristics or differences in different hospital or legal practices. Future studies may aim to answer an important question that carries policy or practice implications could be whether discharge disposition (referral to state hospital, nursing home, rehabilitation, or group home) leads to shorter hospital stays for those who await an opening while in psychiatric hospitals. Finally, our data are relatively old, with possible limitations to current clinical practice, although we are not aware of notable practice or policy changes directly relevant to our research for the last five years. However, we would be interested in the potential impacts of the Affordable Care Act and COVID-19 on psychiatric hospital system as future research.

Our study has some strengths. We included multi-year data from a large urban medical center that represents a diverse population, including 15% Asians. Also, we were able to study and document data less commonly reported in the literature, such as type of court-mandated intervention. Information pertaining to court status entailed authors’ careful reading of legal documentation and crosschecking it with inpatient hospital records, along with ensuing group discussion. Additionally, our study's relatively large sample size of its kind based on a systematic sampling may provide a reasonable estimate of the prevalence of key variables; e.g., 11% presence of court involvement; roughly 50%/20% patients with longer than 14/30 days in hospital; and 6% readmission, that case-control or convenient samples used in previous studies may not offer readily.

We found that variables reflecting court-mandated psychiatric interventions or legal procedures such as AOT, MOO, and retention showed a strong association with longer psychiatric hospital LOS relative to sociodemographic and clinical factors, even after multi-variable adjustment. Patients with legal procedure had substantially longer LOS (more than 3 times by mean or median), compared to those without. These factors may not be routinely considered in the general LOS research and current clinical practice. For example, if mental health clinicians figure out that their patients need legal procedure when they are admitted, they may apply AOT or proceed MOO right away instead of waiting for patients to take medications or wasting time. That way, patients may not need to stay long by waiting for court order during inpatient hospitalization; early recognition and intervention may prevent longer stay. Legal procedures may be emphasized in psychiatric settings as a possible aid or a key factor in inpatient and community care, toward enhanced monitoring, surveillance and support services in this high-risk group.