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ScienceDirect Comprehensive Psychiatry 55 (2014) 681 – 687 www.elsevier.com/locate/comppsych

Factors associated with length of psychiatric hospitalization Grace A. Masters⁎, Ross J. Baldessarini, Dost Öngür, Franca Centorrino Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Schizophrenia and Bipolar Disorders Program and International Consortium for Bipolar & Psychotic Disorders Research, McLean Hospital, Belmont, MA, USA

Abstract Objective: Criteria for psychiatric hospitalization have undergone marked changes. Efforts to limit length-of-hospitalization risk greater morbidity at discharge and increased needs for appropriate aftercare. Accordingly, we evaluated factors associated with length of psychiatric hospitalization and aftercare-types. Methods: We reviewed medical records of 589 patients with major psychiatric disorders hospitalized in a university-affiliated, not-for-profit psychiatric hospital to identify characteristics associated with length of hospitalization, types of aftercare and insurance coverage, using standard bivariate and multivariate analytical methods. Results: Notable factors associated with longer hospitalization included: more highly supervised aftercare, diagnosis of schizophrenia or schizoaffective N affective disorders, longer illnesses, higher antipsychotic doses and more complex drug-treatments at discharge, lower GAF functional status, unemployment, being unmarried, as well as public vs. private insurance. Multivariate modeling sustained association of longer hospitalization with higher antipsychotic doses, more structured aftercare, public insurance, lower GAF scores, and diagnoses of chronic psychotic disorders. Structured aftercare was associated with younger age, fewer years ill, and private insurance, but varied little by diagnosis and was unrelated to ethnicity. Public insurance was associated notably with being unemployed, unmarried, less functional, having a chronic psychotic disorder for more years, and lack of structured aftercare. Conclusions: Illness severity and functional impairment may modulate efforts to limit psychiatric hospitalization. Higher-level aftercare was associated with illness and disability factors as well as with private insurance; public insurance was associated with dysfunction, unemployment and chronic illness, as well as longer hospitalization. © 2014 Elsevier Inc. All rights reserved.

1. Introduction Major changes have evolved in criteria for psychiatric hospitalization and its duration in the past several decades. Currently, psychiatric hospitalization is far shorter than formerly, and tends to be indicated largely to provide a safe environment for persons considered to be suicidal, homicidal,

Supported by: A grant from the Bruce J. Anderson Foundation and by the McLean Private Donors Research Fund (to RJB), and by departmental funds of the Psychotic Disorders Division of McLean Hospital (to DO). Disclosures: Dr. Öngür holds a research award from Rules Based Medicine, Inc. Dr. Centorrino is a member of an Advisory Board for Teva Pharmaceuticals. No other author or any immediate family member has financial relationships with commercial organizations that might present potential conflicts of interest regarding the material reported. ⁎ Corresponding author at: Schizophrenia and Bipolar Disorders Program, McLean Hospital, Mailstop 209, 115 Mill Street, Belmont, MA 02478-9106, USA. Tel.: +1 617 855 2917; fax: +1 617 855 3816. E-mail address: [email protected] (G.A. Masters). 0010-440X/$ – see front matter © 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.comppsych.2013.11.004

or otherwise dangerous [1–3]. The shift toward brief, crisisoriented hospitalizations probably has been encouraged by positive expectations arising from the deinstitutionalization movement of the 1960s and 1970s, as well as optimistic expectations of the effects of modern treatment based heavily on psychotropic drugs [1,4]. However, major motivations for short psychiatric hospitalizations include efforts to limit expenditures since hospitalization and its duration are major contributors to costs of psychiatric care. Psychiatric hospitalization also is largely controllable by administrative and economic means associated with the growth of managed care and the nature of medical insurance benefits for psychiatric disorders [5–9]. Efforts to limit access to hospital-level care and its duration appear to be particularly stringent for mental illnesses [7,10]. Heavily economically driven and administratively enforced reductions in access and duration of psychiatric hospitalization have become increasingly feasible and widely implemented, but such changes leave many questions


G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687

concerning the clinical value and risks of hospital-level care [11]. These relatively recent developments may risk compromising the quality of hospital care and premature discharge of patients with severe illnesses who remain clinically unstable. Such risks are of growing concern as evidence emerges that available treatments for major mental disorders are more limited in effectiveness than is often believed [4,12–14]. Despite the internationally widespread acceptance of care-management to limit psychiatric hospitalization, there is remarkably little research with which to evaluate the potential benefits, limitations, and risks of such changes [14–16]. Available evidence seems to be mixed and inconclusive about the effects of shorter length-of-stay on clinical and functional outcomes and readmission rates [13,17]. Furthermore, length-of-stay is not necessarily even predicted by severity of symptoms on admission [19]. In our own experience at a university-affiliated, not-forprofit, psychiatric hospital during the 1990s, average lengthof-stay for psychotic and major affective disorders declined from 6–8 to 1–2 weeks, where it has remained, largely reflecting administrative and economic considerations and without detectable changes in diagnostic-mix or in standardized ratings of illness-severity [4,18]. During years of declining length-of-hospitalization, we found marked annual changes in average, research-based, systematic ratings of symptomatic morbidity. These changes involved decreases from 40%–50%, to only 10%–20% average levels of symptomatic improvement with shorter hospitalization, as well as 20%–30% increases in rates of readmission within 30 days of discharge [4]. Of note, however, duration of hospitalization appeared to have no detectable residual effect on clinical status based on systematic, prospective assessment at six months post-hospitalization or later—possibly owing in part to increasing reliance on structured, intensive aftercare placements based on clinical need as length-ofhospitalization declined [18]. This experience led us to question to what degree, and based on what factors, length of psychiatric hospitalization may be modified by clinical considerations and other factors. The present study addressed our hypothesis that clinical factors would be significant determinants of days in hospital, within limits imposed by such administrative factors as type of insurance benefits and the nature of planned, posthospital, aftercare. We also considered factors associated with the level of aftercare as well as with the types of medical insurance that supported patient care.

2. Methods We analyzed medical records of 589 patients (every-other admission, consecutively) aged ≥18 years, hospitalized predominantly for psychotic or severe mood disorders in May 2010–April 2011. Patients studied were admitted to units specialized for evaluation and short-term care of psychotic and major affective disorder patients. The McLean

Hospital Institutional Review Board (IRB) approved this analysis and anonymous reporting of aggregate findings. We recorded salient demographic and clinical information, including discharge DSM-IV-TR diagnoses [20] made by experienced clinical–academic psychiatrists, estimated age at illness-onset and years of illness, functional ratings (Global Assessment of Functioning [GAF] [21]) at admission and discharge, days of index hospitalization, all psychotropic drugs and doses given during hospitalization, and health insurance provider (public [Medicare and Medicaid] vs. private [commercial]). Discharge plans and level of aftercare were grouped as: [a] higher-level or more structured aftercare (transfer to another hospital, partial hospital, or group home), or [b] less structured aftercare (outpatient follow-up or no specific plan). Home visits from clinical groups such as PACT teams or VNA programs were not well documented and thus not included, though likely they made up a small portion of aftercare. Psychotropic drug treatments considered specifically were: antipsychotics and FDA-approved or putative moodstabilizing agents, as well as use of any antidepressant or benzodiazepine. Antipsychotic drug doses were converted to estimated total chlorpromazine-equivalent (CPZ-eq) mg/day, and mood-stabilizer doses to approximate lithium carbonateequivalent (Li-eq) mg/day [4,22,23]. Data are presented as mean ± standard deviation (SD), median with interquartile range (IQR), or percentages. Preliminary bivariate analyses used ANOVA (t) for continuous data, and contingency tables (χ 2) for categorical measures. Associations of individual continuous variables were tested with non-parametric, Spearman rankcorrelations (rs). Factors found preliminarily to be associated, at least tentatively, with length-of-hospitalization (at p b 0.10) were then entered, stepwise, into multivariate, linear regression modeling to obtain slope functions (β), or, with other categorical outcomes, into multivariate, logistic regression models to obtain Odds Ratios (OR), all with their 95% confidence intervals (CI). Statistical significance was deferred to the multivariate models, and considered significant at two-tailed p b 0.05. Statistical analyses used commercial software (Statview®, SAS Institute, Cary, NC; Stata®, StataCorp., College Station, TX). 3. Results 3.1. Subject characteristics The 589 study-subjects included 351 men and 238 women, 81.8% were Caucasian, of average age 35.7 ± 13.0 (18–68) years, with 9.55 ± 10.7 years of psychiatric illness prior to the index hospitalization (Table 1). Only 14.9% were married and 36.8% were employed prior to the index hospitalization. Admission GAF scores averaged 28.6 ± 5.49; 39.8% had attempted suicide, and 29.5% also had been psychiatrically hospitalized within the preceding 12 months at the study hospital. Discharge diagnoses ranked

G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687 Table 1 Characteristics of 589 hospitalized patients. Characteristic


Men (%) Race/Ethnicity (%) Caucasian Non-Caucasian Completed high school (%) Marital status (%) Single Married or partnered Divorced Widowed Employment status (%) Unemployed Employed Retired Suicide attempt (lifetime [%]) Have primary care physician (%) Ages (years) Current Approximate at-onset Years of illness Hospitalized within 12 months (%) Index discharge diagnosis (%) Bipolar disorder Schizoaffective Other affective Other psychoses Schizophrenia Major depression Current substance abuse Axis II disorders ≥2 Psychiatric diagnoses Medical illness Index admission GAF score Length of index hospitalization (days) Mean ± SD Median [IQR) Range Psychotropics at discharge (%) None 1 ≥2 Antipsychotics at discharge (%) None 1 ≥2 Other drugs given at index discharge (%) Mood-stabilizers Antidepressants Sedative-hypnotics Discharge drug dose (mg/day) Antipsychotics (CPZ-eq) Mood-stabilizers (Li2CO3-eq) Type of aftercare (%) No specific plan Outpatient Partial-hospital Residential Program Group home Transfer to another hospital unit Transfer to State Hospital

59.6 81.8 18.2 90.6 70.5 14.9 13.6 1.02 62.2 36.8 1.03 39.8 66.6 35.7 ± 13.0 24.7 ± 9.53 9.55 ± 10.7 29.5 29.4 18.3 14.9 12.9 12.6 11.9 35.8 8.32 51.3 63.2 28.6 ± 5.49 13.2 ± 13.3 10 [6–15] 1–132 2.72 16.0 81.3 17.2 57.8 25.0 48.9 38.5 43.3 305 ± 303 533 ± 734 2.04 47.7 35.0 7.81 3.06 2.89 1.53


by prevalence as: bipolar disorder, schizoaffective disorder, other affective disorders (not meeting full DSM criteria for bipolar or major depressive disorder, or severe anxiety disorders), miscellaneous psychoses (mostly schizophreniform, acute, or unspecified), schizophrenia, and major depression. Of the 589 subjects, 35.8% met DSM-IV criteria for a current substance-use disorder, and 8.32% for an Axis II personality disorder. On average, the index hospitalization lasted 13.2 ± 13.3 (median: 10 days; IQR: 6–15, range: 1–132 days; 94.1% were ≤30 days). At discharge, 97.3% of subjects were prescribed at least one psychotropic drug and 81.3% received two or more; the mean daily (CPZ-eq) dose of antipsychotics at discharge was 305 ± 303 mg, and of mood-stabilizers (Li-eq), 533 ± 734 mg. Post-discharge aftercare ranged from transfer to another hospital (4.41%), a supervised facility (45.8%) or to outpatient care (47.7%), or to no specific plan (2.01%). 3.2. Factors associated with length-of-stay We first carried out preliminary, bivariate analyses of associations of selected measures with days of index hospitalization (Table 2). There were tentative associations of days-in-hospital with 12 factors, ranking: (a) more highly supervised or structured aftercare; (b) diagnosis (schizophrenia N schizoaffective N bipolar ≥ major depressive disorder ≥ other psychoses N other affective disorders); (c) higher discharge dose of antipsychotic or mood-stabilizing drugs; (d) lower functional status (mean of admission and discharge GAF scores); (e) public more often than private insurance; (f) absence of substance-abuse; (g) two or more psychiatric diagnoses, (excluding substance-abuse); (h) being unemployed; (i) more years of illness; (j) discharged with two or more psychotropic drugs; (k) medical co-morbidity; and weakly with (l) being unmarried. Factors not related to days-in-hospital included nine other characteristics: (a) sex; (b) race or ethnicity; (c) current age or age-at-onset; (d) educational level; (e) Axis II diagnoses; (f) prior psychiatric hospitalization within the preceding year; (g) lifetime history of suicide attempt; (h) discharged with a psychotropic drug other than an antipsychotic; or (i) having a primary-care-physician. 3.3. Multivariate modeling Factors (Table 2) with at least suggestive association with length-of-index-hospitalization (p b 0.10) were then entered, stepwise, into multivariate linear regression modeling to test for independent association with days-in-hospital. Significant and independent association with hospital lengthof-stay ranked: (a) higher discharge CPZ-eq daily dose of antipsychotic drugs, (b) more structured or supervised aftercare, (c) public more than private insurance, (d) lower functional rating (GAF score), (e) diagnosis of schizophrenia or schizoaffective disorder (Table 3).


G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687

Table 2 Factors associated with length of psychiatric hospitalization. Factor Level of aftercare No specific plan Transfer to psychiatric hospital Outpatient Partial-hospital Group home Residential program Transfer to state hospital Diagnosis Schizophrenia Schizoaffective disorder Bipolar disorder Major depressive disorder Other psychoses Other affective Discharge dose Antipsychotics (CPZ-eq) Mood-stabilizers (Li-eq) Mean GAF level Insurance type Public (49.0%) Private (50.4%) Number of psychiatric diagnoses 1 2 ≥3 Substance use disorder Present (35.8%) Absent (64.2%) Employment status Unemployed (63.2%) Employed (36.8%) Duration of illness (years) Treatments at discharge One psychotropic ≥2 drugs Medical co-morbidity Present (63.2%) Absent (36.8%) Marital status (%) Single, divorced separated (85.1%) Married, widowed (14.9%)

LOS (days) Statistic [p-value] t = 8.01 [b0.0001] 5.33 6.76 11.8 12.4 15.4 15.9 78.9

± ± ± ± ± ± ±

4.50 8.25 10.3 8.46 14.7 12.8 26.9 t = 3.31 [b0.0001]

21.8 15.4 11.9 11.8 10.8 8.55

± ± ± ± ± ±

23.9 13.9 8.48 11.4 5.26 9.58

– – –

Table 3 Multivariate linear regression modeling for factors independently associated with longer index psychiatric hospitalization. Factor

Slope Function (β) [95% CI]

Higher discharge dose 0.011 [0.007 to 0.015] of antipsychotics More structured aftercare 4.06 [2.00 to 6.13] Public vs. private 2.59 [4.76 to 0.456] health insurance Lower mean GAF −0.241 [−0.448 to −0.034] functional score Schizophrenia or 2.97 [0.39 to 5.54] schizoaffective disorder

t-score p-value 5.64


3.87 2.38

b0.0001 0.018





Other factors considered in Table 2 were not significantly associated with length-of-stay in multivariate modeling.

rs = 0.402 [b0.0001] rs = 0.169 [b0.0001] rs = –0.146 [0.0004] t = 3.59 [0.0004]

15.2 ± 16.5 11.3 ± 8.80 t = 2.57 [0.002] 15.2 ± 15.8 11.4 ± 10.0 11.0 ± 10.2 t = 2.96 [0.003] 11.0 ± 9.58 14.4 ± 14.9 t = 2.90 [0.004] 14.1 ± 14.6 11.0 ± 8.32 – rs = 0.115 [0.01] t = 2.50 [0.01] 10.5 ± 10.9 13.9 ± 13.8 t = 2.35 [0.02] 14.2 ± 15.0 11.5 ± 9.44 t = 1.77 [0.06] 13.6 ± 14.0 10.9 ± 8.11

LOS = length-of-stay at index hospitalization.

3.4. Factors associated with level of aftercare As length-of-index-hospitalization was very strongly associated with the type of aftercare, we considered factors that might also be associated with this outcome measure. Significantly associated with higher levels of aftercare in preliminary bivariate comparisons (Table 4) were: (a) younger current age or age-at-onset; (b) private insurance; (c) fewer total years of illness; (d) diagnosis; and (e) longer index hospitalization. Additional factors not significantly associated with aftercare-level included: sex, race or ethnicity, marital or education status, or being employed before hospitalization; having more than one psychiatric disorder; history of suicide attempt; psychiatric hospitalization within the previous year,

admission or discharge functional rating (GAF); type, number, or dose of psychotropic agents; and having a medical diagnosis or a primary-care-physician. Logistic, multivariate modeling (not shown) found three factors to remain significantly and independently associated with higher-level aftercare, in the following rank-order by Odds Ratio (OR): (a) private insurance (OR: 1.60 [CI: 1.06– 2.42];χ2 = 4.95, p = 0.03); (b) longer index hospitalization (OR: 1.03 [CI: 1.01–1.05]; χ 2 = 8.55, p = 0.003); (c) younger onset-age (OR: 1.03 [CI: 1.01–1.05]; χ 2 = 7.30, p = 0.007); and [4] fewer years ill (OR: 1.02 [CI: 1.00–1.04]; χ 2 = 4.24, p = 0.04). 3.5. Factors associated with type of insurance Since the type of medical insurance held by a patient may reflect both long-term morbidity and various social Table 4 Factors associated with level of aftercare. Factor

Aftercare Type High

Age (years) Current At onset Insurance type (%) Public Private Years of illness Diagnosis Major depression Schizophrenia Bipolar disorder Other affective Other psychoses Schizoaffective Days of index hospitalization


Relative Statistic Risk (p-value)

31.3 ± 11.8 36.7 ± 12.9 1/1.15 23.6 ± 8.75 25.8 ± 10.2 1/1.09 42.2 56.5 1/1.34 57.8 43.5 1.33 8.27 ± 10.4 10.8 ± 11.0 1/1.31 58.6



55.3 54.3 50.0 48.6 36.1 14.4 ± 13.6

44.7 45.7 50.0 51.4 63.9 11.6 ± 10.7

1.24 1.19 1.00 1/1.06 1/1.77 1.24

t = 4.27 (b0.0001) t = 2.48 (0.01) χ2 = 11.9 (0.0006)

t = 2.57 (0.01) χ 2 = 12.6 (0.03)

t = 2.48 (0.01)

After care types: high level = hospital, partial-hospital, day-treatment, halfway house or other supervised site; low level = outpatient follow-up. Factors are in descending rank by significance of the association with high vs. low levels of aftercare.

G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687 Table 5 Factors associated with insurance types. Factor

Employed pre-admission (%) Diagnosis (%) Schizophrenia Schizoaffective Major depression Other affective Bipolar disorder Other psychoses Years of illness Suicide attempt ever (%) Medical illness Current age (years) Education ≥ high school (%) Index hospital-stay (days) ≥2 Psychotropics at discharge Level of aftercare (%) Structured Outpatient Discharge functional status (GAF) Married

Insurance Type

Relative Statistic Risk (p-value)






26.3 34.3 46.3 65.3 52.3 68.9 6.11 ± 8.38 60.8

73.7 65.7 53.7 47.7 34.7 30.1 13.6 ± 11.7 39.2

0.36 0.52 0.86 1.10 1.88 2.29 0.45




31.2 ± 12.1 97.3

40.2 ± 12.3 83.8


11.3 ± 8.80 47.1

15.2 ± 16.5 52.9

60.2 39.8 53.3 ± 8.36 18.0

44.9 55.1 51.5 ± 7.06 11.3


1.16 0.74 0.89

χ 2 = 90.2 (b0.0001) χ 2 = 55.2 (b0.0001)


being married (OR: 3.33 [CI: 1.06–6.64]; χ2 = 11.7, p = 0.0006); (d) higher-level, structured aftercare (OR: 1.88 [CI: 1.07–3.32]; χ2 = 4.80, p = 0.03); (e) fewer psychotropic drugs prescribed at discharge (OR: 1.88 [CI: 1.07–3.32; χ2 = 4.75, p = 0.03]); and (f) fewer years of illness (OR: 1.07 [CI: 1.04–1.10]; χ2 = 29.2, p b 0.0001). 4. Discussion

t = 7.88 (b0.0001) χ 2 = 21.9 (b0.0001) χ 2 = 19.3 (b0.0001) t = 8.85 (b0.0001) χ 2 = 30.1 (b0.0001) t = 3.60 (0.0004) χ 2 = 12.4 (0.0004) χ 2 = 13.6 (0.0002)

1.34 0.72 1.04

t = 2.78 (0.006)


χ 2 = 5.18 (0.02)

Factors are in descending rank by relative significance of association of public vs. private insurance with each factor.

and functional factors that might also be related to duration of hospitalization, we considered factors associated with insurance-type. Factors associated significantly with public insurance (Medicaid, Medicare) in preliminary bivariate comparisons (Table 5) included: (a) being unemployed; (b) diagnosis of schizophrenia, schizoaffective or major depressive disorder; (c) more years since illness-onset (or being older currently); (d) lack of a history of attempted suicide; (e) medical illness; (f) older current age; (g) less education; (h) longer index hospitalization; (i) greater likelihood of receiving ≥2 psychotropic drugs at discharge; (j) less structured aftercare; (k) lower discharge functional rating (GAF); and (l) being unmarried. Additional factors not significantly associated with insurance-type included: sex, race or ethnicity, having more than one psychiatric diagnosis, having been hospitalized within 12 months of the index admission, and having a primary-care physician. Logistic, multivariate modeling (not shown) found six factors to remain significantly and independently associated with private insurance, in the following rank-order by OR: (a) being educated through high school or longer (OR:6.20 [CI: 2.46–15.6]; χ2 = 14.9, p = 0.0001); (b) being employed (OR: 4.75 [CI: 2.95–7.64]; χ 2 = 41.2, p b 0.0001); (c)

This study aimed to evaluate factors associated with the duration of psychiatric hospitalization, insurance type, and level of aftercare in an era of closely managed care that attempts to limit length-of-hospitalization and the costs of care. The observed length-of-index-hospitalization averaged 13.2 days (median: 10 days) among patients with a variety of relatively severe psychiatric illnesses. Despite a brief average length-of-stay, time-in-hospital ranged widely, from one day to 4.4 months (Table 1), supporting the aim of seeking to identify factors that might predict duration of hospitalization. Individual length of hospitalization was strongly associated with the level of post-discharge aftercare provided, ranging from 36.9 days when followed by further hospitalization elsewhere, to only 11.8 days for patients transferred to outpatient follow-up, and intermediate durations among those with other, structured forms of aftercare (Table 2). In addition, as might be expected, diagnosis was an important predictor of hospital length-ofstay, ranging from 21.8 days among patients diagnosed with schizophrenia to less than 12 days for those diagnosed with bipolar or major depressive disorders or other (mainly affective) conditions, and intermediate times for those with schizoaffective disorder (Table 2). The third most powerful predictor was a higher dose of antipsychotic medicine, with lesser effects of doses of moodstabilizers and of the total number of psychotropic drugs prescribed at discharge. The preceding factors evidently reflect more severe illnesses, as would be expected to influence hospitalization. Not surprisingly, lower functional status, as reflected in being unemployed and having lower GAF scores, also was associated with longer hospitalization. In addition, medical co-morbidity and being unmarried were at least weakly associated with longer stays. Another unexpected factor associated with longer hospitalization was not being diagnosed with a substance-use disorder. Substance abuse may be more likely in cases involving relatively brief admissions primarily for detoxification rather than for treatment of a primary psychiatric disorder. Notably, also, the type of medical insurance was strongly associated with length-ofstay. Patients with public insurance (mainly Medicaid or Medicare) were hospitalized an average of four days longer than the median of 10 days compared to those with private insurance (Table 2). Several previous studies also found associations of hospital length-of-stay with types of insurance available [5,6,8].


G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687

Since several factors preliminarily associated with lengthof-hospitalization (Table 2) might co-vary, we carried out multivariate, linear regression modeling for all factors with at least suggestive preliminary associations with length-ofstay. Five factors remained significantly and independently associated with longer index hospitalizations (Table 3). In descending order of strength of association, they were: (a) higher discharge dose of antipsychotics, (b) relatively highly structured aftercare, (c) public health insurance, (d) lower GAF ratings of functional status, and (e) being diagnosed with a chronic psychotic disorder (schizophrenia or schizoaffective disorder). The associations of length-ofhospitalization with severity or chronicity of illness (higher antipsychotic doses and schizophrenia-schizoaffective diagnoses) and a lower level-of-functioning (lower GAF score and unemployment) was consistent with clinical expectations [24]. Higher levels of aftercare in structured settings involved just over half of the subjects (50.2%; Table 1), indicating that many were sufficiently symptomatic at the end of hospitalization as to require further treatment at more than routine outpatient levels of intensity and supervision. Several factors were associated with such higher levels of supervised aftercare (Table 4). Particularly important were younger current (and onset) age and fewer years of illness. Younger age and shorter illness may reflect the level of acuity of illness or high risk for treatment non-adherence, but these hypotheses could not be tested adequately. Interestingly, access to aftercare was strongly associated with having private medical insurance. Major means of coping with continuing illness in the face of increasingly restricted hospitalization have been to divert patients from inpatient settings to less intensive or expensive settings such as partial-hospital, day-treatment, half-way houses, or intensively active outpatient or community programs [25–29]. Still, both the clinical and cost-effectiveness of alternatives to longer inpatient treatment, remain remarkably little tested [3,30]. Despite its evident plausibility, adherence to aftercare is typically left to the patient’s own willingness or ability to attend recommended programs, and is often negatively influenced by more symptoms. Patients who do not use aftercare are at risk of being left without care until the next psychiatric crisis. When they are brought back into care, it is often for another expensive inpatient hospitalization, and the cost could be equivalent to years of more targeted and efficient aftercare treatment. Public insurance, associated with longer length of hospitalization and less aftercare services, could indicate disability and unemployment that are often associated with severe mental illness, further complicating these issues. Furthermore, the aftercare programs that are most often supported by public insurance programs, including state hospitalization, often have long waiting lists. Considering this, both federally funded and private insurance companies should consider aftercare intervention more tailored to the severely mentally ill recently discharged

from the hospital, such as home visits by a psychiatric team, VNA services, with more supportive medication management and education for both the patient and the family that could allow the individual to be ready to “step-up” to programs such as partial hospitalization and day treatment. These may ultimately have the effect of cutting down on relapse rates and costly inpatient hospitalizations. Interpretation of the strong association of longer hospitalization with public insurance may be confounded by both clinical and social factors (Table 5) associated with ability to obtain and support private insurance [31]. These observations are consistent with other findings indicating that psychiatric hospital length-of-stay is driven heavily by economic factors, including benefits associated with particular types of insurance and their management, rather than by purely clinical considerations [32–34]. Finally, it should be acknowledged that medical comorbidity is at least weakly associated with increased length of hospitalization. This observation emphasizes the dramatic physical toll that severe mental illness also takes on these patients and the importance of incorporating preventative medical care in overall psychiatric treatment, both in and out of hospital. Limitations to this study include lack of quantitative ratings of symptomatic illness-severity and possible underreporting of co-morbid Axis II and III diagnoses, as well as sampling patients in a single institution with limited proportions of racial minorities and impoverished patients, so that the findings may not necessarily generalize to other circumstances. We also should reiterate that these findings are from psychiatric units specifically targeted at a population of severely mentally ill patients with major psychotic or mood disorders. In conclusion, we confirmed with repeated observations that current efforts to limit access to inpatient hospitalization and management of duration of psychiatric hospitalization are driven heavily by economic factors. Remarkably, there is little research to test the clinical value and later consequences of brief, managed psychiatric inpatient care. Nevertheless, the findings support the partly reassuring conclusion that flexibility in length-of-stay and the potential for use of more targeted and individualized aftercare resources can be adapted to the clinical severity of the severely mentally ill. References [1] Sharfstein SS, Dickerson FB, Oldham JM, editors. Textbook of inpatient psychiatry. Washington, DC: American Psychiatric Publishing Inc.; 2008. [2] Sharfstein SS, Dickerson FB. Hospital psychiatry for the twenty-first century. Health Aff (Millwood) 2009;28:685-8. [3] Glick ID, Sharfstein SS, Schwartz HI. Inpatient psychiatric care in the 21st century: the need for reform. Psychiatr Serv 2011;62:206-9. [4] Baldessarini RJ. Chemotherapy in psychiatry. 3rd ed. New York, NY: Springer Press; 201354-6. [5] Hendryx MS, DeRyan J. Psychiatric hospitalization characteristics associated with insurance type. Adm Policy Ment Health 1998;25: 437-48.

G.A. Masters et al. / Comprehensive Psychiatry 55 (2014) 681–687 [6] Fisher WH, Barreira PJ, Lincoln AK, Simon LJ, White AW, Roy-Bujnowski K, et al. Insurance status and length of stay for involuntarily hospitalized patients. J Behav Health Serv Res 2001;28:334-46. [7] Fleming E, Lien H, Ma CT, McGuire TG. Managed care, networks and trends in hospital care for mental health and substance abuse treatment in Massachusetts: 1994–1999. J Ment Health Policy Econ 2003;6:3-12. [8] Bodner E, Sarel A, Gillath O, Iancu I. Relationship between type of insurance, time period and length of stay in psychiatric hospitals: the Israeli case. Isr J Psychiatry Relat Sci 2010;47:284-90. [9] Hudson CG, Chafets J. Comparison of acute psychiatric care under Medicaid carve-outs, HMOs, and fee-for-service. Soc Work Public Health 2010;25:527-49. [10] Murray ME, Henriques JB. Test of mental health parity: comparisons of outcomes of hospital concurrent utilization review. J Behav Health Serv Res 2004;31:266-78. [11] Mardis R, Brownson K. Length of stay at an all-time low. Health Care Manag (Frederick) 2003;22:122-7. [12] Lieberman JA, Stroup TS, McEvoy JP, Swartz MS, Rosenheck RA, Perkins DO, et al. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med 2005;353:1209-23. [13] Baldessarini RJ, Salvatore P, Khalsa HM, Gebre-Medhin P, Imaz H, González-Pinto A, et al. Morbidity in 303 first-episode bipolar I disorder patients. Bipolar Disord 2010;12:264-70. [14] Tulloch AD, Fearon P, David AS. Length-of-stay of general psychiatric inpatients in the United States: systematic review. Adm Policy Ment Health 2011;38:155-68. [15] Goldman HH. Inpatient care in the 21st century: we need more evidence. Psychiatr Serv 2011;62:117-8. [16] Jonas DE, Mansfield AJ, Curtis P, Gilmore JH, Watson LC, Brode S, et al. Identifying priorities for patient-centered outcomes research for serious mental illness. Psychiatr Serv 2012;63:1125-30. [17] Rocca P, Mingrone C, Mongini T, Montemagni C, Pulvirenti L, Rocca G, et al. Outcome and length of stay in psychiatric hospitalization, the experience of the University Clinic of Turin. Soc Psychiatry Psychiatr Epidemiol 2010;45:603-10. [18] Tohen M, Zarate Jr CZ, Hennen Jr J, Khalsa HM, Strakowski SM, Gebre-Medhin P, et al. The McLean–Harvard First-Episode Mania Study: prediction of recovery and first recurrence. Am J Psychiatry 2003;160:2099-106. [19] Warnke I, Rössler W, Herwig U. Does psychopathology at admission predict the length of inpatient stay in psychiatry? Implications for financing psychiatric services. BMC Psychiatry 2011;11:120-9.


[20] American Psychiatric Association (APA). Diagnostic and statistical manual of mental disorders, fourth edition, text revision (DSM-IV-TR). 4th ed. Washington, DC: American Psychiatric Association; 2000. [21] Hall RC. Global assessment of functioning: modified scale. Psychosomatics 1995;36:267-75. [22] Gardner DM, Murphy AL, O’Donnell H, Centorrino F, Baldessarini RJ. International consensus study of antipsychotic dosing. Am J Psychiatry 2012;167:686-93. [23] Centorrino F, Masters GA, Talamo A, Baldessarini RJ, Öngur D. Metabolic syndrome in psychiatrically hospitalized patients treated with antipsychotics and other psychotropics. Hum Psychopharmacol 2012;27:521-6. [24] Bourgeois JA, Kremen WS, Servis ME, Wegelin JA, Hales RE. Impact of psychiatric diagnosis on length of stay in a university medical center in the managed care era. Psychosomatics 2005;46:431-9. [25] Salkever D, Domino ME, Burns BJ, Santos AB, Deci PA, Dias J, et al. Assertive community treatment for people with severe mental illness: effect on hospital use and costs. Health Serv Res 1999;34:577-601. [26] Geller JL. The last half-century of psychiatric services as reflected in psychiatric services. Psychiatr Serv 2000;51(1):41-67. [27] Smith L, Newton R. Systematic review of case management. Aust N Z J Psychiatry 2007;41:2-9. [28] Steffen S, Kosters M, Becker T, Puschner B. Discharge planning in mental health care: systematic review of the recent literature. Acta Psychiatr Scand 2009;120:1-9. [29] Lee S, Rothbard AB, Noll EL. Length of inpatient stay of persons with serious mental illness: effects of hospital and regional characteristics. Psychiatr Serv 2012;63:889-95. [30] Sheppard S, Parkes J, McClaron J, Phillips C. Discharge planning from hospital to home. Cochrane Database Syst Rev 2004;1:CD000313. [31] Smoyak SA. History, economics, and financing of mental health care: the present. J Psychosoc Nurs Ment Health Serv 2000;38:32-8. [32] Wickizer TM, Lessler D, Travis KM. Controlling inpatient psychiatric utilization through managed care. Am J Psychiatry 1996;153: 339-45. [33] Wickizer TM, Lessler D. Do treatment restrictions imposed by utilization management increase the likelihood of readmission for psychiatric patients? Med Care 1998;36:844-59. [34] Stensland M, Watson PR, Grazier KL. Examination of costs, charges, and payments for inpatient psychiatric treatment in community hospitals. Psychiatr Serv 2012;63:666-71.

Factors associated with length of psychiatric hospitalization.

Criteria for psychiatric hospitalization have undergone marked changes. Efforts to limit length-of-hospitalization risk greater morbidity at discharge...
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