Predictors of Admission to Acute Inpatient Psychiatric Care Among Children Enrolled in Medicaid

Bryson, Stephanie A.; Akin, Becci A.

doi:10.1007/s10488-014-0560-6

Cited by 21 publications

(33 citation statements)

References 33 publications

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“…In line with the previous studies, patients who were hospitalized after emergency consultation had more severe psychiatric disorders. As described in other studies, we also found older age to be associated with hospitalization after emergency consultation [16,18,35].…”

Section: Discussionsupporting

confidence: 88%

Predictors of voluntary and compulsory admissions after psychiatric emergency consultation in youth

Wierdsma

Kasius

et al. 2020

Eur Child Adolesc Psychiatry

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As hospital beds are scarce, and emergency admissions to a psychiatric ward are major life-events for children and adolescents, it is essential to have insight into the decision-making process that leads to them. To identify potentially modifiable factors, we, therefore, studied the contextual and clinical characteristics associated with the voluntary and compulsory emergency admission of minors. We used registry data (2008-2017) on 1194 outpatient emergencies involving children aged 6-18 who had been referred to the mobile psychiatric emergency service in two city areas in The Netherlands. Demographic and contextual factors were collected, as well as clinical characteristics including diagnoses, psychiatric history, Global Assessment of Functioning (GAF), and the Severity of Psychiatric Illness (SPI) scale. Logistic regression analyses were used to identify factors that predict voluntary or compulsory admission. Of 1194 consultations, 227 (19.0%) resulted in an admission, with 137 patients (11.5%) being admitted voluntarily and 90 (7.5%) compulsorily. Independently of legal status, the following characteristics were associated with admission: severity of psychiatric symptoms, consultation outside the patient's home, and high levels of family disruption. Relative to voluntary admission, compulsory admission was associated with more severe psychiatric problems, higher suicide risk, and prior emergency compulsory admission. Two potentially modifiable factors were associated with psychiatric emergency admission: the place where patients were seen for consultation, and the presence of family problems. Psychiatric emergency admissions may be reduced if, whenever possible, minors are seen in their homes and if a system-oriented approach is used.

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Section: Discussionsupporting

confidence: 88%

Predictors of voluntary and compulsory admissions after psychiatric emergency consultation in youth

Wierdsma

Kasius

et al. 2020

Eur Child Adolesc Psychiatry

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“…Compared to prior work that utilized either large health care administrative databases or survey-only data (e.g. Bryson and Akin 2015; Lokhandwala et al 2012; Mandell 2008), the size of the sample available is relatively small, and as such it will be important to validate the current findings with larger datasets. As both the RI-CART and AIC study are progressing concurrently, validation in the future will be possible after the next phase of each study.…”

Section: Discussionmentioning

confidence: 99%

Predictors of Inpatient Psychiatric Hospitalization for Children and Adolescents with Autism Spectrum Disorder

Righi

Benevides

Mazefsky

et al. 2017

J Autism Dev Disord

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Autism Spectrum Disorder (ASD) is associated with significant healthcare expenditures and a greater utilization of psychiatric health services. High utilization may not be evenly distributed across individuals with ASD. The objective of this study was to identify individual and family characteristics that increase the risk of psychiatric hospitalization. Naturalistic study of two age- and gender-matched ASD cohorts, inpatients enrolled in the Autism Inpatient Collection (AIC) and outpatients enrolled in the Rhode Island Consortium of Autism Research and Treatment (RI-CART), revealed a number of factors associated with hospitalization. Multiple logistic regression analyses revealed that adaptive functioning, ASD symptom severity, primary caregiver's marital status, the presence of mood disorders, and the presence of sleep problems independently increased the risk of psychiatric hospitalization.

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“…Previous research examining predictors of PRTF entry using Medicaid reimbursement data showed that clinical factors were strong predictors of hospitalization. 7 Youths with mood, disruptive and psychotic disorder diagnoses, major depression, affective psychoses, and conduct disorders were commonly treated in PRTF. 2,7 Other predictors of acute admission included prior hospitalization, receipt of two or more concurrent psychotropic medications, older age, and urban residence.…”

Section: Introductionmentioning

confidence: 99%

“…7 Youths with mood, disruptive and psychotic disorder diagnoses, major depression, affective psychoses, and conduct disorders were commonly treated in PRTF. 2,7 Other predictors of acute admission included prior hospitalization, receipt of two or more concurrent psychotropic medications, older age, and urban residence. 7 A study examining predictors of PRTF entry among children involved with the child welfare system (CWS) found that trauma-related conditions, antipsychotic medication prescriptions, and entry into lower levels of out-of-home care were associated with PRTF entry, thus supporting the view that youth are admitted to PRTFs largely due to clinical need.…”

Section: Introductionmentioning

confidence: 99%

Predictive Modelling of Service Pathways to Admission in Psychiatric Residential Treatment Facilities

Vsevolozhskaya

Turner

Schnimshock

et al. 2022

Preprint

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Objective: To develop and test predictive models of admissions to a psychiatric residential treatment facility (PRTF) in transitional age youth using routinely collected health insurance claims and enrollment data. Data Sources: We used outpatient service and pharmaceutical claims from Medicaid beneficiaries aged 6- to 21-years old in Kentucky for the years 2010-2017. Study Design: We assessed over 1,250 predictors (derived from Medicaid claims data) prior to the first PRTF admission. An ensemble machine learning (ML) algorithm based on logistic regression models fitted to a random subsample of the original data was used to predict pathways to the first PRTF admission. Discrimination performance of the ML ensemble was evaluated by comparing predictions to actual outcomes and calculating area under the curve (AUC), accuracy, sensitivity, and specificity. Additionally, a multivariate logistic regression model was fit to investigate the contribution of the continuity of mental health care after the initial PRTF admission on the risk of readmission. Data Collection/Extraction Methods: We identified N=519,011 unique children and youth with at least one outpatient service or pharmaceutical claim during our study period (January 1, 2010 through December 31, 2017). Principal Findings: Fewer than 0.5% of children and youth in Kentucky had an episode of PRTF admission. Despite a very low prevalence of PRTF admission, classification accuracy of the ML ensemble for identifying PRTF youth achieved over 90% accuracy (AUC = 0.96). Factors associated with the initial PRTF admission were having been prescribed anti-psychotic and anti-manic medications, and receiving outpatient psychiatric care. Within six months after the initial PRTF discharge, there was a surprising drop in service utilization with a large proportion of youth not appearing to receive any follow-up care. Conclusions: Despite the fact that admission into a PRTF was a relatively rare event, our findings suggest that it is a predictable event among youth with identified mental health conditions who are receiving care in the community.

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Predictors of Admission to Acute Inpatient Psychiatric Care Among Children Enrolled in Medicaid

Cited by 21 publications

References 33 publications

Predictors of voluntary and compulsory admissions after psychiatric emergency consultation in youth

Predictors of voluntary and compulsory admissions after psychiatric emergency consultation in youth

Predictors of Inpatient Psychiatric Hospitalization for Children and Adolescents with Autism Spectrum Disorder

Predictive Modelling of Service Pathways to Admission in Psychiatric Residential Treatment Facilities

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