Predicting Psychiatric Rehospitalization in Adolescents

Joyce, Victoria W.; King, Christopher D.; Nash, Carol C.; Lebois, Lauren A. M.; Ressler, Kerry J.; Buonopane, Ralph

doi:10.1007/s10488-019-00982-7

Cited by 15 publications

(13 citation statements)

References 31 publications

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“…This misclassification of the AD-PDR model is likely related to the patients admitted for unclear admitting diagnosis (e.g., unspecified fever and abdominal pain), as their primary diagnosis usually (53.2% reported in our study) changed after additional clinical tests. Besides, predicting readmission for children with unspecified mental health disorders is challenging due to the unpredictable nature of the episodes [48].…”

Section: Discussionmentioning

confidence: 99%

Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model

Symum

Zayas‐Castro

2021

Healthcare

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The timing of 30-day pediatric readmissions is skewed with approximately 40% of the incidents occurring within the first week of hospital discharges. The skewed readmission time distribution coupled with delay in health information exchange among healthcare providers might offer a limited time to devise a comprehensive intervention plan. However, pediatric readmission studies are thus far limited to the development of the prediction model after hospital discharges. In this study, we proposed a novel pediatric readmission prediction model at the time of hospital admission which can improve the high-risk patient selection process. We also compared proposed models with the standard at-discharge readmission prediction model. Using the Hospital Cost and Utilization Project database, this prognostic study included pediatric hospital discharges in Florida from January 2016 through September 2017. Four machine learning algorithms—logistic regression with backward stepwise selection, decision tree, Support Vector machines (SVM) with the polynomial kernel, and Gradient Boosting—were developed for at-admission and at-discharge models using a recursive feature elimination technique with a repeated cross-validation process. The performance of the at-admission and at-discharge model was measured by the area under the curve. The performance of the at-admission model was comparable with the at-discharge model for all four algorithms. SVM with Polynomial Kernel algorithms outperformed all other algorithms for at-admission and at-discharge models. Important features associated with increased readmission risk varied widely across the type of prediction model and were mostly related to patients’ demographics, social determinates, clinical factors, and hospital characteristics. Proposed at-admission readmission risk decision support model could help hospitals and providers with additional time for intervention planning, particularly for those targeting social determinants of children’s overall health.

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Section: Discussionmentioning

confidence: 99%

Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model

Symum

Zayas‐Castro

2021

Healthcare

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“…There is also the possibility that having a 7-or 30-day follow-up outpatient mental health visit leads to increased recognition of a crisis and thus increases the risk of ED use or rehospitalization. A recent study by Joyce et al 21 revealed that a lack of treatment alliance with a mental health provider was associated with decreased psychiatric rehospitalization after discharge; the authors suggest as an explanation that outpatient care leads to increased recognition of emotional dysregulation and, hence, to appropriate referrals to ED or inpatient care.…”

Section: Discussionmentioning

confidence: 99%

ED Visits and Readmissions After Follow-up for Mental Health Hospitalization

et al. 2020

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OBJECTIVES: A national quality measure in the Child Core Set is used to assess whether pediatric patients hospitalized for a mental illness receive timely follow-up care. In this study, we examine the relationship between adherence to the quality measure and repeat use of the emergency department (ED) or repeat hospitalization for a primary mental health condition. METHODS:We used the Truven MarketScan Medicaid Database 2015-2016, identifying hospitalizations with a primary diagnosis of depression, bipolar disorder, psychosis, or anxiety for patients aged 6 to 17 years. Primary predictors were outpatient follow-up visits within 7 and 30 days. The primary outcome was time to subsequent mental health-related ED visit or hospitalization. We conducted bivariate and multivariate analyses using Cox proportional hazard models to assess relationships between predictors and outcome.RESULTS: Of 22 844 hospitalizations, 62.0% had 7-day follow-up, and 82.3% had 30-day followup. Subsequent acute use was common, with 22.4% having an ED or hospital admission within 30 days and 54.8% within 6 months. Decreased likelihood of follow-up was associated with non-Hispanic or non-Latino black race and/or ethnicity, fee-for-service insurance, having no comorbidities, discharge from a medical or surgical unit, and suicide attempt. Timely outpatient follow-up was associated with increased subsequent acute care use (hazard ratio [95% confidence interval]: 7 days: 1.20 [1.16-1.25]; 30 days: 1.31 [1.25-1.37]). These associations remained after adjusting for severity indicators.CONCLUSIONS: Although more than half of patients received follow-up within 7 days, variations across patient population suggest that care improvements are needed. The increased hazard of subsequent use indicates the complexity of treating these patients and points to potential opportunities to intervene at follow-up visits.WHAT'S KNOWN ON THIS SUBJECT: A nationally endorsed pediatric quality measure is used to assess rates of timely followup for patients hospitalized for a mental health diagnosis. Rates range from 48% to 67%, but little is known about variations by patient characteristics or about the relationship between followup and a subsequent psychiatric crisis.

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“…Justamente, observou-se que, na anamnese, são registrados aspectos estigmatizantes sobre a pessoa na relação com o corpo social, fundamentando a internação; do que segue como conclusão as condições que a justificam, um "risco para si e para outros" -achado esse similar aos de Barker et al 7 e Joyce et al 8 . Note-se que, a sua maneira, as crianças e os adolescentes compreendiam essas questões, atribuindo como motivo de internação situações entendidas como desviantes, que iam de brigar, cometer infrações e usar drogas, até desrespeitar alguém, não obedecer aos pais, ir ao baile funk e fazer "rolês".…”

Section: Discussão Curto-circuito E O Aval Da Ciênciaunclassified

“…Já Barker et al 7 identificaram que 82,6% dos jovens internados eram de baixa classe socioeconômica, que 35,7% estavam fora da escola e que a causa mais frequente de internação psiquiátrica era "risco para si e para outros". Joyce et al 8 identificaram que "risco para si" e "risco para outros" era o mais frequente motivo de internação.…”

Section: Introductionunclassified

Motivos e mecanismos de internação de crianças e adolescentes em hospital psiquiátrico: o circuito do controle

Braga

d’Oliveira

2022

Cad. Saúde Pública

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Os avanços da reforma psiquiátrica incluem a implantação de serviços de saúde mental substitutivos à lógica asilar. Porém, internações em hospitais psiquiátricos, inclusive de crianças e adolescentes, continuam ocorrendo. Esse estudo buscou compreender os motivos de internação em um hospital psiquiátrico a partir da perspectiva da instituição e das crianças e adolescentes internados. Trata-se de pesquisa qualitativa, de abordagem hermenêutico-dialética, tendo sido feita a leitura de documentos institucionais, entrevistas abertas com oito adolescentes e observação participante. Os resultados indicaram que o motivo principal alegado pelo hospital psiquiátrico para internação foi nomeado como “agressividade”, justificada pelo “risco para si e para outros”, enquanto, para as crianças e os adolescentes, os motivos de internação eram múltiplos, incluindo uso de drogas, pequenas brigas e infrações. A análise indicou que os mecanismos para a internação pelo hospital psiquiátrico envolvem, durante a anamnese, uma leitura sobre o outro que o define como desviante de normas sociais e a posterior atribuição de um diagnóstico, avalizando a internação psiquiátrica. Também indicou que a sustentação e continuidade de internações psiquiátricas ocorrem em um circuito do controle operado entre diferentes instituições para tutela dos desviantes. Este estudo evidencia que, para evitar internações em hospitais psiquiátricos, além do fechamento destes, é preciso superar o paradigma psiquiátrico, sendo, para isso, necessárias as práticas de desinstitucionalização e na perspectiva da atenção psicossocial nos serviços de saúde mental abertos, territoriais e substitutivos.

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Predicting Psychiatric Rehospitalization in Adolescents

Cited by 15 publications

References 31 publications

Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model

Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model

ED Visits and Readmissions After Follow-up for Mental Health Hospitalization

Motivos e mecanismos de internação de crianças e adolescentes em hospital psiquiátrico: o circuito do controle

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