Resource Intensity for Children and Youth: The Development of an Algorithm to Identify High Service Users in Children's Mental Health.
Children's mental health care plays a vital role in many social, health care, and education systems, but there is evidence that appropriate targeting strategies are needed to allocate limited mental health care resources effectively. The aim of this study was to develop and validate a methodology fo...
| Publicado en: | Health Services Insights Vol. 12 |
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| Autores principales: | , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=140939588&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 140939588 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11786329 B10H jtl: Health Services Insights issn: 11786329 maglogo: Y pubinfo: dt: 2019 vid: 12 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 140939588 140939588 140939588 10.1177/1178632919827930 140939588 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Resource Intensity for Children and Youth: The Development of an Algorithm to Identify High Service Users in Children's Mental Health. aug: au: Stewart, Shannon L Poss, Jeff W Thornley, Elizabeth Hirdes, John P affil: Western University, Faculty of Education, London, ON, Canada sug: subj: Resource Allocation Mental Health In Infancy and Childhood Human Male Female Child Adolescence Decision Support Systems, Clinical Ontario Psychometrics Reliability and Validity Descriptive Statistics Semi-Structured Interview Scales Odds Ratio Confidence Intervals Data Analysis Software Affect Disruptive Behavior Anxiety Attention Deficit Hyperactivity Disorder Autism Spectrum Disorder Child: 6-12 years Adolescent: 13-18 years Male Female ab: Children's mental health care plays a vital role in many social, health care, and education systems, but there is evidence that appropriate targeting strategies are needed to allocate limited mental health care resources effectively. The aim of this study was to develop and validate a methodology for identifying children who require access to more intense facility-based or community resources. Ontario data based on the interRAI Child and Youth Mental Health instruments were analysed to identify predictors of service complexity in children's mental health. The Resource Intensity for Children and Youth (RIChY) algorithm was a good predictor of service complexity in the derivation sample. The algorithm was validated with additional data from 61 agencies. The RIChY algorithm provides a psychometrically sound decision-support tool that may be used to inform the choices related to allocation of children's mental health resources and prioritisation of clients needing community- and facility-based resources. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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