A2 Refereed review article in a scientific journal

Clinical decision support systems in child and adolescent psychiatry: a systematic review




AuthorsKoposov R, Fossum S, Frodl T, Nytro O, Leventhal B, Sourander A, Quaglini S, Molteni M, Vaya MD, Prokosch HU, Barbarini N, Milham MP, Castellanos FX, Skokauskas N

PublisherSPRINGER

Publication year2017

JournalEuropean Child and Adolescent Psychiatry

Journal name in sourceEUROPEAN CHILD & ADOLESCENT PSYCHIATRY

Journal acronymEUR CHILD ADOLES PSY

Volume26

Issue11

First page 1309

Last page1317

Number of pages9

ISSN1018-8827

eISSN1435-165X

DOIhttps://doi.org/10.1007/s00787-017-0992-0


Abstract
Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13: 395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.



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