Case identification of mental health and related problems in children and young people using the New Zealand Integrated Data Infrastructure.

Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE

Original Publication: London : BioMed Central, [2001-

Databases, Factual* ; Mental Health*; Data Collection/*methods ; Mental Disorders/*diagnosis; Adolescent ; Adult ; Child ; Child, Preschool ; Female ; Humans ; Infant ; Infant, Newborn ; Male ; Mental Disorders/epidemiology ; New Zealand ; Prevalence ; Young Adult

Background: In a novel endeavour we aimed to develop a clinically relevant case identification method for use in research about the mental health of children and young people in New Zealand using the Integrated Data Infrastructure (IDI). The IDI is a linked individual-level database containing New Zealand government and survey microdata.
Methods: We drew on diagnostic and pharmaceutical information contained within five secondary care service use and medication dispensing datasets to identify probable cases of mental health and related problems. A systematic classification and refinement of codes, including restrictions by age, was undertaken to assign cases into 13 different mental health problem categories. This process was carried out by a panel of eight specialists covering a diverse range of mental health disciplines (a clinical psychologist, four child and adolescent psychiatrists and three academic researchers in child and adolescent mental health). The case identification method was applied to the New Zealand youth estimated resident population for the 2014/15 fiscal year.
Results: Over 82,000 unique individuals aged 0-24 with at least one specified mental health or related problem were identified using the case identification method for the 2014/15 fiscal year. The most prevalent mental health problem subgroups were emotional problems (31,266 individuals), substance problems (16,314), and disruptive behaviours (13,758). Overall, the pharmaceutical collection was the largest source of case identification data (59,862).
Conclusion: This study demonstrates the value of utilising IDI data for mental health research. Although the method is yet to be fully validated, it moves beyond incidence rates based on single data sources, and provides directions for future use, including further linkage of data to the IDI.

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Keywords: Administrative data; Big data; Case identification; Integrated data infrastructure; Mental health

Date Created: 20200229 Date Completed: 20200918 Latest Revision: 20200918

20221213

PMC7045433

10.1186/s12911-020-1057-8

32106861