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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2020

Open Access 01-12-2020 | Research article

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

Authors: Nicholas Bowden, Sheree Gibb, Hiran Thabrew, Jesse Kokaua, Richard Audas, Sally Merry, Barry Taylor, Sarah E Hetrick

Published in: BMC Medical Informatics and Decision Making | Issue 1/2020

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Abstract

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.
Appendix
Available only for authorised users
Footnotes
4
It is important to note that data in the IDI is updated periodically, typically quarterly.
 
5
This is a composite group formed because a number of medications exist which are typically good indications of either Anxiety Disorders or Depressive Disorders but not specifically one in particular. There are several diagnostic codes that contribute to this group as well.
 
6
This is a composite group, which for the sake of completeness includes all mental health diagnostic codes not otherwise used in the first ten groups.
 
7
This is a composite group formed because a number of medications are typically indications for a range of potential mental health problems but not specific disorders and in many cases. ‘Mental health not defined’ is also a diagnostic code commonly assigned to people with mental health problems that for whatever reason cannot be specified with more detail.
 
8
For fatal self-harm, the youth population for the previous fiscal year was used as the denominator to allow for mortality in the 2014/15 year.
 
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Metadata
Title
Case identification of mental health and related problems in children and young people using the New Zealand Integrated Data Infrastructure
Authors
Nicholas Bowden
Sheree Gibb
Hiran Thabrew
Jesse Kokaua
Richard Audas
Sally Merry
Barry Taylor
Sarah E Hetrick
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2020
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-020-1057-8

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