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

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.

SUBMITTER: Bowden N

PROVIDER: S-EPMC7045433 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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

Bowden Nicholas N Gibb Sheree S Thabrew Hiran H Kokaua Jesse J Audas Richard R Merry Sally S Taylor Barry B Hetrick Sarah E SE

BMC medical informatics and decision making 20200227 1

<h4>Background</h4>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.<h4>Methods</h4>We drew on diagnostic and pharmaceutical information contained within five secondary care service use and medication dispensing datasets t ...[more]

PMID: 32106861

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Project description:Aims/hypothesisType 1 diabetes is one of the most common chronic diseases of childhood. It is hypothesised that the metabolic and psychosocial consequences of type 1 diabetes may affect educational outcomes; however, existing literature presents conflicting results. This study aimed to assess whether educational outcomes differ for young people with and without type 1 diabetes in Aotearoa/New Zealand (NZ).MethodsThis was a nationwide 9 year birth cohort study of all people born in NZ from 1993 to 2001 using linked administrative data held within the Integrated Data Infrastructure, a national research database containing linked health and non-health data. Educational outcomes of high school attainment, high school attendance and university enrolment were measured from age 13 years until 20 years. Generalised linear regression models with log link and Gaussian distributions were used to compare educational outcomes between those with and those without type 1 diabetes, adjusting for sociodemographic and maternal characteristics.ResultsOf the 442,320 children in the birth cohort, type 1 diabetes was identified in 2058 (0.47%) (mean [SD] age of type 1 diabetes diagnosis 7.7 [3.4] years). Educational outcomes were significantly lower for children with type 1 diabetes than for those without type 1 diabetes, including for any high school qualification (RR 0.97 [95% CI 0.95, 0.99]), university entrance-level high school attainment (RR 0.88 [95% CI 0.84, 0.92]), regular high school attendance (RR 0.91 [95% CI 0.85, 0.97]) and university enrolment (RR 0.93 [95% CI 0.88, 0.98]), even after adjusting for sociodemographic and maternal factors. In addition, educational outcomes were substantially lower for those with post type 1 diabetes diagnosis hospitalisations for diabetic ketoacidosis and hypoglycaemia.Conclusions/interpretationIn this whole NZ birth cohort study, type 1 diabetes was associated with lower educational outcomes spanning secondary school and into university enrolment. Ongoing efforts to support students with type 1 diabetes are needed, particularly for those with a greater risk profile.

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

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

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