Identification of children at risk for mental health problems in primary care-Development of a prediction model with routine health care data.

ABSTRACT:

Background

Despite being common and having long lasting effects, mental health problems in children are often under-recognised and under-treated. Improving early identification is important in order to provide adequate, timely treatment. We aimed to develop prediction models for the one-year risk of a first recorded mental health problem in children attending primary care.

Methods

We carried out a population-based cohort study based on readily available routine healthcare data anonymously extracted from electronic medical records of 76 general practice centers in the Leiden area, the Netherlands. We included all patients aged 1-19 years on 31 December 2016 without prior mental health problems. Multilevel logistic regression analyses were used to predict the one-year risk of

SUBMITTER: Koning NR 

PROVIDER: S-EPMC6833364 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature