Risk score for predicting adolescent mental health problems among children using parental report only: the TRAILS study

Identification of child mental health problems by combining electronic health record information from different primary healthcare professionals: a population-based cohort study

OBJECTIVES

To investigate the potential value of combining information from electronic health records from Dutch general practitioners (GPs) and preventive youth healthcare professionals (PYHPs) in predicting child mental health problems (MHPs).

DESIGN

Population-based retrospective cohort study.

SETTING

General practice, children who were registered with 76 general practice centres from the Leiden University Medical Centre (LUMC) primary care academic network Extramural LUMC Academic Network in the Leiden area, the Netherlands. For the included children we obtained data regarding a child's healthy development from preventive youth healthcare.

PARTICIPANTS

48 256 children aged 0-19 years old who were registered with participating GPs between 2007 and 2017 and who also had data available from PYHPs from the period 2010-2015. Children with MHPs before 2007 were excluded (n=3415).

PRIMARY OUTCOME

First MHPs based on GP data.

RESULTS

In 51% of the children who had MHPs according to GPs, PYPHs also had concerns for MHPs. In 31% of the children who had no MHPs according to GPs, PYHPs had recorded concerns for MHPs. Combining their information did not result in better performing prediction models than the models based on GP data alone (c-statistics ranging from 0.62 to 0.64). Important determinants of identification of MHPs by PYHPs 1 year later were concerns from PHYPs about MHPs, borderline or increased problem scores on mental health screening tools, life events, family history of MHPs and an extra visit to preventive youth healthcare.

CONCLUSIONS

Although the use of combined information from PYHPs and GPs did not improve prediction of MHPs compared with the use of GP data alone, this study showed the feasibility of analysing a combined dataset from different healthcare providers what has the potential to inform future studies aimed at improving child MHP identification.

The Usefulness of Electronic Health Records From Preventive Youth Healthcare in the Recognition of Child Mental Health Problems

Background and Objectives: Early identification of child mental health problems (MHPs) is important to provide adequate, timely treatment. Dutch preventive youth healthcare monitors all aspects of a child's healthy development. We explored the usefulness of their electronic health records (EHRs) in scientific research and aimed to develop prediction models for child MHPs.

Methods: Population-based cohort study with anonymously extracted electronic healthcare data from preventive youth healthcare centers in the Leiden area, the Netherlands, from the period 2005–2015. Data was analyzed with respect to its continuity, percentage of cases and completeness. Logistic regression analyses were conducted to develop prediction models for the risk of a first recorded concern for MHPs in the next scheduled visit at age 3/4, 5/6, 10/11, and 13/14 years.

Results: We included 26,492 children. The continuity of the data was low and the number of concerns for MHPs varied greatly. A large number of determinants had missing data for over 80% of the children. The discriminatory performance of the prediction models were poor.

Conclusions: This is the first study exploring the usefulness of EHRs from Dutch preventive youth healthcare in research, especially in predicting child MHPs. We found the usefulness of the data to be limited and the performance of the developed prediction models was poor. When data quality can be improved, e.g., by facilitating accurate recording, or by data enrichment from other available sources, the analysis of EHRs might be helpful for better identification of child MHPs.