Identification of child mental health problems by combining electronic health record information from different primary healthcare professionals: a population-based cohort study. Issue 1 (12th January 2022) - Koning, Nynke R; Büchner, Frederike L; Leeuwenburgh, Nathalie A; Paijmans, Irma JM; van Dijk-van Dijk, DJ Annemarie; Vermeiren, Robert RJM; Numans, Mattijs E; Crone, Mathilde
Abstract : 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.