Identifying what anxiety treatments are provided to neurodivergent children and young people and their outcomes in routine care: protocol for a data-driven electronic health records study (ACECAT-CRIS)

Abstract

Lay SummaryAnxiety is a common problem for neurodivergent children and young people, however it can be very challenging to identify and to manage. In a national survey, many neurodivergent children and young people and their parents expressed their frustration with not getting the right support and not “being treated seriously until at a crisis point” (National Autistic Society, 2021). As a first step to understand what has been done and what else can be done to manage anxiety problems among neurodivergent children and young people, we will explore what interventions are currently offered by child and adolescent mental health services in a large NHS Trust to autistic children and young people who have problems with anxiety, and what the outcomes of these interventions are (if recorded). We will search the structural data field in current medical records and free-text clinical notes using a Natural Language Processing (NLP) model.AbstractBackground: Anxiety problems are more prominent in neurodivergent children and young people than in their neurotypical peers. Such high rates of comorbidity are important to recognise as this comorbidity is associated with a greater risk of adverse outcomes, including self-harm and suicidality, than either condition on its own. While both pharmacological and psychological treatments are often prescribed for anxiety problems in autistic children and young people, as well as in those with ADHD, the evidence base for their effectiveness has so far been inconclusive, and little is known about their treatment outcomes in routine care. Methods: This study aims to explore the nature and outcomes of anxiety treatments for autistic children and young people and for those with ADHD using pseudonymised electronic health record data. Longitudinal trends of both structured records of diagnoses (as recorded by ICD-10 codes), demographic information, treatment team and free-text clinical notes on presenting problems, indication of treatments, treatment provision, treatment outcomes and side effects, will be extracted and analysed. Free-text clinical notes will be processed to extract key concepts of interest using Natural Language Processing.Discussion: This study will explore what treatments are available for autistic children and young people, and those with ADHD, in routine care, as well as treatment outcomes. However, due to the nature and availability of data, the findings will inevitably be limited in their generalisability, which we aim to address in future phases of research.