Using Electronic Health Records to provide decision support in child and adolescent mental health services

Abstract

This philosophiae doctor (PhD) thesis investigates the impact of specialized Electronic Health Records (EHRs) on decision-making processes in Child and Adolescent Mental Health Services (CAMHS). The study aims to enhance decisionmaking within CAMHS by using clinical data. Employing a mixed-methods approach, the research integrates qualitative interviews with healthcare professionals and an in-depth examination of backgrounds, processes, and documents, alongside a quantitative analysis of clinical data from specialized EHRs systems. The findings suggest that the use of specialized EHRs may assist in improving decision-making by offering more accurate, timely information and potentially valuable insights. Key success factors of the BUPdata system were identified, along with challenges related to BUPdata analysis and interpretation. A framework was established to structure the services, functions, and collaborations among service providers. Analytical methods for predicting patient readmission and visualizing patient trajectory patterns and disorder co-occurrences were developed and evaluated. This thesis contributes to the field of health informatics by providing a foundation for developing data-driven decision aids in CAMHS. The research suggests that enhanced data analysis and visualization techniques may improve decisionmaking and service delivery in mental health services. The study indicates that integrating more advanced methods into EHR systems could enhance decision support in CAMHS. Future research should refine these techniques and explore their broader application in mental health services, with guidance from healthcare professionals, who are key stakeholders.