Language Models for Standardising Clinical Notes and Information Extraction in Addiction Psychiatry—An Empirical Study

Fine-tuned LLMs effectively standardised clinical notes and extracted structured information from addiction psychiatry records. Both these functionalities have important applications. Standardising improves the readability of clinical documentation and facilitates communication within and between interdisciplinary teams. Automated information extraction can decrease the burden on clinical staff, allow the creation of research cohorts from existing records and improve treatment outcomes by extracting critical information, such as 'time since last drink', which can be used to raise alerts. Even with limited computational resources, it is possible to adapt open-source LLMs for bespoke tasks in the field of addiction psychiatry. Our proposed solution is a model that can be deployed on consumer-grade servers, thus ensuring data privacy and security.