This use case describes the automation of monitoring obstetric clinical indicators using SNOMED CT encoded clinical notes. The semi-structured clinical notes were extracted and encoded with SNOMED CT using a natural language processing system called MyHarmony. A tri-partite arrangement was established, which involved the informaticians at the Health Informatics Centre (Pusat Informatik Kesihatan, PIK) in the Ministry of Health Malaysia, the clinicians headed by the head of Malaysia’s obstetric speciality, and the Information Technology (IT) engineers of the hospitals involved. Each party has specific roles and responsibilities. There were four benefits identified with using this approach: (1) No data entry required. (2) Saved time and resources due to the automation process for data submission, codification, and reporting. Hence, there is no effect on clinical workflow or requires additional workload. (3) Richer analysis due to the granularity of the data written in free text. (4) Timely result which enables clinicians to monitor and intervene faster. However, there were several expected challenges during this project. First is the incompleteness of the documentation by the doctors which need can be improved with continuous awareness. the documentation and the resulting reports. Secondly, the team must standardize the semi-structured clinical notes from different hospitals. Therefore, it is important that the informatician understand the clinical requirement to ensure the right data are extracted by the IT engineers. This approach will be introduced to other clinical specialities so they can experience the same benefit when using SNOMED CT.

The EU QUANTUM Data Holder’s Maturity Model represents a significant advancement in the assessment and enhancement of health data quality and management maturity across Europe. Developed as part of the QUANTUM initiative, this model provides a structured approach to evaluating data holders’ capabilities in managing health data, ensuring alignment with the European Health Data Space (EHDS) regulations. This presentation will explore the development, methodology, and key findings of the model, highlighting its relevance for standardisation, interoperability and governance within health data ecosystems. Attendees will gain insight into the model’s application and its role in fostering a more integrated and reliable data-sharing environment.

As a key component of the Quality Improvement project, the SI Content Team is engaged in the ongoing evaluation and refinement of the 71388002 |Procedure (procedure)| hierarchy. This process aims to standardize and normalize content, ensuring strict compliance with established Editorial Guidance and Policy to uphold terminology structural quality, consistency, accuracy and usability. Furthermore, user feedback is systematically analyzed to optimize modeling patterns, resulting in the creation and dissemination of updated Model Patterns, Editorial Guidance and Templates designed to support SCT authors and implementers.