The clinical challenges of today include access to data for clinical decisions – both in internal and external systems - and clinical decision support for making sense of and prioritizing the information available. The work in BigMed focuses on getting the right information to the point of care; structuring data for easier use and reuse of data, access to internal and external knowledge etc.
Activities and deliverables are described below:
- Mapping of clinical needs based on design thinking
- Implementation of Dashboard for clinical decision support in DIPS Arena – including timeline and structured patient information to reduce errors and reduce clinician time spent searching for information
- Text mining from electronic health record for automatic population of Dashboard
- Data extraction from registries to populate patient timeline – previous disease incidents. Demo.
- Open EHR Archetypes definition for structured report to cancer registry, saving valuable clinician time and improving valuable data gathering.
- Statistics for patients like me: Application showing live cancer registry outcome data based on different clinical interventions for similar patient cases, clinical decision support. Prototype.
- Patient similarity tool: Advanced clustering techniques for multi criteria similarity.
- Clinical reporting of molecular diagnostics:
- Genomics-based reports from somatic sequencing.
- Clinical decision support module for tumor board meeting dashboard