This webinar covers best practices for integrating data from multiple clinical and genomic sources for clinical decision support.
New data sources, technologies, and workflows are being developed and refined to advance clinical decision support and improve patient outcomes, but challenges remain. Research teams today are hampered by the manual effort required to identify, standardize, aggregate, and interpret data. These manual workflows may be manageable during the development of precision medicine programs, but quickly lead to concerns around scaling to meet increasing demand and greater patient numbers.
View this webcast to hear Mayo Clinic’s Research Scientist Jan Egan discuss the value and complexities of compiling data from multiple clinical and genomic sources for clinical decision support. Dr. Egan also shares experiences with standardizing and automating this effort to help clinical and scientific staff in clinical decision support and reporting.
Key takeaways for attendees:
· An understanding of what data can be used for which decisions with sample use cases
· Real-world case study insight and best practices for building an environment to leverage omics data for clinical decisions
· Practical tips for evaluating and selecting a clinical decision support solution