Victoria Morris has a BA in Theater Acting so naturally she went on to get her MSc in Information Systems. She has spent longer than she cares to remember working with data in various organizations. Before entering the healthcare industry, she was responsible for coding lottery and gaming tickets including writing an algorithm for unique crosswords extended play games. Challenging herself further, she worked to define dynamic logistic routes for shipping goods and pricing commodities across northern Canada and the U.S. Victoria has worked in healthcare for the last decade, focusing on integration for both Oncology and Emergency Medicine. Having worked in the U.S., Canada, and Australia she brings unique experience into the inner workings of various healthcare systems and several major EHR’s. Victoria is passionate about making lives easier for healthcare providers and their patients by using automation to remove barriers to care.
Molecular profiling provides precise and individualized cancer treatment options and decisions points. By assessing DNA, RNA, proteins, etc. clinical teams are able to understand the biology of the disease and provide specific treatment plans for oncology patients. An integrated database with demographic, clinical and molecular data was created to summarize individualized genomic reports. Oncologist are able to review the reports and receive assistance interpreting results and potential treatments plans. The architecture to support the current environment includes Wasbi storage, bash/corn/PowerShell, Hive and Office 365 (SharePoint). Via an automated process personalized genomics data is delivered to physicians. As we supported this environment we noted unique challenges and brainstormed a plan for the next generation of the critical business pipeline line.
After researching different platforms we felt that Databricks would allow us to cut cost, standardize our workflow and easily scale for a large organization. This presentation will detail some of the challenges with the previous environment, why we chose Apache Spark and Databricks, migration plans and lessons learned, new technology used after the migration (Data Factory/Databricks, PowerApp/Power Automate/Logic App, Power BI), and how the business has been impacted post migration. Migration to Databricks was critical for our organization due to the time sensitivity of the data and our organizational commitment to personalized treatment for oncology patients.