December 19, 2017
Quarterly Event Recap: Applied Data Science
A huge thank you to Optum for hosting our Quarterly Event as well as our panelists: Jeffrey Hertzberg, MD, MS, Medical Director, Informatics and Data Science at Optum; Dan Abdul, VP Data Solutions Strategy and Commercial Solutions at Optum; and Randy Kirsch, Co-head of IT, Director of Applications and Support at Presbyterian Homes and Services, for sharing their experiences with Applied Data Science. We hope you were able to walk away with some new information and clarification on any questions you may have had regarding this topic.
Jeffrey kicked off the panel discussion with use-cases from Optum and how applied data science has given him new and helpful findings for his work. Artificial Intelligence (A.I.) was one of the main focuses of his discussion. A.I. can be defined as the development of computer systems that are able to perform tasks that require human intelligence. For clinical imputation and prediction, Jeffrey noted three strengths of A.I.: it uses medical SMEs efficiently and has more exhaustive feature sets, and improves or “learns” as the data accumulates, and outperforms in part by identifying variable interactions.
Dan Abdul then jumped into supporting data science. Data science includes data sets that are specific and tricky to work with because they include such raw and rich data. With the right tools and data access, you can easily place data into a model. Just remember, as Dan Abdul mentioned “If there is a model, there is always a chance to tweak it and make it better.” Make the model fit your needs.
Optum as we all know is a very large company – utilizing data science makes sense for them because they have the budget to do so. However, utilizing data science makes sense for smaller companies as well. Randy Kirsch shared what applied data science can do for senior care through his experience at Presbyterian Homes and Services.
As stated in the slides, for the next 20 years, 10,000 people will turn 65 every day. This rapidly growing senior population isn’t the only factor in what we may call a senior care crisis. There are fewer informal caregivers, declining care center beds, an increased need for healthcare workers, and insufficient retirement assets – to name a few. So, how can applied data science address these issues?
Applied data science has influence and can improve things like telemedicine, smart homes, wearable technologies, embedded and ingestible sensors, genetic testing and analysist, etc.
How is data science contributing to your organization’s business?