Three Takeaways from Barnes-Jewish Hospital Data Disruptors Webcast

Putting data to good use is an area of growing importance across the entire healthcare delivery value chain – from hospitals and health insurers to medical device manufacturers, EHR software vendors, genomic researchers, fitness tracker manufacturers, and more.

In fact, according to the 2018 Predictive Analytics in Healthcare report from the Society of Actuaries, 58% of organizations that currently use predictive analytics expect to increase their budgets by 15% or more over the next five years. A number of Vertica customers, including Cerner, New York Genome Center, hMetrix, Philips Healthcare, Suunto, and others are leading this transformation.

Last week, I hosted Linh Dye, Director of Data Management & Performance Measurement (DMPM) at Barnes-Jewish Hospital (BJH) for our latest Data Disruptors customer webcast. Dr. Dye and her team use advanced analytics to enable data-driven operations and business decisions at all levels of healthcare delivery – including the prediction of Sepsis, labor resources, employee turnover, and more.

Dr. Dye’s presentation tells the incredible story of her organization’s journey from data silos and static dashboards to fully automated data processing and predictive analytics. Whether you work in the healthcare field or not, the on-demand webinar will teach you powerful lessons about transforming how data is managed and used within your organization. These are my three main takeaways from Dr. Dye’s presentation:

  1. Start with a clear vision and mission. The team at BJH had a clear vision for introducing data-driven decision making into the organization: simplify technology for dynamic success. While that sounds straight forward enough, simplifying a data analytics architecture so it can be used as a strategic asset across an organization is a time-consuming and resource-intensive undertaking. To accomplish this, Dr. Dye’s team put together an ambitious five-year mission to guide their success: maximize availability of information assets, improve and ensure information asset integrity, establish an accountability infrastructure, prioritize areas for business improvement, and ultimately bring human and machine learning closer to the operations.
  2. Treat data transformation as a journey. As you’ll see from the webcast, BJH’s transformation didn’t happen overnight. Rather, it was an evolution of technology adoption, skills development, organizational buy-in, and continuous learning. First they “crawled” – with static dashboards and reports. Then they “walked” – with live data and some automation. Then they “ran” – with alert capability, fully automated data processes, and user feedback. And now they’re “leaping” – with predictive analytics and quick turnarounds generating positive outcomes and greater satisfaction from both IT and business users and leaders.
  3. The right technologies make a difference. Implementing a transformative data analytics strategy requires a breadth of resources. Success requires availability of data, a strong team, a sound approach, stakeholder buy-in, and ultimately the right technologies. The DMPM team knew that to achieve their ambitious goals, they would need new technologies that supported fast turnaround times and methods for automating processes. To accomplish this, they turned to Vertica as the underlying data warehouse and Tableau as the data visualization environment. With this combination, BJH achieved results beyond their expectations for high speed, low cost, agility, and ease of use.

Want to hear the Barnes-Jewish story first-hand? Watch the webcast on-demand.