EHRs are full of valuable data. Flagler realized that with very little work, AI could produce actionable insights from their data. Dr. Michael Sanders, CMIO of Flagler Hospital, thinks of EHRs as the new textbook of medicine—there’s a lot to learn if you can just pull out the right information.
Flagler’s eight-person informatics team wrote 2,500 lines of Structured Query Language (SQL) code to pull the data for the pneumonia pilot from the EHR. Fortunately, the data requirements were well defined and already standard outputs of the EHR, so it was relatively quick and simple to get the data.
Because the AI solution could comb through different kinds of data, Flagler’s team also pulled data from sources outside of the EHR. The other two sources of data were the financial system and the surgical system. The informatics team collected and recorded data for everything that happened to patients from admission to discharge, including standard lab results and vital signs. The team even recorded small details like what meals the patients ate and the exact times they ate each day.
At this point, the solution recognized patterns in Flagler’s data and sorted the patients into treatment groups. Each group represented a typical patient population with similar treatment patterns. The software analyzed the data to create a care path for each group and displayed a dashboard comparing each group by costs, mortality, and care outcomes.
Flagler’s team used the dashboard to identify the optimal treatment group (the group with the best outcomes at the lowest cost) and used the generated care path as a template for a new order set.