We’re back with another example of our work with interesting and meaningful revenue cycle challenges. Today, we’re reflecting on our cutting-edge project with South Shore Health System on understanding and managing their Bundled Payments initiative. If you missed our last post, we’re framing our rev cycle case studies using the STAR format.
South Shore Health System, an integrated health system, signed up for a pilot of the Bundled Payments for Care Improvement (BPCI) initiative. The program links payments for the multiple services patients receive during an episode of care based on a coded DRG. Under the initiative, organizations enter into payment arrangements that include financial and performance accountability for episodes of care even when the patient doesn’t present at the organization’s centers for care. These models may lead to higher quality and more coordinated care at a lower cost to Medicare. There were 11 scenarios the organization was monitoring, from Sepsis to orthopedic surgery events. This equates to about 2,000 bundles over a six-month period, over 40,000 visits to the hospital, PCPs, SNFs, etc. and a multi-million dollar impact to the bottom line.
In order to monitor the success of this initiative, they needed a way to see data from their EMR, their case management system, claims data from an external claims aggregator, and data from patient satisfaction surveys. We built an application that was able to blend data from many different sources and visualize trends to drill into the patient and visit level detail. The team needed help to pull all the data together quickly and design a comprehensive scoreboard for the program based on lag but also lead measures.
Our team tackled the challenge by;
Jacqueline Goeldner, the Director of Medical and Performance Management said that with access to the blended data, they have been able to see readmissions across the board decreasing. Staff are able to dig into relationships they were previously unable to make between readmissions and continued hospitalizations and between SNFs and VNAs and hospitalizations.
Jason Ryan, the Manager of Analytics said about the process:
“The discipline of going through the metric workbook to get all the end users of the tool to agree on what each metric means and how it is calculated is well-invested time. It takes a while as these can be lengthy conversations, but when the dashboard is finally up and running, everyone is in agreement regarding what the dashboard means.”