Business Problem
Insurance companies frequently fail to pay hospitals what they are contractually owed. For large hospitals and health systems, these underpaid and denied claims can add up to tens of millions of dollars in uncollected revenue each year. The existing tools and process for identifying, validating, appealing, and collecting on these claims is time and resource-intensive.
My Role
As the UX lead for this project, I collaborated with the product management and development teams to plan and conduct all UX research and design activities. I produced and presented all of the related deliverables, including:
User interview transcripts and recordings,
Mental model diagrams for primary and secondary user personas,
Process flows,
Site maps,
Wireframes / design specifications,
Data visualization concepts,
Interactive prototypes, and
Usability test results.
Discovery & Design Deliverables
To understand how primary and secondary users think about this problem, and what their existing processes were, I conducted one-on-one interviews with executives, managers, and business office staff at healthcare systems across the U.S., including our alpha development partner, The Cleveland Clinic Foundation.
Mental Model Diagram
Based on the work of Indi Young (co-founder of Adaptive Path), mental model diagrams are a great way to organize, present, and design for the way that users actually think and behave. This mental model focused on the tasks, goals, and beliefs primary users (revenue recovery specialists) as well as the managers or executives responsible for maximizing contract value for their hospitals.
Process Flow Diagram
One of the most significant findings from the discovery interviews was that hospitals don't usually attempt to collect "small-dollar" underpayments because appealing them one at a time is not financially beneficial. We devised a process that would allow collectors to identify similar underpayments, and appeal them in a single bulk package called an "Appeal Project". I also helped to define algorithms used in an "opportunity engine" which could filter out "false" (non-recoverable) underpayments. This led to immediate ROI for our alpha partner, and has proven to be a MAJOR differentiator for the product.
Site map
Wireframes
The Variance Explorer dashboard view utilizes an algorithm to identify and aggregate potentially-similar line items, and proactively surface them as bulk-collection opportunities.
Drilling in and dynamically filtering from the dashboard allows users to examine and compare line-items to decide if they should be appealed.
This versatile "Assignment Rules" form allows managers to define logic that will automatically flag, status, or assign particular line items to specific staff members to be investigated and appealed. The next phase of this effort would be to enable the system to automatically generate and submit appeal documentation for certain underpayments without any human intervention.
Executives and managers need a high-level view of trends and root causes for underpayments and denials. Being able to show that a particular payer is a poor performer, gives hospitals tremendous leverage when it's time to negotiate new contracts. This dark dashboard view has been a huge hit with users (as well as the sales and marketing group).
Project Outcome
Since the alpha roll out late in 2015, The Cleveland Clinic Foundation has identified and recovered over $28,000,000 in underpaid and denied claims. Their managing director of contract management described PIC by saying, "This application literally prints money!" Since that time, seventy-five other health systems have purchased the product and are starting to report similar success stories. We estimate close to $350 million in verifiable ROI for our members so far.