How Tighter IT & Processes Can Pick Up Revenue Left on the Table
Many hospitals typically are leaving 2 to 5 percent of net revenue on the table because of internal processes that impede full collection of payment, says Jim Lazarus, managing director of strategy and innovation at The Advisory Board Company, a consultancy.
“These are internally controllable losses,” he adds. The reason why is because hospitals have silos across their revenue cycle infrastructure. The first silo is the front-end patient access process that includes registration and patient-facing pre-service components. The second silo includes physician documentation and coding departments. The third silo is the business office, which sends the bills, collects payments and deals with insurance reimbursement. “Money is left on the table because the functions and departments don’t collaborate enough,” Lazarus explains.
And a big reason for lack of collaboration is that each of these silos often uses different information systems, he contends. “You need one integrated technology that is the source of truth. Each silo has its own data and analysis.”
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The hope had been that newer electronic health records systems would assist in improving revenue cycles, but that is not their competency, Lazarus says. Organizations spend a lot of money on EHRs, many of which come with a hospital information system or practice management system, yet they still need to supplement with a next-generation revenue cycle system to complement the EHR and generate efficiencies. “There is some pain in shifting, but tremendous value to gain.”
Key questions that Lazarus advises asking vendors include:
* Are their technologies truly integrated? They have to be not just from a single vendor, but on a single platform. Can someone in the business office using the technology find out something without having to call someone else or log into the system to see what actions were taken by other silos?
* Does the platform offer workflows for reporting functions and for predictive and preventive analytics that go beyond canned analytic reporting? Preventive analytics is critical in helping predict what will happen before bills are sent out to prevent problems down the road.
* Using predictive analytics, can the platform help identify claims likely to be denied before the claims are even built? Can the system identify insurers who will look at the claim and kick it back saying there isn’t enough documentation?