Predictive Payment Modeling Foresees ICD-10 Impact
Crystal balls and tea leaf readings are not the only ways to foresee the impact ICD-10 will have on a hospital’s bottom line. Advanced analytics can be used to understand how payments will change when using ICD-10 codes. At an ICD-10 Summit session Tuesday, Louis Rossiter, PhD, leader of scientific methods at New Health Analytics, and Maria Bounos, RN, MPM, CPC-H, business development manager with consulting firm Wolters Kluwer, showed how to leverage ICD-10 data within an organization in order to reduce uncertainty in how ICD-10 changes reimbursement.
While the Centers for Medicare & Medicaid Services (CMS) has said their own predictive modeling of ICD-10 shows a neutral financial impact on providers, Rossiter and Bounos said that is not entirely true. While the overall impact on all providers nationwide is neutral, the specific impact will vary between facilities.
“Some hospitals will be winners and some will be losers,” Rossiter said.
There are steps providers can take to prevent a drop in reimbursement, but hospitals need to understand the financial implications of the transition and determine the revenue impact by provider, system facility, service line, and geography in order to fine tune their conversion strategy.
Conducting a detailed risk assessment is the first step to determining the financial impact.
“If you can convert your issues into dollar signs, you will get a hospital administration’s attention,” Rossiter said.
A payment impact analysis can be done by translating two or more years of ICD-9 hospital claims into ICD-10, then using the expected Medicare MS-DRG ICD-10 payment rates to compare reimbursement between ICD-9 and ICD-10. While translated historical data is not the same as live coded ICD-10 data, the comparison can enable a close look at reimbursement rates.
The impact can be broken down by facility, DRG, service line, and other line items.
In an example model, Rossiter showed how some DRGs can lose more than others. The DRG for “cardiac defibrillator implant w/o cardiac cath w/o MCC” showed a loss in reimbursement of $663,821 between ICD-9 and ICD-10 over the entire span of reviewed records. However, a look at all Medicare fee-for-service payments showed a 2.7 percent increase in reimbursement under ICD-10.
This information should be used to understand where careful coding, coder training, and clinical documentation should be focused today to negate the potential risk when ICD-10 becomes required practice.
The model not only attaches a dollar amount to the impact of ICD-10, which bolsters buy in, but informs strategic planning by service line.
ICD-10 needs to be taken seriously. It is multifaceted, requires a holistic implementation approach, is a major change in health IT systems, and can have a significant financial impact.
“ICD-10 involves the full spectrum of the revenue cycle, from when the patient walks through the door to the bill drop,” Bounos said. “This is one of the biggest changes we have had in the last 30 years.”