Rapidly changing reimbursement terms make it extremely difficult to know whether a new—or proposed—payer contract is good, bad, or ugly. Hospital executives often tell us they worry managed care teams don’t have easy access to the right data to negotiate on equal footing with payers.
Even with the right data, evaluating the financial impact of new contracts is a complex exercise given the multiple variables that may come into play: changing from "percent of charge" to "fee schedule," incorporating a complex (and often proprietary) grouper, or accounting for shifting patient populations and chargemaster changes.
Putting your data to work
To avoid contracting missteps, it’s essential to arm your team with the right data and analytical tools to negotiate fair reimbursement. Hospitals with advanced contracting analytics are best equipped to model a multitude of variables and ensure adequate payment for care delivered.
• Patient population
• Grouping or overall reimbursement schema (i.e. % of charges or fee schedule, MS or APR-DRGs, APCs, eAPGs, etc.)
• Chargemaster weighting system and dollar values of procedure shifts
• Assigned or negotiated weight and rate or reimbursement per grouping value
Recently our Payment Integrity Compass team worked with Spencer Health (pseudonym), a two-hospital system with 600 beds, to secure a rate increase with one of its large payers. The payer and the provider agreed to maintain the existing inpatient net yield and implement a 4.7% chargemaster increase, which the hospital initially calculated would generate $600,000 more revenue annually.
However, Spencer also agreed to update its pricing methodology, which made it extremely challenging to know at a glance whether each price change in the contract would in fact add up to the expected revenue increase. Executives at Spencer feared that the new contract wouldn’t deliver the $600,000 revenue increase and—worse—that they might end up losing money instead.
This is when analytical horsepower became critical. When the payer proposed a new base rate for APR-DRGs of $14,500, Spencer Health used Payment Integrity Compass to model reimbursement for 1,100 inpatient stays with the payer. The results showed that the payer’s proposal was below the health system’s target base rate, resulting not in the expected $600,000 increase, but instead in a net decrease in revenue of $200,000.
Here’s where things got interesting. To make up the revenue gap they had uncovered, Spencer Health countered with a base rate of $14,900, but the payer did not accept. They insisted Spencer’s analysis was flawed, because they hadn’t factored in the impact of some specific financial adjustments, such as accounts that qualified for a high-charge outlier and lesser-of provisions.
A hospital with lesser data analysis capabilities might have been stumped at this point, but Payment Integrity Compass enabled Spencer to show unequivocally that their calculations were correct: further analysis revealed the payer had failed to factor in the annual chargemaster increase into its calculations.
The Spencer Health team confidently readjusted the base rates to account for the change. Ultimately, the hospital and the payer reached an agreement that secured the $600,000 revenue increase and avoided the $200,000 loss that would have occurred with the original proposal—a loss that, without easy access to data, Spencer Health would likely not have known about until it was too late.
Don't face multi-million dollar contract decisions blind
Scenarios such as Spencer Health’s contract negotiation, where multiple variables shift at the same time, are extremely difficult to analyze.
"We were able to produce reliable data to support our agenda points during negotiation. If you come with better data than the person on the other side of the desk then you have quite a bit of power." —VP, Managed care
For more information about how Payment Integrity Compass can give you the upper hand in your next contract negotiation, contact Adam Rosenberg at email@example.com.