Poliakoff & Associates, P.A. Medicare, Staffing No Comments

Recalibrating Reimbursement

Data Metrics

CMS continues to rely on nursing home’s self-reported and unreliable data for adjustments to the Patient Driven Payment Model (PDPM). PDPM went into effect Oct. 1, 2019. It was the biggest change to the nursing home reimbursement system in 20 years. Colleen Muncy is with data analytics firm StarPro. She told McKnight’s Long-Term Care News:

“[The Centers for Medicare & Medicaid Services] took on a huge initiative to implement PDPM because they felt that providers were gaming the RUGs system.” 

SNF spending unintentionally increased by $1.7 billion, or 5%, under the PDPM model. PDPM was designed to eliminate the “perverse” financial incentive to deliver unnecessary therapy. However, the quality of care declined significantly. Staff and customer satisfaction is at an all time low. CMS is now trying to understand the negative impacts of PDPM.

CMS has collected data metrics for all of fiscal year 2020, and is still gathering FY 2021 and 2022 metrics to fully grasp what trends may have started under COVID versus PDPM.  I am not sure why CMS relies on provider’s data metrics to determine changes in provider behavior, payments and care quality. Care follows money and oversight.  A major industry-wide drop in therapy minutes drew scrutiny.

Changes to the reimbursement model are expected for skilled nursing facilities. CMS spent more under PDPM than under the old RUG-IV model. Any changes to PDPM reimbursements, however, wouldn’t come before next year’s (FY 2023) SNF PPS proposed rule.

Reimbursement Refunds?

Some Chicken Littles warn that CMS may reduce reimbursement rates by double digits. That is doubtful. CMS might attempt a small clawback or refund but that is also doubtful. CMS might make changes to account for over-coding depression. Diagnoses went from 4% of the population to 13% under PDPM. Providers need to document services provided and the level of care needed for patients.

Good documentation leads to good data. Good data leads to good policy decisions on reimbursement. Hopefully, any increase in reimbursement rates will go directly to increasing staffing to safe numbers.