A 5 minute read
September 21, 2017

The American Hospital Association (AHA) is urging CMS to implement an alternate Medicare reimbursement model for skilled nursing facilities (SNFs) before a new clinical groupings model is in place. The current model of Resource Utilization Groups (RUGS) has been criticized as incentivizing the overutilization of resources, as well as demanding reimbursements that exceed actual care costs.

According to a CMS notice in April 2017, RUGS would be replaced with a system called the Resident Classification System Version 1 (RCS-1). Four new case-mix categories would be implemented under RCS-1: physical/occupational therapy, speech language pathology, nursing, and non-therapy ancillaries. Each category would contain its own case-mix group, for a total of 300,000 payment groups—far more than exist under the RUGS model.

Largest SNF Networks by Member Beds

SNF Name Member Beds
Genesis HealthCare 53,967
Heartland ManorCare 33,379
Life Care Centers of America 26,144
SavaSeniorCare 24,903
Ensign Group 18,549
Consulate Health Care 18,496
Good Samaritan Society -- Sioux Falls 15,041
Senior Care Centers 12,468
Five Star Senior Living 12,063
Trilogy Health Services 10,703

Fig 1 Data from Definitive Healthcare

These new categories will also affect SNFs’ daily reimbursement rates. Rather than maintaining a flat reimbursement rate throughout a resident’s stay, reimbursement rates would be higher toward the beginning of the stay and slowly decline as additional days of therapy are provided.
Additionally, SNFs that provide fewer than 15 therapy days and only one form of therapy will receive higher reimbursement rates than those who do not. Reimbursement rates would also be higher if between 50 and 75 percent of a skilled nursing facility’s Medicare days are classified as non-rehabilitation.

This shift raises some red flags. SNFs primarily serve chronically ill patients with complex medical needs, many of whom are older Americans. These residents likely require multiple kinds of highly coordinated care, including multiple types of therapy. Would reimbursing SNFs at lower rates for providing these services deter them from doing so, or would it simply discourage them from using unnecessary resources? Will there be greater motivation for SNFs to discharge patients in under 15 days, even if they’re not entirely ready? CMS also revealed reimbursement rates will be lower for facilities treating patients aged 90 or older, receiving three types of therapy, or undergoing treatment for longer than 31 days.

The AHA is concerned that RCS-1 will not be able to accurately predict resource needs for patients with complex medical issues, which would lead to less accurate payment data and lower care access. In addition, the ACA suggested that CMS use updated data to re-assess the impact of the RCS-1 system—the original analysis used data from 1995 and 2006, casting doubt on whether costs were reliably predicted.

Since 2006, there have been significant changes in post-acute care patterns under new value-based purchasing (VBP) guidelines. Greater numbers of patients have received care at SNFs over intensive-care settings due to bundled payments and ACO affiliations. The number of joint replacement patients in SNFs also declined after a change in 2010 rehabilitation admission rules, and site-neutral payment rules for long-term care facilities impacted admission practices.

In instituting the RCS-1 model in place of RUGS, are SNFs being put in a position to perform poorly? Providers would need significant time to educate staff on new measures and payment groups, adjust workflows to accommodate new expectations, and update their IT and EHR systems.

A new study in the September edition of Health Affairs found that hospitals with formal skilled nursing facility networks had reduced admission rates compared to hospitals that did not include SNFs as part of care management. The readmission rate for patients discharged to SNFs declined from 24 percent in 2009 to 18 percent in 2013, compared to 21.5 percent to 20 percent for patients discharged directly home. This is especially significant because the direct costs of developing a formal network between hospitals and SNFs is relatively small, yet the benefits are demonstrable.

SNFs have already been lagging behind in EHR adoption, and adding RCS-1 to the mix could potentially hinder their progress even further. According to a recent ONC Data Brief, only 64 percent of SNFs used an EHR system in 2016, compared to 91 percent of acute care hospitals tracked by Definitive Healthcare. The study also found that 20 percent of SNFs used both an EHR system and a regional health information exchange organization (RHIO) to share health data.

Skilled Nursing Facility

Fig 2 Data from Definitive Healthcare and HealthIT.gov

The facilities that used both an EHR and an RHIO were able to send, receive, and integrate patient health data at higher rates than those solely using an EHR system. Additionally, SNFs using both technologies exchanged patient data at a rate five times that of facilities that used neither technology. This includes rural SNFs, which have historically lagged behind their urban counterparts in EHR and other technology adoption. In 2016, 67 percent of rural SNFs adopted an EHR system and only 62 percent or urban SNFs did the same.

Skilled nursing facilities still lag behind their acute-care counterparts in EHR adoption and health IT integration, yet have demonstrated an important place in the care continuum. Though the goal of replacing RUGS with RCS-1 aims to reduce overall care costs, it has the potential to inaccurately predict patient needs, leading to an excess or dearth of resources. CMS has offered a provider-specific impact analysis on its website.

Visit the Definitive Blog to read more about CMS Reimbursements and Skilled Nursing Facility Corporations.

Definitive Healthcare has the most integrated, comprehensive data on nearly 20,000 skilled nursing facilities, over 7,500 hospitals, and 107,000 skilled nursing facility executives. Search for specific facilities using dozens of filters, and compile lists of hospitals, SNFs, and IDNs by region, net patient revenue, CMS program participation, and more.

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