Longitudinal look at nursing-home closures uncovers some telling wrinkles

When a nursing home closes down, the local population and press often perceive the move as a simple exit from the market due to failing fiscal health. But in about half the cases, additional forces are in play—and “closures” may be, in truth, do-overs of one kind or another. 

Researchers at the University of Massachusetts fill out the picture with facts in a study published July 31 by JAMA Health Forum.

Joohyun Chung, PhD, RN, and colleagues suggest understanding the dynamics behind nursing-home closings is important because such events can disrupt continuity of care, place additional burdens on remaining facilities and disproportionately affect vulnerable populations. 

The latest CDC statistics on the sector suggest the scale of the undertaking. As of 2022, some 1.2 million patients resided in around 14,700 nursing homes, which cumulatively ran 1.6 million beds. 

Around 72% of the facilities were owned by for-profit businesses.

Meanwhile Chung and colleagues show a total of 1,440 nursing homes closed across the U.S. between 2016 and early 2025. 

Annual closure rates hovered at an average of 0.9% pre-pandemic, the researchers report, and rose modestly to 1.1% annually through the post-2020 period.

Restructuring as a ‘key mechanism of adaptation’ 

For the present study, Chung and co-researchers sought to produce a “comprehensive longitudinal characterization” of U.S. nursing homes’ life-cycle trajectories over four decades.

To meet the objective, the team used CMS Provider of Service files to analyze around 39,400 records representing 33,000 unique physical locations and 80,300 event records spanning 1985 to 2025.

They tracked facilities’ trajectories using physical location identifiers rather than facility names or provider identifiers, the aim being to distinguish true closures from changes of ownership. 

Their key findings and conclusions: 

• Nursing-home markets are defined less by stable institutional persistence and more by continuous organizational change, including entry, exit, ownership transitions and capacity reconfiguration. 
   
• Nearly half of facilities followed simple entry-exit patterns, while a substantial share remained active despite changes of ownership, indicating restructuring as a key mechanism of adaptation. 
   
• Notably, what is traditionally labeled as closure often reflects heterogeneous processes embedded within broader life cycle pathways, including consolidation and reclassification rather than solely regulatory or financial failure. 
   
• Over time, system dynamics shifted from entry-exit dominated activity toward increasing reliance on ownership transitions and capacity adjustments, with pronounced geographic variation, including substantial bed expansion in states such as Texas. 

Chung and co-authors observe that these patterns are “consistent with a maturing and increasingly consolidated sector, potentially influenced by changing reimbursement structures and broader financialization of long-term care.”

‘Closure’ isn’t always what it sounds like 

In their discussion, Chung et al. cite prior studies showing that nursing-home closures are influenced by facility financial performance, payer mix, staffing intensity, ownership structure and local market competition.

Earlier research further revealed that certain factors are associated with heightened risk of closure. These include Medicaid dependence, small size and low occupancy.

Conversely, the prior literature shows, lowered likelihood of closure tends to track with higher Medicare share, greater acuity and prior changes of ownership. 

“Our findings extend this literature by showing that ‘closure’ in administrative data often reflects heterogeneous life cycle processes,” Chung and co-authors write. “Rather than a strict terminal event, closure may represent restructuring, consolidation or reentry.”

The UMass researchers state that, going forward, evaluations of regulatory policies overseeing nursing-home operations “should move beyond static facility counts to incorporate dynamic measures of organizational change, ownership instability and capacity reconfiguration to better reflect the evolving structure of the long-term care system.”

The study is posted in full for free.