Key Takeaways
- 3.2% annual decline in the number of nursing facilities from 2015–2022 (CMS facility count trend)
- 24% of nursing home residents reported pain frequently or worse (NH data; pain measure)
- 9.1% of nursing home residents had pressure ulcers at any time (national prevalence estimate from MDS-based analyses)
- $4.7 billion projected 2024 U.S. nursing home IT market value (including health IT and related services)
- ~$1.0 trillion U.S. long-term care market size (including nursing facilities) in 2023 estimate by IBISWorld (category coverage includes nursing homes)
- ~11.6% annual share of U.S. adults aged 65+ who live in nursing homes at some point (lifetime risk estimate)
- 47% of nursing homes have staffing shortfalls compared with minimum staffing target levels (analysis of CMS staffing data)
- 4.6% of nursing homes were rated 5 stars by CMS overall quality in 2023
- 15% of nursing homes cited medication management as a deficiency area in 2023 surveys (survey category breakdown)
- $70,000 median annual cost of labor per staff FTE in nursing homes in 2021 (labor-cost estimate from CMS cost report analyses)
- 31% registered nurse (RN) staffing variance gap between high- and low-performing nursing homes (analysis of staffing star correlation)
- $23.5 billion labor costs in U.S. nursing homes attributable to staffing wages and benefits in 2021 (industry estimate)
- 22.8% of nursing homes had pressure ulcers at any time in 2018–2020 (MDS-based prevalence estimate)
- 5.7% of nursing home residents had a urinary tract infection (UTI) in 2018–2020 (MDS-based prevalence estimate)
- 24.6% of nursing home residents had moderate to severe pain in 2018–2020 (MDS-based prevalence estimate)
Fewer nursing homes and major staffing gaps are driving rising costs, quality risks, and higher resident harm.
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How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
David Sutherland. (2026, February 13). Nursing Home Industry Statistics. Gitnux. https://gitnux.org/nursing-home-industry-statistics
David Sutherland. "Nursing Home Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/nursing-home-industry-statistics.
David Sutherland. 2026. "Nursing Home Industry Statistics." Gitnux. https://gitnux.org/nursing-home-industry-statistics.
References
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- 22data.cms.gov/provider-data/dataset?q=5-star+rating+category&sortBy=relevance
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