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What is the average length of stay in a skilled nursing facility in the United States 2023?
Executive Summary
There is no single authoritative figure in the supplied materials that states the nationwide average length of stay (LOS) in U.S. skilled nursing facilities (SNFs) for calendar year 2023; available analyses point to an average in the high-20s of days and substantial geographic variation. Recent work shows national trends around ~27 days in nearby years and regional LOS ranging roughly 20–35 days during a 12‑month window ending September 22, 2023 [1] [2] [3].
1. Why the headline number is missing, and what the best approximations show
No single source in the provided set reports a definitive national average LOS specifically for the 2023 calendar year; instead, the strongest, most recent approximations come from studies that cover overlapping periods or earlier years. A Trella Health analysis reports a national average increase from 25.8 days in 2019 to 27.5 days in 2022, noting the trend but not publishing a 2023 national point estimate [1]. A CMS‑based reference notes an average LOS of about 27 days in 2020, which aligns with the Trella trend and suggests stability in the high‑20s across recent years [3]. These multiple nearby-year data points point toward a national average LOS in the high‑20s of days, but they stop short of declaring a single 2023 number, leaving an evidence gap for that specific year [1] [3].
2. The one clear headline: wide regional variation masking any single national average
A September 2024 white paper analyzing 627,095 SNF stays spanning September 22, 2022, to September 22, 2023, shows substantial local variation, with average LOS by metropolitan statistical area ranging from 20.4 to 35.3 days [2]. That spread means a single national average would hide meaningful differences driven by local practice patterns, discharge arrangements, and payer mixes. The white paper also finds that case mix does not fully explain the variation, pointing to facility‑ and system‑level decisions as key drivers. When variation of this magnitude exists across MSAs, reporting a single national average is of limited use for local planning and policy because local averages diverge materially from any national mean [2].
3. Payment rules and incentives that shape length of stay patterns
Payment structure likely contributes to observed spikes and cutoffs in LOS metrics. Medicare covers SNF care fully for the first 20 days, with beneficiaries facing per‑day cost sharing thereafter, which correlates with observed clustering around the 20‑day mark [2]. The white paper links this policy nuance to behavioral responses: facilities and discharge planners may time transitions around day 20 to reduce patient or payer costs, affecting the distribution of LOS. This makes comparing raw LOS figures across regions or years tricky because policy‑driven behavior—not only clinical needs—shapes averages and can produce abrupt changes when payment rules or utilization management practices shift [2].
4. Older and alternative data points: consistency around the high‑20s, but conflicting long‑stay statistics
A 2014 snapshot of Medicare beneficiaries reported a mean LOS of 26.78 days, with state differences such as New York at 28.35 days, reinforcing a long‑standing central tendency in the mid‑to‑high 20s [4]. CMS documentation and the Trella Health write‑up both point to averages near 27 days in recent years [3] [1]. Other sources provided in the analyses discuss long‑term nursing home residency measures (years rather than months) and median stays that apply to different populations; those figures are not comparable to short‑ or post‑acute SNF LOS and can mislead if conflated with SNF averages [5] [6].
5. What this means for policymakers, providers, and researchers—data gaps and next steps
The supplied materials indicate a clear need for a single, transparent national estimate for 2023 produced by a federal body or a peer‑reviewed analysis that uses standardized inclusion criteria (e.g., Medicare FFS vs. all payers, post‑acute vs. long‑term admissions). The white paper’s finding that variation is not explained by case mix suggests interventions should target practice patterns and discharge coordination, not just patient characteristics [2]. Researchers and policymakers should prioritize disaggregated reporting by MSA and payer, publish a 2023 national estimate using the same case definitions as prior CMS releases, and examine the role of Medicare cost‑sharing rules that produce behavioral clustering around day 20 [2].