PlainNursing

Understanding Nursing Home Star Ratings

How CMS rates every nursing home in America, what each component measures, and what the ratings don't tell you.

Key Takeaway

The CMS Five-Star Quality Rating System scores every Medicare and Medicaid nursing home on health inspections, staffing, and quality measures — then combines them into an overall 1–5 star rating. Health inspections carry the most weight. A 5-star rating signals above-average performance, but no single number captures the full picture of a facility. Use star ratings as a starting filter, not a final answer.

The Three Rating Components

CMS calculates three separate star ratings and then combines them into an overall score. Each component measures something distinct, and a weakness in any one area can suppress the overall rating even if the others are strong.

How star ratings map to national facility distribution
Stars Meaning Percentile Approx. Count
5Much above averageTop 20%~3,000
4Above average60th-80th~3,000
3Average40th-60th~3,000
2Below average20th-40th~3,000
1Much below averageBottom 20%~3,000

Worked Example

A 4-star facility with 0.85 RN HPRD and 8 deficiencies over 3 years is quantitatively above average. A 2-star facility in the same state with 0.35 RN HPRD and 22 deficiencies needs careful scrutiny. The star rating is a quick filter — always check the underlying data. Our staffing evaluation guide and deficiency guide explain the details.

1. Health Inspections (Most Weight)

The health inspection rating is based on the results of the three most recent standard surveys plus any complaint investigations conducted in the past three years. Surveyors from state health departments visit facilities unannounced and evaluate compliance with federal care standards across dozens of categories — from infection control and medication management to residents' rights and nutrition.

Each deficiency is scored on a scope-and-severity grid. "Immediate jeopardy" citations — situations that could cause serious injury or death — carry heavy penalty weights and can dramatically lower a facility's health inspection star. The score reflects performance over time: a single bad survey can hurt the rating for up to three years.

Explore facilities by their inspection records on our state pages or search by facility name at PlainNursing Search. For a complete evaluation process, see our choosing a nursing home guide.

2. Staffing

The staffing rating is based on nurse hours per resident per day, sourced from Payroll-Based Journal (PBJ) data — actual payroll submissions, not self-reported estimates. CMS evaluates two staffing measures: RN hours per resident day and total nurse staffing hours per resident day (RN + LPN + CNA combined). Facilities are compared to national medians after adjusting for resident case mix, since higher-acuity residents require more nursing time.

A critical constraint: a facility cannot receive a 4- or 5-star overall rating if it earns only 1 star for staffing. This rule reflects research showing that staffing levels are among the strongest predictors of care quality outcomes. Read our guide on staffing levels explained for benchmarks and what the numbers mean.

3. Quality Measures

Quality measures (QMs) are clinical outcome metrics derived from the Minimum Data Set (MDS), which facilities submit for every resident. CMS tracks separate sets of measures for long-stay residents (those living in the facility long-term) and short-stay residents (those in post-acute rehabilitation). Examples include rates of pressure ulcers, falls with major injury, urinary tract infections, antipsychotic medication use without a diagnosis, and flu/pneumonia vaccination.

Each measure is risk-adjusted to account for resident health status. Facilities that specialize in complex or high-acuity care may still score lower on some measures despite providing excellent nursing care.

How the Overall Rating Is Calculated

The overall star rating is not a simple average of the three component ratings. CMS uses a sequential adjustment method:

  1. Start with the health inspection score as the base.
  2. Add one star if the staffing rating is 5 stars; subtract one star if it is 1 star.
  3. Add one star if the quality measure rating is 5 stars; subtract one star if it is 1 star.
  4. Cap and floor the result so it stays in the 1–5 range.
  5. Apply the constraint: no facility with a 1-star staffing rating can receive an overall rating above 2 stars.

This means a facility with excellent inspection results but chronically thin staffing will be held back. CMS designed this intentionally, viewing adequate staffing as a non-negotiable baseline for quality care.

Limitations of Star Ratings

Star ratings are a useful starting point, but they have documented limitations that families should understand before relying on them exclusively:

  • Survey variability by state: The rigor of health inspections varies significantly across state survey agencies. A 3-star facility in a strict state may provide better care than a 4-star facility in a lenient state.
  • Data lag: Ratings reflect data that can be several months old. A facility that recently changed ownership, lost key staff, or received a serious deficiency may not yet show the impact in its rating.
  • Gaming risk: Some facilities have been found to manipulate MDS submissions to improve quality measure scores. CMS audits for this, but it remains a concern.
  • Acuity adjustment limitations: Risk adjustment for quality measures is imperfect. Facilities serving sicker or more complex populations may be unfairly penalized.
  • What ratings don't measure: Staff turnover, culture, family engagement, food quality, and the overall environment are not captured in star ratings. These factors can matter as much as clinical outcomes to a resident's well-being.

For guidance on translating data into a real-world evaluation, see our guide on choosing a nursing home. You can also browse our national rankings to see how facilities compare across states.

Frequently Asked Questions

Sources

  • Centers for Medicare & Medicaid Services — CMS Nursing Home Compare
  • CMS — Five-Star Quality Rating System Technical Users' Guide (cms.gov)
  • CMS — Payroll-Based Journal (PBJ) staffing data methodology
  • CMS — Minimum Data Set (MDS) 3.0 quality measure specifications

This content is for informational purposes only and does not constitute medical advice. Star ratings are a decision support tool, not a substitute for in-person visits and professional guidance. Always consult a qualified healthcare professional before making care placement decisions.

Understanding the Data

The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.

It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.

For readers who want to conduct their own research, we recommend going directly to the source whenever possible. federal and state government agencies provides detailed documentation on collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.

How We Analyze Data Records

Our analytical approach involves several steps designed to surface meaningful insights from large datasets. First, we clean and standardize the raw data, handling variations in naming conventions, date formats, and categorical labels. Then we compute summary statistics, distributions, and comparative benchmarks across relevant dimensions such as geography, time period, and category type.

Key metrics we examine include statistical records, geographic distributions, temporal trends. These indicators provide a multi-dimensional view of each entity in our database, allowing users to understand not just individual records but how they compare to peers, regional averages, and national benchmarks. We believe this contextual approach is far more valuable than presenting raw numbers in isolation.