Live Data Walk Through — No Obligation

You need more than a snapshot in time
to get the full data story.

The data you need — all in one place. In 15-30 minutes, a StarPRO data expert walks you through the complete picture on any nursing home you choose — the history, the trends, and what the data shows about where that facility has been and where it's headed.

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Any facility
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15-30 minutes
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Free data session
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Every data point raises a question.
We have the answers.

CMS Care Compare is just one chapter of a much deeper story. The history behind the data and the context around it only comes from seeing it all together.

Book now and see for yourself what the full story looks like.

Here are some common questions we can help you answer.

An abuse citation — how long does that designation stay on a home and what does it mean while it's there?
CMS adds a red hand designation to any home with recent abuse citations — and it can take 1–2 years to fall off. While active it limits star ratings and signals to hospitals, lenders, and insurers. Full citation history shows the severity, the specific findings, and whether the underlying issues have been resolved.
📈A facility with an abuse flag that is actively remediating looks very different from one that has had multiple citations across several years. History shows you which one you're looking at.
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SFF and SFF Candidates — how long have they been there and are they actually improving?
SFF and SFF Candidate status isn't binary — some facilities enter and exit quickly, others cycle in and out for years. Full SFF history shows how long a facility has been under heightened oversight or on the candidate watchlist, whether they've made measurable progress, and what the realistic path forward looks like.
📈Facilities that show survey score improvement within 12 months of SFF designation have a materially different outlook than those that plateau or worsen. SFF Candidates on a downward trend are worth watching closely.
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The survey score — but what's actually driving it? Sub-standard quality of care tags, harm-level deficiencies, and Immediate Jeopardy citations tell a very different story than the score alone.
Survey scores are built from deficiency tags — and not all tags are equal. A sub-standard quality of care tag triggers automatic star rating penalties. A harm-level (G+) deficiency signals a resident was actually harmed. An Immediate Jeopardy citation is the most serious finding CMS issues — it means residents were or are at risk of serious harm or death. The full tag-level breakdown across all survey cycles shows exactly what's driving the score and how severe the underlying findings really are.
📈Facilities with recurring harm-level or IJ tags across multiple cycles face a fundamentally different regulatory trajectory than those with high deficiency counts driven by lower-severity tags. The tag type matters as much as the count.
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Is a facility's financial loss a new problem or a long pattern?
One year of cost report data can't answer that. Five years of financial history shows whether a margin is compressing steadily, spiked recently, or has always run negative — each tells a very different story about what comes next.
📈Historical trend shows whether a facility is deteriorating, stabilizing, or showing early signs of recovery — before it shows up in the headline numbers.
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Are they paying enough to keep staff — or cutting wages to survive the operating loss?
Wages paid per hour by role, compared to market rates, show whether a facility is competitive enough to attract and retain qualified nurses and aides. Wage data by role shows whether compensation is keeping pace with the market or falling behind — and whether the gap is widening or closing over time.
📈Wage trends relative to the local market and their own history reveal whether a facility is investing in its workforce or quietly hollowing it out to manage cash flow.
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Who has actually been running the facility and what's their track record?
Ownership history matters — especially for troubled facilities. Full ownership and operator analysis shows when current management took over, what ratings looked like before and after, and how their other facilities have performed.
📈Full ownership history lets you see the difference and draw your own conclusions.
This is the data that validates decisions.
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Is the star rating going to improve, stay flat, or get worse?
Star ratings are based on points accumulated from survey deficiencies, staffing levels, and quality measures. Knowing where a facility is losing the most points tells you exactly where improvement efforts will have the fastest impact on the overall rating.
📈Understanding the point breakdown across all three domains shows which lever to pull first — and how close a facility is to gaining or losing a star on its next survey cycle.
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A facility can show adequate staffing on paper and still be losing its best people every 90 days.
Turnover rates tell you something raw staffing hours don't — whether the staff showing up are experienced or constantly being replaced by agency workers and new hires. High turnover correlates directly with survey deficiencies, quality measure declines, and resident safety events.
📈Is turnover accelerating or improving quarter over quarter? A facility with declining turnover is building institutional knowledge. One with rising turnover is quietly destabilizing — often before the next survey catches it.
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Is a facility's reliance on agency staffing growing or shrinking over time?
Agency staffing is expensive and disruptive — it signals a facility can't consistently fill shifts with its own employees. Agency usage trends over time show whether a facility is stabilizing its workforce or becoming increasingly dependent on outside staff to keep the doors open.
📈Rising agency usage quarter over quarter is one of the earliest warning signs of operational instability — it shows up in the data long before it shows up in survey results or star ratings.
The full data story is waiting. Pick your facility and see it live.
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Strong occupancy but losing money — what's actually eating the revenue?
High occupancy and negative margins mean the problem is reimbursement mix, not census. Full payer mix detail shows exactly how much of that occupied census is Medicaid vs. Medicare A vs. managed care — and what each is actually paying.
📈A payer mix shifting toward lower-reimbursing payers explains margin compression before it shows up in the bottom line.
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How does a facility's Medicare A mix and length of stay compare to every competitor fighting for the same short-stay patients?
Medicare A short-stay patients are the highest-reimbursing population in a SNF — and every facility in the market is competing for the same referrals. ALOS by payer combined with full market comparison shows whether a facility is maximizing its highest-value census or losing days and referrals to competitors down the road.
📈Is Medicare A as a share of the mix growing or shrinking relative to the local market? Losing short-stay rehab referrals shows up in payer mix before it shows up in revenue.
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A facility ranks near the bottom of its local market — has it always, or is this a recent slide?
A low ranking is the current snapshot. Historical market positioning shows whether a facility was mid-pack two years ago and has been deteriorating, or whether it has always been at the bottom. That changes everything about how you read the current standing.
📈Full market positioning history shows whether a facility is gaining or losing ground relative to competitors over time.
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What were the fines and payment denials actually for — and are the same problems recurring?
Fine amounts don't tell you which survey tags triggered them. Tag-level deficiency detail across all survey cycles shows the specific failures — and whether the same issues keep appearing despite remediation.
📈Recurring tags across cycles are a strong predictor of continued regulatory exposure and SFF status that doesn't resolve on its own.
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What do extended admission bans actually do to a facility's revenue?
Denial periods are quantifiable revenue events — no Medicare reimbursement for new admissions during those windows. Full detail shows the overlap between denial periods and census dips, making the true financial impact visible.
📈Are denial periods getting shorter or longer? A facility whose most recent denial was significantly shorter than prior ones may be getting its compliance act together — or not.
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Is CMS adjusting this facility's Medicare reimbursement up or down — and by how much?
Value-Based Purchasing means a facility's actual Medicare reimbursement is higher or lower than the base rate depending on quality performance. A facility already losing money on operations may also be receiving a VBP penalty that compounds the problem. VBP adjustment history makes that visible.
📈VBP adjustment history shows whether a facility's reimbursement environment is improving or worsening independent of payer mix shifts — a dimension most analyses miss entirely.
The story behind the data is there, let us show you.
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15-30 minutes. Any facility you want. A StarPRO data expert walks you through the full picture.