A building can hit full occupancy and still bleed margin. Here is how we measure the difference.
Quality occupancy is not retention-based, and it is not acuity-matched. It is both, plus two things operators rarely see in the same view: whether the census is being carried by the schedule or by agency, and whether each occupied unit is accretive at its actual rate net of concessions. SeniorCRE measures occupancy against four tests and scores them as twelve components per community.
SeniorCRE Research·Published ·Updated
Download the Quality Occupancy Score methodology (PDF)Key takeaways
For operators
- Headline occupancy answers one question — how many units are filled today. It says nothing about whether that census is supportable, accretive, or durable.
- The four tests localize the failure. A single failing pillar tells you whether the problem is admissions, the schedule, the rate, or length of stay.
- Referral sources are weighted by contribution margin, not tour volume, so a high-volume net-negative source becomes visible as one.
For capital partners
- Two portfolios at equivalent census are not equivalent assets. Band durability across consecutive periods is the underwriting-relevant signal.
- Unmeasurable components are excluded rather than imputed, and every score publishes its own data completeness — a thin score is legible as thin.
- Band overrides are recorded with actor, timestamp, and reason. Computed score and human judgment are never merged.
The four tests
Every occupied unit is evaluated against all four. Passing three is a finding, not a result — the failure modes operators describe (right census, wrong residents; right residents, no systems to keep them stable) each show up as a single failing pillar.
Clinical fit
Is this resident’s acuity supportable by the care model and staffing actually on that wing?
Not the building average — the wing, the shift, and the licensed depth present when care is delivered. A mis-fit admission absorbed by an already-stretched team can cost more than the resident contributes.
Operational fit
Is the census being carried by the schedule, or by overtime and agency?
Fill that is sustained through open-shift backfill, agency exposure, and med-pass compression is not stable occupancy. It is deferred cost with a clinical risk attached.
Financial fit
Does the unit generate accretive NOI at its actual rate and its actual cost to serve?
Actual rate net of concessions, and actual care cost — not the rack rate in the rent roll. Occupancy is a volume measure; contribution margin is the profitability measure. Quality Occupancy connects the two.
Durability
Will this occupancy still be here, at this rate, in twelve months?
Length of stay, renewal, rate integrity, discharge reason, and hospitalization frequency. Retention is one input band inside durability — it is not the whole definition of quality.
Twelve components, one score
The Quality Occupancy Score is a 100-point weighted composite. Every component carries a published weight, a refresh cadence, and a named data source with lineage back to source rows in the operating record. The score is banded — At Risk, Watch, Stable, Strong — and paired with a directional trend. Weights below are the reference calibration; they are re-fit per operator during onboarding, and any change is versioned so a score is always reproducible against the weights in force when it was computed.
| Component | Pillar | Weight | Cadence | Data source | What it measures |
|---|---|---|---|---|---|
| Acuity-fit index | Clinical fit | 12 | Nightly | Assessment + census records in the operating record | Resident acuity measured against licensed capacity and clinical staffing depth. |
| Care-plan executability | Clinical fit | 8 | Nightly | Clinical system of record (integration not live) | Assessed care plans compared with delivered care events. |
| Incident trend | Clinical fit | 8 | Nightly | Incident and risk log in the operating record | 30/60/90-day incident velocity, weighted by severity. |
| Staffing supportability | Operational fit | 12 | Nightly | Scheduling / timekeeping system (integration not live) | Ratios, agency exposure, PTO overhang, and open-shift density. |
| Med-pass load | Operational fit | 6 | Nightly | eMAR / clinical system of record (integration not live) | Pass count per licensed staff hour, by shift. |
| Compliance posture | Operational fit | 8 | Weekly | Survey and plan-of-correction register in the operating record | Open state findings, plan-of-correction age, and tag exposure. |
| Contribution-margin index | Financial fit | 14 | Nightly | Billing ledger + labor cost feed (integration not live) | Resident-level revenue less true cost-to-serve, including labor and ancillary. |
| Rate-integrity index | Financial fit | 8 | Nightly | Rent roll + concession register in the operating record | Level-of-care accuracy, ancillary capture, and discount discipline. |
| Level-of-care accuracy | Financial fit | 6 | Nightly | Assessment records reconciled against billed level | Assessed acuity compared with billed acuity. |
| Resident tenure | Durability | 10 | Weekly | Move-in / move-out history in the operating record | Projected length of stay against the underwriting assumption. |
| Satisfaction trajectory | Durability | 4 | Monthly | Survey and family-communication records | Resident and family sentiment velocity. |
| Referral-source quality mix | Durability | 4 | Weekly | Referral and admissions pipeline in the operating record | Weighted lifetime value of the community’s active referral portfolio. |
| Total | 100 | ||||
Sources marked “integration not live” describe designed intent. No integration to a third-party system of record is live today; sequencing is agreed per operator during the Operating Record Diagnostic.
Worked example: 92% can score below 86%
Two communities in the same portfolio. Ridgeline is at 92% headline occupancy, filled with rate concessions, off-target acuity, and agency backfill. Brookfield is at 86% with matched acuity, a schedule that covers itself, and stable tenure. Scored against the same twelve components, the higher-census building is the weaker business.
| Component | Weight | Ridgeline (92% census) | Brookfield (86% census) |
|---|---|---|---|
| Acuity-fit index | 12 | 5 / 12 | 11 / 12 |
| Care-plan executability | 8 | 4 / 8 | 7 / 8 |
| Incident trend | 8 | 3 / 8 | 7 / 8 |
| Staffing supportability | 12 | 4 / 12 | 11 / 12 |
| Med-pass load | 6 | 3 / 6 | 5 / 6 |
| Compliance posture | 8 | 5 / 8 | 7 / 8 |
| Contribution-margin index | 14 | 5 / 14 | 12 / 14 |
| Rate-integrity index | 8 | 3 / 8 | 7 / 8 |
| Level-of-care accuracy | 6 | 3 / 6 | 5 / 6 |
| Resident tenure | 10 | 4 / 10 | 9 / 10 |
| Satisfaction trajectory | 4 | 2 / 4 | 3 / 4 |
| Referral-source quality mix | 4 | 1 / 4 | 3 / 4 |
| Quality Occupancy Score | 100 | 42 — At Risk | 87 — Strong |
Illustrative scenario built to demonstrate the scoring mechanics. Community names and component values are hypothetical and are not realized operator results.
Why census, billing, and financial occupancy may disagree
Resident census, operational occupancy, billing, and general-ledger reporting can differ because they measure different events, use different definitions, or reflect different reporting periods. An Operator-Controlled Operating Record does not assume that one source is universally correct. It preserves the evidence, identifies the disagreement, applies operator-authorized definitions, and records which number governs for a specified decision and reporting period.
See the illustrative institutional owner reconciliation example (illustrative: hypothetical figures, not operator results).
What the score refuses to do
A component that cannot be measured is treated as unavailable and excluded from the score. It is never imputed, never estimated from a peer community, and never inherited from a sibling building. Every score reports its own data completeness alongside the number, so a reader can tell the difference between a strong score and a thin one.
Band overrides are allowed and governed. A named senior operator can override a band with written justification; the override is recorded with actor, timestamp, and reason, and stays visible on downstream surfaces. The computed score and the human judgment are never merged into one undifferentiated number.
How it is reported
- Community. Score, band, day-over-day trend, the top three risk drivers, and one recommended action.
- Portfolio. Ranked bands with the divergence view — where headline occupancy and quality occupancy disagree, which is where the operating decision usually is.
- Enterprise and capital. Band durability over consecutive periods, override history, and action-closure record. Two portfolios at equivalent census, one with that record and one without, are different underwriting propositions.
- Referral sources. Weighted by contribution margin rather than tour volume, so a source that looks productive on move-ins and is net-negative on length of stay and cost to serve is visible as such.
The point of the score is not to grade census. It is to make the disagreement legible. Two communities at the same occupancy can be different businesses, and an operator who can see both measures can act on both.
Build status, stated plainly
The four-test framework, the twelve-component score, the banding and override governance, and the community, portfolio, and enterprise reporting surfaces are built in main and built, not yet validated. They have not yet been run against operator production data. Founding Operator deployment dates are not yet scheduled and remain to be determined.
Several components depend on data that lives in clinical, workforce, and financial systems of record. No integration to a third-party system of record is live today; those bands are described as designed intent, and the sequencing is agreed per operator during the Operating Record Diagnostic, which is delivered as an off-platform consulting engagement.
Bring your own portfolio to the framework
The useful version of this conversation is your communities, your acuity mix, and your referral sources against the four tests — including the buildings where headline occupancy and quality occupancy disagree.
Request an Executive BriefingFrequently asked questions
- How does SeniorCRE define "quality" in quality occupancy?
- Quality is defined by four tests applied to each occupied unit: clinical fit (is the acuity supportable by the care model and staffing actually present), operational fit (is the census carried by the schedule rather than overtime and agency), financial fit (does the unit produce accretive NOI at its actual rate net of concessions and its actual cost to serve), and durability (length of stay, renewal, rate integrity, discharge reason, and hospitalization frequency). It is not retention alone and not acuity matching alone — retention sits inside durability and acuity matching sits inside clinical fit.
- Is quality occupancy retention-based or acuity-matched?
- Both, and neither on its own. Retention is measured as resident tenure and satisfaction trajectory inside the durability pillar. Acuity matching is measured as the acuity-fit index and level-of-care accuracy across the clinical and financial pillars. A community can retain residents it should never have admitted, and it can admit perfectly matched residents at rates that do not cover cost to serve. Quality Occupancy is designed to make both failure modes visible in the same view.
- How is the Quality Occupancy Score tracked?
- The Quality Occupancy Score is a 100-point weighted composite of twelve components across the four pillars, each with a defined data source, weight, refresh cadence, and lineage back to source rows in the operating record. It is scored per community and rolled up to portfolio and enterprise. Components that cannot be measured are excluded rather than imputed, and every score reports its own data completeness alongside the number.
- Why can a community be at full occupancy and still lose margin?
- Because headline occupancy answers one question — how many units are filled at a point in time — and says nothing about the four tests. Full census bought with rate concessions, off-target acuity, and agency backfill can compress contribution margin while raising incident frequency and survey exposure. The divergence case is common enough to be a design assumption: a community with lower headline occupancy and a higher Quality Occupancy Score can be the healthier business.
- How are referral sources evaluated under quality occupancy?
- By contribution margin rather than lead or tour volume. A referral source that appears productive on move-ins can be net-negative once length of stay, discharge reason, rehospitalization frequency, and cost to serve are attributed back to it. The referral-source quality mix component is designed to weight a community’s active referral portfolio by lifetime value rather than volume.
- How are score overrides governed?
- A named senior operator can override a band with written justification. Every override is recorded with actor, timestamp, and reason, and remains visible on downstream surfaces. The computed score and the human override are kept distinct so a board or diligence reader can always see which is which.
Related reading
Illustrative figures on this page describe the measurement framework and are not representations of realized operator results. Nothing here is an offer to sell securities or investment advice. SeniorCRE is a registered trademark. Page current as of August 4, 2026.