California Nursing ObservatoryPublic evidence for nurses
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A nurse in rose-pink scrubs watches changing weather and operational signals above California hospitals

Check the forecast before you clock in.

A hospital weather report for the nurses working inside it.

You wouldn’t plan a trip without checking the weather. Why accept a hospital job without checking the conditions? Look beyond the posting at nursing workforce, contract reliance, staffed capacity, and the questions management still needs to answer.

Before you accept the jobSee the conditions behind the offer.

Is the workforce recovering? Are travelers filling the gaps? Are more patients competing for fewer staffed beds? Follow the evidence—and the questions it cannot answer.

444facility identities listed
56California counties
30reviewed pilot profiles · 26 audited / 4 pending
0manufactured safety scores

The public reports are the raw material. The reconstruction is the work.

The Observatory does not merely display pages from a state filing. It connects separate reporting systems, reconciles hospital identities and campus boundaries, preserves incompatible years and denominators, tests whether comparisons are defensible, and leaves contradictions visible when the evidence will not support a clean answer.

Inspect the 27-sheet, 739-formula model →
01 / MatchWhich hospital does this number actually describe?

Stable facility IDs, licenses, campus records, ownership, and consolidated reporting boundaries are checked before figures are combined.

02 / ReconcileDo the periods and denominators line up?

Workforce, capacity, utilization, and operational records keep their original years and definitions. A mismatch is disclosed—not silently repaired.

03 / CompareIs the peer group defensible?

Hospitals are matched by reporting category, ownership, and size when the sample permits. Unlike facilities are not pooled to manufacture a benchmark.

04 / InterpretWhat can a nurse responsibly conclude?

The model separates observations from safety claims, keeps unknown values unknown, and turns missing bedside data into specific questions to ask.

Burn-capacity pressure reconstructedFresno’s ten-bed burn service used 88%–90% of licensed bed-days before Bakersfield’s closure.
Reporting boundary uncoveredKaiser Modesto’s individual picture disappears inside a combined Modesto–Manteca filing.
Campus scope correctedOak Valley’s 144-bed reporting total includes a 115-bed nursing facility; the acute hospital has 29 beds.

Built by a nurse. Open to anyone.

The California Nursing Observatory is an independent, free resource for nurses, researchers, journalists, and anyone seeking a clearer view of hospital workforce conditions. Public records are presented alongside their limitations—not manufactured scores or claims the evidence cannot support.

Independent and free to explore. Missing information remains unknown; public data does not establish bedside staffing or patient safety.

It started with a question.

Have California hospitals returned to their pre-pandemic baseline?

That question opened a bigger one: what can publicly reported data actually tell us about the condition of the nursing-care system?

California Nursing Observatory weather-station gauges tracking staffed capacity, contract dependence, nursing capacity, patient demand, and operational pressure
A weather station for the nursing-care system.
What the question became

A weather report for the hospital.

A weather report does not rely on temperature alone. It reads temperature, wind, pressure, and visibility together to describe the conditions.

We do the same with publicly reported hospital data: consider nursing capacity, contract dependence, staffed beds, patient demand, and operational pressure together—and see how much of the picture emerges.

The result is not a made-up safety score. It is a clearer view of the conditions, the changing signals, and what remains out of sight.

What can you do with a hospital forecast?

A job posting tells you the hospital is hiring. The Observatory helps you investigate the conditions behind the offer—and ask the questions the posting leaves out.

01 / Before you apply

See past the recruiting pitch.

This helps you prepare, not decide. Is this hospital rebuilding its nursing workforce—or still leaning on travelers? Check contract reliance, reported nursing hours, and staffed beds before you sign.

02 / Before the interview

Walk in with sharper questions.

Missing information is a reason to ask, not evidence that a problem does not exist. Does the charge nurse carry patients? Are there dedicated break nurses, resource nurses, and real orientation? Use the missing answers to guide the conversation.

03 / When you compare offers

Compare conditions—not promises.

This supports comparison, not a claim that unlike hospitals are interchangeable. Put workforce, contract labor, and staffed capacity side by side. See what each hospital reports, what changed, and where meaningful information is missing.

04 / When you raise concerns

Bring evidence into the room.

Observed patterns are not proof of causation, unsafe care, or a legal violation. Support staffing-committee discussions, workplace questions, union conversations, community inquiries, or requests for information with cited public records.

05 / If you already work there

Check what your experience lines up with.

A hospital-wide filing never replaces the bedside story. Does the public record reflect the pressure you feel? Compare contract dependence, staffing capacity, and historical trends with what you see on the floor.

06 / When the system stays quiet

See what hospitals do not disclose.

UNKNOWN stays visible. UNKNOWN never becomes zero. Missed breaks, actual assignments, unit turnover, educator support, and workplace harm often disappear from public reporting. The blank spaces matter too.

A nurse compares two California hospitals experiencing distinctly different operational weather conditions

Compare the forecast.

Two hospitals. Two different conditions. See what the public record reveals before you decide where to work.

Compare two hospitals ↓

Choose the hospitals you want to compare.

Start with a county, search by hospital name, and compare the measures without an invented safety score.

First hospital
Second hospital

These hospitals have different ownership models (investor-owned versus nonprofit). Their benchmarks use separate ownership-matched peer groups where sufficient records exist.

Publicly reported measureDoctors Medical Center - ModestoMemorial Hospital Modesto
Contract RN shareHow much reported nursing work came from contract, agency, or registry nurses.2024 workforce report
Doctors Medical Center - Modesto2.0%
Memorial Hospital Modesto1.8%
RN hours per patient dayHospital-wide reported RN intensity—not your unit assignment or a staffing ratio.2024 workforce report
Doctors Medical Center - Modesto12.9
Memorial Hospital Modesto17.4
Pre-pandemic contract baselineThe hospital's own historical contract reliance when its earlier identity can be matched.2018–2019 baseline
Doctors Medical Center - Modesto6.2%
Memorial Hospital Modesto2.8%
Staffed versus licensed bedsBeds reported with staffing compared with the hospital's reported licensed beds.2025 capacity report
Doctors Medical Center - Modesto342 / 461
Memorial Hospital Modesto316 / 419
Staffed share of licensed bedsReported staffed beds divided by reported licensed beds—not a closed-unit count.2025 capacity report
Doctors Medical Center - Modesto74.2%
Memorial Hospital Modesto75.4%
Ownership and sizePeer context uses reporting category, ownership, and licensed-bed size when at least five usable matches exist.Facility reporting context
Doctors Medical Center - Modestoinvestor-owned · 400+ beds
Memorial Hospital Modestononprofit · 400+ beds
Evidence availableWhether the facility received additional pilot review or has descriptive public data only.Evidence review status
Doctors Medical Center - ModestoVerified pilot
Memorial Hospital ModestoReviewed · filing pending

Contract reliance is below the peer median · below its own pre-pandemic level · 74.2% of licensed beds reported staffed · combined campus/license reporting scope.

Contract reliance is below the peer median · below its own pre-pandemic level · 75.4% of licensed beds reported staffed.

Still unknown for both: actual assignments, charge-nurse coverage, missed breaks, overtime, turnover, acuity, and unit-specific conditions.

Find a California hospital.

444 hospitals · Most listings are not yet independently reviewed · Most listings are not yet independently reviewed

444 hospitalsNo composite scores · Unknown never means zero

Ask the public record.

How much does this hospital rely on contract nurses? How does it compare with similar hospitals? What share of licensed beds are staffed? Choose a hospital and get answers grounded in the available public record. Answers are generated from CNO's own dataset and may be incomplete or out of date. Always verify a figure against the linked source before citing it, and treat any answer outside the published metrics as unverified.

What can the evidence tell you?

Start with the questions public records can answer. We will show the numbers, explain their context, and flag what still needs to be asked in an interview.

What the larger pilot actually found.

Thirty hospitals received facility-specific review. These findings describe the reliability and limits of their public records, not whether any hospital or nursing unit is safe.

Facility-level evidence review30 of 30 reviewed

Hospital identity, reporting category, financial-filing status, workforce figures, capacity records, and comparison boundaries were examined.

Financial filing status26 audited · 4 pending

Hospitals with financial filings still in process remain visible and clearly distinguished from hospitals with audited filings.

Capacity reporting conflicts2 require reconciliation

Reported staffed beds exceed reported licensed beds in two hospital records. Capacity percentages are withheld until the reporting scopes can be reconciled.

Workforce denominator limitations25 contract · 28 RN intensity

Reported contract shares or RN intensity cannot be independently recreated from the other displayed fields. Different source definitions and 2024-versus-2025 reporting windows remain visible.

What changed at the five hospitals we studied?

These findings describe only Doctors Modesto, Memorial Modesto, UC Davis, San Joaquin General, and Adventist Sonora. They are not statewide results.

Hospital-wide RN hours per patient day3 of 5 declined

Doctors Modesto, UC Davis, and Adventist Sonora reported fewer RN hours per inpatient day. Memorial Modesto and San Joaquin General reported more.

Number of staffed hospital beds3 of 5 increased

Memorial Modesto, UC Davis, and Adventist Sonora added staffed beds. Doctors Modesto and San Joaquin General each reported 21 fewer.

How much licensed-bed capacity was used3 of 5 increased

Licensed-bed occupancy increased at Memorial Modesto, UC Davis, and Adventist Sonora; it decreased at Doctors Modesto and San Joaquin General.

RN share of nursing labor hoursAll 5 increased

Each pilot hospital reported a larger RN share of combined RN, LVN, and aide hours. The measure does not reveal whether support staffing was sufficient.

Five different stories.

Select a hospital, then change the evidence layer. Unlike time windows remain visibly separate.

Community / for-profit

Doctors Medical Center – Modesto

Facility RN proxy
2022 · 2023 · 2024
Facility RN proxy-4.0%2022–2024 · hospital-wide
Med-surg RN HPPD-15.6%2022–2023 · cost center
Weighted inpatient RN HPPD-11.8%2022–2023 · varying unit blend
Supported interpretation

Facility RN intensity fell 4.0% in 2022–2024. In the earlier unit window, med-surg and weighted inpatient RN HPPD fell 15.6% and 11.8%. The unit evidence localizes the earlier change, but it is not shift-level staffing.

Best next evidence

Quarterly unit staffing, acuity, overtime, missed-break and ratio records.

Functional nursing capacity has four parts.

The pilot is strongest in resources and demand. Sustainability and care completion remain the decisive gaps.

1

Nursing resources

How much nursing capacity was available?

Partly observable
2

Work demand

What was nursing being asked to absorb?

Partly observable
3

Workforce sustainability

Can the workforce continue doing it?

Mostly missing
4

Care completion

Was necessary nursing work completed?

Mostly missing

Unknown is a finding—not reassurance.

These measures may determine whether reported capacity translated into workable nursing conditions.

Missing measureWhy it mattersCurrent status
Shift/unit RN:patient assignmentsDirect workload realityNot publicly standardized
Missed meal and rest breaksImmediate overload signalNo reliable public facility feed located
Overtime and mandatory overtimeWhether nominal capacity is sustainableFragmented labor records
Turnover, vacancies and first-year attritionWorkforce stabilityNot consistently public by hospital
Missed or delayed nursing careWhether necessary nursing work was completedRarely collected for public use
Acuity and assignment complexityDemand per nurse, not merely patient countUnavailable in standardized public data

Every ladder rung stays inspectable.

Sources, age, denominator, definition, missingness and limitations remain visible. This is not a safety rating, causal claim or statewide trend.

Never pool unlike hospitalsPeer type and service mix remain visible.
Never hide missingnessUnavailable information stays unknown.
Never equate capacity with safetySafety requires direct evidence.
Never manufacture one scoreThe contradictions are important.

Follow every source back to its original file.

These source files document the original longitudinal pilot only. Statewide directory records and 2025 capacity figures have separate reporting scope and should not be represented as coming from these six files.

AFD-2022Annual selected financial · 2022October 2024 extract

Original file: hadr-2022.xlsx

SHA-256: c401ad8434633231387c4728e4082ac144035f192d8e3eb4486d0cbecaf21b29

Archived size: 779,866 bytes

Download original public source ↗
AFD-2023Annual selected financial · 2023October 2025 extract

Original file: hadr-2023.xlsx

SHA-256: a1e6def0758349901fb6024632ec808664a9e0d2c9465780dbf4b9159c792d19

Archived size: 783,155 bytes

Download original public source ↗
AFD-2024Annual selected financial · 2024April 2026 extract

Original file: hadr-2024.xlsx

SHA-256: 0fcc4c3c52f335adc63699cf65d5ecbe28b94bb2d20433508cfe799e82541e26

Archived size: 788,481 bytes

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AUR-2022Annual utilization · 2022Revised final 2023-11-28

Original file: hosp22_util_data_final_revised_11.28.2023.xlsx

SHA-256: e94af1efd72ea5eec5d8db0302c3cb9f7070d0eac794be60d51909df5beaa466

Archived size: 586,048 bytes

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AUR-2023Annual utilization · 2023Final November 2024

Original file: hosp23_util_data_final.xlsx

SHA-256: 26de94367bc4c9056a18cd7517dbedc377bb2dea6d9b54627a4c87dd43a1c9f1

Archived size: 598,028 bytes

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AUR-2024Annual utilization · 2024Final October 2025

Original file: hosp24_util_data_final.xlsx

SHA-256: f423f999c729ee333169bd161ade11550158d5147ae1ed91c1cfafe2d3e6f953

Archived size: 584,496 bytes

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