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CMS certification 330250

The University of Vermont Health Network - Champl

75 Beekman Street, Plattsburgh, NY 12901

Acute Care Hospitals Emergency services Birthing-friendly

The University of Vermont Health Network - Champl has a CMS overall rating of 2 out of 5 stars. 60% of patients who answered CMS's national survey would definitely recommend it, against a US average of 71%. Of the 24 death, complication, infection and readmission measures CMS could compare, it does better than the nation on 2 and worse on 4. Emergency patients spend a median of 3 h 43 min in its emergency department before leaving (US median 2 h 42 min).

Every figure on this page is published by CMS; we arrange and explain it, and score nothing ourselves.

CMS overall rating 2/5 CMS summary of quality measures
Would definitely recommend 60% US average 71%
Patient survey rating 3/5 462 completed surveys
Compared with the nation 4 worse 2 better of 24 measures CMS could compare

What patients said

Answers from patients who stayed here, collected by CMS in the national HCAHPS survey: 462 completed surveys, 23% response rate, Oct 2024 – Sep 2025.

Would definitely recommend the hospital
60%
NY 67% · US 71% · 2 of 5 stars
Rated the hospital 9 or 10 out of 10
61%
NY 66% · US 72% · 2 of 5 stars
Nurses always communicated well
79%
NY 77% · US 80% · 3 of 5 stars
Doctors always communicated well
80%
NY 77% · US 80% · 3 of 5 stars
Staff always explained new medicines
60%
NY 59% · US 62% · 3 of 5 stars
Given information about recovering at home
87%
NY 85% · US 86% · 3 of 5 stars
Room was always clean
67%
NY 69% · US 74% · 3 of 5 stars
Always quiet at night
47%
NY 49% · US 60% · 2 of 5 stars

This hospital New York average US average

Emergency department

How long emergency patients spent here and how some time-critical care went, from CMS's timely and effective care measures, Oct 2024 – Sep 2025. CMS classes this emergency department's patient volume as high; busier departments tend to have longer times, so the national median for departments of the same volume is shown too. These are medians over a year of visits, not a live wait time.

Measure This hospital NY US
Median time in the emergency department before leaving Lower is better · 544 visits sampled · US median for EDs of the same volume: 3 h 22 min 3 h 43 min 3 h 14 min 2 h 42 min
Median time for psychiatric and mental health patients Lower is better · 29 visits sampled 6 h 38 min 4 h 54 min 4 h 17 min
Left before being seen Lower is better · 40,050 patients 2% 2% 2%
Stroke symptoms: brain scan read within 45 minutes Higher is better · 25 patients 48% 67% 69%
Severe sepsis and septic shock: all recommended care given Higher is better · 534 patients 48% 60% 65%

How The University of Vermont Health Network - Champl compares with nearby hospitals

The closest hospitals of the same kind that CMS rates or surveys - the same city first, then the same county and ZIP area. Every figure is CMS's: the overall star rating, the share of patients who would definitely recommend the hospital, the median time emergency patients spent before leaving, and how many death, complication, infection and readmission measures CMS found better or worse than the national rate.

Hospital CMS stars Would recommend ER median time Vs the nation
The University of Vermont Health Network - ChamplThis hospital2/560%3 h 43 min2 better 4 worse
Elizabethtown Community HospitalSame ZIP area · Elizabethtown4/592%1 h 49 minNo different
The University of Vermont Health Network-Alice HySame ZIP area · Malone1/557%2 h 38 min1 worse
Adirondack Medical Center - Saranac LakeSame ZIP area · Saranac Lake4/583%2 h 16 min1 better 1 worse

Hospitals differ in size and in how sick their patients are. CMS adjusts its outcome measures for that, but a star or a percentage is a starting point for questions, not a verdict.

Deaths

How many patients died within 30 days of admission, adjusted by CMS for how sick they were. Lower is better. Data from Jul 2022 – Jun 2025.

Measure CMS comparison This hospital National
All patients, hospital-wide 2,077 cases Too few cases 3.7% 3.9%
Heart attack 243 cases Too few cases 12.3% 11.9%
Heart failure 432 cases Too few cases 12.4% 11.1%
Pneumonia 482 cases Too few cases 14.6% 15.2%
Stroke 127 cases Too few cases 12.6% 11.9%
COPD 169 cases Too few cases 7.7% 8.6%

1 more measure had too few cases here to report.

Complications

How often patients had serious complications, most of them after surgery, adjusted for how sick they were. Lower is better. Data from Jul 2022 – Jun 2024.

2 worse than the nation 10 no different
Measure CMS comparison This hospital National
Serious complications, combined measure Worse 2.02 likely 1.67 – 2.37 1
After hip or knee replacement 44 cases Too few cases 4.5% 4.1%
Deaths after a serious but treatable surgical complication 43 cases No different 186.74 per 1,000 likely 129.09 per 1,000 – 244.4 per 1,000 173.3 per 1,000
Pressure ulcers (bed sores) 4,478 cases Worse 4.02 per 1,000 likely 3.29 per 1,000 – 4.76 per 1,000 0.63 per 1,000
Collapsed lung caused by a procedure 4,993 cases No different 0.2 per 1,000 likely 0 per 1,000 – 0.4 per 1,000 0.21 per 1,000
Broken bones from falls in the hospital 4,990 cases No different 0.27 per 1,000 likely 0.07 per 1,000 – 0.47 per 1,000 0.27 per 1,000
Bleeding or hematoma after surgery 818 cases No different 2.22 per 1,000 likely 0.64 per 1,000 – 3.8 per 1,000 2.34 per 1,000
Kidney injury needing dialysis after surgery 227 cases No different 1.51 per 1,000 likely 0 per 1,000 – 3.16 per 1,000 1.67 per 1,000
Breathing failure after surgery 236 cases No different 10.46 per 1,000 likely 3.09 per 1,000 – 17.83 per 1,000 9.42 per 1,000
Blood clots in the lungs or legs after surgery 828 cases No different 4.01 per 1,000 likely 1.77 per 1,000 – 6.25 per 1,000 3.52 per 1,000
Sepsis after surgery 192 cases No different 5.36 per 1,000 likely 1.32 per 1,000 – 9.4 per 1,000 5.27 per 1,000
Surgical wound splitting open 140 cases No different 2.31 per 1,000 likely 0.83 per 1,000 – 3.8 per 1,000 1.77 per 1,000
Accidental cut or tear during abdominal surgery 731 cases No different 0.9 per 1,000 likely 0 per 1,000 – 1.91 per 1,000 1.06 per 1,000

Infections caught in the hospital

Standardized infection ratio: 1.0 means as many infections as CMS predicted for a hospital like this one. Lower is better. Data from Oct 2024 – Sep 2025.

1 worse than the nation 4 no different
Measure CMS comparison This hospital National
Bloodstream infections from central lines (CLABSI) No different 0.26 likely 0.01 – 1.26 1
Urinary tract infections from catheters (CAUTI) No different 1.12 likely 0.41 – 2.48 1
Surgical site infections after colon surgery Worse 2.54 likely 1.18 – 4.83 1
MRSA bloodstream infections No different 0.25 likely 0.01 – 1.25 1
C. diff intestinal infections No different 1.09 likely 0.78 – 1.49 1

1 more measure had too few cases here to report.

Readmissions and return visits

How often patients had to come back to a hospital after going home. Lower is better. Data from Jul 2023 – Jun 2025.

4 no different
Measure CMS comparison This hospital National
Readmitted after a heart attack 318 cases Too few cases 14.2% 14.4%
Readmitted after heart failure 512 cases Too few cases 23.7% 21.3%
Readmitted after pneumonia 504 cases Too few cases 17.4% 17.3%
Readmitted after COPD 268 cases Too few cases 20.6% 20%
Readmitted after hip or knee replacement 44 cases Too few cases 6.1% 5.8%
Days back in hospital after a heart attack 230 cases Too few cases -0.1 days per 100 —
Days back in hospital after heart failure 454 cases Too few cases 103.6 days per 100 —
Days back in hospital after pneumonia 471 cases Too few cases 10 days per 100 —
Unplanned visits after an outpatient colonoscopy 1,850 cases No different 13.7 per 1,000 likely 10.8 per 1,000 – 17.4 per 1,000 13 per 1,000
Hospital admissions during outpatient chemotherapy 212 cases No different 12.3 per 100 likely 9.4 per 100 – 15.9 per 100 10.7 per 100
ER visits during outpatient chemotherapy 212 cases No different 4.3 per 100 likely 2.9 per 100 – 6.3 per 100 5.4 per 100
Unplanned visits after outpatient surgery 667 cases No different 1 likely 0.7 – 1.3 —

2 more measures had too few cases here to report.

Clinicians registered at this address

198 clinicians give this hospital's street address as their practice location in NPPES, the federal provider registry. The same address can take in offices and clinics in the building, and a listing does not prove admitting privileges or current employment.

Specialty Clinicians
Emergency Medicine 22
Internal Medicine 18
Physical Therapist 17
Physician Assistant 17
Anesthesiology 14
Family 11
Occupational Therapist 9
Pharmacist 7
Anatomic Pathology & Clinical Pathology 5
Hospitalist 5
Psychiatry 5
Speech-Language Pathologist 5

First 12 alphabetically

Money from drug and device companies

Drug and device makers have to report what they pay teaching hospitals to CMS's Open Payments program. At many teaching hospitals most of it is research funding, or royalties for inventions the hospital licensed to a company. A payment on its own does not show a conflict of interest.

2025 total $3,416 general $3,416 · research $0
All years, 2019–2025 $155,686 70 reported payments
  • 2019 $44,118
  • 2020 $25,226
  • 2021 $40,737
  • 2022 $36,915
  • 2023 $2,829
  • 2024 $2,445
  • 2025 $3,416

General payments Research payments

What the 2025 general payments were for

Type of payment Amount Payments
Debt forgiveness $2,485 6
Space rental and facility fees $500 1
Medical devices and supplies on long-term loan $431 1

Largest paying companies, 2025

Company Amount Payments
Stryker Corporation $2,033 5
B. Braun Interventional Systems Inc. $694 1
Novo Nordisk Inc $500 1
Aesculap, Inc. $189 1

Amounts are as the paying companies reported them to CMS; Open Payments data retrieved 13 Sep 2026. Full record on CMS Open Payments.

How to read this page

  • Everything here is published by CMS on Care Compare. We arrange it and explain it; the star ratings and the better / worse verdicts are CMS's, not ours.
  • “No different” is the most common result on most measures at most hospitals. CMS only calls a result better or worse when the difference from the national rate is statistically clear.
  • Death, complication and readmission rates are adjusted by CMS for how sick patients were, so hospitals that treat sicker patients can be compared fairly.
  • Infection results are ratios: 1.0 means as many infections as CMS predicted for a hospital like this one, below 1.0 is fewer.
  • These are hospital-wide results. They do not rate an individual doctor, nurse or department, and they are not medical advice.

CMS Care Compare data retrieved 4 Oct 2026, refreshed weekly. Where this data comes from and how we handle it · Report an error

Common questions about The University of Vermont Health Network - Champl

Is The University of Vermont Health Network - Champl a good hospital?

The University of Vermont Health Network - Champl has a CMS overall rating of 2 out of 5 stars. Of the 24 death, complication, infection and readmission measures CMS could compare, it does better than the nation on 2 and worse on 4. These are hospital-wide results published by CMS; they do not rate individual doctors or departments.

Would patients recommend The University of Vermont Health Network - Champl?

60% of patients who answered CMS's national survey would definitely recommend it, against a US average of 71%. The figure comes from 462 completed HCAHPS surveys.

How long is the wait in the The University of Vermont Health Network - Champl emergency room?

Emergency patients spend a median of 3 h 43 min in its emergency department before leaving (US median 2 h 42 min). Among US emergency departments with high patient volume, like this one, the median is 3 h 22 min. 2% of emergency patients left before being seen (US 2%). These are medians over a year of visits, not a live wait time.

Does The University of Vermont Health Network - Champl receive money from drug and device companies?

Drug and device makers reported $3,416 in payments to The University of Vermont Health Network - Champl for 2025, under the federal Open Payments program. A payment on its own does not show a conflict of interest.