UNIVERSITY HOSPITALS SUSSEX NHS FOUNDATION TRUST
7,501
Bed days above the simple monthly median counterfactual.
Provider benchmarking
Use variation to decide where to investigate, not who to blame.
The first national study uses July 2026 NHS England discharge-ready-date data. Rankings are investigation signals only and do not prove waste, poor care or recoverable savings.
Providers128
Provider records
4,096 provider measure rows used.Median0.89 days
Average delay
Provider median after discharge readiness.Upper quartile1.18 days
Average delay
25% of included providers sit above this level.Same day85.3%
Median rate
Discharged on the recorded ready date.Investigation signals
Where is delay materially above the national pattern?
Minimum 100 discharges. These are prompts for operational investigation.
| Provider | Average delay | Delayed bed days | Same day | 21+ days |
|---|---|---|---|---|
| UNIVERSITY HOSPITALS SUSSEX NHS FOUNDATION TRUST SOUTH EAST | 2.16 days | 12,736 | 84.9% | 3.4% |
| EAST SUSSEX HEALTHCARE NHS TRUST SOUTH EAST | 2.15 days | 5,562 | 75.3% | 2.9% |
| JAMES PAGET UNIVERSITY HOSPITALS NHS FOUNDATION TRUST EAST OF ENGLAND | 2.07 days | 2,705 | 73.3% | 2.4% |
| SOMERSET NHS FOUNDATION TRUST SOUTH WEST | 2.00 days | 6,869 | 80.8% | 2.6% |
| MEDWAY NHS FOUNDATION TRUST SOUTH EAST | 1.96 days | 3,517 | 76.4% | 1.7% |
| COUNTESS OF CHESTER HOSPITAL NHS FOUNDATION TRUST NORTH WEST | 1.89 days | 3,231 | 83.8% | 2.8% |
| NORTH CHESHIRE AND MERSEY NHS FOUNDATION TRUST NORTH WEST | 1.78 days | 2,849 | 83.3% | 2.6% |
| ISLE OF WIGHT NHS TRUST SOUTH EAST | 1.68 days | 1,543 | 70.2% | 1.4% |
| NORTHAMPTON GENERAL HOSPITAL NHS TRUST MIDLANDS | 1.66 days | 3,784 | 72.9% | 1.2% |
| PORTSMOUTH HOSPITALS UNIVERSITY NHS TRUST SOUTH EAST | 1.66 days | 6,271 | 75.7% | 1.6% |
Counterfactual screen
What sits above a simple national-median scenario?
This is an investigative screen only, not a savings forecast.
SOMERSET NHS FOUNDATION TRUST
3,811
Bed days above the simple monthly median counterfactual.
EAST SUSSEX HEALTHCARE NHS TRUST
3,263
Bed days above the simple monthly median counterfactual.
MERSEY AND WEST LANCASHIRE TEACHING HOSPITALS NHS TRUST
3,146
Bed days above the simple monthly median counterfactual.
PORTSMOUTH HOSPITALS UNIVERSITY NHS TRUST
2,912
Bed days above the simple monthly median counterfactual.
LEEDS TEACHING HOSPITALS NHS TRUST
2,577
Bed days above the simple monthly median counterfactual.
Benchmarking rules, source coverage and verified examples
No crude league tables
- Compare like with like: acute teaching trusts, district general hospitals, specialist trusts and community providers should not be ranked as one undifferentiated group.
- Use rates and denominators, not raw counts alone.
- Require a minimum activity volume before flagging an outlier.
- Separate case-mix and structural constraints from avoidable operational variation.
- Show trend alongside current position so improving providers are not labelled solely by historic performance.
- Never convert statistical variation directly into cashable savings without pathway-level validation.
- Flag data-quality limitations and methodology breaks explicitly.
- Use benchmark variation to trigger investigation, not to declare poor care.
Available benchmark sources
Hospital flow
Bed days after discharge-ready date and threshold-based discharge performance
Source: NHS England, Discharge Ready Date ↗Hospital flow
Patients no longer meeting criteria to reside, non-discharges, delay reasons and additional days
Source: NHS England, Acute Discharge Situation Report ↗Elective care
Referral-to-treatment waiting list activity and pathway performance
Source: NHS England, Consultant-led RTT Waiting Times ↗Cross-domain productivity
Selected quality, productivity and responsiveness benchmarks across specialties and workforce
Source: NHS England, Open Model Health System ↗Theatres and productivity
Theatre utilisation, cancellations, length of stay and specialty productivity metrics
Source: NHS England, Model Health System ↗System flow
Average discharge delay, non-elective admissions and long-term care admissions
Source: NHS England, Better Care Fund 2026/27 planning data ↗Examples of improvement
Chesterfield Royal Hospital NHS Foundation Trust
232 additional patients treated between April and December 2024; daily cases rose from 2.8 to 3.5; lists overrunning materially reduced
This is evidence that better scheduling and visibility can convert theatre time into additional treated patients. It is a case study, not a national effect estimate.
Source ↗Kingston Hospital NHS Foundation Trust
Scheduling information was consolidated from fragmented spreadsheets and systems, reducing manual administrative work and improving theatre planning
The operational lesson is that data fragmentation itself consumes staff time and weakens scheduling decisions even before clinical capacity loss is counted.
Source ↗Benchmarking should answer one question: where is variation large enough that somebody should investigate why?