Version: 1.0.0 | Published: 21 Aug 2026 | Updated: 0 days ago
Summary
Documentation
Associated Media:
Description:
The SUS (Secondary Uses Service) Unified Admitted Patient Care dataset is essentially the national, standardised record of every inpatient admission to NHS-funded hospitals in England. It captures the full journey of an admitted patient (from admission to discharge) and is designed for secondary uses such as research, planning, commissioning, quality improvement and population health analytics.
SUS APC is one of the most powerful datasets for understanding how inpatient care is delivered and how it can be improved.
That data set includes:
1. Core patient and administrative details such as Demographics (age, sex, ethnicity), GP practice and geographic identifiers, Admission method (elective, emergency, maternity, transfer), Admission source (home, A&E, other hospital).
2. Clinical information such as Diagnoses coded using ICD-10, Procedures/interventions coded using OPCS-4, Comorbidities and complications recorded during the stay, Maternity-specific fields (if relevant).
3. Activity and episode structure including Consultant episodes (each time care transfers to a new consultant team), Episode start/end dates, Length of stay, Ward type and specialty, Discharge destination (home, care home, other hospital, deceased).
4. Operational and performance-related fields such as HRG (Health Resource Group) codes used for costing, Provider identifiers (trust, site, specialty).
5. Financial and commissioning data including Tariff information, Payment and commissioning codes, Flags for specialised services.
It excludes private hospital activity unless NHS-funded.
Researchers use the SUS Admitted Patient Care dataset to understand patterns, outcomes, and pressures within inpatient care. The most valuable elements typically include:
1. Understanding disease burden and comorbidities by using ICD 10 diagnosis fields, which allows:
- Case-mix adjustment
- Identification of multimorbidity patterns
- Tracking trends in specific conditions (e.g., frailty, diabetes, COPD)
2. Evaluating quality of care and outcomes which supports:
- Mortality analysis (in-hospital death flags)
- Readmission studies (linking episodes over time)
- Complication rates
- Length-of-stay benchmarking
- Variation between providers or regions
3. Studying care pathways by using episode-level detail, which helps researchers:
Map patient journeys across specialties, Identify delays or bottlenecks, Understand how transfers between teams affect outcomes.
4. Health inequalities research which use demographic fields (age, ethnicity, deprivation via postcode linkage) to enable:
- Equity analysis
- Identification of groups with poorer outcomes
- Targeting interventions
5. Service planning and resource allocation by using HRG codes and activity data to support: Demand forecasting, Workforce planning, Bed occupancy modelling, Costing and tariff analysis
6. Evaluating policy interventions
SUS is national and longitudinal, it’s ideal for: Pre/post policy comparisons, Studying the impact of new clinical pathways, Monitoring national programmes (e.g., elective recovery, frailty initiatives).
Using SUS Admitted Patient Care data, researchers can:
- Spot early warning signs of deteriorating patient groups
- Identify unwarranted variation between hospitals
- Improve safety by analysing complications and adverse events
- Optimise pathways to reduce length of stay and readmissions
- Support personalised care by understanding how comorbidities affect outcomes
- Inform national strategy on capacity, funding, and workforce needs.
In Pipeline:
Available
Coverage
Spatial:
- United Kingdom
- England
- London
Typical Age Range Min:
0
Typical Age Range Max:
150
Material Type:
None/not available
Follow Up:
1 - 10 Years
Pathway:
This dataset contains all Admitted Patient Care for London patients. Each
patient will be identified using an unique patient key, this can be used to link
to other London SDE datasets that will help track the patient pathway.
Provenance
Origin
Purpose:
- Administrative
- Care
- Other
Dataset Type:
- Health and disease
- Treatments/Interventions
Dataset Sub-Type:
- Others
- Others
Source:
EPR
Collection Source:
Secondary care - In-patients
Image Contrast:
No
Temporal
Publishing Frequency:
Monthly
Distribution Release Date:
01 September 2026
Start Date:
01 April 2018
Time Lag:
1-2 weeks
Accessibility
Access
Access Rights:
London Secure Data Environment Enquiry Form
Access Service Category:
TRE/SDE
Access Service:
Researchers will have access to a secure workspace via an airlocked Azure
Virtual Desktop with a specific username and password, MFA (multi-factor
authentication) and OAUTH (open authentication). Researchers will get specific
access to a relevant subset of the datasets that are present in the SDE
catalogue for their project and will be able to carry out their research within
the safe haven. There are restrictions applied which prevent the researchers
from taking data out of the safe haven. Once the research is completed the
London SDE admin team will need to be contacted for any requests to egress
summary analysis out of the safe haven which will not breach secure data
environment disclosure control standards.
Access Request Cost:
Access costs will be determined on a project-by-project basis and will depend on
the specific data requirements, platform setup, and any additional services
needed to deliver the project successfully.
Delivery Lead Time:
1-2 months
Data Controller:
Participating London health care organisations act as Joint Data Controllers
within the London SDE. These organisations include for example GP Practices and
Acute Providers from across London.
Data Processor:
The data processor for the London Secure Data Environment (SDE) is primarily
managed by OneLondon, a partnership of London's five integrated care systems
(ICSs) and three health innovation networks. NHS North East London ICB hosts
OneLondon and operates the London Data Service (LDS) as a data processor on
behalf of those organisations, whilst Imperial College Healthcare NHS Trust
hosts the London Analytics Platform (LAP), with Imperial NHS Trust acting as the
data processor for data processing activities undertaken within the platform.
Jurisdiction:
United Kingdom of Great Britain and Northern Ireland
Usage
Data Use Limitation:
No restriction
Data Use Requirements:
- Collaboration required
- Institution-specific restrictions
- Project-specific restrictions
- Time limit on use
- User-specific restriction
Resource Creator:
- NHS NWL ICS
- London SDE
Format and Standards
Vocabulary Encoding Scheme:
- NHS NATIONAL CODES
- LOCAL
- OPCS4
- ICD10
Conforms To:
- NHS DATA DICTIONARY
- LOCAL
Language:
English
Format:
Text
Enrichment and Linkage
Investigations:
Linkable Datasets
PID
Title
URL
Each patient will be identified by an unique patient key that can be used to link to all other datasets available within London SDE Platform
Observations
Statistical Population
Population Description
Population Size
Measured Property
Observation Date
Events
30912786
Count
21 September 2026
Persons
Distinct Patient Count
6517926
Count
21 September 2026
Origin
Name:
NWL Data Catalogue