London SUS Emergency Care Dataset (SUS ECDS)

The SUS (Secondary Uses Service) Unified Emergency Care Data Set (ECDS) is the national patient level dataset capturing all NHS-funded emergency care activity in London. It provides detailed clinical, demographic, and operational information about every emergency department attendance. It is richer and more clinically descriptive than the older A&E Commissioning Dataset, making it a core resource for researchers studying urgent and emergency care. ECDS is the most clinically rich and operationally detailed dataset for understanding emergency care in England — essential for improving safety, flow, and patient outcomes. That data set includes: 1. Patient demographics such as Age, Sex, Ethnicity, Geographical identifiers (region, trust, site). 2. Attendance details including Arrival date/time, Attendance type (Type 1-3 etc), Arrival mode (walk-in, ambulance, transfer), Triage category, Chief complaint / presenting condition, Clinical observations (where recorded). 3. Clinical information including Diagnoses (SNOMED CT rather than ICD-10), Clinical condition at arrival, Mental health indicators (including stays >24 hours), Paediatric-specific fields, Procedures/interventions performed in ED. 4. Operational and performance data such as Time stamps for key stages (arrival, triage, treatment, decision to admit/discharge), 4-hour performance (admitted and non-admitted pathways), 12-hour waits from arrival, Long-stay metrics (e.g., mental health >24 hours), Site-level performance data, Discharge destination (home, ward, other hospital). 5. Admission and outcome information including: - Whether the patient was admitted - Time to admission - Discharge status - Transfers to other services 6. Coverage includes All NHS emergency departments (Type 1 & 2), Urgent treatment centres where ECDS is implemented, NHS-funded emergency care delivered in independent sector sites. It excludes private emergency care not funded by the NHS. Researchers use SUS Emergency Care Data Set to: 1. Understand demand and capacity by using the figures to help model demand, staffing needs, and seasonal pressures. 2. Waiting time analysis is crucial for evaluating the Urgent & Emergency Care Recovery Plan. ECDS provides granular timestamps enabling: - 4 hour performance analysis - 12 hour waits from arrival - Paediatric vs adult performance - Mental health long stays (>24 hours) 3. Clinical acuity and case mix Due to the fact that ECDS uses SNOMED CT, the following can be analysed: - Researchers can analyse presenting complaints more precisely - Identify high-acuity groups - Study variation in triage and treatment pathways 4. Flow and bottleneck identification by using time stamps allow: - Mapping patient flow through ED - Identifying delays (triage, treatment, decision to admit) - Understanding causes of long ED stays 5. Health inequalities by using demographic fields support: - Analysis of who waits longest - Differences in admission rates - Variation in outcomes by ethnicity, age, or region 6. Policy evaluation by using ECDS to monitor: - UEC Recovery Plan commitments - Performance improvements - Impact of operational changes (e.g., Same Day Emergency Care expansion) 7. Safety and quality improvement Researchers can examine Mental Health crisis care in ED, Paediatric emergency performance, Complications or deterioration in ED, Variation between sites and regions. Using ECDS, researchers can support improving patient care in the following ways: - Reduce long ED waits by identifying bottlenecks - Improve triage accuracy through analysis of presenting complaints - Enhance mental health crisis pathways using long stay data - Support paediatric emergency improvements with age specific metrics - Target inequalities by understanding demographic variation in waits and outcomes - Inform national strategy on emergency care redesign, staffing, and capacity.