London SUS Admitted Patient Care Dataset (SUS APC)

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.