The number of hospital beds in the United Kingdom has undergone a decline since the year 2000. Whereas in 2000, there were around 240 thousand beds in the UK, by 2020 this figure was approximately 163 thousand. This means over this period there were over 80 thousand fewer hospital beds in the UK. However in the recent years since 2020, the number of hospital beds have been increasing, the first time in the recorded time period.

Fewer beds but admissions are still high

There were almost 16.4 million admissions to hospital between April 2022 to March 2023 in England. The number of admissions has recovered somewhat since the drop in year 2020/21. The busiest hospital trust in England by admissions in the year 2022/23 was the University Hospitals Birmingham Foundation Trust with over 333 thousand admissions. The average length of stay in hospitals in the UK in 2021 for acute care was seven days.

Accident and Emergency

In the first quarter of 2023/24, A&E in England received around 6.5 million attendees. The number of attendances has been creeping upwards since 2012. Around 2.4 percent of people attending A&E in the last year were diagnosed with an upper respiratory condition, followed by 1.8 percent with a lower respiratory tract infection.

On March 31, 2024, there were 50 critical care (CC) beds in England occupied with patients who had tested positive for COVID-19. The number of critical care beds occupied with COVID patients peaked in England on January 22, 2021 when 4,096 patients required critical care treatment. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Bed availability and bed occupancy.

Source agency: NHS England

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Bed availability and occupancy

Click on a hospital ID or zoom in to see information about a hospital and bed occupancy. Click on a hospital to see data about patients. This dashboard is an example of bringing together different datasets and separate tables by tying them together through Hospital ID. Patient records have no spatial information related to them, but the ID allows us to map and visualise the data as well as keeping track of what patient needs are. When someone is ready to be discharged, their care can be handed over to the most suitable organisation or division of the NHS in confidence, knowing exactly where a patient would need to go and being able to supply them with that information. This will help reduce the risk of readmission, as patients feel a continuous support and care throughout their recovery journey.Dashboard contains Living Atlas data as well as openly sourced OS and NHS data. Bed occupancy and availability, as well as patient information are all generated randomly.

Parameter variables and values for the compartmental model.

State variables for the compartmental model.

Objective: to investigate factors associated with unscheduled admission following presentation to Emergency Departments (EDs) at three hospitals in England. Design and setting: cross-sectional analysis of attendance data for patients from three urban EDs in England: a large teaching hospital and major trauma centre (Site 1), and two district general hospitals (Sites 2 and 3). Variables included: patient age, gender, ethnicity, deprivation score, arrival date and time, arrival by ambulance or otherwise, a variety of ED workload measures, inpatient bed occupancy rates and admission outcome. Coding inconsistencies in routine ED data used for this study meant that diagnosis could not be included. Outcome measure: The primary outcome for the study was unscheduled admission. Participants: all adults aged 16 and over attending the three inner London EDs in December 2013. Data on 19,734 unique patient attendances were gathered. Results: outcome data were available for 19,721 attendances (>99%), of whom 6,263 (32%) were admitted to hospital. Site 1 was set as the baseline site for analysis of admission risk. Risk of admission was significantly greater at Sites 2 and 3 (AOR relative to Site 1 for Site 2 was 1.89, 95% CI 1.74-2.05, p<0.001), and for patients of black or black British ethnicity (1.29, 1.16-1.44, p<0.001). Deprivation was strongly associated with admission. Analysis of departmental and hospital-wide workload pressures gave conflicting results, but proximity to the "four-hour target" (a rule that limits patient stays in EDs to four hours in the NHS in England) emerged as a strong driver for admission in this analysis (3.61, 3.30-3.95, p<0.001). Conclusion: this study found statistically significant variations in odds of admission between hospital sites when adjusting for various patient demographic and presentation factors, suggesting important variations in ED- and clinician-level behaviour relating to admission decisions. The four-hour target is a strong driver for emergency admission.

Mid-year (30 June) estimates of the usual resident population for health geographies in England and Wales.