This data covers a time period during the coronavirus (COVID-19) pandemic, which has affected NHS services. During the pandemic, hospital services in Wales were reorganised due to enhanced infection prevention and control measures, and the need to treat COVID and non-COVID patients separately. Subsequently, planned operations were significantly reduced and non-urgent emergency admissions decreased. As a result, hospitals experienced lower occupancy rates in 2020-21 than in previous years. This table presents summary information, from the QueSt1 return, provided by the NHS Wales Informatics Service (NWIS), on bed use in Wales. Data presented in this statistical release are an annual average and illustrate yearly changing occupancy rates and bed availability. Therefore, these data won’t reflect changing levels of activity throughout the year. The data do not present data on average length of stay, turnover interval and bed use factor. These indicators are calculated using data on deaths and discharges which is no longer collected via the QS1 return, and need to be derived from the Patient Episode Database for Wales (PEDW) for 2012-13 onwards. When carrying out more detailed analysis of the deaths and discharges data from PEDW in preparation for the 2012-13 release, data quality issues arose in relation to assessment unit (AU) activity reporting in QS1 and in PEDW and how this should be treated in the data. It was identified that there is inconsistency in the reporting of assessment units, with some LHBs reporting AU activity within their beds data, and others omitting them. This inconsistency in the reporting of AU activity is also likely to affect historic data. Please find information on changes to the data published on NHS beds, as per the given weblink.

Daily returns are collected from acute trusts and includes data bed availability for adult and paediatric general and acute beds – split by Core and Escalation beds, as well as adult critical care, paediatric intensive care and neonatal critical care. The data also includes counts of patients with a Length of Stay (LOS) of 7+, 14+ and 21+ days. The publication contains management data which has been collected on a rapid turn-round basis from the NHS. The speed of the collection only permits minimal validation to be undertaken but the data is considered ‘fit-for-purpose’. For further information on this collection, please see the Urgent and Emergency Care Daily Situation Reports page on this site: https://www.england.nhs.uk/statistics/statistical-work-areas/uec-sitrep/ This data is published on the NHS England website. Please follow the link below.

This dataset provides information on the total number of available and occupied bed days for facility wards open "overnight" and "day only" by NHS (National Health Service) Trust by Sector.

This data package contains the hospital bed availability and occupancy data by consultant main specialty and sector as well as data on inpatient and outpatient related hospital activity in England. It also contains information on Sub-Saharan public hospitals.

The acute-care pathway (from the emergency department (ED) through acute medical units or ambulatory care and on to wards) is the most visible aspect of the hospital health-care system to most patients. Acute hospital admissions are increasing yearly and overcrowded emergency departments and high bed occupancy rates are associated with a range of adverse patient outcomes. Predicted growth in demand for acute care driven by an ageing population and increasing multimorbidity is likely to exacerbate these problems in the absence of innovation to improve the processes of care.

Key targets for Emergency Medicine services are changing, moving away from previous 4-hour targets. This will likely impact the assessment of patients admitted to hospital through Emergency Departments.

This data set provides highly granular patient level information, showing the day-to-day variation in case mix and acuity. The data includes detailed demography, co-morbidity, symptoms, longitudinal acuity scores, physiology and laboratory results, all investigations, prescriptions, diagnoses and outcomes. It could be used to develop new pathways or understand the prevalence or severity of specific disease presentations.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

Electronic Health Record: University Hospital Birmingham is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All patients with a medical emergency admitted to hospital, flowing through the acute medical unit. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes patient demographics, co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (timings, admissions, wards and readmissions), physiology readings (NEWS2 score and clinical frailty scale), Charlson comorbidity index and time dimensions.

Available supplementary data: Matched controls; ambulance data, OMOP data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

This dataset includes information split by location for health board of available staffed beds, hospital and council area. Due to the variability in the number of available beds in a ward or specialty, the total number of available beds is calculated by taking the average of the number of beds available in each day of the quarter and percentage occupancy for acute specialties for acute hospital care services.

This data package contains information about Acute Hospital for Outpatient Activity Cross Boundary Flow, statistics on attendances at Accident and Emergency (A&E) services and Emergency Hospital Admissions due to Unintentional Injuries. It also includes information for Inpatient and Daycase Activity Stays and Episodes by Health Board Residence and Treatment as well as NHS Staffed Beds and Percentage Occupancy and Procedures Performed for Children In An Acute Setting For NHS Scotland.

Virtual wards (also known as hospital at home) allow patients to get the care they need at home safely and conveniently, rather than being in hospital. This includes either preventing avoidable hospital admissions or supporting people to safely leave hospital sooner. Systems are asked to continue to embed, standardise and scale virtual ward capacity, ensuring that local virtual ward services are aligned to local demand for both children and adults. This is outlined in the 2025/26 Priorities and Operational Planning Guidance and the Neighbourhood Health Guidelines 2025/26. This data is published on the NHS England website. Please follow the link below.

This publication was archived on 12 October 2023. Please see the Viral Respiratory Diseases (Including Influenza and COVID-19) in Scotland publication for the latest data. This dataset provides information on number of new daily confirmed cases, negative cases, deaths, testing by NHS Labs (Pillar 1) and UK Government (Pillar 2), new hospital admissions, new ICU admissions, hospital and ICU bed occupancy from novel coronavirus (COVID-19) in Scotland, including cumulative totals and population rates at Scotland, NHS Board and Council Area levels (where possible). Seven day positive cases and population rates are also presented by Neighbourhood Area (Intermediate Zone 2011). Information on how PHS publish small are COVID figures is available on the PHS website. Information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system is provided in this publication. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. COVID-19 was declared a pandemic by the World Health Organisation on 12 March 2020. We now have spread of COVID-19 within communities in the UK. Public Health Scotland no longer reports the number of COVID-19 deaths within 28 days of a first positive test from 2nd June 2022. Please refer to NRS death certificate data as the single source for COVID-19 deaths data in Scotland. In the process of updating the hospital admissions reporting to include reinfections, we have had to review existing methodology. In order to provide the best possible linkage of COVID-19 cases to hospital admissions, each admission record is required to have a discharge date, to allow us to better match the most appropriate COVID positive episode details to an admission. This means that in cases where the discharge date is missing (either due to the patient still being treated, delays in discharge information being submitted or data quality issues), it has to be estimated. Estimating a discharge date for historic records means that the average stay for those with missing dates is reduced, and fewer stays overlap with records of positive tests. The result of these changes has meant that approximately 1,200 historic COVID admissions have been removed due to improvements in methodology to handle missing discharge dates, while approximately 820 have been added to the cumulative total with the inclusion of reinfections. COVID-19 hospital admissions are now identified as the following: A patient's first positive PCR or LFD test of the episode of infection (including reinfections at 90 days or more) for COVID-19 up to 14 days prior to admission to hospital, on the day of their admission or during their stay in hospital. If a patient's first positive PCR or LFD test of the episode of infection is after their date of discharge from hospital, they are not included in the analysis. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. Data visualisation of Scottish COVID-19 cases is available on the Public Health Scotland - Covid 19 Scotland dashboard. Further information on coronavirus in Scotland is available on the Scottish Government - Coronavirus in Scotland page, where further breakdown of past coronavirus data has also been published.

The number of inpatient occupancy days at public hospitals and private hospitals accredited with the national health service (Servizio Sanitario Nazionale - SSN) in Italy reached approximately ** million in 2018. As the graphic shows, the vast majority of inpatient care was provided by public hospitals.

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.

Psychiatric crisis care is under great pressure, with the number of psychiatric presentations to emergency departments increasing and inpatient wards operating with occupancy rates above recommended levels. Internationally, hospital-based short-stay crisis units (named Psychiatric Decision Units; (PDU) in the UK) have been introduced to address these challenges, but the current evidence for their effectiveness is limited. We estimated the effects of PDUs in four geographic locations in England, linked to three National Health Service (NHS) mental health trusts and six NHS acute hospital trusts. Using national data sets to create synthetic controls from areas without PDUs (following the generalised synthetic control method), we estimated trust-wide changes to the primary outcomes of psychiatric inpatient admissions and psychiatric presentations to emergency departments (ED), compared to the synthetic controls, alongside secondary outcomes. We used meta-analysis to robustly combine outcomes. We analysed NHS hospital activity data for adults aged between 18 and 75 years covering 24 months preceding and following the introduction of each PDU (November 2012 to January 2021). We found no significant impacts of PDUs on primary outcomes, except at Sheffield Teaching Hospitals NHS Foundation Trust with 1.5 fewer psychiatric presentations to ED per 10,000 trust population per month (relative difference: 24.9%, p = 0.034) than the synthetic control. We found mixed effects of the opening of PDUs on secondary outcomes. Meta-analyses indicated a significantly lower mean length of stay for psychiatric admissions (-6.4 days, p