In March 2023, a patient in an Accident and Emergency in England would spend approximately 70 minutes waiting before treatment would begin. After the wait times dropped due to COVID-19 effects, it reached a record high of 81 minutes in May 2021 and November 2021. The median wait time for treatment has been fluctuating since the pandemic began in March 2020.

Substantial waiting times experienced by patients

In the first quarter of 2021/2022 in England 83.4 percent of patients who attended A&E were admitted, transferred or discharged within four hours. This is below the NHS’s target that 95 percent of attendees to A&E should be seen within four hours. Since 2011, the share of patients seen within four hours has been declining. In addition, since 2016 there has been a marked increase in examples of patients waiting for more than twelve hours at A&E to be admitted, with a recorded high of 7,161 individuals in 2020/21 third quarter.

Increased number of attendances

The reasons behind the increased waiting times and the missed treatment targets could be partially explained by the increased number of people attending A&E. There were over 6.1 million attendances to the A&E department in England in the first quarter of 2021/22. This figure has been increasing since 2012, which means there is a greater strain on emergency services across the country. The large drop in number of attendances is reflected in wait times and with number of attendances rebounding again, wait times have also increased.

The number of patients waiting twelve hours or more has dramatically increased in recent years. In 2022, around 347,707 patients waited twelve hours or more, compared with 1,306 in 2015. Updated quarterly data can be found here. NHS waiting times Waiting times in the NHS have become increasingly high in recent years, especially starting the winter of 2022 with rates of hospitalization due to influenza surpassing those due to COVID-19. A national outbreak of Strep A infections put additional strain on the health service. Despite the beginning of the COVID-19 pandemic in 2020, the median wait-times have far outpaced the peak reached in September 2020 of 48 minutes. Staff shortages The NHS was the world's 7th largest employer in 2022, employing more than 1.3 million individuals. Due to increasingly difficult working conditions and disputes over pay, the NHS is struggling to fill vacancies and had more than 110,000 in December 2021. Additionally, expenditure on staff as a share of total expenditure has fallen in recent years. A survey conducted in December 2021 found that more than 30 percent of NHS staff had thought about leaving the organization. 2022 and 2023 saw a record number of strikes across the UK in various sectors. Support for the strikes has generally been high, but none higher than support for NHS nurses, who enjoyed 64 percent of public support as of November 2022.

This table provides the current data on referral to treatment waiting times for patient pathways waiting (open pathway) to start treatment by grouped weeks. Hywel Dda health board has no patients waiting for audiological medicine from January 2019 onwards, this is due to the service moving into the community based model. In March 2016, we changed some of the terminology used in referral to treatment reporting. Previously, when publishing these statistics, we used the terminology ‘patients’. However, some users misinterpreted this as unique patients. It is possible that a person could be on a number of different lists waiting for different conditions – i.e. there would be one patient but more than one pathway. Due to the RTT dataset being an aggregate data collection we’re not able to measure the number of unique patients. Therefore, we are using the terminology ‘patient pathways’, to better reflect the fact that one person can be on multiple waiting lists. The methodology use to measure and calculate these statistics has not changed. This is also more consistent with the other nations of the UK in their reporting of RTT.

From February 2021, data is only published for the suspected cancer pathway. Targets for the urgent and not via the urgent pathway have ceased and no new data will be collected or published for these pathways. The patients shown here are those newly diagnosed with cancer who started definitive treatment via the Urgent Suspected Cancer route. The national target for these patients is: at least 95 per cent of patients diagnosed with cancer, via the urgent suspected cancer route will start definitive treatment within 62 days of receipt of referral. Care should be taken when interpreting percentages, especially when dealing with small numbers.

In 2023, less than half of Swedes considered the waiting time to be reasonable for hospital care. During 2020 and 2021, there was a higher share of respondents that believed the waiting time for hospitals was reasonable.

The National Treatment Purchase Fund (NTPF) is responsible for the collection, collation and validation of inpatient, Day Case and Outpatient waiting lists.

The IPDC Waiting List Open Data report shows the total number of people waiting, across the various time Bands, for inpatient and Day treatment in each Specialty (these numbers do not include GI Endoscopies, see separate report).

Statistical Disclosure Control (SDC) techniques have been applied to the data to preserve confidentiality and mitigate against Identification or self-Identification of individuals. In cases where there are less than 5 people in any particular cell, that value has been replaced with the average (mean) of all values that are less than 5 across that category. Any decimal values which Arise have then been Rounded. This may cause some rounding to occur when calculating sub-totals.

Where there are less than 20 people waiting in a particular specialty/hospital, the numbers have been aggregated under a ‘Small Volume’ heading

The Children’s Health Act 2018 came into effect on 1st January 2019. Under this act, Children’s Health Ireland was established and all assets, liabilities and records were transferred from Our Lady’s Children’s Hospital Crumlin, Temple Street Children’s University Hospital and National Children’s Hospital at Tallaght University Hospital to the new body. From 1st January 2019, all NTPF reports reflect this change and data from the three sites of Children’s Health Ireland are reported as one entity. On the 31st of July 2019 Children’s Health Ireland opened a new Paediatric Outpatient Department and Urgent Care Centre at CHI Connolly in Blanchardstown. The waiting lists for this site are incorporated into the Children’s Health Ireland figures.

Please note that NTPF does not collect activity data, i.e., numbers treated or removed. A Snapshot of the number of patients waiting in each hospital is collected and published, monthly, on the NTPF website.

Boards and management of individual public hospitals are responsible for the accuracy and the integrity of patient data submitted to NTPF.

The NTPFF resume publishing separate Adult and Child Waiting List Reports in April 2021. The Open Data report formats reflect this change from that date forward.

In November 2020, 87 percent of patients with suspected cancer in England were seen by a specialist within fourteen days of a referral by a GP, lower than the NHS operational standard that 93 percent of patients should be seen within this timeframe. Since January 2018, the NHS waiting time target for cancer referral has only been met six times.

These statistics present a group of measures on waiting times for autism spectrum disorder diagnostic pathways, based on the time between a referral for suspected autism and the first care contact associated with that referral. There are also multiple breakdowns based on the progression and outcomes of those referrals. Each of these measures contributes to an overall picture of waiting times for diagnostic pathways. The approach is outlined in the methodology section of this publication.

The National Treatment Purchase Fund (NTPF) is responsible for the collection, collation and validation of inpatient, Day Case and Outpatient waiting lists. The OP Waiting List Open Data report shows the total number of people waiting, across the various time Bands, for a first appointment at a consultant-led Outpatient clinic. Statistical Disclosure Control (SDC) techniques have been applied to the data to preserve confidentiality and mitigate against Identification or self-Identification of individuals. In cases where there are less than 5 people in any particular cell, that value has been replaced with the average (mean) of all values that are less than 5 across that category.Any decimal values which Arise have then been Rounded. This may cause some rounding to occur when calculating sub-totals. Where there are less than 20 people waiting in a particular specialty/hospital, the numbers have been aggregated under a ‘Small Volume’ heading The Children’s Health Act 2018 came into effect on 1st January 2019. Under this act, Children’s Health Ireland was established and all assets, liabilities and records were transferred from Our Lady’s Children’s Hospital Crumlin, Temple Street Children’s University Hospital and National Children’s Hospital at Tallaght University Hospital to the new body. From 1st January 2019, all NTPF reports reflect this change and data from the three sites of Children’s Health Ireland are reported as one entity.On the 31st of July 2019 Children’s Health Ireland opened a new Paediatric Outpatient Department and Urgent Care Centre at CHI Connolly in Blanchardstown. The waiting lists for this site are incorporated into the Children’s Health Ireland figures. Please note that NTPF does not collect activity data, i.e., numbers treated or removed. A Snapshot of the number of patients waiting in each hospital is collected and published, monthly, on our website. Boards and management of individual public hospitals are responsible for the accuracy and the integrity of patient data submitted to NTPF. The NTPFF resume publishing separate Adult and Child Waiting List Reports in April 2021. The Open Data report formats reflect this change from that date forward.

From February 2021, data is only published for the suspected cancer pathway. Targets for the urgent and not via the urgent pathway have ceased and no new data will be collected or published for these pathways. The patients shown here are those treated via the non urgent route. The national target for these patients is: at least 98 per cent of patients newly diagnosed with cancer, not via the urgent route will start definitive treatment within 31 days of diagnosis (regardless of the referral route). Care should be taken when interpreting percentages, especially when dealing with small numbers.

ObjectiveThe coronavirus disease (COVID-19) disrupted healthcare systems and medical care worldwide. This study attempts to assess the performance of three Saudi hospitals during COVID-19 by comparing waiting times for outpatient appointments and the volume of elective surgeries before and after COVID-19.MethodsWe used ADA’A data collected from three Saudi hospitals for this retrospective cohort study. The outcome variables were “Waiting Time for Appointment” and “Elective OR Utilization”. The hospitals included in this study were: a 300-bed maternity and children’s hospital; a 643-bed general hospital; and a 1230-bed tertiary hospital. We included all patients who visited the OPD and OR in the time period from September 2019 to December 2021. A two-way ANOVA test was used to examine the differences in the outcome variables by hospital and by the phase of COVID-19.ResultsFor the elective OR utilization rate, the results showed that both the hospital and the phase of COVID-19 were significantly different (p-value < 0.05). On average, the elective OR utilization rate dipped considerably in the early phase of COVID-19 (33.2% vs 44.9%) and jumped sharply in the later phase (50.3%). The results showed that the waiting time for OPD appointment was significantly different across hospitals and before and after COVID-19 in each hospital (p-value < 0.05). the waiting time dropped during the early phase of COVID-19 for both the general hospital (GEN) (24.6 days vs 34.8 days) and the tertiary hospital (MDC) (40.3 days vs 48.6 days), while the maternity and children’s hospital (MCH)’s score deteriorated sharply (24.6 days vs 9.5 days).ConclusionThis study indicates that COVID-19 led to a significant impact on elective surgery rates and waiting time for OPD appointments in the early stage of the pandemic when the lockdown strategy was implemented in the country. Although the elective surgery rate had decreased at the designated COVID-hospital, the waiting time for OPD appointment had improved. This is a clear indication that the careful planning and management of resources for essential services during pandemic was effective.

As of 27/09/2022, this dataset has been superseded by a new version found here This data provides a quarterly update on waiting times for people accessing specialist drug and alcohol treatment services. In 2011, the Scottish Government set a standard that 90% of people referred for help with problematic drug or alcohol use will wait no longer than three weeks for specialist treatment that supports their recovery. This data was extracted from the new Drug and Alcohol Information System (DAISy) and its predecessor the Drug and Alcohol Treatment Waiting Times (DATWT) database. DAISy was implemented in four NHS Boards (Ayrshire & Arran, Dumfries & Galloway, Grampian and Western Isles) from December 2020, and was available in all NHS Boards from April 2021. All publications and supporting material to this topic area can be found on Public Health Scotland Substance Use page. The date of the next release can be found on our list of forthcoming publications.

Emergency room visit rates across the United States show significant variation, with a national average of 422 visits per 1,000 population in 2023. This average masks considerable differences between states, ranging from 596 visits per 1,000 population in West Virginia to just 226 in Nevada. Wait times in emergency rooms While ER visit rates provide insight into utilization, wait times offer a glimpse into the efficiency of emergency care delivery. In 2022, ER patients waited an average of 38.1 minutes to see a healthcare provider in emergency departments nationwide. Interestingly, the COVID-19 pandemic temporarily reduced wait times in 2020, but they rebounded to pre-pandemic levels by 2021. Most patients, roughly 70 percent, spend less than an hour in the emergency department before being seen by a medical professional. These figures suggest that despite high utilization in some areas, many emergency departments manage to process patients relatively quickly. Demographic disparities in emergency care Emergency department usage varies significantly across different demographic groups, revealing important healthcare access disparities. Infants under one-year-old and adults 75 years and over have the highest ED visit rates among all age groups. Additionally, racial disparities in ED rates are evident, with non-Hispanic Black individuals having double the ED visit rate of non-Hispanic White individuals. These patterns underscore the need for targeted healthcare interventions and improved access to acute care for vulnerable populations.

This publication provides the most timely picture available of people using NHS funded secondary mental health, learning disabilities and autism services in England. These are experimental statistics which are undergoing development and evaluation. This information will be of use to people needing access to information quickly for operational decision making and other purposes. More detailed information on the quality and completeness of these statistics is made available later in our Mental Health Bulletin: Annual Report publication series. The Data Collection Board (DCB) has now approved the decommissioning of the interim collection of Early Intervention in Psychosis (EIP) waiting times information, known as NHS England Unify Collection within this publication. Waiting times for EIP for October 2019 activity onwards are now monitored using data from the Mental Health Services Data Set (MHSDS). From April 2020 NHS Digital is implementing a multiple submission window model for MHSDS which will enable the resubmission of data throughout the financial year. Following the implementation of the multiple submission window model providers will optionally be able to submit/resubmit data for each month of 2019-20 from April 2020 to 21 May 2020. The opportunity to resubmit data for each month of 2019-20 will impact on the statistics already published for the 2019-20 year. It is likely that the statistics for each month will be republished; however the publication method is as yet undecided and will be proportionate to the changes; further details will be communicated closer to the time. Please be aware of the potential impact of the multiple submission window model on previously published data and use these statistics with reference to it. Further information can be found on the NHS Digital Multiple submission window model for MHSDS webpage linked below. The Provisional March data file has been removed as this is now superseded by the published Performance March data. NHS Digital apologises for any inconvenience caused. From April 2020 onwards, NHS Digital has been implementing a multiple submission window model (MSWM) for MHSDS. This allows providers to retrospectively submit data for a specific reporting period once the initial provisional and performance submission windows have closed. For a limited time, providers were given the opportunity to submit revised monthly data for all months within 2019/20 using the MSWM. As of January 2021, NHS Digital has now released revised 'End of Year' versions of the main monthly csv files for each month between April 2019 and February 2020 which reflect these revised 2019/20 MSWM submissions that occurred after 'Final' monthly data had already been published. Both the 'Final' and 'End of Year' versions of the main monthly csv files are available to download under 'Resources'. The key facts corresponding to both versions are also presented below.

This statistical release is the annual report on the Improving Access to Psychological Therapies (IAPT) programme from 1st April 2021 to 31st March 2022. IAPT is run by the NHS in England and offers NICE-approved therapies for treating people with anxiety or depression. The publication contains analyses on activity, waiting times and outcomes such as recovery in 2021-22. In addition, the report covers a range of demographic analyses including outcomes for patients of different ages, ethnic group and separately for ex-British Armed Forces personnel. This report also contains additional analysis for therapy-based outcomes in IAPT services. The attached outputs for this publication still refer to some old terminology i.e. 'started' or 'entered treatment', which map to the new terminology of 'accessing services' as presented on the publication pages. This will be updated for next year's annual report.

Lengthy waiting times for ophthalmology appointments in the UK National Health Service (NHS) increased further in the immediate aftermath of the Covid-19 pandemic, necessitating a different approach to triaging patients safely and at speed. Moorfields Eye Hospital NHS Trust therefore opened an additional diagnostic hub designed with a linear spatial layout and patient flow system, which is analyzed in this paper in comparison to an existing clinic. We integrate direct observations of patient flows, and an architectural layout analysis based on space syntax methods with queuing simulations from operations research and show that the two clinics operate differently and that both clinics have their advantages and disadvantages. The newly opened clinic with a lane system supports flows and coordination by line of sight between stations, which contrasts with a lack of sightlines in the existing clinic. The latter layout with clusters of stations compensates by enabling a more organic flow, especially in conjunction with experienced technicians, which is beneficial when the clinic gets busy. When high patient load is simulated in the queuing models, the lane system results in slightly bigger bottlenecks and longer clinic durations. An ideal allocation of the number of stations to diagnostic activities based on clusters is suggested. This work stands in the tradition of combining architectural and operations research. By reflecting on the variability of diagnostic processes found in our observations, we contribute to the understanding of routines as performative. We also add insight to the growing field of evidence-based design, particularly by highlighting the importance of line-of-sight relationships in ophthalmology. Methods Fieldwork was undertaken in June and July 2021 in two outpatient clinics of Moorfield Eye Hospital NHS Trust, the Cayton Street clinic and the Hoxton Hub. Two main data sets were collected for each clinic: 1) an up-to-date floor plan of each clinic including the locations and types of all diagnostic equipment marked up, and 2) direct observations of glaucoma patient flows, recorded on tablets, including exact time stamps of entry and exit of the clinic as well as start and end times for all diagnostic tests. For the observations, patients received a sticker with a study ID number at the reception desk, which was recorded by observers as an identifier. Over the course of ten days of observations, participant observers captured nine 4-hour shifts in the period from 8:30 to 17:00 in Hoxton, and six 4-hour day shifts and seven 3-hour evening shifts between 8:30 and 20:00 in Cayton Street. 14 patients at Cayton Street and 11 patients at Hoxton were shadowed for the entirety of their journey through the clinics with an average duration of 36 minutes (range 19-70min) and 37 minutes (range 26-79min) respectively. The majority of the data, however, was captured by additional, so called ‘zonal’ observations, where each observer was placed in a position to monitor a discrete space as well as all start and end times of diagnostic tests completed in this area, resulting in a total of 152 and 83 unique patients observed in the clinics respectively. From these data, full patient journeys were reconstructed using the patient identifiers. Aggregating data from both observation methods resulted in a sample size of 621 single data points of activity durations in Cayton Street and 485 at Hoxton (which includes observed activities of standing and waiting), hence n=1106. This full data set contained a subsample of actual examinations at stations (excluding standing and waiting) of n=1007. Each observer was asked to record an identifier for each technician looking after a patient, i.e., the first two letters of the technician’s first name and the first two letters of their last name. Each technician was wearing a name tag which was visible to the observers. This was used in the analysis stage to understand technician workflows, for example, whether they guide a single patient through every stage of the diagnostic process, or whether they mainly stick to a particular diagnostic activity. Afterwards, all identifiers were anonymized. The observers were also asked to assess and record the fluency in English of each patient where they could choose from four levels: ‘fluent’, ‘few issues’, ‘many issues’, and ‘translator’. Using the patient ID numbers, which were cross-referenced by hospital staff to their patient database, additional information was obtained from the hospital including age, gender, and if the patient was a first-time or a follow-up patient. The observers also recorded anything they felt worth noting down in the form of a qualitative note. This included reasons for occurring delays, causes for waiting, patients with mobility difficulties, etc. In summary, for each diagnostic activity, the following data was collected: 1) patient ID, 2) date, 2) exact time stamps for the moment a patient sat down at each station (start time), and got up again (end time), 3) location (corridor, waiting area or station number), 4) activity (exam, wait while sitting, wait while standing), 5) technician ID, 6) English proficiency, 7) qualitative notes (see supplemental material S1 on the observation protocol). The dataset has been processed in the following ways:

Floor plans have been analysed based on space syntax techniques to understand differences in architectural layout between the two clinics. The patient flow data has been analysed statistically using Jupyter Notebooks to understand how the two clinics operated. Queuing simulations have been run in R to understand how the diagnostic stations can be arranged differently, and what impact this would have on clinic effectiveness.

The National Treatment Purchase Fund (NTPF) is responsible for the collection, collation and validation of inpatient, Day Case and Outpatient waiting lists. The IPDC GI Endoscopy Waiting List Open Data report shows the total number of people waiting, across the various time Bands, for GI Endoscopy treatment. The Children’s Health Act 2018 came into effect on 1st January 2019. Under this act, Children’s Health Ireland was established and all assets, liabilities and records were transferred from Our Lady’s Children’s Hospital Crumlin, Temple Street Children’s University Hospital and National Childrens Hospital at Tallaght University Hospital to the new body. From 1st January 2019, all NTPF reports reflect this change and data from the three sites of Children’s Health Ireland are reported as one entity. On the 31st of July 2019 Children’s Health Ireland opened a new Paediatric Outpatient Department and Urgent Care Centre at CHI Connolly in Blanchardstown. The waiting lists for this site are incorporated into the Children’s Health Ireland figures. Please note that NTPF does not collect activity data, i.e., numbers treated or removed. A Snapshot of the number of patients waiting in each hospital is collected and published, monthly, on the NTPF website. Boards and management of individual public hospitals are responsible for the accuracy and the integrity of patient data submitted to NTPF.

Healthcare spending in the United Kingdom stood at 317 billion British pounds in 2024. When looking at real healthcare expenditure*, spending already exceeded this amount in 2021, where it reached 324 billion British pounds in 2024 prices. Health expenditure in the UK compared to Europe In 2024, the UK spent almost 11 percent of its GDP on healthcare. In comparison to other European countries, this ranked the UK fifth in terms of health expenditure. At the top of the list was Switzerland, which spent 12 percent of its GDP on healthcare that year.  Performance of the NHS in the UK Waiting times have been getting worse in the A&E department over the years. The NHS has been falling behind the target that 95 percent of patients should be seen within four hours of arrival. As a result, the primary reasons for dissatisfaction with the NHS among the public are the length of time required to get a GP or hospital appointment and the lack of staff.