This is a monthly report on publicly funded community services for people of all ages using data from the Community Services Data Set (CSDS) reported in England for November 2022. It has been developed to help achieve better outcomes and provide data that will be used to commission services in a way that improves health, reduces inequalities, and supports service improvement and clinical quality. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website (linked at the bottom of this page). The csv data file for November 2022 and provisional data file for December 2022 now include organisational level breakdown by Integrated Care Board (ICB). This change occured from October 2022, and is reflected in the Power BI dashboard.

A highly granular dataset of 16,052 Same day emergency care (SDEC) spells with a focus on care pathways. It includes demography, co-morbidities, presenting symptoms, serial physiology, investigations, and outcomes.

Description (3000 Characters) – Current 2540 (with spaces)

Emergency care services face increasing pressure. NHS England (NHSE) has prioritised pathways for patients which avoid admission, including Same Day Emergency Care (SDEC) services. The NHS Long Term Plan recommends SDEC assessment for one third of medical attendances.

​Care quality indicators (CQI) include times from arrival to assessment by senior clinical teams. Performance measured against these CQI are impacted by other factors, such as delays in referrals, awaiting investigation results.​ 

PIONEER has curated a highly granular dataset of 16,052 Same day emergency care (SDEC) spells, including not only detailed patient level information, but data about the wider clinical environment on the day of admission.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB 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 & > 120 ITU bed capacity. 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”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

The topology of the patient flow network in a hospital is complex, comprising hundreds of overlapping patient journeys, and is a determinant of operational efficiency. To understand the network architecture of patient flow, we performed a data-driven network analysis of patient flow through two acute hospital sites of King’s College Hospital NHS Foundation Trust. Administration databases were queried for all intra-hospital patient transfers in an 18-month period and modelled as a dynamic weighted directed graph. A ‘core’ subnetwork containing only 13–17% of all edges channelled 83–90% of the patient flow, while an ‘ephemeral’ network constituted the remainder. Unsupervised cluster analysis and differential network analysis identified sub-networks where traffic is most associated with A&E performance. Increased flow to clinical decision units was associated with the best A&E performance in both sites. The component analysis also detected a weekend effect on patient transfers which was not associated with performance. We have performed the first data-driven hypothesis-free analysis of patient flow which can enhance understanding of whole healthcare systems. Such analysis can drive transformation in healthcare as it has in industries such as manufacturing.

OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 2.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases & more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) & death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID OMOP dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) 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 & 100 ITU beds. 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”. UHB has cared for >5000 COVID admissions to date. This is a subset of data in OMOP format.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – August 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data. Further OMOP data available as an additional service.

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.

Patients undergoing elective inpatient surgery for hip and knee replacement, funded by the English NHS are asked to complete questionnaires before and after their operations to assess improvement in health as perceived by the patients themselves. This publication is for Finalised Patient Reported Outcome Measures (PROMs) in England - April 2023 to March 2024. It is possible that the response rates could still be impacted by the COVID-19 pandemic. The response levels may be also been impacted by a reduction in resource at NHSE in recent years. We will monitor the number questionnaires arriving to late for this publication and will consider revising key figures if a large volume are received. In analysing outcomes driven by the difference in pre-operative and post-operative questionnaires, please note that some data breakdowns or analyses are dependent on questionnaire pairs being linked to operations in Hospital Episode Statistics (HES) while others are not. As shown in the data quality section, not all questionnaire pairs link to HES, for reasons including correct patient identifiers not being returned or data inconsistencies. This means that the breakdowns that are dependent on linkage to HES, including by primary/revision, commissioner, or any casemix adjusted score comparisons will have lower totals than those not dependent on linkage to HES such as grand totals or some provider-level outputs. In addition, the report presents both adjusted and non-adjusted figures and this should be borne in mind when summarising any findings. There may also be some disparities in the way figures are calculated across products. *** Update 20/3/25: We are currently investigating some issues with the way the modelled records are constructed and will provide an update in due course. A small number of provider and site codes rolled out in the last few years, particularly those in the ANANA format, are not recognised or correctly processed by the system and they are mapped inconsistently to codes for different publication measures. They are typically given an organisation name of unknown in the interest of making the data available in a timely manner. Subject to user demand, we anticipate that the system will be developed to address this issue ahead of subsequent publications. *** The Summary Comparison Tool published on the 13th February 2025 contained missing formula for pre-operative participation and linkage rate and post-operative issue and response rate in the Key Facts tab. The formulas have now been reintroduced and corrected (19th February 2025).

DECOVID, a multi-centre research consortium, was founded in March 2020 by two United Kingdom (UK) National Health Service (NHS) Foundation Trusts (comprising three acute care hospitals) and three research institutes/universities: University Hospitals Birmingham (UHB), University College London Hospitals (UCLH), University of Birmingham, University College London and The Alan Turing Institute. The original aim of DECOVID was to share harmonised electronic health record (EHR) data from UCLH and UHB to enable researchers affiliated with the DECOVID consortium to answer clinical questions to support the COVID-19 response.   ​​   ​​The DECOVID database has now been placed within the infrastructure of PIONEER, a Health Data Research (HDR) UK funded data hub that contains data from acute care providers, to make the DECOVID database accessible to external researchers not affiliated with the DECOVID consortium.  

This highly granular dataset contains 256,804 spells and 165,414 hospitalised patients. The data includes demographics, serial physiological measurements, laboratory test results, medications, procedures, drugs, mortality and readmission.

Geography: UHB 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 & > 120 ITU bed capacity. UCLH provides first-class acute and specialist services in six hospitals in central London, seeing more than 1 million outpatient and 100,000 admissions per year. Both UHB and UCLH have fully electronic health records. Data has been harmonised using the OMOP data model. Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2022-23, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2023. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019 the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fourth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with breakdowns including the baby's first feed type, birthweight, place of birth, and breastfeeding activity; and the mothers' ethnicity and age at booking. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. The count of Total Babies includes both live and still births, and previous changes to how Total Babies and Total Deliveries were calculated means that comparisons between 2019-20 MSDS data and later years should be made with care. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

To use the document, click on the link above and scroll to the link on the page titled “View the January 2024 Drug Tariff online”. Once in the file, use the search function on the left-hand side to search for ‘contraceptive’. Click on the link(s) that appear, and you will be able to see a breakdown of the products available and the cost in pence to the NHS. Data on prescribing volumes and costs for English dispensing in the community can be found in the published Prescription Cost Analysis statistics (PCA), this data is classified against what is considered to be the 'main' therapeutic use for the pharmaceutical 'presentation' expressed using the (pseudo) British National Formulary (BNF) hierarchy. The tables include a breakdown with each pharmaceutical presentation reported separately. https://www.nhsbsa.nhs.uk/statistical-collections/prescription-cost-analysis-england To use the document, click on the link above and scroll to the “Resource List”. From here you can choose to view the data on a national scale or narrowed down to local ICB level. Once in the file, we recommend downloading the file in order to filter the columns for ease of access. We recommend using the National Summary Tables and viewing Table 6: BNF presentation level data. Within this file you can filter by name in column C or the measurement in column D. We recommend that you access this data knowing the names of the medication, devices or patches you require. Please be aware of the PCA methodology which may be relevant depending on interpretation. https://nhsbsa-opendata.s3.eu-west-2.amazonaws.com/pca/pca_background_info_methodology_v001.html The basis of the cost information included in the PCA data is described in the 'metadata' section included with the release and relates to the amount included in the reimbursement. NHSBSA prescription data only covers prescription items that have been submitted for reimbursement by community NHS dispensing contractors - this does not include any direct purchases made by other parts of the NHS (for example hospitals or other facilities that are operated by NHS Trusts). The NHS Business Services Authority does not hold data - including cost information - about appointments.

This highly granular synthetic dataset created as an asset for the HDR UK Medicines programme includes information on 680 cancer patients over a period of three years. Includes simulated patient-related data, such as demographics & co-morbidities extracted from ICD-10 and SNOMED-CT codes. Serial, structured data pertaining to acute care process (readmissions, survival), primary diagnosis, presenting complaint, physiology readings, blood results (infection, inflammatory markers) and acuity markers such as AVPU Scale, NEWS2 score, imaging reports, prescribed & administered treatments including fluids, blood products, procedures, information on outpatient admissions and survival outcomes following one-year post discharge.

The data was generated using a generative adversarial network model (CTGAN). A flat real data table was created by consolidating essential information from various key relational tables (medications, demographics). A synthetic version of the flat table was generated using a customized script based on the SDV package (N. Patki, 2016), that replicated the real distribution and logic relationships.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB 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 & > 120 ITU bed capacity. 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”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and provide the real-data via application.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Information on the number of dentists who have carried out NHS activity during the year.

Dentists can work under a number of contracts: - General Dental Services (GDS) providers must provide a full range of mandatory services. - Personal Dental Services (PDS) providers are not obliged to provide the full range of mandatory services. If a provide-only provides specialist services, such as orthodontic work, this has to be under a PDS agreement. - Trust-led Dental Services (TDS) can provide services under PDS agreements and then pay dentists directly rather than through the standard system operated by NHS Dental Services

For more information please see the Guide to NHS Dental Statistics

Data for this publication are extracted each month as a snapshot in time from the GP Payments system (Open Exeter) maintained by NHS Digital. This release is an accurate snapshot as at 1 September 2019. GP Practice; Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG); NHS England Region and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive STP; CCG; Region and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a topic of interest.

1 in 17 people are born with or develop a rare disease during their lifetime. 80% of rare diseases have an identified genetic component. However, there are usually significant diagnostic delays. The 100k Genome project was established to collect clinical data, genomic sequencing and samples from people with cancer and rare diseases, to better understand disease and find novel treatments and interventions. This includes rare cardiovascular, ciliopathy, endocrine, gastroenterological, haematological, metabolic, neurological, renal, respiratory skeletal and rheumatological disorders and cancers.

The PIONEER University Hospital Birmingham (UHB) secondary care 100k genomics dataset contains granular demographic, morbidity, treatment and outcome data, supplemented with acute care contacts with serial physiology, blood biomarker data from UHB patients recruited to this programme, to better understand the acute healthcare needs of this group of patients.

PIONEER geography: The West Midlands has a population of 5.9M and includes a diverse ethnic and socio-economic mix. There is a higher than average percentage of minority ethnic groups and a higher than average proportion of patients with rare diseases. Birmingham is home to the first Centre for Rare Diseases for adults and children, treating more than 500 rare diseases and 9000 patients per year.

Electronic Health Records: University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services and specialist care across four hospital sites, with 2.2M patient episodes per year, 2750 beds and 100 ITU beds.

Scope: All patients recruited to the 100K genome project from UHB. This includes all routinely collected health data for all these patients, but data is uniquely supplemented with all acute care contacts through UHB. The dataset includes highly granular patient demographics and co-morbidities taken from ICD-10 and SNOMED-CT codes. Serial, structured data pertaining to acute care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed and administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Matched controls; ambulance, synthetic data. Available supplementary support: Analytics, Model build, validation and refinement; A.I.; Data partner support for ETL process, Clinical expertise, Patient and end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the NHAIS (National Health Application and Infrastructure Services) system. This release is an accurate snapshot as at 1 April 2021. GP Practice; Primary Care Network (PCN); Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive STP; PCN; CCG and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a spotlight report. The outbreak of Coronavirus (COVID-19) has led to changes in the work of General Practices and subsequently the data within this publication. Until activity in this healthcare setting stabilises, we urge caution in drawing any conclusions from these data without consideration of the country's circumstances and would recommend that any uses of these data are accompanied by an appropriate caveat. NOTE: Due to issues with corporate reference data, the CCG mergers which came into effect in April 2021 are not reflected in this publication. The data in this publication can be aggregated to account for these CCG mergers using the information on the following page. We apologise for any inconvenience. https://digital.nhs.uk/services/organisation-data-service/change-summary-reconfiguration-2021-ccg-mergers#reconfiguration-mapping

Virtual wards provide care at home with remote monitoring for people who do not need admission to hospital, but require hospital-led care. NHS England (NHSE) has requested an extension of a virtual ward model of care, with a national ambition of developing 40-50 virtual ward ‘beds’ per 100,000 population.

​The Surgical Assessment Unit Virtual Ward manages patients who are clinically suitable for home while waiting for investigation or treatment for an acute surgical condition.

To support a better evidence base for surgical virtual wards, PIONEER has curated a highly granular dataset of 1,655,756 spells eligible for Virtual Surgical Assessment Unit (VSAU), with a proportion of patients being admitted to the VSAU, and a proportion remaining in tradition care pathways. The data includes demography, co-morbidities, presenting symptoms, serial physiology, diagnoses, investigations, treatments (including procedures) and outcomes. The current dataset includes admissions from 2018 to 2023 but can be expanded to assess other timelines of interest.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB 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 & > 120 ITU bed capacity. 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”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Welcome to the NHS Business Services Authority’s (NHSBSA) Open Data Portal, the home of all our open data. All of our data is released under the Open Government License and is free for use and re-use. We want to put users at the heart of what we do. You can see what we’re working on at the minute on our Open Data Roadmap that is hosted on our GitHub. You can help shape what we do next by giving us feedback on our roadmap and making suggestions for what data sets you would like see published or expanded on. The Open Data Portal is powered by CKAN - an open source data management system. You can see the code that has been created to help support this implementation of CKAN in a series of public GitHub repositories:

aSLE: Systemic Lupus ErythematosusbSLICC: Systemic Lupus International Collaborating Clinics Damage IndexcSELENA-SLEDAI (SS): Safety of Estrogen in Lupus Erythematosus National Assessment SLE Disease Activity IndexSource: Specchia ML et al. Health Technology Assessment of Belimumab: a new monoclonal antibody for the treatment of Systemic Lupus Erythematosus. BioMed Research International. 2014; http://dx.doi.org/10.1155/2014/704207Base case scenario: patients characteristics (based on BLISS trials).

The global market for NHS-activated magnetic beads (MagBeads) is experiencing robust growth, driven by increasing demand in life science research, diagnostics, and therapeutic applications. The market's versatility, stemming from its use in various techniques like protein purification, immunoassays, and cell sorting, fuels this expansion. While precise market size data for 2025 is unavailable, a reasonable estimation based on the provided data and industry trends suggests a market value of approximately $500 million. Considering a compound annual growth rate (CAGR) of, for example, 8% (a conservative estimate reflecting consistent but not explosive growth in the sector given mature technology), the market is projected to reach approximately $800 million by 2033. This growth is further propelled by advancements in nanotechnology leading to improved bead functionalities and efficiencies in nanoscale applications, particularly in areas like advanced diagnostics and personalized medicine. Key market segments include millimeter-level and nanoscale MagBeads, each serving diverse applications. Millimeter-level beads are commonly employed in large-scale purifications, while nanoscale beads offer advantages in high-throughput assays and more sophisticated applications demanding higher precision. Geographically, North America and Europe currently hold significant market shares, owing to established research infrastructure and a strong presence of major players. However, the Asia-Pacific region is poised for rapid growth, fueled by increasing investments in biotechnology and healthcare research within nations like China and India. Restraining factors might include the high cost of specialized equipment and the relatively complex nature of MagBead technologies, potentially limiting wider adoption in resource-constrained settings. Despite these factors, the overall market outlook remains positive, driven by continuous technological advancements and the ever-growing demand for efficient and high-performance tools in the life sciences sector.

This publication provides the most timely statistics available relating to NHS funded secondary mental health, learning disabilities and autism services in England. This information will be of use to people needing access to information quickly for operational decision making and other purposes. These statistics are derived from submissions made using version 3.0 of the Mental Health Services Dataset (MHSDS). This edition includes final statistics for November 2018 and provisional statistics for December 2018. NHS Digital review the quality and completeness of the submissions used to create these statistics on an ongoing basis. More information about this work can be found in the Accuracy and reliability section of this report. Fully detailed information on the quality and completeness of particular statistics in this release is not available due to the timescales involved in reviewing submissions and engaging with data providers. The information that has been obtained at the time of publication is made available in the Provider Feedback sections of the Data Quality Reports which accompany this release. Information gathered after publication is released in future editions of this publication series. More detailed information on the quality and completeness of these statistics and a summary of how these statistics may be interpreted is made available later in our Mental Health Bulletin: Annual Report publication series. All elements of this publication, other editions of this publication series, and related annual publication series' can be found in the Related Links below. We are aware that a number of providers may have encountered issues submitting mental health data to the Bureau Service Portal (BSP) in December due to a power outage; the issue may have affected the quality of the data the provider was able to submit or prevented the provider from submitting at all. The full impact on the data is being investigated with some information available from the data quality reports. Please note: The provider breakdown for AMH04 (People in contact with adult mental health services on CPA at the end of RP with HoNOS recorded) has not been included in this publication and will not be included in future publications until the cause is rectified. NHS Digital will inform users once this issue has been resolved. NHS Digital apologises for any inconvenience caused.

Treatment and organ damage costs per patient.