This report shows monthly numbers of NHS Hospital and Community Health Services (HCHS) staff working in NHS Trusts and other core organisations in England (excluding primary care staff). Data are available as headcount and full-time equivalents and for all months from 30 September 2009 onwards. These data are a summary of the validated data extracted from the NHS HR and Payroll system. Additional statistics on staff in NHS Trusts and other core organisations and information for NHS Support Organisations and Central Bodies are published each: September (showing June statistics) December/January (showing September statistics) March (showing December statistics) June (showing March statistics) Quarterly NHS Staff Earnings, monthly NHS Staff Sickness Absence reports, and data relating to the General Practice workforce and the Independent Healthcare Provider workforce are also available via the Related Links below. We welcome feedback on the methodology and tables within this publication. Please email us with your comments and suggestions, clearly stating Monthly HCHS Workforce as the subject heading, via enquiries@nhsdigital.nhs.uk or 0300 303 5678.

The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan.

The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565.

Survey and Biomeasures Data (GN 33004):
To date there have been nine attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137) and the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669).

Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.

From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.

Linked Geographical Data (GN 33497):
A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies.

Linked Administrative Data (GN 33396):
A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.

Additional Sub-Studies (GN 33562):
In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website.

The National Child Development Study: Linked Health Administrative Datasets (Hospital Episode Statistics), England, 1997-2017: Secure Access includes data files from the NHS Digital HES database for those cohort members who provided consent to health data linkage in the Age 50 sweep. The HES database contains information about all hospital admissions in England. The following linked HES data are available:

1) Accident and Emergency (A&E)
The A&E dataset details each attendance to an Accident and Emergency care facility in England, between 01-04-2007 and 31-03-2017 (inclusive). It includes major A&E departments, single speciality A&E departments, minor injury units and walk-in centres in England.

2) Admitted Patient Care (APC)
The APC data summarises episodes of care for admitted patients, where the episode occurred between 01-04-1997 and 31-03-2017 (inclusive).

3) Critical Care (CC)
The CC dataset covers records of critical care activity between 01-04-2009 and 31-03-2017 (inclusive).

4) Out Patient (OP)
The OP dataset lists the outpatient appointments between 01-04-2003 and 31-03-2017 (inclusive).

CLS/ NHS Digital Sub-licence agreement
NHS Digital has given CLS permission for onward sharing of the Next Steps/HES dataset via the UKDS Secure Lab. In order to ensure data minimisation, NHS Digital requires that researchers only access the HES variables needed for their approved research project. Therefore, the HES linked data provided by the UKDS to approved researchers will be subject to sub-setting of variables. The researcher will need to request a specific sub-set of variables from the Next Steps HES data dictionary, which will subsequently make available within their UKDS Secure Account. Once the researcher has finished their research, the UKDS will delete the tailored dataset for that specific project. Any party wishing to access the data deposited at the UK Data Service will be required to enter into a Licence agreement with CLS (UCL), in addition to the agreements signed with the UKDS, provided in the application pack.

Latest edition information
For the second edition (September 2022), 7 previously unavailable variables have been added to the A&E, APC and OP data files. The User Guide has also been updated, along with the variable list, to reflect the changes.

NHS 111 / Integrated Urgent Care data describes a range of statistics including NHS 111 and Out of Hours services, which aim to ensure a seamless patient experience with minimum handoffs and access to a clinician where required.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of hypertension (in persons of all ages). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to hypertension (in persons of all ages).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (all ages) with hypertension was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with hypertension was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with hypertension , within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have hypertension B) the NUMBER of people within that MSOA who are estimated to have hypertension An average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have hypertension , compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from hypertension, and where those people make up a large percentage of the population, indicating there is a real issue with hypertension within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of hypertension, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of hypertension .TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Initially this data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). This is submitted to NHS Digital for processing and is returned to healthcare providers as the Secondary Uses Service (SUS) data set and includes information relating to payment for activity undertaken. It allows hospitals to be paid for the care they deliver. This same data can also be processed and used for non-clinical purposes, such as research and planning health services. Because these uses are not to do with direct patient care, they are called 'secondary uses'. This is the SUS data set. SUS data covers all NHS Clinical Commissioning Groups (CCGs) in England, including: • private patients treated in NHS hospitals • patients resident outside of England • care delivered by treatment centres (including those in the independent sector) funded by the NHS Each SUS record contains a wide range of information about an individual patient admitted to an NHS hospital, including: • clinical information about diagnoses and operations • patient information, such as age group, gender and ethnicity • administrative information, such as dates and methods of admission and discharge • geographical information such as where patients are treated and the area where they live NHS Digital apply a strict statistical disclosure control in accordance with the NHS Digital protocol, to all published SUS data. This suppresses small numbers to stop people identifying themselves and others, to ensure that patient confidentiality is maintained.

Who SUS is for SUS provides data for the purpose of healthcare analysis to the NHS, government and others including:

The Secondary Users Service (SUS) database is made up of many data items relating to A&E care delivered by NHS hospitals in England. Many of these items form part of the national Commissioning Data Set (CDS), and are generated by the patient administration systems within each hospital. • national bodies and regulators, such as the Department of Health, NHS England, Public Health England, NHS Improvement and the CQC • local Clinical Commissioning Groups (CCGs) • provider organisations • government departments • researchers and commercial healthcare bodies • National Institute for Clinical Excellence (NICE) • patients, service users and carers • the media

Uses of the statistics The statistics are known to be used for: • national policy making • benchmarking performance against other hospital providers or CCGs
• academic research • analysing service usage and planning change • providing advice to ministers and answering a wide range of parliamentary questions • national and local press articles • international comparison More information can be found at https://digital.nhs.uk/data-and-information/data-tools-and-services/data-services/hospital-episode-statistics https://digital.nhs.uk/data-and-information/publications/statistical/hospital-accident--emergency-activity"

Experiences of local GP services, NHS treatment waiting lists, dentistry and pharmacy services, analysing data from the Health Insight Survey commissioned by NHS England. These are official statistics in development.

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

Latest monthly statistics on Learning Disabilities and Autism (LDA) patients from the Assuring Transformation (AT) collection and Mental Health Services Data Set (MHSDS). Data on inpatients with learning disabilities and/or autism are being collected both within the AT collection and MHSDS. There are differences in the inpatient figures between the AT and MHSDS data sets and work has been ongoing to better understand these. LDA data from MHSDS are experimental statistics, however, while impacts from the cyber incident are still present they will be considered to be management information. From April 2024, LDA MHSDS data has been collected under MHSDS version 6. From 1 July 2022, Integrated Care Boards were established within Integrated Care Systems data and replaced Sustainability and Transformation Plans (STPs). Clinical Commissioning Groups have been replaced by sub-Integrated Care Boards. Data for the AT collection is now submitted by sub-Integrated Care Boards. This has resulted in some renaming within tables and the inclusion of a new Table 5.1b with a patient breakdown by submitting organisation. Patients by originating organisation and commissioning type are still available in Table 5.1a. Data in the tables are now presented by the current organisational structures. Old organisational structures have been mapped to new structures in any time series.

Abstract copyright UK Data Service and data collection copyright owner.The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan. The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565. Survey and Biomeasures Data (GN 33004):To date there have been nine attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137) and the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669). Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.Linked Geographical Data (GN 33497): A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. Linked Administrative Data (GN 33396):A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.Additional Sub-Studies (GN 33562):In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website. The National Child Development Study: Linked Health Administrative Datasets (Hospital Episode Statistics), England, 1997-2017: Secure Access includes data files from the NHS Digital HES database for those cohort members who provided consent to health data linkage in the Age 50 sweep. The HES database contains information about all hospital admissions in England. The following linked HES data are available: 1) Accident and Emergency (A&E) The A&E dataset details each attendance to an Accident and Emergency care facility in England, between 01-04-2007 and 31-03-2017 (inclusive). It includes major A&E departments, single speciality A&E departments, minor injury units and walk-in centres in England. 2) Admitted Patient Care (APC)The APC data summarises episodes of care for admitted patients, where the episode occurred between 01-04-1997 and 31-03-2017 (inclusive). 3) Critical Care (CC) The CC dataset covers records of critical care activity between 01-04-2009 and 31-03-2017 (inclusive). 4) Out Patient (OP) The OP dataset lists the outpatient appointments between 01-04-2003 and 31-03-2017 (inclusive).CLS/ NHS Digital Sub-licence agreement NHS Digital has given CLS permission for onward sharing of the Next Steps/HES dataset via the UKDS Secure Lab. In order to ensure data minimisation, NHS Digital requires that researchers only access the HES variables needed for their approved research project. Therefore, the HES linked data provided by the UKDS to approved researchers will be subject to sub-setting of variables. The researcher will need to request a specific sub-set of variables from the Next Steps HES data dictionary, which will subsequently make available within their UKDS Secure Account. Once the researcher has finished their research, the UKDS will delete the tailored dataset for that specific project. Any party wishing to access the data deposited at the UK Data Service will be required to enter into a Licence agreement with CLS (UCL), in addition to the agreements signed with the UKDS, provided in the application pack.Latest edition informationFor the second edition (September 2022), 7 previously unavailable variables have been added to the A&E, APC and OP data files. The User Guide has also been updated, along with the variable list, to reflect the changes.

Hospital Episode Statistics (HES) is a database containing details of all admissions, A and E attendances and outpatient appointments at NHS hospitals in England.

Initially this data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). This is submitted to NHS Digital for processing and is returned to healthcare providers as the Secondary Uses Service (SUS) data set and includes information relating to payment for activity undertaken. It allows hospitals to be paid for the care they deliver.

This same data can also be processed and used for non-clinical purposes, such as research and planning health services. Because these uses are not to do with direct patient care, they are called 'secondary uses'. This is the HES data set.

HES data covers all NHS Clinical Commissioning Groups (CCGs) in England, including:

• private patients treated in NHS hospitals
• patients resident outside of England
• care delivered by treatment centres (including those in the independent sector) funded by the NHS

Each HES record contains a wide range of information about an individual patient admitted to an NHS hospital, including:

• clinical information about diagnoses and operations
• patient information, such as age group, gender and ethnicity
• administrative information, such as dates and methods of admission and discharge
• geographical information such as where patients are treated and the area where they live

We apply a strict statistical disclosure control in accordance with the NHS Digital protocol, to all published HES data. This suppresses small numbers to stop people identifying themselves and others, to ensure that patient confidentiality is maintained.

Timescales for dissemination can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process

NHS-funded Community Services for children and young people aged 18 years or under using data from the new Children and Young People's Health Services (CYPHS) data set reported in England. The CYPHS is a patient-level dataset providing information relating to NHS-funded community services for children and young people aged 18 years or under. These services can include health centres, schools and mental health trusts. The data collected includes personal and demographic information, diagnoses including long-term conditions and childhood disabilities and care events plus screening activities.

It has been developed as part of the Maternity and Children's Data Set (MCDS) Project to achieve better outcomes of care for children and young people. It provides data that will be used to improve clinical quality and service efficiency, in a way that improves health and reduces inequalities.

These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. More information about experimental statistics can be found on the UK Statistics Authority website.

The National Survey of Bereaved People (VOICES - Views of Informal Carers - Evaluation of Services) is an annual survey designed to measure the quality of end-of-life care. The VOICES survey particularly focuses on the last three months of life. Results are used to inform policy decisions and enable evaluation of the quality of end of life care by age group, sex, in different settings (home, hospital, care homes and hospices) and by different causes of death. Quality of end-of-life care is also included as an indicator in the NHS Outcomes Framework and the VOICES survey is used to monitor progress against this.

The Department of Health (DH) first commissioned the survey in 2011 to follow up on a commitment made in the End of Life Care Strategy. Previously, very little systematic information was available about the quality of care delivered to people approaching the end of life, despite reports from the Healthcare Commission and the Neuberger review highlighting deficiencies in care. The commissioning responsibility for the survey moved from DH to NHS England following the restructuring of the Health and Care systems in England in April 2013. Each year a sample of approximately 49,000 adults who died in England is selected from the deaths registration database held by the Office for National Statistics (ONS). To ensure the sample represents the deaths in England for the given period and covers the key domains of interest, the sample is stratified according to the cause of death, place of death and geography. For the 2011 and 2012 surveys, geography was based on Primary Care Trust (PCT) clusters. For the 2013 survey onwards, this is based on NHS Area Teams (NHS Area Team 2013 has also been applied to the earlier datasets).

The VOICES questionnaire is sent by post to the person who registered the death of the deceased; this is usually a relative or friend of the deceased. Questionnaires are sent out between 4 and 11 months after the patient has died. As is standard in most postal surveys, if no response is received, this first questionnaire is then followed up with two reminders. Once fieldwork, data capture, cleaning and processing are complete, findings are disseminated at both the national and sub-national level.

Further information about the survey and links to related publications may be found on the ONS National Bereavement Survey (VOICES) QMI webpage.

End User Licence and Secure Access versions available
The UK Data Service holds standard End User Licence (EUL) and Secure Access versions of the National Survey of Bereaved People data. EUL data are available to registered users but Secure Access data are only available to ONS Accredited Researchers (in addition, project approval and successful completion of a stringent training course are required before access can be granted). The Secure Access version contains finer detail variables (e.g. IMD deciles as opposed to quintiles in the EUL data, Strategic Clinical Network in addition to NHS Area Teams, and more detailed information on age, causes, dates and place of death). Users are strongly advised to check whether the EUL datasets (SNs 7975-7979, 8017 and 8018) and are sufficient for their research needs before making an application for the Secure Access version.

Indicators from the GP Access Survey related to people’s experiences of NHS waiting times in England.

NHS Wales hospital admissions (Inpatients and daycases) dataset comprising of attendance and clinical information for all hospital admissions: includes diagnoses and operations performed. Includes spell and episode level data.

The data are collected and coded at each hospital. Administrative information is collected from the central PAS (Patient Administrative System), such as specialty of care, admission and discharge dates. After the patient is discharged the handwritten patient notes are transcribed by clinical coder into medical coding terminology (ICD10 and OPCS).

The data held in PEDW is of interest to public health services since it can provide information regarding both health service utilisation and also the incidence and prevalence of disease. However, since PEDW was created to track hospital activity from the point of view of payments for services, rather than epidemiological analysis, the use of PEDW for public health work is not straightforward. For example:

Counts will vary depending on the number of diagnosis fields used e.g. primary only, all fields; There are a number of different things that can be counted in PEDW e.g. individual episodes of care, admissions, discharges, periods of continuous care (group of episodes), patients or procedures. When looking at diagnosis or procedures the number will vary depending on whether you look at only in the primary diagnosis / procedure field or if the secondary fields are also included. Coding practices vary. In particular, coding practices for recording secondary diagnoses is likely to vary for different hospitals. This makes regional variations more difficult to interpret. The validation process led by the Corporate Health Improvement Programme and implemented by Digital Health and Care Wales (DHCW) is aiming to address some of these inconsistencies.

Due to the complexity and pitfalls of PEDW it is recommended that any PEDW requests for public health purposes are discussed with a member of the SAIL team. In turn the SAIL will seek advice from DHCW if required.

This dataset requires additional governance approvals from the data provider before data can be provisioned to a SAIL project.

Pathology services are a fundamental core of healthcare services and are essential in the delivery of many national priorities. A Report of the Review of NHS Pathology Services in England, chaired by Lord Carter of Coles, estimated that 70-80 per cent of all healthcare decisions affecting diagnosis or treatment involve a pathology investigation. With the increased demand on acute care services there is a growing requirement for rapid laboratory results to facilitate the decision to discharge or admit, including the escalation of care. Laboratory turn around times (LTAT) are defined as the interval between when a test is requested to the time the results are available to the clinical team. LTAT is considered one of the most noticeable markers of a laboratory service and is often used as a key performance indicator in healthcare settings.

Computerised Provider Order Entry (CPOE) systems are computer-assisted systems that are designed to replace a hospital’s paper-based ordering system. When configured correctly CPOE systems should increase efficiency and improve patient care.

PIONEER geography: The West Midlands (WM) has a population of 5.9 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 & 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: Clinical and operational pathway data for 323,899 blood tests ordered pre and post implementation of a CPOE system. Data on the time the new system was implemented. Date and time fields are provided for the specimens from the point they were requested through to processing times in the laboratory and finally the date/time results are reported back via the Electronic Health System. Data on the ward and specialty are provided.

Available supplementary data: Matched controls; ambulance, 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.

Abstract copyright UK Data Service and data collection copyright owner.The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.The aims of the HSE series are:to provide annual data about the nation’s health;to estimate the proportion of people in England with specified health conditions;to estimate the prevalence of certain risk factors associated with these conditions;to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;to monitor progress towards selected health targetssince 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;since 1995, monitor the prevalence of overweight and obesity in children.The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change. Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage. Changes to the HSE from 2015:Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL HSE is subject to more restrictive access conditions than the EUL version (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version. The Health Survey for England, 2000 (HSE00) consisted of two samples. The general population sample was a national cross-section sample. Up to two children aged 2-15 years were interviewed in each household, as well as up to 10 adults aged 16 years and over. All private households in the general population sample were eligible for inclusion in the survey (up to a maximum of three households per address). Running alongside the general population sample was a care homes sample, selected from the Laing and Bussion database. The sample contained nursing, residential, dual-registered and small residential homes and covered local authority, voluntary and privately-owned care homes. Up to six people aged 65 and over were selected for interview at each care home, and given a cognitive functioning test to see whether they were capable of being interviewed in person. Proxy interviews for those who were not capable of being interviewed were introduced in June 2000. For the fourth edition (July 2011), the GHQ12 variables were amended to correct errors in the GHQ12 scores. See document 'Note about GHQ12 problems in HSE Data' for details. Main Topics: The interview with informants from the general population sample included the question modules that are asked in most years in the Health Survey ('core' modules), such as general health and longstanding illnesses, use of health services, cigarette smoking, psycho-social health (GHQ12) and accidents. Also included in the 2000 survey were questions on disability (a repeat of the module used in the 1995 Health Survey), the Short-Form Health Outcomes (SF-12) questionnaire (for informants aged 16-64) and a new module on social capital and social exclusion. In addition to the 'core' question modules outlined above, informants in care homes were asked questions about cardiovascular disease (CVD) and respiratory symptoms, eating habits, physical activity and activities in the care home. The disability module was also included in the care home sample interview. A short interview with home managers included details about the type of care home, the number of residents and the availability of services and specialised equipment. Some administrative data and geographic identifiers have been removed from the dataset. Standard Measures:General Health Questionnaire (GHQ12) - copyright David Goldberg, 1978 reproduced by permission of NFER - NELSONMedical Research Council respiratory questionnaireStrengths and Difficulties Questionnaire (SDQ)Short-Form Health Outcomes (SF12) questionnaire Multi-stage stratified random sample Face-to-face interview Self-completion Clinical measurements Physical measurements CAPI 2000 2001 ACCIDENTS ADULTS AGE AGEING ALCOHOL USE ALCOHOLIC DRINKS ALCOHOLISM ANTHROPOMETRIC DATA ANXIETY BEDROOMS BICYCLES BLOOD BUILDING MAINTENANCE CARBOHYDRATES CARDIOVASCULAR DISE... CARDIOVASCULAR SYSTEM CARE OF DEPENDANTS CARE OF THE ELDERLY CAUSES OF DEATH CEREAL PRODUCTS CHILD BENEFITS CHILDREN CHRONIC ILLNESS CLINICAL TESTS AND ... CONCENTRATION CONFECTIONERY CONTRACEPTIVE DEVICES COUGHING CULTURAL IDENTITY DAIRY PRODUCTS DEBILITATIVE ILLNESS DEGREES DEMENTIA DEPRESSION DIABETES DIET AND EXERCISE DISABILITIES DISABLED PERSONS DISEASES DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY EDIBLE FATS EDUCATIONAL BACKGROUND ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY ETHNIC GROUPS ETHNIC MINORITIES EXAMINATIONS EXERCISE PHYSICAL A... England FAMILIES FAMILY MEMBERS FATHERS FISH AS FOOD FRIENDS FRUIT FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GARDENING GENDER GENERAL PRACTITIONERS General health and ... HAEMATOLOGIC DISEASES HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH ADVICE HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HEART DISEASES HEIGHT PHYSIOLOGY HOME OWNERSHIP HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOSPITAL WAITING LISTS HOSPITALIZATION HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSEWORK HOUSING HOUSING TENURE Health care service... ILL HEALTH INCOME INDUSTRIAL INJURIES INDUSTRIES INJURIES JOB SEEKER S ALLOWANCE LANDLORDS LEISURE TIME ACTIVI... MANAGERS MARITAL STATUS MEAT MEDICAL CARE MEDICAL DIAGNOSIS MEDICAL HISTORY MEDICAL PRESCRIPTIONS MEMORY MILK MOTHERS MOTOR PROCESSES MOTOR VEHICLES NEIGHBOURHOODS OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE PAIN PARENTS PART TIME EMPLOYMENT PASSIVE SMOKING PATIENTS PERSONAL PROTECTIVE... PHYSICAL ACTIVITIES PHYSICIANS PLACE OF BIRTH PREGNANCY PRESCRIPTION DRUGS PRIVATE SECTOR QUALIFICATIONS RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL CARE OF... RESPIRATORY SYSTEM RESPIRATORY TRACT D... RETIREMENT ROAD ACCIDENTS SALT SAVINGS SAVOURY SNACKS SELF EMPLOYED SELF ESTEEM SHARED HOME OWNERSHIP SICK LEAVE SICK PERSONS SLEEP SMOKING SMOKING CESSATION SOCIAL CLASS SOCIAL HOUSING SOCIAL INTEGRATION SOCIAL SECURITY BEN... SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPORT STATE RETIREMENT PE... STRESS PSYCHOLOGICAL STUDENTS SUPERVISORS SURGERY SYMPTOMS TIED HOUSING TOBACCO TOP MANAGEMENT TRANSPORT ACCIDENTS UNEMPLOYED UNFURNISHED ACCOMMO... VASCULAR DISEASES VEGETABLES VOCATIONAL EDUCATIO... WAGES WALKING WEIGHT PHYSIOLOGY YOUTH

[ARCHIVED] Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia.

This table reports ethnicity reported by residents. This data is sourced from the 2011 National Household Survey. Geographies available: provinces, counties, communities, municipalities, district health authorities, community health boards, economic regions, police districts, school boards, school areas, municipal electoral districts, provincial electoral districts, federal electoral districts, regional development authorities, watersheds

Experimental statistics from the Mental Health Services Data Set (MHSDS) - Children & Young People

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.