https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions
This publication provides statistics on the number of unique NHS numbers with an associated national data opt-out. The national data opt-out was introduced on 25 May 2018. It was introduced following recommendations from the National Data Guardian. It indicates that a patient does not want their confidential patient information to be shared for purposes beyond their individual care across the health and care system in England. The service allows individuals to set a national data opt-out or reverse a previously set opt-out. It replaced the previous type 2 opt-outs which patients registered via their GP Practice. Previous type 2 opt-outs have been converted to national data opt-outs each month, until November 2018. This is why the monthly increase in opt-outs decreases from December 2018 onward. This publication includes the number of people who have a national data opt-out, broken down by age, gender and a variety of geographical breakdowns. From June 2020 the methodology for reporting NDOP changed, representing a break in time series. Therefore, caution should be used when comparing data to publications prior to June 2020. The number of deceased people with an active NDOP has been captured and reported for the first time in June 2020. Please note that this publication is no longer released monthly. It is released annually or when the national opt-out rate changes by more than 0.1 per cent. Prior to September 2020 there is a slight inflation of less than 0.05 percent in the number of National Data Opt-outs. This is due to an issue with the data processing, which has been resolved and does not affect data after September 2020. This issue does not disproportionately affect any single breakdown, including geographies. Please take this into consideration when using the data. As of January 2023, index of multiple deprivation (IMD) data has been added to the publication, allowing the total number of opt-outs to be grouped by IMD decile. This data has been included as a new CSV, and has also been added to a new table in the summary file. IMD measures relative deprivation in small areas in England, with decile 1 representing the most deprived areas, and decile 10 representing least deprived. Please note that the figures reported in IMD decile tables will not add up to the national totals. This is because the IMD-LSOA mapping reference data was created in 2019, and any geography codes added since then will not be mapped to an IMD decile. For more information about the reference data used, please view this report: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 Management information describes aggregate information collated and used in the normal course of business to inform operational delivery, policy development or the management of organisational performance. It is usually based on administrative data but can also be a product of survey data. We publish these management information to ensure equality of access and provide wider public value.
https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions
Published: 22 March 2018 - This management information publication reports on patient opt-out information that has been received from GP practices, as of March 2018. There are two types of opt-out. A type 1 opt-out prevents information being shared outside a GP practice for purposes other than direct care. A type 2 opt-out prevents information being shared outside of NHS Digital for purposes beyond the individual's direct care. A more detailed description of opt-outs is available (see related links). Type 1 and type 2 opts-outs are presented at GP practice level. Type 1 opt-outs are reported as instances (i.e. number of times the opt-out code occurs within GP records, which may include the same patient recorded at more than one practice) and there is no way to de-duplicate this information. Levels of type 1 opt-outs are therefore likely to be higher than levels of type 2 opt-outs, which are de-duplicated.
There are two types of opt-out. A type 1 opt-out prevents information being shared outside a GP practice for purposes other than direct care.
A type 2 opt-out prevents information being shared outside NHS Digital for purposes beyond the individual’s direct care. A more detailed description of opt-outs is available (see related links).
Type 1 and type 2 opts-outs are presented at GP practice level. Type 1 opt-outs are reported as instances (i.e. number of times the opt-out code occurs within GP records, which may include the same patient recorded at more than one practice) and there is no way to de-duplicate this information.
Levels of type 1 opt-outs are therefore likely to be higher than levels of type 2 opt-outs, which are de-duplicated.
Abstract copyright UK Data Service and data collection copyright owner.
BackgroundI am writing to confirm that I have now completed my search for the information which you requested. Request You asked us: I’m writing to submit a request under the Freedom of Information Act. For each of the last 24 months for which data is available, please could you provide the number of NHS Pension Scheme Members who have opted out of the NHS Pension Scheme, along with any ‘reason for opting out’ data that is collected, such as affordability, Annual Allowance / LTA etc. If possible, please provide a breakdown of the monthly figures between: a) Medical Staff under capacity code 03 b) GPs, specifically b) Dental Staff under capacity code 08 d) General Dental Practitioners, Dental Registrars. Consultant Dentists and Dental Surgeons, specifically c) other The NHS Business Services Authority (NHSBSA) received your request on 23 April 2025. We have handled your request under the Freedom of Information Act (FOIA) 2000. Our response The NHSBSA does not hold the requested information split by the categories as specified in your request; however, we do publish a monthly report which provides data about employees in the Employee Staff Record (ESR) choosing to opt-out of the NHS Pension Scheme. https://www.nhsbsa.nhs.uk/information-about-nhs-pensions/nhs-pensions-opt-out-data Publishing this response Please note that this information will be published on our Freedom of Information disclosure log at: https://opendata.nhsbsa.net/dataset/foi-02775 Your personal details will be removed from the published response.
In 2023/24, 42 percent of the population in the United Kingdom had ‘opted-in’ to the NHS organ donation register, which amounts to over 28 million people registered. This means that the individuals allow their organs to be donated after their death. The share of people registered has been increasing since 2009. Deceased transplant activity in the UK The number of deceased organ donors in the UK has increased alongside the rise in the opt-in registrations. In 2023/24, approximately 3.7 thousand deceased donor transplants took place in the UK, compared to around 2.6 thousand in 2009/10. Around 20.6 deceased organ transplants per million population (pmp) in the UK in 2022. Spain had the highest rate of organ donation after death with 46.7 pmp. Rate of transplants in the UK The overall rate of transplants in the UK was 65 transplants per million people in 2022, this was the tenth-highest transplant rate in Europe. Although as of March 2024, there were still almost 7.5 thousand patients on the organ transplant waiting list in the UK, 5.9 thousand of which were waiting for a kidney transplant.
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License information was derived automatically
This project used a cross-sectional survey method to gather information from GPs practicing in England. As the GP system operates differently in Scotland, Wales and Northern Ireland, these GPs were not included in the study.
The survey was developed based on literature related to GP practice in falls prevention, current falls prevention clinical guidelines, completed Australian studies, and the results of pilot on-line survey, in conjunction with feedback from a group of GPs and a focus group of older people.
All 211 Community Care Groups (CCGs) in NHS England were approached to support the survey, and 4 CCGs opted out. The survey was provided as both a paper survey to 4000 randomly selected GPs and a further 3,200 GPs were invited to participate via an online version of the same survey (using the Bristol Online Survey software). As advised by GP advisors we sent letter to GP practice managers and included an evidence-based invitation letter (as well as participant information sheet) for GPs, in order to enhance response rate.
Survey topics included the perceptions, knowledge and routine practice of GPs in relation to identifying, screening and assessing falls risks in their people, their falls management and referral practices, and barriers and facilitators to them effectively preventing falls in their older people.
The study has contributed to the methodological debate about paper versus online survey response rates. In this study the response rate was equally poor for both versions. Response rate was seemingly higher of GPs from CCGs who had actively endorsed participation in the study.
·
Letter to GP practice managers
·
Evidence-based letter to GPs
·
Participant Information sheet
·
Paper copy of Survey
·
Spreadsheet of raw data – complete set,
paper, online
·
Publication reference: McIntyre A,
Mackenzie L, Harvey M (2018) Engagement of general practitioners in falls
prevention and referral to occupational therapists. British Journal of
Occupational Therapy, (online)
·
Copy of presentation given at Royal
College of Occupational Therapists’ 2017 conference
Background
The Commission for Health Improvement (CHI), in conjunction with the Department of Health (DH), appointed Aston University to develop and pilot a new national National Health Service (NHS) staff survey, commencing in 2003, and to establish an advice centre and web site to support that process. Administration of the programme was taken over by the Healthcare Commission in time for the 2004 series. On the 1st April 2009, the Care Quality Commission (CQC) was formed which replaced the Healthcare Commission (users should note that some of the surveys in the series conducted prior to this date will still be attributed to the Healthcare Commission). In 2011 the Department of Health took over management of the survey. Since 2013 NHS England (NHSE) have been in charge of the survey programme. Researchers at Aston University were responsible for the initial development of the survey questionnaire instrument, and for the setting up of the NHS National Staff Survey Advice Centre. From 2011, Picker Institute Europe took over from Aston University as survey contractors. All organisations concerned worked in partnership to consult widely with NHS staff about the content of the new national survey. The work was conducted under the guidance of a stakeholder group, which contained representatives from the staff side, CQC, DH, human resources directors, Strategic Health Authorities and the NHS workforce.
Aims and conduct of the survey
The purpose of the annual NHS staff survey is to collect staff views about working in their local NHS trust. The survey has been designed to replace trusts' own annual staff surveys, the DH '10 core questions', and the HC 'Clinical Governance Review' staff surveys. It is intended that this one annual survey will cover the needs of HC, DH and trusts. Thus, it provides information for deriving national performance measures (including star ratings) and to help the NHS, at national and local level, work towards the 'Improving Working Lives' standard. The design also incorporates questions relating to the 'Positively Diverse Programme'. Trusts will be able to use the findings to identify how their policies are working in practice. The survey enables organisations, for the first time, to benchmark themselves against other similar NHS organisations and the NHS as a whole, on a range of measures of staff satisfaction and opinion. From 2013, the NHS Staff Survey went out to all main trust types - social enterprises, clinical commissioning groups and clinical support units were able to opt themselves in to the survey. Organisations were allowed to conduct the survey electronically and to submit data for an entire census or extended sample of their organisation. Previously the sample was restricted to 850 staff.
The collection of data (i.e. the survey fieldwork) is conducted by a number of independent survey contractors (see documentation for individual survey information). The contractors are appointed directly by each NHS trust in England and are required to follow a set of detailed guidance notes supplied by the Advice Centre (see web site link above), which covers the methodology required for the survey. For example, this includes details on how to draw the random sample, the requirements for printing of questionnaires, letters to be sent to respondents, data entry and submission. At the end of the fieldwork, the data are then sent to the Advice Centre. From the data submitted, each participating NHS trust in England receives a benchmarked 'Feedback Report' from the Advice Centre, which also produces (on behalf of the Department of Health) a series of detailed spreadsheets which report details of each question covered in the survey for each participating trust in England, and also a 'Key Findings' summary report covering the survey findings at national level. Further information about the survey series and related publications are available from the Advice Centre web site (see link above).
https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/
Over the five years through 2024-25, specialist medical practices’ revenue is expected to sink at a compound annual rate of 0.5% to £11.7 billion. Demand for specialist medical services has remained resilient as an ageing population in the UK and rising obesity levels have elevated health problems. However, stretched funding from the NHS and reduced capacity during the COVID-19 outbreak in 2020-21 have weighed on revenue. The COVID-19 outbreak also delayed millions of non-essential medical procedures. Waiting lists for NHS consultant-led elective care sat at 7.5 million in February 2024, far higher than pre-COVID. Growing waiting lists have encouraged more people to opt for private healthcare, so private demand is rising. A four-year deal made in March 2021 between NHS England and private providers agreed the NHS will pay according to the number of patients treated. Unlike the previous agreement made at the height of COVID-19, which took over all private hospitals’ capacity, providers can also service private medical insurance-funded and self-paying patients, supporting revenue growth. Revenue is forecast to grow by 1.7% in 2024-25. Revenue is anticipated to swell at a compound annual rate of 2.4% to reach £13.2 billion over the five years through 2029-30. Demand for medical specialists will rise as the UK population ages and the obesity crisis continues to unfold. Rising health consciousness and government initiatives to reduce obesity may offset demand as more people lead healthier lifestyles. Medical advances will allow practices to boost productivity and treat more patients. However, addressing workforce shortages across practices in sectors like radiology and oncology through recruitment initiatives and investment in training will be essential.
https://www.pioneerdatahub.co.uk/data/data-request-process/https://www.pioneerdatahub.co.uk/data/data-request-process/
Community Acquired Pneumonia (CAP) is the leading cause of infectious death and the third leading cause of death globally. Disease severity and outcomes are highly variable, dependent on host factors (such as age, smoking history, frailty and comorbidities), microbial factors (the causative organism) and what treatments are given. Clinical decision pathways are complex and despite guidelines, there is significant national variability in how guidelines are adhered to and patient outcomes.
For clinicians treating pneumonia in the hospital setting, care of these patients can be challenging. Key decisions include the type of antibiotics (oral or intravenous), the appropriate place of care (home, hospital or intensive care), and when it is appropriate to stop antibiotics. Decision support tools to help inform clinical management would be highly valuable to the clinical community.
This dataset is synthetic, formed from statistical modelling using real patient data, and represents a population with significant diversity in terms of patient demography, socio-economic status, CAP severity, treatments and outcomes. It can be used to develop code for deployment on real data, train data analysts and increase familiarity with this disease and its management.
PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.
EHR. 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”. This synthetic dataset has been modelled to reflect data collected from this EHR.
Scope: A synthetic dataset which has been statistically modelled on all hospitalised patients admitted to UHB with Community Acquired Pneumonia. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care including timings, admissions, escalation of care to ITU, discharge outcomes, physiology readings (heart rate, blood pressure, AVPU score and others), blood results and drug prescribing and administration.
Available supplementary data: Matched synthetic controls; ambulance, OMOP data, real patient CAP 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.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Proportion of children aged 4 to 5 years classified as overweight or living with obesity. For population monitoring purposes, a child’s body mass index (BMI) is classed as overweight or obese where it is on or above the 85th centile or 95th centile, respectively, based on the British 1990 (UK90) growth reference data. The population monitoring cut offs for overweight and obesity are lower than the clinical cut offs (91st and 98th centiles for overweight and obesity) used to assess individual children; this is to capture children in the population in the clinical overweight or obesity BMI categories and those who are at high risk of moving into the clinical overweight or clinical obesity categories. This helps ensure that adequate services are planned and delivered for the whole population.
Rationale There is concern about the rise of childhood obesity and the implications of obesity persisting into adulthood. The risk of obesity in adulthood and risk of future obesity-related ill health are greater as children get older. Studies tracking child obesity into adulthood have found that the probability of children who are overweight or living with obesity becoming overweight or obese adults increases with age[1,2,3]. The health consequences of childhood obesity include: increased blood lipids, glucose intolerance, Type 2 diabetes, hypertension, increases in liver enzymes associated with fatty liver, exacerbation of conditions such as asthma and psychological problems such as social isolation, low self-esteem, teasing and bullying.
It is important to look at the prevalence of weight status across all weight/BMI categories to understand the whole picture and the movement of the population between categories over time.
The National Institute of Health and Clinical Excellence have produced guidelines to tackle obesity in adults and children - http://guidance.nice.org.uk/CG43.
1 Guo SS, Chumlea WC. Tracking of body mass index in children in relation to overweight in adulthood. The American Journal of Clinical Nutrition 1999;70(suppl): 145S-8S.
2 Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T. Do obese children become obese adults? A review of the literature. Preventative Medicine 1993;22:167-77.
3 Starc G, Strel J. Tracking excess weight and obesity from childhood to young adulthood: a 12-year prospective cohort study in Slovenia. Public Health Nutrition 2011;14:49-55.
Definition of numerator Number of children in reception (aged 4 to 5 years) with a valid height and weight measured by the NCMP with a BMI classified as overweight or living with obesity, including severe obesity (BMI on or above the 85th centile of the UK90 growth reference).
Definition of denominator Number of children in reception (aged 4 to 5 years) with a valid height and weight measured by the NCMP.
Caveats Data for local authorities may not match that published by NHS England which are based on the local authority of the school attended by the child or based on the local authority that submitted the data. There is a strong correlation between deprivation and child obesity prevalence and users of these data may wish to examine the pattern in their local area. Users may wish to produce thematic maps and charts showing local child obesity prevalence. When presenting data in charts or maps it is important, where possible, to consider the confidence intervals (CIs) around the figures. This analysis supersedes previously published data for small area geographies and historically published data should not be compared to the latest publication. Estimated data published in this fingertips tool is not comparable with previously published data due to changes in methods over the different years of production. These methods changes include; moving from estimated numbers at ward level to actual numbers; revision of geographical boundaries (including ward boundary changes and conversion from 2001 MSOA boundaries to 2011 boundaries); disclosure control methodology changes. The most recently published data applies the same methods across all years of data. There is the potential for error in the collection, collation and interpretation of the data (bias may be introduced due to poor response rates and selective opt out of children with a high BMI for age/sex which it is not possible to control for). There is not a good measure of response bias and the degree of selective opt out, but participation rates (the proportion of eligible school children who were measured) may provide a reasonable proxy; the higher the participation rate, the less chance there is for selective opt out, though this is not a perfect method of assessment. Participation rates for each local authority are available in the https://fingertips.phe.org.uk/profile/national-child-measurement-programme/data#page/4/gid/8000022/ of this profile.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains responses from an online survey of 2187 participants primarily located in the UK. All participants stated that they had used the UK National Health Service (NHS) at some time in their lives. The data were collected between December 2018 and August 2019. Participants' views on data sharing - this dataset contains information about people's willingness to share mental and physical health data for research purposes. It also includes information on willingness to share other types of data, such as financial information. The dataset includes participants' responses to questions relating to mental health data sharing, including the trustworthiness of organisations which use such data, how much the presence of different governance measures (such as deidentification, opt-out, etc.) would alter their views, and whether they would be less likely to access NHS mental health services if they knew their data might be shared with researchers. Participants' satisfaction and interaction with UK mental and physical health services - the dataset includes information regarding participants' views on and interaction with NHS services. This includes ratings of satisfaction at first contact and in the previous 12 months, frequency of use, and type of treatment received. Information about participants - the dataset includes information about participants' mental and physical health, including whether or not they have experience with specific mental health conditions, and how they would rate their mental and physical health at the time of the survey. There is also basic demographic information about the participants (e.g. age, gender, location etc.).
Abstract copyright UK Data Service and data collection copyright owner.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Proportion of children aged 10 to 11 years classified as living with obesity. For population monitoring purposes, a child’s body mass index (BMI) is classed as overweight or obese where it is on or above the 85th centile or 95th centile, respectively, based on the British 1990 (UK90) growth reference data. The population monitoring cut offs for overweight and obesity are lower than the clinical cut offs (91st and 98th centiles for overweight and obesity) used to assess individual children; this is to capture children in the population in the clinical overweight or obesity BMI categories and those who are at high risk of moving into the clinical overweight or clinical obesity categories. This helps ensure that adequate services are planned and delivered for the whole population.
Rationale There is concern about the rise of childhood obesity and the implications of obesity persisting into adulthood. The risk of obesity in adulthood and risk of future obesity-related ill health are greater as children get older. Studies tracking child obesity into adulthood have found that the probability of children who are overweight or living with obesity becoming overweight or obese adults increases with age[1,2,3]. The health consequences of childhood obesity include: increased blood lipids, glucose intolerance, Type 2 diabetes, hypertension, increases in liver enzymes associated with fatty liver, exacerbation of conditions such as asthma and psychological problems such as social isolation, low self-esteem, teasing and bullying.
It is important to look at the prevalence of weight status across all weight/BMI categories to understand the whole picture and the movement of the population between categories over time.
The National Institute of Health and Clinical Excellence have produced guidelines to tackle obesity in adults and children - http://guidance.nice.org.uk/CG43.
1 Guo SS, Chumlea WC. Tracking of body mass index in children in relation to overweight in adulthood. The American Journal of Clinical Nutrition 1999;70(suppl): 145S-8S.
2 Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T. Do obese children become obese adults? A review of the literature. Preventative Medicine 1993;22:167-77.
3 Starc G, Strel J. Tracking excess weight and obesity from childhood to young adulthood: a 12-year prospective cohort study in Slovenia. Public Health Nutrition 2011;14:49-55.
Definition of numerator Number of children in year 6 (aged 10 to 11 years) with a valid height and weight measured by the NCMP with a BMI classified as living with obesity or severe obesity (BMI on or above 95th centile of the UK90 growth reference).
Definition of denominator Number of children in year 6 (aged 10 to 11 years) with a valid height and weight measured by the NCMP.
Caveats Data for local authorities may not match that published by NHS England which are based on the local authority of the school attended by the child or based on the local authority that submitted the data. There is a strong correlation between deprivation and child obesity prevalence and users of these data may wish to examine the pattern in their local area. Users may wish to produce thematic maps and charts showing local child obesity prevalence. When presenting data in charts or maps it is important, where possible, to consider the confidence intervals (CIs) around the figures. This analysis supersedes previously published data for small area geographies and historically published data should not be compared to the latest publication. Estimated data published in this fingertips tool is not comparable with previously published data due to changes in methods over the different years of production. These methods changes include; moving from estimated numbers at ward level to actual numbers; revision of geographical boundaries (including ward boundary changes and conversion from 2001 MSOA boundaries to 2011 boundaries); disclosure control methodology changes. The most recently published data applies the same methods across all years of data. There is the potential for error in the collection, collation and interpretation of the data (bias may be introduced due to poor response rates and selective opt out of children with a high BMI for age/sex which it is not possible to control for). There is not a good measure of response bias and the degree of selective opt out, but participation rates (the proportion of eligible school children who were measured) may provide a reasonable proxy; the higher the participation rate, the less chance there is for selective opt out, though this is not a perfect method of assessment. Participation rates for each local authority are available in the https://fingertips.phe.org.uk/profile/national-child-measurement-programme/data#page/4/gid/8000022/ of this profile.
Background
The Commission for Health Improvement (CHI), in conjunction with the Department of Health (DH), appointed Aston University to develop and pilot a new national National Health Service (NHS) staff survey, commencing in 2003, and to establish an advice centre and web site to support that process. Administration of the programme was taken over by the Healthcare Commission in time for the 2004 series. On the 1st April 2009, the Care Quality Commission (CQC) was formed which replaced the Healthcare Commission (users should note that some of the surveys in the series conducted prior to this date will still be attributed to the Healthcare Commission). In 2011 the Department of Health took over management of the survey. Since 2013 NHS England (NHSE) have been in charge of the survey programme. Researchers at Aston University were responsible for the initial development of the survey questionnaire instrument, and for the setting up of the NHS National Staff Survey Advice Centre. From 2011, Picker Institute Europe took over from Aston University as survey contractors. All organisations concerned worked in partnership to consult widely with NHS staff about the content of the new national survey. The work was conducted under the guidance of a stakeholder group, which contained representatives from the staff side, CQC, DH, human resources directors, Strategic Health Authorities and the NHS workforce.
Aims and conduct of the survey
The purpose of the annual NHS staff survey is to collect staff views about working in their local NHS trust. The survey has been designed to replace trusts' own annual staff surveys, the DH '10 core questions', and the HC 'Clinical Governance Review' staff surveys. It is intended that this one annual survey will cover the needs of HC, DH and trusts. Thus, it provides information for deriving national performance measures (including star ratings) and to help the NHS, at national and local level, work towards the 'Improving Working Lives' standard. The design also incorporates questions relating to the 'Positively Diverse Programme'. Trusts will be able to use the findings to identify how their policies are working in practice. The survey enables organisations, for the first time, to benchmark themselves against other similar NHS organisations and the NHS as a whole, on a range of measures of staff satisfaction and opinion. From 2013, the NHS Staff Survey went out to all main trust types - social enterprises, clinical commissioning groups and clinical support units were able to opt themselves in to the survey. Organisations were allowed to conduct the survey electronically and to submit data for an entire census or extended sample of their organisation. Previously the sample was restricted to 850 staff.
The collection of data (i.e. the survey fieldwork) is conducted by a number of independent survey contractors (see documentation for individual survey information). The contractors are appointed directly by each NHS trust in England and are required to follow a set of detailed guidance notes supplied by the Advice Centre (see web site link above), which covers the methodology required for the survey. For example, this includes details on how to draw the random sample, the requirements for printing of questionnaires, letters to be sent to respondents, data entry and submission. At the end of the fieldwork, the data are then sent to the Advice Centre. From the data submitted, each participating NHS trust in England receives a benchmarked 'Feedback Report' from the Advice Centre, which also produces (on behalf of the Department of Health) a series of detailed spreadsheets which report details of each question covered in the survey for each participating trust in England, and also a 'Key Findings' summary report covering the survey findings at national level. Further information about the survey series and related publications are available from the Advice Centre web site (see link above).
The 2007 survey introduced different versions of the core questionnaire for each of the four main sectors (acute, ambulance, mental health and primary care). The majority of the content is the same across the different versions of the core questionnaire but in addition, now include a number of sector specific questions.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
The NHS Fetal Anomaly Ultrasound Screening Programme (FA2) data provides insights into the coverage and effectiveness of the fetal anomaly ultrasound scan conducted between 18 and 20 weeks of pregnancy. This data includes the percentage of eligible pregnant women who received the scan, which is designed to detect a range of fetal anomalies such as Down's syndrome, Edwards' syndrome, Patau's syndrome, and various physical conditions like spina bifida and congenital heart disease.
Rationale The FA2 data helps assess the programme's reach and identify areas for improvement, ensuring that expectant mothers receive timely and accurate information about their baby's health. This information is crucial for healthcare providers to monitor and enhance the quality of prenatal care services.
Definition of numerator The number of eligible pregnant women who received the fetal anomaly ultrasound scan between 18 and 20 weeks of pregnancy.
Definition of denominator The total number of eligible pregnant women who were offered the fetal anomaly ultrasound scan between 18 and 20 weeks of pregnancy.
Caveats
Eligibility Criteria: The data only includes pregnant women who meet specific eligibility criteria, such as those with a fetal crown rump length (CRL) measurement between 45.0mm and 84.0mm (11 weeks plus 2 days to 14 weeks plus 1 day of pregnancy). Women who fall outside these parameters are excluded. Exclusions: Certain groups are excluded from the data, such as women who miscarry, opt for termination, transfer out before testing, or have pregnancies of a higher order than twins. Technical Limitations: There may be instances where it is not technically possible to measure the nuchal translucency (NT), leading to exclusions from the data. Service Capacity: The capacity of ultrasound departments to accommodate women presenting later in pregnancy can affect the data. If the service cannot offer the combined test to women presenting between 13 weeks plus 1 day and 14 weeks plus 1 day, these women can be excluded. Informed Choice: The data includes women who decline the screening after being offered, which can impact the overall coverage rates.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
The NHS Sickle Cell and Thalassaemia (SCT) Screening Programme aims to identify carriers of sickle cell disease and thalassaemia, as well as individuals affected by these conditions.
Rationale The rationale for the NHS Sickle Cell and Thalassaemia (SCT) Screening Programme is to identify carriers and individuals affected by these inherited blood disorders early in pregnancy. Early detection allows for informed decision-making by prospective parents and ensures timely medical intervention. Sickle cell disease and thalassaemia can lead to severe health complications, including chronic pain, anemia, and increased risk of infections. By screening pregnant women and, if necessary, their partners, the programme aims to provide crucial information about the risk of passing these conditions to their offspring. This proactive approach helps manage and mitigate potential health issues, improving outcomes for both mothers and babies.
Definition of numerator The number of pregnant women who have been screened for sickle cell and thalassaemia.
Definition of denominator The total number of pregnant women who are eligible for screening for sickle cell and thalassaemia.
Caveats
Eligibility Criteria: The data only includes pregnant women who meet specific eligibility criteria for screening. Exclusions: Certain groups may be excluded from the data, such as women who miscarry, opt for termination, or transfer out before testing. Informed Choice: The data includes women who decline the screening after being offered, which can impact the overall coverage rates. Technical Limitations: There may be instances where it is not technically possible to perform the screening, leading to exclusions from the data. Service Capacity: The capacity of healthcare providers to accommodate all eligible women can affect the data, especially if there are resource constraints. Data Accuracy: The accuracy of the data depends on the completeness and correctness of the information recorded by healthcare providers.
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The Medical and Orthopaedic Supplies Retailers industry has endured tough operating conditions. The NHS is a significant opponent, offering free treatments and products to qualifying patients. Competitive threats from the private sector, pharmacy chains and dispensing chemists have persisted. Additionally, online-only operators have expanded their product offerings and captured market share from specialist retailers. Despite this, over the five years through 2024-25 revenue is expected to expand at an overall compound annual rate of 13.4%, reaching £2.1 billion. While the NHS is the industry's biggest competitor, this threat has somewhat subsided due to long waiting times, limited product offerings and budgetary constraints. Products available on the NHS aren't always as technologically advanced and some consumers prefer to opt for private treatment. This has favoured industry retailers. Mobility issues and hearing impairment problems are rising, as well as the generally ageing population, which has contributed to growing markets, while increasing product innovation and differentiation among operators have helped the industry stave off decline. The COVID-19 pandemic caused a sharp decline in demand for the industry over 2020-21, causing industry revenue to plummet over the year; however, the industry rebounded over 2021-22 as restrictions were lifted. In 2024-25, the UK's ageing population is expected to support revenue growth of 14.1%. The outlook of the industry is hazy. Competition is anticipated to grow, particularly from online retailers. Nevertheless, underlying demographic trends will increase the average age of the UK population and encourage demand for the industry's products, supporting revenue. Similarly, advances in hearing care and surgery are likely to increase and reduce demand for mechanical products. Operators will keep differentiating products and expand lines and service offerings to capture market share. Over the five years through 2029-30, industry revenue is anticipated to grow at a compound annual rate of 11.3% to reach £3.5 billion.
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The general practice census is collected each year and records numbers and details of GPs in England along with information on their practices, staff, patients and the services they provide. This publication is one of three that make up the NHS Staff 1996 - 2006 publication. The other two are: Non-Medical staff 1996 - 2006 Medical and Dental staff 1996 - 2006 General Practice staff, 30 September 2006 - Detailed Results The detailed results contain further data tables as at September 2006 for England, broken down by Strategic Health Authority area and selected statistics by Primary Care Trust. Each table can be downloaded using the following links: Selected GP statistics by Primary Care Trust Table 1a - All GPs: headcount by type Table 1b - All GPs: full time equivalents by type Table 2 - All GPs (excluding GP registrars & GP retainers), by ageband Table 3 - All GPs (excluding GP registrars & GP retainers), by country of primary medical qualification group Table 4 - Practice staff by type Table 5 - Registered GP patients by ageband Table 6 - GP Partnerships (excluding GP registrars & GP retainers), by size Table 7 - Analysis of GMS Partnership Opt-Outs Table 8 - Patient registration transactions
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This publication provides statistics on the number of unique NHS numbers with an associated national data opt-out. The national data opt-out was introduced on 25 May 2018. It was introduced following recommendations from the National Data Guardian. It indicates that a patient does not want their confidential patient information to be shared for purposes beyond their individual care across the health and care system in England. The service allows individuals to set a national data opt-out or reverse a previously set opt-out. It replaced the previous type 2 opt-outs which patients registered via their GP Practice. Previous type 2 opt-outs have been converted to national data opt-outs each month, until November 2018. This is why the monthly increase in opt-outs decreases from December 2018 onward. This publication includes the number of people who have a national data opt-out, broken down by age, gender and a variety of geographical breakdowns. From June 2020 the methodology for reporting NDOP changed, representing a break in time series. Therefore, caution should be used when comparing data to publications prior to June 2020. The number of deceased people with an active NDOP has been captured and reported for the first time in June 2020. Please note that this publication is no longer released monthly. It is released annually or when the national opt-out rate changes by more than 0.1 per cent. Prior to September 2020 there is a slight inflation of less than 0.05 percent in the number of National Data Opt-outs. This is due to an issue with the data processing, which has been resolved and does not affect data after September 2020. This issue does not disproportionately affect any single breakdown, including geographies. Please take this into consideration when using the data. As of January 2023, index of multiple deprivation (IMD) data has been added to the publication, allowing the total number of opt-outs to be grouped by IMD decile. This data has been included as a new CSV, and has also been added to a new table in the summary file. IMD measures relative deprivation in small areas in England, with decile 1 representing the most deprived areas, and decile 10 representing least deprived. Please note that the figures reported in IMD decile tables will not add up to the national totals. This is because the IMD-LSOA mapping reference data was created in 2019, and any geography codes added since then will not be mapped to an IMD decile. For more information about the reference data used, please view this report: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 Management information describes aggregate information collated and used in the normal course of business to inform operational delivery, policy development or the management of organisational performance. It is usually based on administrative data but can also be a product of survey data. We publish these management information to ensure equality of access and provide wider public value.