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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.
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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.
BackgroundBackground
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).
As in previous years, the 2010 survey contained 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 there are a few sector-specific questions. A few questions were dropped and some added for 2010 - see Appendix 9 of the Guidance Notes document for details of changes.
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.
https://northwestsde.nhs.uk/for-sde-users/apply-to-use-the-sdehttps://northwestsde.nhs.uk/for-sde-users/apply-to-use-the-sde
This OMOP CDM is built from a flow of primary care data from Cheshire and Merseyside GPs who have signed the ICB Data Sharing Agreement for Population Health. Patients who have signalled that they wish to opt out of their records being shared for secondary uses (i.e. uses beyond Direct Patient Care) are removed as per national data opt-out policy. The source data is refreshed weekly (Sunday evenings) and the data set includes a long list of fields relating to: NHS number, allergies, medications issued, Repeat medications, Covid-19 status, Active and Past Problems, GP Results, Vitals & Measurements (height/weight, BP, physiological function result), Lifestyle factors (smoking and alcohol), GP encounters, vaccinations and immunisations, Contraindications, OTC and Prophylactic Therapy, Family History, Child Health, Diabetes Diagnosis, Chronic Disease Monitoring.
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.).
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 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 year 6 (aged 10 to 11 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 The 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.
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.
Abstract copyright UK Data Service and data collection copyright owner.
https://www.kcl.ac.uk/research/elixir-1https://www.kcl.ac.uk/research/elixir-1
Investment in the earliest stages of life is increasingly recognised to improve health across the life-course, beginning with the health of parents before pregnancy, in embryonic life, through to infancy, childhood, and into adulthood. eLIXIR BiSL combines information from routine maternity and neonatal health records and blood samples at two acute NHS Trust hospitals, along with mental health and primary care data. The study is able to address relationships between maternal and child physical health, and to investigate interactions with mental health. Participants are predominantly residents of South London, in areas with high levels of deprivation and ethnic diversity.
The BiSL data-linkage project uses opt-out consent to collect routine maternity and neonatal clinical patient data (GSTT and KCH NHS Trusts), mental health data from the SLaM CRIS platform, and primary care data from the LDN platform, for those registered with a GP in Lambeth. We hold the approval to also link with emergency and admissions data (HES), national fertility data (HFEA), and immunisation records (NIMS), as well as expanding primary care data to other boroughs in South London, namely: Southwark, Lewisham, and Bromley; the process to link these new data sources is currently ongoing.
At present, eLIXIR holds over 50,000 records. All records are deidentified, including masking of identifying information in open-text fields and use of pseudonymised identifiers. The data refresh process occurs every 6 months, and each update includes all retrospective data since conception of the cohort (October 2018), thus building a dynamic cohort.
The BiSL team includes members King’s College London Faculty of Life Sciences and Medicine and the Institute of Psychiatry, Psychology and Neurosciences (IoPPN), along with services users and patient representatives.
The eLIXIR Born in South London project has now been successfully awarded a MRC Longitudinal Population Study Grant which will enable us to operate for the next 5 years and continue building this dynamic mother-child database. BiSL is part of the MIREDA Study Partnership bringing together birth cohort data across the UK.
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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.