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.

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"

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.

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

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.

Abstract copyright UK Data Service and data collection copyright owner.The National Patient Survey Programme is one of the largest patient survey programmes in the world. It provides an opportunity to monitor experiences of health and provides data to assist with registration of trusts and monitoring on-going compliance. Understanding what people think about the care and treatment they receive is crucial to improving the quality of care being delivered by healthcare organisations. One way of doing this is by asking people who have recently used the health service to tell the Care Quality Commission (CQC) about their experiences. The CQC will use the results from the surveys in the regulation, monitoring and inspection of NHS acute trusts (or, for community mental health service user surveys, providers of mental health services) in England. Data are used in CQC Insight, an intelligence tool which identifies potential changes in quality of care and then supports deciding on the right regulatory response. Survey data will also be used to support CQC inspections. Each survey has a different focus. These include patients' experiences in outpatient and accident and emergency departments in Acute Trusts, and the experiences of people using mental health services in the community. History of the programme The National Patient Survey Programme began in 2002, and was then conducted by the Commission for Health Improvement (CHI), along with the Commission for Healthcare Audit and Inspection (CHAI). Administration of the programme was taken over by the Healthcare Commission in time for the 2004 series. On 1 April 2009, the CQC was formed, which replaced the Healthcare Commission. Further information about the National Patient Survey Programme may be found on the CQC Patient Survey Programme web pages. The Children and Young People's Patient Experience Survey, 2018 is the third national children's survey conducted by CQC. It represents the experiences of nearly 33,179 children and young people who received inpatient or day case care in 129 acute and specialist NHS trusts in 2018. Further information can be found in the CQC document 2018 Children and Young People's Patient Experience Survey Statistical Release.

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.

This dataset has been discontinued and replaced with the Mental Health Services Monthly Statistics dataset, available at https://data.gov.uk/dataset/mental-health-services-monthly-statistics

The Mental Health Minimum Data Set (MHMDS) was renamed Mental Health and Learning Disabilities Data Set (MHLDDS) following an expansion in scope (from September 2014) to include people in contact with learning disability services for the first time.

This monthly statistical release makes available the most recent Mental Health Minimum Dataset (MHMDS) data from April 2013 onwards. Further analysis to support currencies and payment in adult and older people's mental health services was added to the publication of April 2014 final data which can be found in the related links below. These changes are described in the Methodological Change paper referenced below.

As well as providing timely data, it presents a wide range of information about care given to users of NHS-funded, secondary mental health services for adults and older people ('secondary mental health services') in England.

This information will be of particular interest to organisations involved in giving secondary mental health care to adults and older people, as it presents timely information to support discussions between providers and commissioners of services. The MHMDS Monthly Report now includes the ten nationally recommended quality and outcome indicators to support the implementation of currencies and payment in mental health.

For patients, researchers, agencies and the wider public it aims to provide up to date information about the numbers of people using services, spending time in psychiatric hospitals and subject to the Mental Health Act (MHA). Some of these measures are currently experimental analysis.

Abstract copyright UK Data Service and data collection copyright owner.The National Patient Survey Programme is one of the largest patient survey programmes in the world. It provides an opportunity to monitor experiences of health and provides data to assist with registration of trusts and monitoring on-going compliance. Understanding what people think about the care and treatment they receive is crucial to improving the quality of care being delivered by healthcare organisations. One way of doing this is by asking people who have recently used the health service to tell the Care Quality Commission (CQC) about their experiences. The CQC will use the results from the surveys in the regulation, monitoring and inspection of NHS acute trusts (or, for community mental health service user surveys, providers of mental health services) in England. Data are used in CQC Insight, an intelligence tool which identifies potential changes in quality of care and then supports deciding on the right regulatory response. Survey data will also be used to support CQC inspections. Each survey has a different focus. These include patients' experiences in outpatient and accident and emergency departments in Acute Trusts, and the experiences of people using mental health services in the community. History of the programme The National Patient Survey Programme began in 2002, and was then conducted by the Commission for Health Improvement (CHI), along with the Commission for Healthcare Audit and Inspection (CHAI). Administration of the programme was taken over by the Healthcare Commission in time for the 2004 series. On 1 April 2009, the CQC was formed, which replaced the Healthcare Commission. Further information about the National Patient Survey Programme may be found on the CQC Patient Survey Programme web pages. The Community Mental Health Service User Survey, 2021 (CMH21) was designed to provide actionable feedback to each participating trust on service users' views of the care they had received. Fifty-four providers of NHS mental health services in England participated in the Community Mental Health Service User Survey, 2021. This includes combined mental health and social care trusts, foundation trusts and community healthcare social enterprises that provide NHS mental health services. The survey covers issues that affect the quality of care that people receive and were identified by people as important to them. Topics covered include: health and social care workers, planning care, reviewing care, crisis care, treatments and other areas of life. People aged 18 and over were eligible to take part if they were receiving specialist care or treatment for a mental health condition between 1 September 2020 and 30 November 2020. Fieldwork took place between February 2021 and June 2021. The survey team received responses from 17,322 people, a response rate of 26%. As care is ongoing for respondents to this survey, they have experienced community mental health services during different phases of the Covid pandemic.

The Mental Health and Learning Disabilities Data Set version 1 (Episode Level - sensitive data exclusion). The Mental Health Minimum Data Set was superseded by the Mental Health and Learning Disabilities Data Set, which in turn was superseded by the Mental Health Services Data Set. The Mental Health and Learning Disabilities Data Set collected data from the health records of individual children, young people and adults who were in contact with mental health services.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of physical illnesses that are linked with obesity and inactivity. 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:- Asthma (in persons of all ages)- Cancer (in persons of all ages)- Chronic kidney disease (in adults aged 18+)- Coronary heart disease (in persons of all ages)- Diabetes mellitus (in persons aged 17+)- Hypertension (in persons of all ages)- Stroke and transient ischaemic attack (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.For each of the above illnesses, the percentage of each MSOA’s population with that illness 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 area- Of the GPs that covered part of that MSOA: the percentage of patients registered with each GP that have that illnessThe estimated percentage of each MSOA’s population with each illness 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 each illness, within the relevant age range.For each illness, 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 that illnessB) the NUMBER of people within that MSOA who are estimated to have that illnessAn 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 predicted to have that illness, compared to other MSOAs. In other words, those are areas where a large number of people are predicted to suffer from an illness, and where those people make up a large percentage of the population, indicating there is a real issue with that illness within the population and the investment of resources to address that issue could have the greatest benefits.The scores for each of the 7 illnesses were added together then converted to a relative score between 1 – 0 (1 = worst, 0 = best), to give an overall score for each MSOA: a score close to 1 would indicate that an area has high predicted levels of all obesity/inactivity-related illnesses, and these are areas where the local population could benefit the most from interventions to address those illnesses. A score close to 0 would indicate very low predicted levels of obesity/inactivity-related illnesses and therefore interventions might not be required.LIMITATIONS1. GPs do not have catchments that are mutually exclusive from each other: they overlap, with some geographic areas being covered by 30+ practices. This dataset should be viewed in combination with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset to identify where there are areas that are covered by multiple GP practices but at least one of those GP practices did not provide data. Results of the analysis in these areas should be interpreted with caution, particularly if the levels of obesity/inactivity-related illnesses appear to be significantly lower than the immediate surrounding areas.2. 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).3. 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.4. 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 obesity/inactivity-related illnesses, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of these illnesses. 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 outliersDOWNLOADING 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.

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.

Healthcare workers (HCWs) are known to be at increased risk of infection with SARS-CoV-2, although whether these risks are equal across all roles is uncertain. Here we report a retrospective analysis of a large real-world dataset obtained from 10 March to 6 July 2020 in an NHS Foundation Trust in England with 17,126 employees. 3,338 HCWs underwent symptomatic PCR testing (14.4% positive, 2.8% of all staff) and 11,103 HCWs underwent serological testing for SARS-CoV-2 IgG (8.4% positive, 5.5% of all staff). Seropositivity was lower than other hospital settings in England but higher than community estimates. Increased test positivity rates were observed in HCWs from BAME backgrounds and residents in areas of higher social deprivation. A multiple logistic regression model adjusting for ethnicity and social deprivation confirmed statistically significant increases in the odds of testing positive in certain occupational groups, most notably domestic services staff, nurses, and health-care assistants. PCR testing of symptomatic HCWs appeared to underestimate overall infection levels, probably due to asymptomatic seroconversion. Clinical outcomes were reassuring, with only a small minority of HCWs with COVID-19 requiring hospitalization (2.3%) or ICU management (0.7%) and with no deaths. Despite a relatively low level of HCW infection compared to other UK cohorts, there were nevertheless important differences in test positivity rates between occupational groups, robust to adjustment for demographic factors such as ethnic background and social deprivation. Quantitative and qualitative studies are needed to better understand the factors contributing to this risk. Robust informatics solutions for HCW exposure data are essential to inform occupational monitoring.

The Service User (patient) data collected from the Mental Health Services Data Set. The Mental Health Services Data Set (MHSDS) collects data from the health records of individual children, young people and adults who are in contact with mental health services. The data is re-used for purposes other than their direct care and as such is referred to as a secondary uses data set. It defines data items, definitions and information extracted or derived from local information systems.

• 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 targets
• since 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. The household data file is no longer released for analysis. In addition, users may see other changes; for example only grouped age is now available instead of single year of age. NHS Digital have issued the following statement on changes to the HSE from 2015:

"NHS Digital has recently reviewed how we manage access to survey datasets. In doing this we have sought to strike a balance between protecting the privacy of individuals and enabling maximum use of these valuable, publicly funded data collections. We have thoroughly reviewed our disclosure control measures, including taking advice from experts at the Office of National Statistics. The result is that additional disclosure control measures have been applied to the 2015 survey [onwards] to enable a suitable dataset to be made available through the UK Data Service via end user licence. This involved providing less detail on some aspects, such as geographical classifications, ethnicity and household relationships. To provide greater protection of the answers of children and adults within households it is not possible to identify people within the same household on this dataset, however parent/guardian derived variables appended to their children (if they have any) have been added to enable some intra‐household analysis.”

It is hoped that a second dataset with more detail including family and household relationships will be made available via Special Licence. In the meantime, researchers who want to do analysis of health and behaviours within families or households, and the derived intra-household variables do not meet your needs, are advised to register their interest for a more detailed dataset with NatCen Social Research and provide information about their proposed research and which data they want.

For the third edition (December 2019), corrections have been made for two equivalised income derived variables (Eqv3 and Eqv5); in the previous editions the number of cases coded to -1 was incorrectly higher than normal, and some cases have been coded with the wrong score.

The Maternity Indicators Data Set captures data relating to the woman at initial assessment and to mother and baby (or babies) for all births. This relates to initial assessment and birth activity undertaken in Wales only. Each Health Board must make available data in relation to the initial assessments and/or birth events which they managed.

For example, if they only carried out the initial assessment the Health Board would only be required to provide the initial assessment data. This is further detailed in the technical specification (see ‘return submission details’).

Where the initial assessment and birth events take place in different Health Boards, data will be linked nationally by the NHS Wales Informatics Service.

Velindre NHS Trust are excluded from this requirement, as they do not provide any maternity services.

Monthly activity data must include only initial assessment and birth activity that took place in the previous month.

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

The Mental Health Minimum Data Set (MHMDS) was renamed Mental Health and Learning Disabilities Data Set (MHLDDS) following an expansion in scope (from September 2014) to include people in contact with learning disability services for the first time.

This monthly statistical release makes available the most recent Mental Health Minimum Dataset (MHMDS) data from April 2013 onwards. Further analysis to support currencies and payment in adult and older people's mental health services was added to the publication of April 2014 final data which can be found in the related links below. These changes are described in the Methodological Change paper referenced below.

As well as providing timely data, it presents a wide range of information about care given to users of NHS-funded, secondary mental health services for adults and older people ('secondary mental health services') in England.

This information will be of particular interest to organisations involved in giving secondary mental health care to adults and older people, as it presents timely information to support discussions between providers and commissioners of services. The MHMDS Monthly Report now includes the ten nationally recommended quality and outcome indicators to support the implementation of currencies and payment in mental health.

For patients, researchers, agencies and the wider public it aims to provide up to date information about the numbers of people using services, spending time in psychiatric hospitals and subject to the Mental Health Act (MHA). Some of these measures are currently experimental analysis.

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 version of the dataset contains variables with a higher disclosure risk or are more sensitive than those included in the EUL version and is subject to more restrictive access conditions (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.COVID-19 and the HSE:Due to the COVID-19 pandemic, the HSE 2020 survey was stopped in March 2020 and never re-started. There was no publication that year. The survey resumed in 2021, albeit with an amended methodology. The full HSE resumed in 2022, with an extended fieldwork period. Due to this, the decision was taken not to progress with the 2023 survey, to maximise the 2022 survey response and enable more robust reporting of data. See the NHS Digital Health Survey for England - Health, social care and lifestyles webpage for more details. The Health Survey for England, 2016 EUL version is available from the UK Data Archive under SN 8334. Main Topics: Data collection involved an interview, followed by a visit from a specially trained nurse for all those in the core sample who agreed.The 2016 survey included additional topics for adults on physical activity, weight management, kidney and liver disease and problem gambling. The survey also provided updates on repeated core topics, including general health, long standing illness, smoking and drinking.The nurse visit covered height and weight measurement, blood pressure measurement, waist and hip circumference measurement, taking of blood samples for cholesterol and glycated haemoglobin, and taking of adult and child saliva samples. In 2016, urine samples were also collected from adult participants.