AndreaBozzo/ceres-open-data-index huggingface dataset:
Emergency admissions for alcohol-related conditions - ICP Outcomes Framework - Birmingham and Solihull Wards

This dataset provides information on emergency hospital admissions for alcohol-related conditions, using a narrow definition that focuses on cases where the primary diagnosis is directly attributable to alcohol. It presents a directly age-standardised rate per 100,000 population, allowing for meaningful comparisons across different geographical areas and time periods. The data is sourced from the Secondary Uses Service (SUS) inpatient extract and is aligned with population estimates from the 2021 Census. ## Rationale Reducing emergency admissions for alcohol-related conditions is a key public health priority. These admissions often reflect harmful drinking patterns and place a significant burden on healthcare services. By focusing on cases where alcohol is the main reason for admission, this indicator helps identify areas with high levels of alcohol-related harm and supports targeted interventions. ## Numerator The numerator includes hospital admissions where the primary diagnosis is an alcohol-attributable condition. This narrow measure captures instances where alcohol is the main reason for the emergency admission. ## Denominator The denominator is the resident population of the relevant geographical area, based on the 2021 Census. ## Caveats While this indicator provides a focused view of alcohol-related harm, it may not capture the full extent of alcohol’s impact on health, as it excludes cases where alcohol is a contributing factor but not the primary diagnosis. ## External References [Public Health England – Fingertips Indicator] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Emergency admissions for alcohol-related conditions - ICP Outcomes Framework - Resident Locality

This dataset provides information on emergency hospital admissions for alcohol-related conditions, using a narrow definition that focuses on cases where the primary diagnosis is directly attributable to alcohol. It presents a directly age-standardised rate per 100,000 population, allowing for meaningful comparisons across different geographical areas and time periods. The data is sourced from the Secondary Uses Service (SUS) inpatient extract and is aligned with population estimates from the 2021 Census. ## Rationale Reducing emergency admissions for alcohol-related conditions is a key public health priority. These admissions often reflect harmful drinking patterns and place a significant burden on healthcare services. By focusing on cases where alcohol is the main reason for admission, this indicator helps identify areas with high levels of alcohol-related harm and supports targeted interventions. ## Numerator The numerator includes hospital admissions where the primary diagnosis is an alcohol-attributable condition. This narrow measure captures instances where alcohol is the main reason for the emergency admission. ## Denominator The denominator is the resident population of the relevant geographical area, based on the 2021 Census. ## Caveats While this indicator provides a focused view of alcohol-related harm, it may not capture the full extent of alcohol’s impact on health, as it excludes cases where alcohol is a contributing factor but not the primary diagnosis. ## External References [Public Health England – Fingertips Indicator] ## Localities Explained This dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations: * Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs). * Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities. This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address. [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
IMD - Indices of Deprivation 2025 - WMCA Wards (2024)

This dataset presents the latest relative measures of deprivation across England, compiling data for 33,755 LSOAs using the Index of Multiple Deprivation 2025 (IMD25) framework. Rank is based on average LSOA Rank (Lower = More Deprived). Score (Higher = More Deprived) It includes: * A ranking of neighbourhoods from most to least deprived, enabling comparative analysis rather than absolute measurement. * Seven domain indices (Income; Employment; Education, Skills & Training; Health Deprivation & Disability; Crime; Barriers to Housing & Services; Living Environment) which are weighted and aggregated to form the overall IMD25. * Two supplementary indices: the Income Deprivation Affecting Children Index (IDACI) and the Income Deprivation Affecting Older People Index (IDAOPI) * Summary data for higher-level geographies (Local Authority Districts, Integrated Care Boards, etc) derived from the LSOA data. Geographic unit: Administrative wards. ## Temporal Reference This is a cross-sectional release representing a “snapshot” of relative deprivation. While previous versions (e.g., IoD2019) exist, changes to methodology, indicators and geographies mean that direct time-series comparisons should be approached with caution. ## Purpose / Use Cases * To identify and compare areas of relative deprivation across England at small-area level. * To support resource allocation, policymaking, service planning, and funding applications by local and national organisations. * To explore the different domains of deprivation and their spatial patterns. ## Caveats & Limitations * The indices measure relative deprivation only. A rank of “1” identifies the most deprived area relative to others, but this does not quantify the absolute extent of deprivation. * The dataset does not identify deprived individuals nor does it measure affluence. * Comparisons over time (especially across versions) are limited because of changes to data sources, indicator definitions, and geography. * The data apply exclusively to England and should not be directly compared with similar indices from Wales, Scotland or Northern Ireland. ## Methodological Summary * Indicators: 55 indicators used in this version (an increase from 39 in IoD2019) including new and revised measures of income benefit claimants, pupil absence, broadband connectivity, energy performance certificates, access to private gardens, noise pollution, and more. * Domain weights: Income 22.5%; Employment 22.5%; Education/Skills 13.5%; Health 13.5%; Crime 9.3%; Barriers to Housing & Services 9.3%; Living Environment 9.3%. * Extensive quality assurance and validation of indicators and inputs has been conducted. [View full release on GOV.UK]
Smoking prevalence - ICP Outcomes Framework - Registered Locality

This dataset presents the percentage of adults who classify themselves as either regular or occasional smokers, based on responses to the GP Patient Survey (GPPS). It provides a self-reported measure of smoking prevalence across England and is a key indicator of population health and lifestyle behaviours. The data is expressed as a percentage of survey respondents and is used to inform tobacco control strategies and public health planning. ## Rationale Smoking is a major risk factor for a wide range of preventable diseases, including cancer, cardiovascular disease, and respiratory conditions. Reducing smoking prevalence is a central goal of public health policy. This indicator helps track progress in reducing tobacco use and supports targeted interventions to reduce smoking rates, particularly in high-prevalence communities. ## Numerator The numerator is the number of survey respondents who answered "regular smoker" or "occasional smoker" to the question: "Which of the following best describes your smoking habits?" This data is collected through the GP Patient Survey (GPPS). ## Denominator The denominator is the total number of respondents who answered the same question in the GP Patient Survey. ## Caveats No specific caveats were noted in the source metadata. However, as this is a self-reported measure, responses may be subject to reporting bias or underreporting of smoking behaviour. ## External References [Public Health England – Fingertips Tool] ## Localities Explained This dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations: * Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs). * Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities. This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address. [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Smoking prevalence - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the percentage of adults who classify themselves as either regular or occasional smokers, based on responses to the GP Patient Survey (GPPS). It provides a self-reported measure of smoking prevalence across England and is a key indicator of population health and lifestyle behaviours. The data is expressed as a percentage of survey respondents and is used to inform tobacco control strategies and public health planning. ## Rationale Smoking is a major risk factor for a wide range of preventable diseases, including cancer, cardiovascular disease, and respiratory conditions. Reducing smoking prevalence is a central goal of public health policy. This indicator helps track progress in reducing tobacco use and supports targeted interventions to reduce smoking rates, particularly in high-prevalence communities. ## Numerator The numerator is the number of survey respondents who answered "regular smoker" or "occasional smoker" to the question: "Which of the following best describes your smoking habits?" This data is collected through the GP Patient Survey (GPPS). ## Denominator The denominator is the total number of respondents who answered the same question in the GP Patient Survey. ## Caveats No specific caveats were noted in the source metadata. However, as this is a self-reported measure, responses may be subject to reporting bias or underreporting of smoking behaviour. ## External References [Public Health England – Fingertips Tool] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Smoking attributable hospital admissions - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the rate of hospital admissions attributable to smoking among adults in England. It is calculated using Smoking Attributable Fractions (SAFs) applied to hospital admissions data from the Hospital Episode Statistics (HES). The indicator includes admissions where smoking-related conditions are recorded as the primary diagnosis and provides a measure of the health burden of smoking on secondary care services. ## Rationale Smoking is a major risk factor for a wide range of diseases, including cancers, cardiovascular and respiratory conditions, and other chronic illnesses. Monitoring hospital admissions attributable to smoking helps local authorities and health services understand the impact of tobacco use on healthcare demand and supports the development of targeted public health interventions to reduce smoking prevalence and associated harms. ## Numerator The numerator is the estimated number of hospital admissions attributable to smoking. This is calculated by multiplying the number of admissions for specific smoking-related conditions by the corresponding Smoking Attributable Fractions (SAFs). The dataset includes a wide range of diagnoses across cancer, cardiovascular, respiratory, and other disease categories. ## Denominator The denominator is the mid-year population estimate for the relevant area, as provided by the Office for National Statistics (ONS). ## Caveats Not all smoking-related conditions result in inpatient admissions, so this indicator captures only a portion of the total health burden of smoking. However, it provides a consistent and routinely available measure for monitoring the impact of smoking at the local level. The indicator is limited to individuals aged 35 and over and includes only finished admission episodes with specific criteria for admission type and residency. ## External References More information is available from the following source: * [Fingertips Public Health Profiles] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Long-acting Reversible Contraception prescriptions - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the rate of prescribing long-acting reversible contraception (LARC), excluding injections, to females aged 15 to 44 in England. It includes prescriptions for implants, intrauterine systems (IUS), and intrauterine devices (IUD) issued during the calendar year. The data is sourced from the NHS Business Services Authority (NHSBSA) and is expressed as a crude rate per 1,000 women in the target age group. ## Rationale Increasing the uptake of LARC is a key public health objective, as these methods are among the most effective forms of contraception. They help reduce unintended pregnancies and support reproductive autonomy. Monitoring prescription rates helps assess access to and utilisation of these contraceptive options, informing service planning and sexual health strategies. ## Numerator The numerator is the total number of LARC prescriptions (implants, IUS, and IUDs) issued to women of all ages during the calendar year. This data is obtained from NHSBSA’s ePACT2 prescription dataset. ## Denominator The denominator is the number of females aged 15 to 44, based on mid-year population estimates from the Office for National Statistics (ONS). ## Caveats This dataset does not include LARC prescriptions issued in abortion, maternity, or gynaecology settings. Additionally, GP prescribing data reflects all-purpose prescriptions rather than individual-level data, which may not accurately represent the number of women using LARC for contraceptive purposes. ## External References [NHSBSA – Prescription Data (ePACT2)] [Public Health England – Sexual Health Profile] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
People with a learning disability having a GP health check - ICP Outcomes Framework - Registered Locality

This dataset presents the percentage of individuals on GP learning disability registers who received an annual health check. It reflects the uptake of health checks among people with learning disabilities, as reported by GP practices participating in the Learning Disabilities Health Check Scheme. The data is sourced from NHS Digital and includes individuals aged 14 and over. ## Rationale People with learning disabilities often face significant health inequalities and are at greater risk of undiagnosed or poorly managed health conditions. Annual health checks are a key intervention to identify unmet health needs and support better health outcomes. This indicator helps monitor the reach and effectiveness of the scheme and supports efforts to increase access to preventative care for this population. ## Numerator The numerator is the number of annual health checks completed for individuals with learning disabilities, as reported by participating GP practices through the Learning Disabilities Health Check Scheme. ## Denominator The denominator is the total number of individuals registered with a GP as having a learning disability, based on definitions used in the Quality and Outcomes Framework (QOF). ## Caveats There is a known misalignment ## Localities Explained This dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations: * Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs). * Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities. This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address. [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
IMD - Indices of Deprivation 2025 - WMCA Postcodes

This dataset presents the latest relative measures of deprivation across England, compiling data for 33,755 LSOAs using the Index of Multiple Deprivation 2025 (IMD25) framework. It includes: * A ranking of neighbourhoods from most to least deprived, enabling comparative analysis rather than absolute measurement. * Seven domain indices (Income; Employment; Education, Skills & Training; Health Deprivation & Disability; Crime; Barriers to Housing & Services; Living Environment) which are weighted and aggregated to form the overall IMD25. * Two supplementary indices: the Income Deprivation Affecting Children Index (IDACI) and the Income Deprivation Affecting Older People Index (IDAOPI) * Summary data for higher-level geographies (Local Authority Districts, Integrated Care Boards, etc) derived from the LSOA data. Geographic unit: Postcodes. Data for the IoD is modelled at LSOA level. This dataset contains the postcodes within each LSOA and will report on the LSOA scores and ranks as well as provide the values for the respective local authority. ## Temporal Reference This is a cross-sectional release representing a “snapshot” of relative deprivation. While previous versions (e.g., IoD2019) exist, changes to methodology, indicators and geographies mean that direct time-series comparisons should be approached with caution. ## Purpose / Use Cases * To identify and compare areas of relative deprivation across England at small-area level. * To support resource allocation, policymaking, service planning, and funding applications by local and national organisations. * To explore the different domains of deprivation and their spatial patterns. ## Caveats & Limitations * The indices measure relative deprivation only. A rank of “1” identifies the most deprived area relative to others, but this does not quantify the absolute extent of deprivation. * The dataset does not identify deprived individuals nor does it measure affluence. * Comparisons over time (especially across versions) are limited because of changes to data sources, indicator definitions, and geography. * The data apply exclusively to England and should not be directly compared with similar indices from Wales, Scotland or Northern Ireland. ## Methodological Summary * Indicators: 55 indicators used in this version (an increase from 39 in IoD2019) including new and revised measures of income benefit claimants, pupil absence, broadband connectivity, energy performance certificates, access to private gardens, noise pollution, and more. * Domain weights: Income 22.5%; Employment 22.5%; Education/Skills 13.5%; Health 13.5%; Crime 9.3%; Barriers to Housing & Services 9.3%; Living Environment 9.3%. * Extensive quality assurance and validation of indicators and inputs has been conducted. [View full release on GOV.UK]
People with a learning disability having a GP health check  - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the percentage of individuals on GP learning disability registers who received an annual health check. It reflects the uptake of health checks among people with learning disabilities, as reported by GP practices participating in the Learning Disabilities Health Check Scheme. The data is sourced from NHS Digital and includes individuals aged 14 and over. ## Rationale People with learning disabilities often face significant health inequalities and are at greater risk of undiagnosed or poorly managed health conditions. Annual health checks are a key intervention to identify unmet health needs and support better health outcomes. This indicator helps monitor the reach and effectiveness of the scheme and supports efforts to increase access to preventative care for this population. ## Numerator The numerator is the number of annual health checks completed for individuals with learning disabilities, as reported by participating GP practices through the Learning Disabilities Health Check Scheme. ## Denominator The denominator is the total number of individuals registered with a GP as having a learning disability, based on definitions used in the Quality and Outcomes Framework (QOF). ## Caveats There is a known misalignment [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Covid-19 immunisations - ICP Outcomes Framework - Birmingham and Solihull

This dataset reports the uptake of at least one dose of the COVID-19 vaccine among patients registered with GP practices in England. It provides a measure of immunisation coverage and supports monitoring of public health efforts to reduce the spread and severity of COVID-19. The data is sourced from Immform, EMIS Health, and TPP systems. ## Rationale Vaccination is a critical tool in controlling the COVID-19 pandemic. Monitoring vaccine uptake helps identify gaps in coverage, inform targeted outreach, and evaluate the effectiveness of immunisation campaigns. This indicator supports efforts to increase vaccine uptake and protect vulnerable populations. ## Numerator The numerator is the number of patients who have received at least one dose of a COVID-19 vaccine. ## Denominator The denominator is the total number of patients registered with GP practices, as recorded in the Immform-EMIS Health and TPP systems. ## Caveats Automated data collection is only possible from GP practices whose IT suppliers support automatic extraction. Some organisations may not have responded or submitted data, which could affect completeness and accuracy. ## External References More information is available from the following source: * [Immform COVID-19 Collections Portal] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.