- EU nationals register for a National Insurance number (NINo) more quickly than non-EU nationals, with median lags of 72 days and 135 days respectively. Non-EU nationals register with the NHS more quickly, with median lags of 60 days compared to 276 days for EU nationals.
- Linking administrative data sources like the Migrant Worker Scan (NINo registrations) and Personal Demographic Service (NHS registrations) provides insights into how international migrants interact with different systems and leave data footprints.
- Certain groups like females and younger individuals tend to register more quickly with the NHS than others. Analyzing registration lags by characteristics like nationality, age and sex can help understand
This slide pack illustrates the Office for National Statistics’ (ONS) research into developing an alternative approach to producing administrative data-based population stocks and flows.
The National Tobacco Control Program aims to eliminate exposure to secondhand smoke, promote quitting among adults and youth, and prevent tobacco initiation among youth. Tobacco use is the leading cause of preventable disease and death in the United States, responsible for over 480,000 deaths per year. The program monitors outcomes through several national and state surveys to track objectives like decreasing secondhand smoke exposure and increasing tobacco cessation attempts. The goals of the program help promote sustainability and accountability over the next 10 years as outlined in Healthy People 2020.
The document provides an overview of the health system in Sri Lanka. It discusses the following key points in 3 sentences:
Sri Lanka has a universal health care system with free health services provided through a network of public health facilities across the country. The country has achieved high health indicators comparable to developed nations despite spending a low percentage of GDP on health. However, the health system is now facing challenges due to the country's ongoing economic crisis including shortages of essential medicines and staffing issues.
The document outlines the French school system, beginning with an overview of the founding principles of free, secular, and compulsory public education. It then describes the different levels and cycles of education from nursery school through high school/university, including typical course contents and objectives at each level. Key aspects of the primary education system such as the organization of the school day and teaching time allotted to different subjects are also summarized.
Chi Square Test…..
This topic comes under Biostatistics…….
This is useful for Maths students, B.Pharm Students ,M.Pharm Students who studying Biostatistics.
This Presentation Contain following...
#History and Introduction
#Conditions
#Formula
#Classification
#Types of Non-Parametric Chi Square Test
#Test of Independence
#Steps for Test of Independence
#Problem and Solution for Test of Independence
#Test of Goodness of Fit
#Problem and Solution for Test of Goodness of Fit
#Applications of Chi Square Test
Thanks for the Help and Guidance of Dr. M. S. Bhatia Sir
The UK education system is overseen by different government departments in each constituent country. In England, the Department for Children, Schools and Families and Department for Business, Innovation and Skills are responsible. Local authorities and school governing bodies administer schools. Compulsory education ranges from ages 5-16. The education system includes primary, secondary, further education, and higher education.
1) The document describes the unpaired t-test and paired t-test. The unpaired t-test is used to compare the means of two independent samples, while the paired t-test compares the means of two related samples or samples measured under different conditions.
2) For the unpaired t-test, the null hypothesis is that there is no difference between the population means, while the alternative hypothesis is that there is a difference. The test statistic is calculated as the difference between the sample means divided by the standard error.
3) For the paired t-test, the null hypothesis is that the mean of the differences between pairs is zero, indicating no change. The alternative hypothesis is that the mean
This slide pack illustrates the Office for National Statistics’ (ONS) research into developing an alternative approach to producing administrative data-based population stocks and flows.
The National Tobacco Control Program aims to eliminate exposure to secondhand smoke, promote quitting among adults and youth, and prevent tobacco initiation among youth. Tobacco use is the leading cause of preventable disease and death in the United States, responsible for over 480,000 deaths per year. The program monitors outcomes through several national and state surveys to track objectives like decreasing secondhand smoke exposure and increasing tobacco cessation attempts. The goals of the program help promote sustainability and accountability over the next 10 years as outlined in Healthy People 2020.
The document provides an overview of the health system in Sri Lanka. It discusses the following key points in 3 sentences:
Sri Lanka has a universal health care system with free health services provided through a network of public health facilities across the country. The country has achieved high health indicators comparable to developed nations despite spending a low percentage of GDP on health. However, the health system is now facing challenges due to the country's ongoing economic crisis including shortages of essential medicines and staffing issues.
The document outlines the French school system, beginning with an overview of the founding principles of free, secular, and compulsory public education. It then describes the different levels and cycles of education from nursery school through high school/university, including typical course contents and objectives at each level. Key aspects of the primary education system such as the organization of the school day and teaching time allotted to different subjects are also summarized.
Chi Square Test…..
This topic comes under Biostatistics…….
This is useful for Maths students, B.Pharm Students ,M.Pharm Students who studying Biostatistics.
This Presentation Contain following...
#History and Introduction
#Conditions
#Formula
#Classification
#Types of Non-Parametric Chi Square Test
#Test of Independence
#Steps for Test of Independence
#Problem and Solution for Test of Independence
#Test of Goodness of Fit
#Problem and Solution for Test of Goodness of Fit
#Applications of Chi Square Test
Thanks for the Help and Guidance of Dr. M. S. Bhatia Sir
The UK education system is overseen by different government departments in each constituent country. In England, the Department for Children, Schools and Families and Department for Business, Innovation and Skills are responsible. Local authorities and school governing bodies administer schools. Compulsory education ranges from ages 5-16. The education system includes primary, secondary, further education, and higher education.
1) The document describes the unpaired t-test and paired t-test. The unpaired t-test is used to compare the means of two independent samples, while the paired t-test compares the means of two related samples or samples measured under different conditions.
2) For the unpaired t-test, the null hypothesis is that there is no difference between the population means, while the alternative hypothesis is that there is a difference. The test statistic is calculated as the difference between the sample means divided by the standard error.
3) For the paired t-test, the null hypothesis is that the mean of the differences between pairs is zero, indicating no change. The alternative hypothesis is that the mean
Understanding the concept of Universal Health Coverage (UHC) and how can we reach it, both globally and also in India. The presentation also includes HLEG report , which is the proposed architecture for India's guide to reach UHC.
Pharmaceutical marketing channels - selecting appropriate channel of distribu...AkankshaAshtankar
A marketing channel, also known as a distribution channel, involves the movement of goods and services from manufacturers through intermediaries to consumers. It is the set of interdependent organizations that facilitate making a product or service available. For pharmaceutical companies, the standard marketing channel involves the manufacturer, physician, wholesaler, retailer, and consumer. When selecting distribution channels, pharmaceutical firms consider the infrastructure, marketing capabilities, relationship intensity, logistics capabilities, and strategic issues of potential intermediaries.
Graphs are used to visually represent data and relationships between variables. There are various types of graphs that can be used for different purposes. Histograms represent the distribution of continuous variables. Bar graphs display the distribution of categorical variables or allow for comparisons between categories. Line graphs show trends and patterns over time. Pie charts summarize categorical data as percentages of a whole. Cubic graphs refer to graphs where all vertices have a degree of three. Response surface plots visualize the relationship between multiple independent variables and a response variable.
A sample design is a definite plan for obtaining a sample from a given population. Researcher must select/prepare a sample design which should be reliable and appropriate for his research study.
The document is a powerpoint presentation about life expectancy. It aims to explain that (1) life expectancy is an average and (2) when life expectancy is low, it is often due to high child mortality rather than everyone dying slightly earlier. It illustrates these points by comparing expected lifespans of newborns in Burundi versus Sweden, finding that while the average life expectancy is lower in Burundi, some Burundians live into old age, but many die young as children, bringing down the overall average.
The document discusses the Demographic Transition Model, which attempts to show how population changes as a country develops. The model divides development into four stages:
Stage 1 has high birth and death rates, leading to low population growth. Stages 2 and 3 see birth rates remain high while death rates fall dramatically, resulting in rapid population increase. Stage 4 is characterized by low birth and death rates, leading again to low population growth. The model shows these stages through a country's population pyramid shape. However, the model is an overgeneralization and does not consider exceptions like war or political issues.
This case study aims to understand the activity patterns of international migrants in income and benefit data. The slides summarise what research is already published on these activity patterns and illustrate what exploratory research, using linked administrative data sources, can further tell us. The findings from this case study provide important insights which are key to the successful development of a population and migration statistics system based on administrative data sources.
This document provides information about data sources on migration available from the GLA Intelligence Unit. It discusses various administrative data sources like the NHS Central Register and International Passenger Survey that provide information on internal and international migration trends in London. It also summarizes key findings from these sources, like over 30% of London's population being foreign-born. The document outlines the strengths and limitations of different data sources and highlights opportunities from the 2011 Census to improve understanding of migration patterns.
Estimating The Size of the Irish PopulationAlan McSweeney
The various sources of population-related data are inconsistent with one another. There has been past issues with determining the extent of immigration. This in turn creates an issue with the size of the population of Ireland.
This analysis has identified one possible set of inconsistencies relating to the size of the Irish population. It may well be that the population of Ireland is greater that than counted by the CSO in the census.
Population sizes at various ages determine the demand for different societal resources. People are, after all, the direct and indirect buyers and users of products and services, both public and private sector. People drive demand. Changes in the profile of people – numbers and ages – will change the demand profile.
Discrepancies between other data sources from which population data can be inferred and the CSO’s population data indicate that there may be ongoing errors.
Consistency checking between multiple sets of related data is a standard technique to identify potential quality data issues that should then be the subject of further analysis. Detailed consistency checking is hampered by the limited set of information made publically available by various state agencies.
This analysis has looked at the following sets of data with a view to identifying potential data conflicts:
1. DEASP PPSN Registration Numbers
2. CSO PPSN Numbers
3. CSO Migration Numbers
4. CSO Population Numbers
5. Revenue Income Tax Numbers
6. Department of Education Third-Level Numbers
7. DEASP Pensioner Numbers
8. DEASP Live Register/Disability/Work Activation Numbers
9. Irish Naturalisation and Immigration Service (INIS) Statistics
One of the central goals for the province of New Brunswick is to boost economic development by increasing labour market participation, and immigration is key to this plan. However, while NB has welcomed a growing number of immigrants over time, a substantial number still choose to leave the province years after landing.
This raises questions, such as, “Who decides to stay? Who decides to leave? And what factors influence these decisions?”
Understanding the backgrounds and experiences of immigrants residing in NB may help the province address challenges related to immigrant retention. Since there is a well-established link between mobility and economic opportunity, focusing on the entry streams and economic experiences of immigrants in NB may shed light on a correlation between experiences and retention. NB-IRDT’s 2021 publications on immigrant retention do just that.
Immigrant Retention in New Brunswick (McDonald & Miah) estimates the retention rates of all immigrants who intended to arrive in the province by immigration stream, and Immigrant Income and Labour Market Outcomes (Boco et al.) examines the economic outcomes and retention rates of immigrants to investigate trends and determinants of income and retention. Comparing these two reports allows us to highlight similarities and differences in the datasets, associated methodologies, and results.
We aim for the findings of these reports to contribute to evidence-based assessments of provincial immigration policies and efforts, while presenting detailed descriptive and empirical evidence on the evolution of immigrant retention and immigrants’ post-landing labour market experiences in NB.
The document summarizes UK travel restrictions for returning passengers from green, amber, and red list countries. Passengers returning from green countries do not need to quarantine but must take a COVID-19 test. Those returning from amber countries must self-isolate for 10 days and take two tests. For red list countries, passengers must quarantine in a hotel for 10 days and take two tests. The UK government will review the rules monthly and aims to reduce travel restrictions over time if vaccination rates, case numbers, and variants of concern remain stable.
The document summarizes UK travel restrictions for returning passengers from green, amber, and red list countries. Passengers returning from green countries do not need to quarantine but must take a COVID-19 test. Those returning from amber countries must self-isolate for 10 days and take two tests. For red list countries, passengers must quarantine in a hotel for 10 days and take two tests. The UK government will review the rules monthly and aims to reduce travel restrictions over time if vaccination rates increase and new variants and infections remain low.
2015 01 22_briefing - family and dependents_mig_observatoryMiqui Mel
This document summarizes data on non-European family and dependent migration to the UK from various sources such as the Office for National Statistics and Home Office statistics. Some key points:
- Non-EU family migration has increased since the 1990s but at a slower rate than other migration categories. Asia remains the most common region of origin for non-EEA family migrants.
- Most non-EEA family migrants entering under unification rules are women. Over 90% of those entering as spouses or fiancés are already married.
- Tier 1 and Tier 2 migrants (high-skilled workers and investors) bring the most dependents per capita.
- Family migration peaked in
After a +3% point rise in consumer confidence in the third quarter of 2017, the latest Deloitte Consumer Tracker remains flat at -7%. This quarter’s results represent the first time since our survey began in 2011 that confidence has not fallen in the final quarter of the year.
Ta2.09 1 mills.un data forum innovations crvs idms sam mills jan 14 2017Statistics South Africa
Overview of importance of CRVS in monitoring SDGs, Principles on Identification for Sustainable Development, CRVS eLearning course by the Global CRVS group - presented at the UN World Data Forum
For The State of the State 2017-18 Deloitte LLP commissioned Ipsos MORI to survey c.1000 UK adults on their attitudes to public service spending and austerity; social care services and personal data sharing.
The document outlines a night nursing service in Ireland for people with non-malignant illnesses and compares data on access to specialist palliative care services between Ireland and the UK from 2011-2013. It finds that in both countries, the number of people with non-malignant illnesses accessing specialist palliative care services is rising, accounting for 16-17% in the UK and 19-26% in Ireland. There is some variance between referrals to specialist palliative care services and the night nursing service in different areas of Ireland that is not fully explained by population differences or UK trends, suggesting limited awareness of the service in some areas.
Rising unscheduled care attendances are putting pressure on A&E departments across Scotland. Attendances have increased by 63,750 (4.8%) over the past two years, with the largest rises in NHS Highland, Greater Glasgow and Clyde, Fife, and Lanarkshire. Self-referrals have risen the most, increasing by 3.6%. Younger age groups like 0-4 have seen higher attendance increases. Several initiatives are underway to better manage demand, including improved redirection of non-emergency cases, social media campaigns on alternative care options, and consultant-led triage of referrals.
On Wednesday, 3 March 2021, ESRI researcher Conor Keegan presented the topic ‘Understanding the drivers of hospital expenditure’ at the conference ‘Irish hospital expenditure beyond the era of COVID-19.’
The conference examined issues relating to expenditure on acute hospital care in Ireland. Findings from recent ESRI research, undertaken as part of the ESRI Research Programme in Healthcare Reform, which is funded by the Department of Health, were presented.
To view the presentation slides and other event details, click here: https://www.esri.ie/events/irish-hospital-expenditure-beyond-the-era-of-covid-19
To view a video of the presentation, click here: https://www.youtube.com/watch?v=cEHsUI0EmQ4
This presentation discusses understanding local populations and issues with population data and projections. It notes challenges including a lack of single comprehensive data source, outdated estimates that don't reflect diversity, and inaccuracies from using short-term immigration trends to make long-term projections. Improving data requires regular updated systems covering demographics like ethnicity and birthplace. Caution is urged against getting "transfixed" on data limitations or pursuing "perfection" if existing information is adequate for decision-making.
Universal Patient Identity: eliminating duplicate records, medical identity t...3GDR
This document discusses challenges in healthcare such as medical identity theft, duplicate patient records, and payment fraud. It argues that existing approaches using enterprise master patient indexes have limitations and do not fully address these issues. A single universal patient identity approach is needed that uses a unique health safety identifier coupled with multi-factor authentication. This could eliminate medical identity theft, duplicate records, and payment fraud by providing a consistent patient identity across the healthcare system. It would improve data quality and support value-based care delivery.
Understanding the concept of Universal Health Coverage (UHC) and how can we reach it, both globally and also in India. The presentation also includes HLEG report , which is the proposed architecture for India's guide to reach UHC.
Pharmaceutical marketing channels - selecting appropriate channel of distribu...AkankshaAshtankar
A marketing channel, also known as a distribution channel, involves the movement of goods and services from manufacturers through intermediaries to consumers. It is the set of interdependent organizations that facilitate making a product or service available. For pharmaceutical companies, the standard marketing channel involves the manufacturer, physician, wholesaler, retailer, and consumer. When selecting distribution channels, pharmaceutical firms consider the infrastructure, marketing capabilities, relationship intensity, logistics capabilities, and strategic issues of potential intermediaries.
Graphs are used to visually represent data and relationships between variables. There are various types of graphs that can be used for different purposes. Histograms represent the distribution of continuous variables. Bar graphs display the distribution of categorical variables or allow for comparisons between categories. Line graphs show trends and patterns over time. Pie charts summarize categorical data as percentages of a whole. Cubic graphs refer to graphs where all vertices have a degree of three. Response surface plots visualize the relationship between multiple independent variables and a response variable.
A sample design is a definite plan for obtaining a sample from a given population. Researcher must select/prepare a sample design which should be reliable and appropriate for his research study.
The document is a powerpoint presentation about life expectancy. It aims to explain that (1) life expectancy is an average and (2) when life expectancy is low, it is often due to high child mortality rather than everyone dying slightly earlier. It illustrates these points by comparing expected lifespans of newborns in Burundi versus Sweden, finding that while the average life expectancy is lower in Burundi, some Burundians live into old age, but many die young as children, bringing down the overall average.
The document discusses the Demographic Transition Model, which attempts to show how population changes as a country develops. The model divides development into four stages:
Stage 1 has high birth and death rates, leading to low population growth. Stages 2 and 3 see birth rates remain high while death rates fall dramatically, resulting in rapid population increase. Stage 4 is characterized by low birth and death rates, leading again to low population growth. The model shows these stages through a country's population pyramid shape. However, the model is an overgeneralization and does not consider exceptions like war or political issues.
This case study aims to understand the activity patterns of international migrants in income and benefit data. The slides summarise what research is already published on these activity patterns and illustrate what exploratory research, using linked administrative data sources, can further tell us. The findings from this case study provide important insights which are key to the successful development of a population and migration statistics system based on administrative data sources.
This document provides information about data sources on migration available from the GLA Intelligence Unit. It discusses various administrative data sources like the NHS Central Register and International Passenger Survey that provide information on internal and international migration trends in London. It also summarizes key findings from these sources, like over 30% of London's population being foreign-born. The document outlines the strengths and limitations of different data sources and highlights opportunities from the 2011 Census to improve understanding of migration patterns.
Estimating The Size of the Irish PopulationAlan McSweeney
The various sources of population-related data are inconsistent with one another. There has been past issues with determining the extent of immigration. This in turn creates an issue with the size of the population of Ireland.
This analysis has identified one possible set of inconsistencies relating to the size of the Irish population. It may well be that the population of Ireland is greater that than counted by the CSO in the census.
Population sizes at various ages determine the demand for different societal resources. People are, after all, the direct and indirect buyers and users of products and services, both public and private sector. People drive demand. Changes in the profile of people – numbers and ages – will change the demand profile.
Discrepancies between other data sources from which population data can be inferred and the CSO’s population data indicate that there may be ongoing errors.
Consistency checking between multiple sets of related data is a standard technique to identify potential quality data issues that should then be the subject of further analysis. Detailed consistency checking is hampered by the limited set of information made publically available by various state agencies.
This analysis has looked at the following sets of data with a view to identifying potential data conflicts:
1. DEASP PPSN Registration Numbers
2. CSO PPSN Numbers
3. CSO Migration Numbers
4. CSO Population Numbers
5. Revenue Income Tax Numbers
6. Department of Education Third-Level Numbers
7. DEASP Pensioner Numbers
8. DEASP Live Register/Disability/Work Activation Numbers
9. Irish Naturalisation and Immigration Service (INIS) Statistics
One of the central goals for the province of New Brunswick is to boost economic development by increasing labour market participation, and immigration is key to this plan. However, while NB has welcomed a growing number of immigrants over time, a substantial number still choose to leave the province years after landing.
This raises questions, such as, “Who decides to stay? Who decides to leave? And what factors influence these decisions?”
Understanding the backgrounds and experiences of immigrants residing in NB may help the province address challenges related to immigrant retention. Since there is a well-established link between mobility and economic opportunity, focusing on the entry streams and economic experiences of immigrants in NB may shed light on a correlation between experiences and retention. NB-IRDT’s 2021 publications on immigrant retention do just that.
Immigrant Retention in New Brunswick (McDonald & Miah) estimates the retention rates of all immigrants who intended to arrive in the province by immigration stream, and Immigrant Income and Labour Market Outcomes (Boco et al.) examines the economic outcomes and retention rates of immigrants to investigate trends and determinants of income and retention. Comparing these two reports allows us to highlight similarities and differences in the datasets, associated methodologies, and results.
We aim for the findings of these reports to contribute to evidence-based assessments of provincial immigration policies and efforts, while presenting detailed descriptive and empirical evidence on the evolution of immigrant retention and immigrants’ post-landing labour market experiences in NB.
The document summarizes UK travel restrictions for returning passengers from green, amber, and red list countries. Passengers returning from green countries do not need to quarantine but must take a COVID-19 test. Those returning from amber countries must self-isolate for 10 days and take two tests. For red list countries, passengers must quarantine in a hotel for 10 days and take two tests. The UK government will review the rules monthly and aims to reduce travel restrictions over time if vaccination rates, case numbers, and variants of concern remain stable.
The document summarizes UK travel restrictions for returning passengers from green, amber, and red list countries. Passengers returning from green countries do not need to quarantine but must take a COVID-19 test. Those returning from amber countries must self-isolate for 10 days and take two tests. For red list countries, passengers must quarantine in a hotel for 10 days and take two tests. The UK government will review the rules monthly and aims to reduce travel restrictions over time if vaccination rates increase and new variants and infections remain low.
2015 01 22_briefing - family and dependents_mig_observatoryMiqui Mel
This document summarizes data on non-European family and dependent migration to the UK from various sources such as the Office for National Statistics and Home Office statistics. Some key points:
- Non-EU family migration has increased since the 1990s but at a slower rate than other migration categories. Asia remains the most common region of origin for non-EEA family migrants.
- Most non-EEA family migrants entering under unification rules are women. Over 90% of those entering as spouses or fiancés are already married.
- Tier 1 and Tier 2 migrants (high-skilled workers and investors) bring the most dependents per capita.
- Family migration peaked in
After a +3% point rise in consumer confidence in the third quarter of 2017, the latest Deloitte Consumer Tracker remains flat at -7%. This quarter’s results represent the first time since our survey began in 2011 that confidence has not fallen in the final quarter of the year.
Ta2.09 1 mills.un data forum innovations crvs idms sam mills jan 14 2017Statistics South Africa
Overview of importance of CRVS in monitoring SDGs, Principles on Identification for Sustainable Development, CRVS eLearning course by the Global CRVS group - presented at the UN World Data Forum
For The State of the State 2017-18 Deloitte LLP commissioned Ipsos MORI to survey c.1000 UK adults on their attitudes to public service spending and austerity; social care services and personal data sharing.
The document outlines a night nursing service in Ireland for people with non-malignant illnesses and compares data on access to specialist palliative care services between Ireland and the UK from 2011-2013. It finds that in both countries, the number of people with non-malignant illnesses accessing specialist palliative care services is rising, accounting for 16-17% in the UK and 19-26% in Ireland. There is some variance between referrals to specialist palliative care services and the night nursing service in different areas of Ireland that is not fully explained by population differences or UK trends, suggesting limited awareness of the service in some areas.
Rising unscheduled care attendances are putting pressure on A&E departments across Scotland. Attendances have increased by 63,750 (4.8%) over the past two years, with the largest rises in NHS Highland, Greater Glasgow and Clyde, Fife, and Lanarkshire. Self-referrals have risen the most, increasing by 3.6%. Younger age groups like 0-4 have seen higher attendance increases. Several initiatives are underway to better manage demand, including improved redirection of non-emergency cases, social media campaigns on alternative care options, and consultant-led triage of referrals.
On Wednesday, 3 March 2021, ESRI researcher Conor Keegan presented the topic ‘Understanding the drivers of hospital expenditure’ at the conference ‘Irish hospital expenditure beyond the era of COVID-19.’
The conference examined issues relating to expenditure on acute hospital care in Ireland. Findings from recent ESRI research, undertaken as part of the ESRI Research Programme in Healthcare Reform, which is funded by the Department of Health, were presented.
To view the presentation slides and other event details, click here: https://www.esri.ie/events/irish-hospital-expenditure-beyond-the-era-of-covid-19
To view a video of the presentation, click here: https://www.youtube.com/watch?v=cEHsUI0EmQ4
This presentation discusses understanding local populations and issues with population data and projections. It notes challenges including a lack of single comprehensive data source, outdated estimates that don't reflect diversity, and inaccuracies from using short-term immigration trends to make long-term projections. Improving data requires regular updated systems covering demographics like ethnicity and birthplace. Caution is urged against getting "transfixed" on data limitations or pursuing "perfection" if existing information is adequate for decision-making.
Universal Patient Identity: eliminating duplicate records, medical identity t...3GDR
This document discusses challenges in healthcare such as medical identity theft, duplicate patient records, and payment fraud. It argues that existing approaches using enterprise master patient indexes have limitations and do not fully address these issues. A single universal patient identity approach is needed that uses a unique health safety identifier coupled with multi-factor authentication. This could eliminate medical identity theft, duplicate records, and payment fraud by providing a consistent patient identity across the healthcare system. It would improve data quality and support value-based care delivery.
ILC Future of Ageing 2022 - Prof. Sir Ian Diamond.pptxILCUK1
Presentation slides from Prof Sir Ian Diamond (UK National Statistician) from the ILC-UK Future of Ageing Conference in London, UK, on Thursday 24 November 2022.
Bad Effects of Urbanization and Lifestyles, Population Health Improvements us...IRJET Journal
This document discusses the effects of urbanization and modern lifestyles on population health. It notes that urban populations face increased risk of spreading infectious diseases due to population density. Lifestyles in urban areas have also become less physically active. However, urban populations may have better access to healthcare and immunizations. The document proposes using predictive analytics and machine learning on healthcare data to predict future population health trends based on current lifestyles and identify ways to improve health outcomes. It evaluates several classification algorithms on a diabetes dataset and finds that a Naive Bayes classifier achieved the best performance. Suggested countermeasures to improve urban population health include promoting sustainable urbanization and economic reinvestment in healthcare.
This case study examines what we can discover about circular patterns of movement into and out of the UK for non-EU nationals in Home Office data. This research has shown that people’s travel patterns can be complex and further examination is needed to understand what these patterns mean. The findings from this case study provide important insights that will be key to the successful development of a population and migration statistics system based on administrative data sources.
This document provides an overview of migration trends and data for Leeds. It summarizes statistics on arrivals to Leeds by country of origin over time. It also discusses programs to support migrants, including refugees resettling in Leeds from Syria. Challenges migrants may face are outlined, as well as opportunities migration brings. Resources are listed to help services support migrants.
Millions Potentially Eligible for Marketplace Coverage Outside Open Enrollmentsoder145
Millions of people may be eligible for Marketplace coverage outside of open enrollment due to qualifying life events. An analysis found that over 8 million people lost minimum essential health coverage from 2012 to 2013, making them eligible for a special enrollment period. Additionally, around 3.7 million people experienced income changes that could make them eligible. Improving outreach about coverage options when life events occur, such as job loss, could help more people enroll.
Similar to Transforming population and migration statistics: NINo and NHS registration lags (20)
The document summarizes the agenda and presentations from the ONS Economic Forum. It includes summaries on the state of the UK economy by the ONS Chief Economist highlighting a slight rise in GDP in January but broadly flat on the quarter. It also includes summaries on owner-occupier housing costs in household cost indices and progress on transforming R&D statistics at ONS. The forum provided insights into the UK economic outlook, drivers of inflation, and improvements in key economic indicators and statistics.
The document summarizes an economic forum held by the Office for National Statistics (ONS). It includes presentations on:
- The state of the UK economy, which entered a mild recession in late 2023 while living standards declined. Core inflation remains elevated despite some easing of pressures.
- Labour market data from the Labour Force Survey, which was recently reweighted. This increased population and employment estimates. Rates were also impacted but trends remain clear.
- Questions and answers followed the presentations.
The document summarizes findings related to average hours worked in the UK economy from 1998 to 2022. Key points:
- Average weekly hours worked have decreased for all workers and men, but increased for women over this period.
- The decline in average hours worked partially explains decreases in employment since the pandemic.
- Compositional changes, including a growing share of female and older workers who tend to work fewer hours, explain part of the decline in average hours worked overall.
The document summarizes an event discussing developments beyond GDP metrics for measuring societal progress. It includes the agenda for the event, which has presentations on the UN's 2022 Beyond GDP report, the work of the UN Network of Economic Statisticians, and the European Horizon Project. The event aims to discuss international frameworks and initiatives for developing metrics beyond GDP to provide a more holistic assessment of societal progress.
The document summarizes an economic forum hosted by the Office for National Statistics (ONS). It includes an agenda with presentations on various topics including public service productivity, transforming price statistics, the state of the UK economy, trends in business dynamism and productivity, and the System of National Accounts 2025. The forum provided an opportunity for the ONS to share updates on key economic statistics and receive feedback.
- The ONS Economic Forum discussed the state of the UK economy and labour market.
- Speakers presented on declining Labour Force Survey response rates, subdued UK GDP growth, strong earnings growth, and measures like real GDI and real income that provide a better view of economic welfare than GDP alone.
- Insights from the Annual Survey of Hours and Earnings showed ongoing strong earnings inflation across sources, a rightward shift in the earnings distribution, and a record low in low-paying jobs in 2023.
This document summarizes the agenda and presentations for the ONS Economic Forum. The agenda included welcome and introduction by Sumit Dey-Chowdhury, a presentation on the state of the UK economy by Mike Keoghan, a presentation on the role of labour costs and profits in UK inflation by Stefan Ubovic, and presentations on experimental estimates of green jobs and provisional estimates of greenhouse gas emissions. The forum included discussions on recent inflation trends in the UK, the contributions of labour costs and profits to domestic inflation, estimates of employment in green industries, occupations and firms, and latest estimates of UK greenhouse gas emissions in 2022.
The document summarizes a presentation on measuring societal progress beyond GDP in the UK. It discusses how the Office for National Statistics is developing broader measures of economic welfare, well-being, and sustainability. These include measures of inclusive income and wealth that account for household production, human capital, the environment, and other factors not captured by GDP. The ONS is also reviewing and improving its measures of national well-being across domains like health, education, environment and developing a new well-being dashboard. The goal is to better inform policymaking by measuring what makes life worthwhile beyond economic outputs.
The document summarizes an event discussing recent UK economic data releases from the Office for National Statistics. It includes an agenda for presentations on the latest GDP data and revisions, trade and balance of payments data, and the ONS approach to measuring GDP. The presentations provide details on revisions to GDP estimates from 1997 to 2021, improvements in measuring globalization and other factors, and explain that revisions are common due to updated data sources and balancing different estimates.
This presentation covers the key question: Why dashboards? Local authorities and other public bodies have largely ended publishing reports and now produce dashboards. What are the factors that have contributed to this change?
This is the first presentation from our Workshop on 21 September 2023 on Dashboards, APIs and PowerBI.
This document summarizes an economic forum hosted by the Office for National Statistics (ONS). The agenda includes welcome remarks, presentations on the state of the UK economy, consumer price inflation persistence, and changes in labor costs and prices. There will also be a question and answer session. Presenters will discuss revisions to GDP estimates, inflation trends, labor market tightness, and how businesses are passing on higher input costs to consumers. The forum aims to provide insights into key economic indicators and price pressures in the UK.
The document provides guidance on connecting to the StatXplore API using Power BI to retrieve updated data. It discusses querying the API, processing the response, and transforming the data. Key steps include preparing the query body, creating queries in Power BI, accessing labels and values from the response, and linking the labels and values tables to create a single flat table for analysis.
ONS Local has been established by the Office for National Statistics (ONS) to support evidence-based decision-making at the local level. We aim to host insightful events that connect our users with exciting developments happening in subnational statistics and analysis at the ONS and across other organisations.
In April 2022, as the impact of increases in the Cost of Living really came to the forefront, Public Health & Communities, Suffolk County Council published a Cost of Living profile as part of the Joint Strategic Needs Assessment.
Alongside a written Cost of Living report ‘Making ends meet: The cost of living in Suffolk’, an interactive dashboard was also created using Power BI. In addition to internal data flows, publicly available data from sources such as the ONS have been used to provide a rich picture of the current situation for the local community.
The dashboard was developed in order to:
• Provide up to date data and information on the Cost of Living for Suffolk County Council, partner organisations, and members of the public.
• Deliver an interactive tool to allow users to focus on areas most relevant to them.
• Demonstrate that, while increases in the cost of living affect everyone, impact will be greatest for those who are already under financial pressure, exacerbating inequalities.
• Provide a source of actionable insight to support the system with the evidence base needed to support project development, drive change and really make a difference in the community.
Features of the dashboard:
• Place-focused - published at smaller geographies where possible
• Collaborative - Includes local data from across the system such as data shared by Citizens Advice and other system partners.
• Automated - Most data sources have automated connections, meaning there is little manual intervention required.
• Self-Service - Making the report publicly available puts data at the fingertips of colleagues, system partners and members of the public.
• Live - The dashboard is a living report which is frequently updated.
This session will:
• Provide a demonstration of Suffolk County Council’s Cost of Living dashboard
• Give an overview of data sources
• Explore opportunities for automation using Power BI
• Discuss how the data dashboard is used locally
This event is open to all; however, we anticipate it will be of most interest to anyone working on cost of living dashboards at the local level.
If you have any questions, please contact ons.local@ons.gov.uk.
ONS Local has been established by the Office for National Statistics (ONS) to promote evidence-based decision-making at the local level. We aim to host insightful workshops which will provide practical, technical support to help users make the most of ONS data. The Cross-Government Data Science Community brings together data scientists and analysts to build data science capability across the UK governments and public sector.
We are delighted to welcome you to our inaugural Workshop in our new series, entitled: 'How to use APIs'. The session will cover what Application Programming Interfaces (APIs) are, the advantages in using them and a practical demonstration of how they can be used. The journey of two Local Authority analysts as they begin using APIs in place of manual processes will be showcased to the audience. The session will conclude by explaining the plan for the forthcoming series of Workshops that will begin in September and introducing the Slack channel that ONS Local and Cross-Government DS community will be using to support users' technical questions going forward.
This event is open to all; however, we anticipate it will be of most interest to anyone working at a local level on creating data dashboards for internal or external use.
If you have any questions, please contact ons.local@ons.gov.uk.
ONS Local has been established by the Office for National Statistics (ONS) to promote evidence-based decision-making at the local level. We aim to host insightful workshops which will provide practical, technical support to help users make the most of ONS data. The Cross-Government Data Science Community brings together data scientists and analysts to build data science capability across the UK governments and public sector.
We are delighted to welcome you to our inaugural Workshop in our new series, entitled: 'How to use APIs'. The session will cover what Application Programming Interfaces (APIs) are, the advantages in using them and a practical demonstration of how they can be used. The journey of two Local Authority analysts as they begin using APIs in place of manual processes will be showcased to the audience. The session will conclude by explaining the plan for the forthcoming series of Workshops that will begin in September and introducing the Slack channel that ONS Local and Cross-Government DS community will be using to support users' technical questions going forward.
This event is open to all; however, we anticipate it will be of most interest to anyone working at a local level on creating data dashboards for internal or external use.
If you have any questions, please contact ons.local@ons.gov.uk.
ONS Local has been established by the Office for National Statistics (ONS) to promote evidence-based decision-making at the local level. We aim to host insightful workshops which will provide practical, technical support to help users make the most of ONS data. The Cross-Government Data Science Community brings together data scientists and analysts to build data science capability across the UK governments and public sector.
We are delighted to welcome you to our inaugural Workshop in our new series, entitled: 'How to use APIs'. The session will cover what Application Programming Interfaces (APIs) are, the advantages in using them and a practical demonstration of how they can be used. The journey of two Local Authority analysts as they begin using APIs in place of manual processes will be showcased to the audience. The session will conclude by explaining the plan for the forthcoming series of Workshops that will begin in September and introducing the Slack channel that ONS Local and Cross-Government DS community will be using to support users' technical questions going forward.
This event is open to all; however, we anticipate it will be of most interest to anyone working at a local level on creating data dashboards for internal or external use.
If you have any questions, please contact ons.local@ons.gov.uk.
ONS Local has been established by the Office for National Statistics (ONS) to support evidence-based decision-making at the local level. We aim to host insightful events that connect our users with exciting developments happening in subnational statistics and analysis at the ONS and across other organisations.
From 1 August 2019, the Secretary of State for Education delegated responsibility for the commissioning, delivery and management of London’s Adult Education Budget (AEB) to the Mayor of London. The AEB helps Londoners to get the skills they need to progress both in life and work. The overarching aim of London’s AEB is to make adult education in London even more accessible, impactful and locally relevant.
In this presentation, the Greater London Authority will be going through the results of the pioneering 2021/22 London Learner Survey (LLS). The survey’s objective is to gain insight into the outcomes of learners to inform and improve policy. The LLS consists of two linked surveys of learners who participated in GLA-funded Adult Education Budget (AEB) learning in the academic year 2021/22.
In the LLS, Learners are surveyed prior to and 5-7 months after completing their course to estimate the economic and social changes that learners experience following an AEB course.
In particular, the presentation will show the economic impact broken down by:
. Progression into employment
. Progression within work
. Progression into further learning.
The social impact will be explored by looking at changes in:
. Health and wellbeing
. Improved self-efficacy
. Improved social integration
. Participation in volunteering
The presentation will also cover how outcomes vary by funding type, breaking down the results by Community Learning and Adult Skills.
This event is open to all; however, we anticipate it will be of most interest to anyone working at a local level on skills, education and employment.
If you have any questions, please contact ons.local@ons.gov.uk.
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Transforming population and migration statistics: NINo and NHS registration lags
1. Key messages
• EU nationals register more quickly for a National Insurance number (NINo) than non-EU nationals
• Non-EU nationals register more quickly with the NHS than EU nationals
Transforming Population and Migration Statistics
Case Study: NINo and NHS registration lags
Centre for International Migration
Published: 30th January 2019
Coverage: England and Wales (Personal Demographic Service), UK (Migrant Worker Scan)
Disclaimer: These Research Outputs refer to registration lags
produced using Migrant Worker Scan and Personal Demographic
Service data, and are not Official Statistics. These outputs must not
be interpreted as an indicator of registration lags, or migrant estimates
from the different administrative data sources.
What can linking Migrant Worker Scan and Personal Demographic Service data together tell us about
when and how new international migrants appear on different administrative data sources?
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Within 1
month
1-3
months
3-6
months
6-12
months
1-2 years 2-5 years >5 years
Millions Lag between arrival and NINo registration
EU Non-EU
0
10
20
30
40
50
60
Within 1
month
1-3
months
3-6
months
6-12
months
1-2 years 2-5 years > 5 years
Thousands Lag between arrival and NHS registration
EU Non-EU
Source: ONS analysis of DWP/HMRC Migrant Worker Scan data covering NINo
registrations between 2002-2017
Source: ONS analysis of NHS Digital Personal Demographic Service and
DWP/HMRC Migrant Worker Scan data covering type 4 PDS registrations
between 1st August 2016 – 7th August 2017
2. Background
Aim: This case study aims to build our understanding of when and how new
international migrants appear in different data sources, to feed into the work on
using these sources for international migration estimates
Data sources 1. Migrant Worker Scan (MWS), Department for Work and Pensions
(DWP) and HM Revenue & Customs (HMRC)
2. Personal Demographic Service (PDS), NHS Digital
Time period 2016-2017
Population coverage MWS: Overseas nationals who have registered for a NINo since 2002
PDS: People of all ages registered with the NHS during 2016-17
Further background information Previous research (Slide 11), Things you need to know (Slides 12-15)
PDS overview
The PDS is the master demographic database for the NHS
in England, Wales and the Isle of Man. It is the primary
source of information on a patient’s NHS number, name,
address and date of birth. Records are created for
newborns, or when a new patient makes contact with an
NHS service, primarily by registering with a GP or through
accessing A&E or attending hospital.
When someone from overseas makes contact with the
NHS for the first time, they will be given an NHS number. A
new record is created on the PDS and they should be given
a type 4 registration flag to indicate that it is a new
registration of someone from overseas.
MWS overview
The MWS contains information on all adult overseas nationals
who have registered for and been allocated a National Insurance
number (NINo). A NINo is generally required by any overseas
national looking to work or claim benefits / tax credits in the UK.
In order to apply for a NINo, in the first instance, a migrant
worker makes an enquiry to a Job Centre. They must attend an
"Evidence of Identity interview" at a local DWP Jobcentre Plus
office, where they must be able to prove that they are who they
say they are and that they satisfy the criteria for needing a NINo.
The MWS data contain useful information on arrival date and
nationality which are not available in other administrative
sources, such as the PDS.
Both data sources include both long-term and short-term migrants.
3. EU nationals register more quickly for a NINo than non-EU nationals
If administrative data sources are to be used to measure international migration, it is important to understand the lags between
migrants arriving in the UK and appearing in the administrative sources. The MWS contains arrival date and NINo registration
date, so it is possible to look at the time lag between arrival in the UK and registering for a NINo.
Out of all records in the MWS, 84% had registered for a
National Insurance number within a year. The median time lag
between arrival and registration for a NINo was 72 days for
EU nationals and 135 days for non-EU nationals.
The median lag has decreased over time, from 292 days for
individuals who registered in 2002, to 37 days for individuals
who registered in 2017.
For 2017 registrations, the median lags were 32 days for EU
nationals and 71 days for non-EU nationals.
One potential reason for quicker
registration among EU nationals is
that work is the main reason for their
migration, whereas non-EU nationals
are more likely to migrate for study or
family reasons.
Things to be aware of
0.7% of individuals had a registration
date before their arrival date. As
arrival date is self-reported, it is likely
that this arrival date is a date of
return following earlier residence in
the UK, rather than the date of first
arrival.
0
50
100
150
200
250
300
350
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Days
Year of NINo registration
Median lag between arrival and NINo registration
EU Non-EU
Source: ONS analysis of DWP/HMRC Migrant Worker Scan data
0
1
2
3
4
Within 1
month
1-3
months
3-6
months
6-12
months
1-2 years 2-5 years >5 years
Millions Lag between arrival and NINo registration
4. Non-EU nationals in MWS more likely to link to PDS than EU nationals
Of the 10 million records on the MWS², 62% were linked to the PDS and 38% were not. Some of the unlinked records will be
due to the fact that the PDS only covers England, Wales and the Isle of Man, whereas the MWS covers the UK.
Linkage rates were higher among non-EU nationals than EU nationals. Some potential explanations for this are:
• Most non-EEA nationals now have to pay a health surcharge before they move to the UK if they are planning to stay for
more than six months. They perhaps then have more incentive to register for NHS services. EEA nationals do not have to
pay the health surcharge, so may not register with the NHS until they need to use it.
• Short-term migration is more common among EU nationals than non-EU nationals. If an individual is here for only a few
months, they are less likely to need to use NHS services, but are likely to need a NINo to work.
• A large proportion of non-EU nationals are students, who are encouraged by their university to register with a GP.
This analysis shows the importance of using multiple data sources to measure international migration. If only the PDS was
used, a number of potential migrants could be missed.
¹More information is available on Slide 12, Things you need to know
²The ONS version of the MWS only contains individuals who registered for a NINo from 2002 onwards
Looking at the MWS in combination with the PDS can provide new insights into international migrant interactions with
administrative systems and the footprints that migrants leave in administrative data
Source: ONS analysis of DWP/HMRC Migrant Worker Scan and NHS Digital Personal Demographic
Service data
Methodology
The linkage between the MWS
and PDS was done in two steps:
1. Link the PDS to the DWP
Customer Information System
data using the ONS
matchkeys methodology¹.
2. Link to the MWS using the
National Insurance number
This two-step process was used
because the MWS is not updated
with address or name changes
and these variables are needed
for the linkage.
0
20
40
60
80
100
EU Non-EU
%
Linked to PDS Not linked to PDS
Linked to
PDS
Not linked
to PDS
5. Of those linked to a NINo using the Customer Information System data (CIS), but not recorded
in MWS, two-thirds were children, who we would not expect to find in MWS. The remaining may
be examples of incorrect type 4 flag allocations; for example, those given to returning UK
nationals. These potential incorrect flag 4 allocations represent around 3% of all type 4 flag
allocations in the target period.
Of those not linked to a NINo, 24% were under 15, so we would not expect them to be in MWS.
52% were aged 15-29, some of which may be students who are not working during their
studies.
Methodology
A cohort of individuals was selected who registered with the NHS between 1st August 2016 and 7th August 2017 and received a
type 4 flag upon registration. The type 4 registration indicates that they are a potential migrant.
Of the 710,000 individuals
in this cohort:
• 50% were linked to MWS
• 9% were linked to a NINo
(in CIS) but not to MWS
• 41% were not linked to a
NINo
This analysis
shows the
importance of
using PDS in
addition to
MWS to
measure
international
migration,
particularly
for those in
the younger
age groups.
Important to use PDS alongside MWS to measure migration
The PDS contains a variable that indicates the type of registration. If an individual has a type 4 flag, this indicates that they are a
new registration from overseas. By linking PDS to MWS, we can compare the use of type 4 flags in PDS with registration for a
NINo in MWS (which is another indicator that someone is a potential migrant).
Source: ONS analysis of NHS
Digital Personal Demographic
Service and DWP/HMRC Migrant
Worker Scan data
Linked to MWS
Linked to NINo but not MWS
Not linked to a NINo
0
20
40
60
80
100
120
140
160
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+
Thousands
Age group
Linked to MWS
Linked to NINo but not MWS
Not linked to NINo
6. Non-EU nationals register more quickly for the NHS than EU nationals
For those in the PDS cohort who have been linked to MWS, it is possible to look at the time lag between the arrival date stated
in MWS and the NHS registration date stated in PDS.
Things to be aware of
• This analysis excludes individuals who have not registered for a NINo. If an individual has not registered (yet) for a NINo,
we will not have their arrival date so do not know the lag. Therefore, the median lags are only valid for the individuals in the
linked cohort and do not represent median lags for the whole migrant population in the PDS.
• 0.5% of individuals in the cohort had an arrival date in the MWS that was after their NHS registration date in the PDS. This
suggests that the MWS arrival date is a date of return, rather than the date of first arrival.
Non-EU nationals tend to register more quickly with the NHS than EU nationals.
For those in the cohort, the median lags were:
• EU: 276 days
• Non-EU: 60 days
82% of non-EU nationals in the cohort had arrived within the last year whereas
57% of EU nationals had.
Nationality Median lag
(days)
Malaysia 20
Yemen 24
Congo 25
Malawi 26
Bangladesh 29
Nationality Median lag
(days)
Latvia 581
Lithuania 579
Poland 503
Slovakia 496
Hungary 392
As previously discussed, the shorter
registration lags for non-EU nationals may
be linked to the fact that most non-EEA
nationals have to pay a health surcharge
before they come to the UK, so perhaps
have more incentive to register with a GP
when they arrive. EEA nationals may just
register when they need to see a doctor.
Top 5 nationalities with the
longest lag
Top 5 nationalities with the
shortest lag
Source: ONS analysis of NHS Digital Personal Demographic Service and DWP/HMRC Migrant Worker Scan data
0
10
20
30
40
50
60
Within 1
month
1-3 months3-6 months 6-12
months
1-2 years 2-5 years > 5 years
Thousands Lag between arrival and NHS registration
EU Non-EU
7. Females register more quickly for the NHS than males
Things to be aware of
• This analysis excludes individuals who have not registered for a NINo. If an individual has not registered (yet) for a NINo, we
will not have their arrival date so do not know the lag. Therefore, the median lags are only valid for the individuals in the
linked cohort and do not represent median lags for the whole migrant population in the PDS.
• 0.5% of individuals in the cohort had an arrival date in the MWS that was after their NHS registration date in the PDS. This
suggests that the MWS arrival date is a date of return, rather than the date of first arrival.
• The chart does not include individuals aged 65+ due to low numbers in the cohort in this age group.
Females tend to register more quickly with the
NHS than males, with this trend seen in all except
the youngest age group.
For those in the cohort, the median lags were:
• Males: 291 days
• Females: 150 days
70% of females in the cohort had arrived within
the last year whereas 55% of males had.
Source: ONS analysis of NHS Digital Personal Demographic Service and
DWP/HMRC Migrant Worker Scan data
0
50
100
150
200
250
300
350
400
15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64
Days Median lag between arrival and NHS registration
Male Female
The NHS registration analysis can also be broken down by age and sex.
There are also differences across the age groups. This can be seen for males in particular where the median registration lag in
the cohort ranged from 61 days for 15-19 year olds, to just over a year (371 days) for 25-29 year olds. The short registration
lags for 15-19 year olds may reflect children being registered by their parents, or first year students being encouraged to
register by their university.
As 55% of non-EU nationals in the cohort are
female compared with 49% of EU nationals,
these differences by sex may partially explain the
shorter registration lags for non-EU nationals
shown on the previous slide.
8. PDS consistent with MWS for measuring international migration
Registration type 4s were also investigated by looking at whether individuals in the MWS obtained a type 4 flag upon first
registration with the NHS. For this analysis, a cohort of individuals was selected that had an arrival date in the MWS of between
1st August 2016 and 31st January 2017. There were 378,000 individuals in the MWS that had an arrival date in this period and
153,000 linked to the PDS. 138,000 of these had a registration date and were included in the analysis.
Things to be aware of
1) There will be individuals who arrived in the target period but have not yet
registered for a NINo. This means that we do not know that they have arrived
so they cannot be selected for the cohort. Some of these individuals may have
registered with the NHS but we do not know that they are in our cohort, as
arrival date is not available in the PDS.
2) Missing registration type information mainly relates to older PDS records
created prior to 2014. Pre-2014, the PDS system was maintained outside of
NHS Digital and the registration type variable was not used.
3) Of those with a registration type of other than 4, 38% had a PDS registration
date before their MWS arrival date. This suggests that their MWS arrival date
may not reflect their first arrival in the UK. These individuals may have been in
the country for some time before registering for a NINo and, therefore, we may
not be capturing their first registration with the NHS in this analysis. If this is
not their first registration, they will not receive a type 4 registration flag.
4) As the linkage was done using the 2017 CIS and PDS datasets, which have
extraction dates of July/August 2017, the individuals in the cohort have only
had 6-12 months to register with the NHS. This explains the lower linkage
rates for this cohort when compared with the MWS as a whole. The reasons
behind selection of this cohort can be found on slide 15.
Of all individuals in the cohort who linked to PDS, 91% received a type 4 flag. When
those with a missing registration type are excluded, this figure is 95%. This
suggests that the MWS and PDS are fairly consistent for measuring international
migration.
Type 4: 1st acceptance – from
overseas
Other: 1st acceptance not from
overseas or 2nd acceptance
Missing: No registration type for the
individual
Source: ONS analysis of NHS Digital Personal Demographic Service and DWP/HMRC Migrant Worker Scan data
PDS registration type
Type 4 Other Missing
9. It provides evidence for:
• Development of a Statistical Population Dataset (SPD) from
linked administrative data
Analysis shows that the inclusion of both Migrant Worker Scan
and Personal Demographic Service data is necessary to ensure
that the SPD covers all international migration and that linkage of
multiple datasets is required to develop a full understanding of the
population.
• Development of rules for stocks and flows approaches
Identifies the need to assess and take into account differences in
registration lags when applying rules to both develop the SPD
and in the application of methods to measure both stocks and
flows. This relates to both registration lag differences between
datasets and registration lag differences between groups with
different characteristics.
Next steps
Further work to use this linked dataset
to assess the quality of local level
address information.
Putting administrative data at the core of our evidence on international migration (UK)
and on population (England and Wales) in 2020
This analysis also helps us to understand how different types of
international migrants interact with services. For example, those
registering for a NINo aren’t accessing health services
immediately.
The findings from this case study provide important insights that
will be key to the successful development of a population and
migration statistics system based on administrative data sources.
10. Next Steps
Further research using MWS and PDS to help understand migrant destinations:
• Compare address information in the MWS and PDS for linked records to better understand the quality
of address information and how quickly the MWS address information becomes out of date (as
address is not changed after first registration).
• Investigate frequency and timing of address moves in PDS for new international migrants, which is
important for the internal migration component of population estimates.
Research from linking MWS/PDS to other datasets:
• Link MWS to Exit Checks data to better understand the accuracy of the arrival date variable in MWS,
for non-EU nationals.
• Link PDS to Exit Checks data to identify, for non-EU nationals:
• a first arrival date for individuals not in MWS, so that registration lags can be calculated.
• the quality of PDS data for estimating population stocks.
• For individuals in MWS not linked to PDS, link to benefits, PAYE and self-assessment data to look for
other signs of activity.
Further collaboration with DWP on using MWS data for measuring international migration.
11. Previous research and statistics
DWP statistics on National Insurance number allocations to adult overseas nationals entering the UK
The latest statistics showed that:
• 641,000 new NINos were registered in the year to June 2018, a decrease of 17% on the previous year
• 70% of these were from within the EU
DWP statistics on National Insurance numbers allocations to adult overseas nationals entering the UK – registrations
to March 2014
This release included a section focusing on EU2 nationals and included some analysis of registration lags:
• Restrictions on the employment of Romanian and Bulgarian migrants in the UK were lifted on 1st January 2014
• In 2013/14, there were 47,000 NINo registrations from Romanian nationals and 18,000 from Bulgarian nationals.
These were 163% and 71% higher respectively than in the previous year.
• Of those that registered between 1st January 2014 and 31st March 2014:
• Over 30% of EU2 nationals had arrived in the UK over a year prior to registration, compared with around 4%
for Polish and Spanish nationals
• 22% of EU2 nationals registered for a NINo within 3 months of arrival, compared with approximately 70% of
Polish and Spanish nationals.
Local Area Migration Indicators
The ONS local area migration indicators contain data on the number of records with a type 4 flag in each annual NHS
Patient Register stock dataset. More information on the Patient Register data is available here.
MAC report on international students in the UK
• International students can access public healthcare while studying in the UK; EEA students can use their
European Health Insurance Card and most international students from non-EEA countries must pay a health
surcharge of £150 per year as part of their visa application.
• Most universities have recommended GP practices near campus which they encourage students to register with.
Please note that our exploratory analysis is not directly comparable with these statistics.
12. Things you need to know
• Disclaimer: These Research Outputs refer to registration lags produced using Migrant Worker
Scan and Personal Demographic Service data, and are not Official Statistics.
• Rather, they are published as outputs from exploratory research to show users of international migration
statistics where we are on our transformation journey to put administrative data at the core of our evidence
on international migration (UK) and on population (England and Wales) in 2020.
• These research outputs must not be interpreted as an indicator of registration lags, or migrant
estimates from the different administrative data sources.
• These research outputs are based on experimental analysis of linked MWS and PDS data. We are still
developing methods; therefore, the numbers or proportions reported here may change in future reporting
on our journey to put administrative data at the core of population and migration statistics.
• It is important that the information and research presented here be read alongside the population and
migration statistics transformation update report to aid interpretation and avoid misunderstanding.
• These research outputs must not be reproduced without this disclaimer and warning note.
13. Things you need to know
Averages
Average lags are based on the median, rather than the mean, as lags are not normally distributed. Lags are
skewed towards shorter lags, so if the mean was used, the smaller number of long lags would have a
disproportionate impact on the average. The median is therefore more representative of the data.
Nationality
Nationality has been classified using the International Passenger Survey (IPS) country groupings found in the
International Migration - Table of Contents (citizenship/nationality groupings tab).
The EU nationality group excludes British nationals.
Nationality is grouped into EU and non-EU instead of EEA and non-EEA (which is generally more related to
immigration control and policy, such as the immigration health surcharge) to be consistent with previous
research. For this reason the following three EEA countries will appear in the non-EU nationality group:
o Iceland
o Norway
o Liechtenstein
Additionally, Swiss nationals are included in the non-EU nationality group. Switzerland is neither part of the
EU nor the EEA but is part of the single market, so Swiss nationals have the same rights to live and work in
the UK as other EEA nationals.
Data linkage
The data linkage was conducted using the ONS matchkeys methodology. Matchkeys are created by putting
together pieces of information to create unique keys that can be hashed and used for automated matching.
For example, a matchkey might be constructed from an individual’s forename and surname, combined with
their date of birth, sex and postcode district. The resulting string is then ‘hashed’ and can be used to link
records between datasets in the anonymous data research environment.
14. Things you need to know
Migrant Worker Scan (MWS)
The geographic coverage of the MWS is the UK.
The MWS has been used as the source of nationality information. It should be noted that nationality is based
upon nationality at the time the individual first registered for a NINo. There are no records of individuals
holding more than one nationality, nor when a change in nationality occurs after registration. Therefore,
naturalisation to UK citizenship is not recorded.
Arrival date in MWS has been taken as the individual’s first arrival in the UK. However, the arrival date is later
than the NINo registration date and/or PDS registration date in some cases, which suggests that the arrival
date may reflect the individual’s most recent, rather than first, arrival in the UK.
The MWS data extract includes any NINo allocations to overseas nationals since 2002. This means that
foreign nationals who registered for a NINo before 2002 are not captured in the data.
A Temporary Reference Number can be allocated while the NINo application is in progress. Temporary
Reference Numbers are not included in the MWS data.
For more information on NINo allocations to adult overseas nationals, see Background Information produced
by DWP.
Further information on the NINo application process is available here.
Customer Information System (CIS)
The CIS was used in the data linkage process. It is a dataset that contains a record for all individuals who
have registered and been issued with a National Insurance number in the UK.
15. Things you need to know
Personal Demographic Service (PDS)
The geographic coverage of the PDS is England and Wales.
Records on the PDS are updated at GP surgeries, pharmacies, drop-in-clinics, A&E, hospitals and Primary
Care Trusts. The PDS relies on people interacting with the NHS to update their health records when entering
or leaving England and Wales, or when they change their address.
The analysis of the PDS data used a combination of the 2016 and 2017 PDS stock files and the 2016-17 PDS
movers files. The movers files contain updates to the PDS between stock extracts, such as new registrations
or address changes. As an individual could register and then move, all between stock extracts, the movers
files needed to be used so that their first registration could be captured. For example, if an individual
registered from overseas in November 2016 and then moved to a different part of the country in January
2017, they would be given a type 4 registration flag at that first registration and then get a type 3 flag after they
moved. They would not be in the 2016 extract as they registered after the data extract was taken, and in the
2017 extract it would have a registration date of January 2017 and a registration type of 3. Therefore, without
using the movers files, we would not know the date of first registration and would not know that they had come
from overseas. The movers files are only available from the 2016 stock onwards, which restricted the cohorts
that could be selected for analysis.
The registration date in PDS is the date of registration with a particular NHS system, rather than the date that
the individual first obtained an NHS number. The earliest available registration date has been taken but in
some cases this may not reflect the first registration.
Any missing values in the registration type variable may be due to the records being in the PDS prior to 2014.
Pre-2014, the PDS system was maintained outside of NHS Digital and the registration type variable was not
used.
16. Contact Us
We would welcome your feedback on the exploratory research
presented here. Please get in touch at:
Email: pop.info@ons.gov.uk
Tel: 01329 444661
17. Further Links
Go back to: An update on our population and migration statistics transformation journey: A research
engagement report
Explore our other case studies on SlideShare
Transforming population and migration statistics: Administrative data-based population stocks and
flows
Transforming population and migration statistics: Emigration patterns of non-EU students
Transforming population and migration statistics: International student employment activity
Transforming population and migration statistics: Benefits and income activity patterns
Transforming population and migration statistics: Patterns of circular movement into the UK