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TwitterThere were approximately *** thousand Indian nationals residing in the United Kingdom in 2021, around **** thousand more than there were a year earlier.
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According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.
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TwitterIn 2020/21 there were approximately 696,000 Polish nationals living in the United Kingdom, the highest non-British population at this time. Indian and Irish were the joint second-largest nationalities at approximately 370,000 people.
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TwitterThe statistic shows the total population in the United Kingdom from 2015 to 2019, with projections up until 2025. The population grew steadily over this period.
Population of the United Kingdom
Despite a fertility rate just below the replacement rate, the United Kingdom’s population has been slowly but steadily growing, increasing by an average of 0.6 percent every year since 2002. The age distribution has remained roughly the same for the past ten years or so, with the share of the population over 65 years old seeing a slight increase as the baby boomer generation enters into that age bracket. That share is likely to continue growing slightly, as the United Kingdom has one of the highest life expectancies in the world.
The population of the island nation is predominantly white Christians, but a steady net influx of immigrants, part of a legacy of the wide-reaching former British Empire, has helped diversify the population. One of the largest ethnic minorities in the United Kingdom is that of residents of an Indian background, born either in the UK, India, or in other parts of the world. India itself is experiencing problems with rapid population growth, causing some of its population to leave the country in order to find employment. The United Kingdom’s relatively lower levels of unemployment and the historical connection between the two countries (which has also resulted in family connections between individuals) are likely reasons that make it a popular destination for Indian emigrants.
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According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.
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39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.
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TwitterIn 2011, 87.2 percent of the total population of the United Kingdom were white British. A positive net migration in recent years combined with the resultant international relationships following the wide-reaching former British Empire has contributed to an increasingly diverse population. Varied ethnic backgrounds Black British citizens, with African and/or African-Caribbean ancestry, are the largest ethnic minority population, at three percent of the total population. Indian Britons are one of the largest overseas communities of the Indian diaspora and make up 2.3 percent of the total UK population. Pakistani British citizens, who make up almost two percent of the UK population, have one of the highest levels of home ownership in Britain. Racism in the United Kingdom Though it has decreased in comparison to the previous century, the UK has seen an increase in racial prejudice during the first decade and a half of this century. Racism and discrimination continues to be part of daily life for Britain’s ethnic minorities, especially in terms of work, housing, and health issues. Moreover, the number of hate crimes motivated by race reported since 2012 has increased, and in 2017/18, there were 3,368 recorded offenses of racially or religiously aggravated assault with injury, almost a thousand more than in 2013/14.
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The dataset tabulates the population of New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.
Key observations
The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 82.88% are white, 4.57% are Black or African American, 0.35% are American Indian and Alaska Native, 5.78% are Asian, 0.39% are some other race and 6.02% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for New Britain Population by Race & Ethnicity. You can refer the same here
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TwitterIn 1800, the population of the region of present-day India was approximately 169 million. The population would grow gradually throughout the 19th century, rising to over 240 million by 1900. Population growth would begin to increase in the 1920s, as a result of falling mortality rates, due to improvements in health, sanitation and infrastructure. However, the population of India would see it’s largest rate of growth in the years following the country’s independence from the British Empire in 1948, where the population would rise from 358 million to over one billion by the turn of the century, making India the second country to pass the billion person milestone. While the rate of growth has slowed somewhat as India begins a demographics shift, the country’s population has continued to grow dramatically throughout the 21st century, and in 2020, India is estimated to have a population of just under 1.4 billion, well over a billion more people than one century previously. Today, approximately 18% of the Earth’s population lives in India, and it is estimated that India will overtake China to become the most populous country in the world within the next five years.
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This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.
These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.
For quality information in general, please read more from here.
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
No qualifications
No qualifications
Level 1
Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills
Level 2
5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma
Apprenticeship
Apprenticeship
Level 3
2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma
Level 4 +
Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)
Other
Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)
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Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.
DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.
REGION: Africa
SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)
PROJECTION: Geographic, WGS84
UNITS: Estimated persons per grid square
MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.
FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)
FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.
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This dataset represents ethnic group (19 tick-box level) by dwelling tenure and by occupancy rating, for England and Wales combined. The data are also broken down by age and by sex.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.
All housing data in these tables do not include commual establishments.
For quality information in general, please read more from here.
For specific quality information about housing, please read more from here
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
Occupancy rating of bedrooms: 0 or more
A household’s accommodation has an ideal number of bedrooms or more bedrooms than required (under-occupied)
Occupancy rating of bedrooms: -1 or less
A household’s accommodation has fewer bedrooms than required (overcrowded)
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AimsTo derive cut-points for body mass index (BMI) and waist circumference (WC) for minority ethnic groups that are risk equivalent based on endogenous glucose levels to cut-points for white Europeans (BMI 30 kg/m2; WC men 102 cm; WC women 88 cm).Materials and MethodsCross-sectional data from participants aged 40–75 years: 4,672 white and 1,348 migrant South Asian participants from ADDITION-Leicester (UK) and 985 indigenous South Asians from Jaipur Heart Watch/New Delhi studies (India). Cut-points were derived using fractional polynomial models with fasting and 2-hour glucose as outcomes, and ethnicity, objectively-measured BMI/WC, their interaction and age as covariates.ResultsBased on fasting glucose, obesity cut-points were 25 kg/m2 (95% Confidence Interval: 24, 26) for migrant South Asian, and 18 kg/m2 (16, 20) for indigenous South Asian populations. For men, WC cut-points were 90 cm (85, 95) for migrant South Asian, and 87 cm (82, 91) for indigenous South Asian populations. For women, WC cut-points were 77 cm (71, 82) for migrant South Asian, and 54 cm (20, 63) for indigenous South Asian populations. Cut-points based on 2-hour glucose were lower than these.ConclusionsThese findings strengthen evidence that health interventions are required at a lower BMI and WC for South Asian individuals. Based on our data and the existing literature, we suggest an obesity threshold of 25 kg/m2 for South Asian individuals, and a very high WC threshold of 90 cm for South Asian men and 77 cm for South Asian women. Further work is required to determine whether lower cut-points are required for indigenous, than migrant, South Asians.
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Context
The dataset tabulates the population of England by race. It includes the population of England across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of England across relevant racial categories.
Key observations
The percent distribution of England population by race (across all racial categories recognized by the U.S. Census Bureau): 67.17% are white, 24.82% are Black or African American, 0.31% are American Indian and Alaska Native, 4.02% are some other race and 3.67% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for England Population by Race & Ethnicity. You can refer the same here
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Context
The dataset tabulates the Non-Hispanic population of England by race. It includes the distribution of the Non-Hispanic population of England across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of England across relevant racial categories.
Key observations
Of the Non-Hispanic population in England, the largest racial group is White alone with a population of 1,68 (69.97% of the total Non-Hispanic population).
https://i.neilsberg.com/ch/england-ar-population-by-race-and-ethnicity.jpeg" alt="England Non-Hispanic population by race">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for England Population by Race & Ethnicity. You can refer the same here
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TwitterIn the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.
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TwitterOral squamous cell carcinoma (OSCC) is a major public health concern, particularly in India, where it is the leading cause of cancer-related mortality among men and the fourth among women, resulting in approximately nine deaths per hour. Despite advancements in clinical management, the prognosis for OSCC remains poor due to late-stage detection and the absence of specific, reliable biomarkers for early diagnosis and disease monitoring. This study aims to identify potential salivary biomarkers and enriched protein domain/motif families for the early detection of OSCC and its progression, including lymph node invasion. A comparative salivary proteomics approach was employed using diaPASEF mode on 45 saliva samples from healthy individuals, pre-malignant (PM) lesions, and OSCC patients (with and without lymph node invasion), followed by targeted proteomics validation in 40 additional saliva samples. Data analysis was performed using FragPipe, Perseus, and InterPro/SMART for domain and motif enrichment. Signal peptides were predicted using SignalP, while pathway and protein interaction analyses were conducted via STRING. Multi-classifier biomarkers were identified using LASSO and logistic regression, with validation through targeted proteomics and TCGA datasets. A total of 1,068 proteins were identified, with differential expression patterns observed across disease stages (PM vs. Healthy, OSCC vs. PM). Several protein domain/motif families were significantly enriched, including SERPINS, ITI family, Lipocalins, Calcium-binding EF-hand motifs, Trypsin-like serine proteases, and Annexin repeats. Functional analysis highlighted pathways related to negative regulation of wound healing and calcium ion binding. Key potential biomarkers, such as ITIH4, RBP4, NUCB2, TXN, and ELANE, exhibited an AUC > 0.7 in classification models. These findings provide novel insights into salivary biomarkers and enriched protein domain families that may aid in the early detection of OSCC and prediction of lymph node invasion, offering a promising non-invasive diagnostic tool for the Indian population.
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BackgroundMigrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and findingsWe linked the Scottish 2001 Census to mortality data (2001–2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.ConclusionsThere was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.
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This dataset contains information on life history variation and population dynamics in response to coloured environmental variation in the laboratory model system comprised of the moth Plodia interpunctella (Pyralidae; Hübner) and the parasitoid wasp Venturia canescens (Ichneumonidae; Gravenhorst). Data were collected from two complementary experiments investigating the effects of daily coloured temperature fluctuations on individual life history variation (single-generation life history experiment) and population dynamics (multi-generation microcosm experiment) in both species. In both experiments, the effects of three types of coloured noise were investigated and compared to constant temperature conditions: blue noise (characterized by rapid (negatively autocorrelated) fluctuations), red noise (characterized by slow (positively autocorrelated) fluctuations) and white noise (characterized by random fluctuations). The life history experiment lasted 56 days and the microcosm experiment lasted 310 days.
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Population Health Management Market Size 2025-2029
The population health management market size is valued to increase USD 19.40 billion, at a CAGR of 10.7% from 2024 to 2029. Rising adoption of healthcare IT will drive the population health management market.
Major Market Trends & Insights
North America dominated the market and accounted for a 68% growth during the forecast period.
By Component - Software segment was valued at USD 16.04 billion in 2023
By End-user - Large enterprises segment accounted for the largest market revenue share in 2023
Market Size & Forecast
Market Opportunities: USD 113.32 billion
Market Future Opportunities: USD 19.40 billion
CAGR : 10.7%
North America: Largest market in 2023
Market Summary
The market encompasses a continually evolving landscape of core technologies and applications, service types, and regulatory frameworks. With the rising adoption of healthcare IT solutions, population health management platforms are increasingly being adopted to improve patient outcomes and reduce costs. According to a recent study, The market is expected to witness a significant growth, with over 30% of healthcare organizations implementing these solutions by 2025. The focus on personalized medicine and the need to manage the rising cost of healthcare are major drivers for this trend. Core technologies such as data analytics, machine learning, and telehealth are transforming the way healthcare providers manage patient populations.
Despite these opportunities, challenges such as data privacy concerns, interoperability issues, and the high cost of implementation persist. The market is further shaped by regional differences in regulatory frameworks and healthcare infrastructure. For instance, in North America, the Affordable Care Act has fueled the adoption of population health management solutions, while in Europe, the European Medicines Agency's focus on personalized medicine is driving demand.
What will be the Size of the Population Health Management Market during the forecast period?
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How is the Population Health Management Market Segmented and what are the key trends of market segmentation?
The population health management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Component
Software
Services
End-user
Large enterprises
SMEs
Delivery Mode
On-Premise
Cloud-Based
Web-Based
On-Premise
Cloud-Based
End-Use
Providers
Payers
Employer Groups
Government Bodies
Providers
Payers
Employer Groups
Geography
North America
US
Canada
Europe
France
Germany
Italy
UK
APAC
China
India
Japan
South Korea
Rest of World (ROW)
By Component Insights
The software segment is estimated to witness significant growth during the forecast period.
The market is experiencing significant growth, with the software segment playing a crucial role in this expansion. Currently, remote patient monitoring solutions are witnessing a 25% adoption rate, enabling healthcare providers to monitor patients' health in real-time and intervene promptly when necessary. Additionally, predictive modeling and risk stratification models are being utilized to identify high-risk patients and provide personalized care plans, contributing to a 21% increase in disease management efficiency. Furthermore, the integration of electronic health records, wellness programs, care coordination platforms, and value-based care models is fostering a data-driven approach to healthcare, leading to a 19% reduction in healthcare costs.
Health equity initiatives and healthcare data analytics are essential components of population health management, ensuring equitable access to care and improving healthcare quality metrics. Looking ahead, the market is expected to grow further, with utilization management and care management programs seeing a 27% increase in implementation. Preventive health programs and clinical decision support systems are also anticipated to experience a 24% surge in adoption, emphasizing the importance of proactive care and early intervention. Moreover, population health strategies are evolving to incorporate behavioral health integration, interoperability standards, and disease registry data to provide comprehensive care. The use of disease prevalence data and public health surveillance is becoming increasingly crucial in addressing population health challenges and improving overall health outcomes.
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The Software segment was valued at USD 16.04 billion in 2019 and showed a gradual increase during the forecast period.
In conclusion, the market is
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