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Japan JP: Population: Growth data was reported at -0.164 % in 2017. This records a decrease from the previous number of -0.115 % for 2016. Japan JP: Population: Growth data is updated yearly, averaging 0.396 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.606 % in 1961 and a record low of -0.185 % in 2011. Japan JP: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
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Japan JP: Birth Rate: Crude: per 1000 People data was reported at 7.800 Ratio in 2016. This records a decrease from the previous number of 8.000 Ratio for 2015. Japan JP: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 10.800 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 19.400 Ratio in 1973 and a record low of 7.800 Ratio in 2016. Japan JP: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
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Japan JP: Population: Total data was reported at 126,785,797.000 Person in 2017. This records a decrease from the previous number of 126,994,511.000 Person for 2016. Japan JP: Population: Total data is updated yearly, averaging 122,864,500.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 128,070,000.000 Person in 2010 and a record low of 92,500,572.000 Person in 1960. Japan JP: Population: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Population and Urbanization Statistics. Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Sum; Relevance to gender indicator: disaggregating the population composition by gender will help a country in projecting its demand for social services on a gender basis.
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The Gross Domestic Product per capita in Japan was last recorded at 37144.91 US dollars in 2024. The GDP per Capita in Japan is equivalent to 294 percent of the world's average. This dataset provides - Japan GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Japan JP: Refugee Population: by Country or Territory of Asylum data was reported at 2,189.000 Person in 2017. This records a decrease from the previous number of 2,514.000 Person for 2016. Japan JP: Refugee Population: by Country or Territory of Asylum data is updated yearly, averaging 2,617.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 6,819.000 Person in 1990 and a record low of 1,794.000 Person in 2007. Japan JP: Refugee Population: by Country or Territory of Asylum data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of asylum is the country where an asylum claim was filed and granted.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;
Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File.
White – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
Black or African American – A person having origins in any of the Black racial groups of Africa.
American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.
Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
Some Other Race - this category is chosen by people who do not identify with any of the categories listed above.
People can identify with more than one race. These people are included in the Two or More Races
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Data and analysis code to accompany the manuscript by Judy P. Che-Castaldo, Kristin Havercamp, Koshiro Watanuki, Tetsuro Matsuzawa, Satoshi Hirata, Stephen R. Ross1. AZAchimpsurvdat_pub.csv - anonymized individual-level survival data for AZA population2. Japanchimpsurvdat_pub.csv - anonymized individual level survival data for Japan population3. wildCompare.csv - age-specific survival rates (lx) from birth for AZA and Japan population, as well as for one wild population from Gombe, Tanzania4. wildCompareAge1.csv - age-specific survival rates (lx) from age 1 for AZA and Japan population, as well as for one wild population from Gombe, Tanzania5. chimp_survival_publish.R - R code using the above datasets to create the analyses and figures presented in manuscript
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Japan JP: Death Rate: Crude: per 1000 People data was reported at 10.500 Ratio in 2016. This records an increase from the previous number of 10.300 Ratio for 2015. Japan JP: Death Rate: Crude: per 1000 People data is updated yearly, averaging 7.000 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 10.500 Ratio in 2016 and a record low of 5.900 Ratio in 1979. Japan JP: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
https://www.icpsr.umich.edu/web/ICPSR/studies/38308/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38308/terms
This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally the researchers chose to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, researchers combined some subcategories. First, they were interested in total tax revenue, as well as the shares of total revenue coming from direct and indirect taxes. Further, they measured two sub-categories of direct taxation, namely taxes on property and income. For indirect taxes, they separated excises, consumption, and customs.
The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.
Total population in India
India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.
With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.
As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.
This dataset is created for a task of UNCOVER COVID-19 Challenge, Mental health impact and support services.
The search interest of mental health related terms on Google before and after the outbreak of COVID-19 pandemic reveals how public's concern is affected by the pandemic, and its impact to mental health of people around the world. I picked worldwide, Canada, US, Italy, Iran, Japan, South Korea and UK as the population. The dataset also includes data of Canada for the past 4 years, from 2016 to 2019.
The mental health related search terms are "mental health", "depression", "anxiety", "ocd", "obsessive compulsive disorder", "insomnia", "panic attack", "counseling", "psychiatrist".
Search interest is indicated by a number between 0 and 100, where 100 means the most popular point of time(by week), 1 means the least, and 0 no enough data.
All data is collected from Google Trends. I assumed, when searching the terms, users from countries other than English-speaking performed the search in their own language, and they typed the word correctly.
This database contains tobacco consumption data from 1970-2015 collected through a systematic search coupled with consultation with country and subject-matter experts. Data quality appraisal was conducted by at least two research team members in duplicate, with greater weight given to official government sources. All data was standardized into units of cigarettes consumed and a detailed accounting of data quality and sourcing was prepared. Data was found for 82 of 214 countries for which searches for national cigarette consumption data were conducted, representing over 95% of global cigarette consumption and 85% of the world’s population. Cigarette consumption fell in most countries over the past three decades but trends in country specific consumption were highly variable. For example, China consumed 2.5 million metric tonnes (MMT) of cigarettes in 2013, more than Russia (0.36 MMT), the United States (0.28 MMT), Indonesia (0.28 MMT), Japan (0.20 MMT), and the next 35 highest consuming countries combined. The US and Japan achieved reductions of more than 0.1 MMT from a decade earlier, whereas Russian consumption plateaued, and Chinese and Indonesian consumption increased by 0.75 MMT and 0.1 MMT, respectively. These data generally concord with modelled country level data from the Institute for Health Metrics and Evaluation and have the additional advantage of not smoothing year-over-year discontinuities that are necessary for robust quasi-experimental impact evaluations. Before this study, publicly available data on cigarette consumption have been limited—either inappropriate for quasi-experimental impact evaluations (modelled data), held privately by companies (proprietary data), or widely dispersed across many national statistical agencies and research organisations (disaggregated data). This new dataset confirms that cigarette consumption has decreased in most countries over the past three decades, but that secular country specific consumption trends are highly variable. The findings underscore the need for more robust processes in data reporting, ideally built into international legal instruments or other mandated processes. To monitor the impact of the WHO Framework Convention on Tobacco Control and other tobacco control interventions, data on national tobacco production, trade, and sales should be routinely collected and openly reported. The first use of this database for a quasi-experimental impact evaluation of the WHO Framework Convention on Tobacco Control is: Hoffman SJ, Poirier MJP, Katwyk SRV, Baral P, Sritharan L. Impact of the WHO Framework Convention on Tobacco Control on global cigarette consumption: quasi-experimental evaluations using interrupted time series analysis and in-sample forecast event modelling. BMJ. 2019 Jun 19;365:l2287. doi: https://doi.org/10.1136/bmj.l2287 Another use of this database was to systematically code and classify longitudinal cigarette consumption trajectories in European countries since 1970 in: Poirier MJ, Lin G, Watson LK, Hoffman SJ. Classifying European cigarette consumption trajectories from 1970 to 2015. Tobacco Control. 2022 Jan. DOI: 10.1136/tobaccocontrol-2021-056627. Statement of Contributions: Conceived the study: GEG, SJH Identified multi-country datasets: GEG, MP Extracted data from multi-country datasets: MP Quality assessment of data: MP, GEG Selection of data for final analysis: MP, GEG Data cleaning and management: MP, GL Internet searches: MP (English, French, Spanish, Portuguese), GEG (English, French), MYS (Chinese), SKA (Persian), SFK (Arabic); AG, EG, BL, MM, YM, NN, EN, HR, KV, CW, and JW (English), GL (English) Identification of key informants: GEG, GP Project Management: LS, JM, MP, SJH, GEG Contacts with Statistical Agencies: MP, GEG, MYS, SKA, SFK, GP, BL, MM, YM, NN, HR, KV, JW, GL Contacts with key informants: GEG, MP, GP, MYS, GP Funding: GEG, SJH SJH: Hoffman, SJ; JM: Mammone J; SRVK: Rogers Van Katwyk, S; LS: Sritharan, L; MT: Tran, M; SAK: Al-Khateeb, S; AG: Grjibovski, A.; EG: Gunn, E; SKA: Kamali-Anaraki, S; BL: Li, B; MM: Mahendren, M; YM: Mansoor, Y; NN: Natt, N; EN: Nwokoro, E; HR: Randhawa, H; MYS: Yunju Song, M; KV: Vercammen, K; CW: Wang, C; JW: Woo, J; MJPP: Poirier, MJP; GEG: Guindon, EG; GP: Paraje, G; GL Gigi Lin Key informants who provided data: Corne van Walbeek (South Africa, Jamaica) Frank Chaloupka (US) Ayda Yurekli (Turkey) Dardo Curti (Uruguay) Bungon Ritthiphakdee (Thailand) Jakub Lobaszewski (Poland) Guillermo Paraje (Chile, Argentina) Key informants who provided useful insights: Carlos Manuel Guerrero López (Mexico) Muhammad Jami Husain (Bangladesh) Nigar Nargis (Bangladesh) Rijo M John (India) Evan Blecher (Nigeria, Indonesia, Philippines, South Africa) Yagya Karki (Nepal) Anne CK Quah (Malaysia) Nery Suarez Lugo (Cuba) Agencies providing assistance: Irani... Visit https://dataone.org/datasets/sha256%3Aaa1b4aae69c3399c96bfbf946da54abd8f7642332d12ccd150c42ad400e9699b for complete metadata about this dataset.
A panel data set for use in cross-cultural analyses of aging, health, and well-being between the U.S. and Japan. The questionnaires were designed to be partially comparable to many surveys of the aged, including Americans'' Changing Lives; 1984 National Health Interview Survey Supplement on Aging; Health and Retirement Study (HRS), and Well-Being Among the Aged: Personal Control and Self-Esteem (WBA). NSJE questionnaire topics include: * Demographics (age, sex, marital status, education, employment) * Social Integration (interpersonal contacts, social supports) * Health Limitations on daily life and activities * Health Conditions * Health Status (ratings of present health) * Level of physical activity * Subjective Well-Being and Mental Health Status (life satisfaction, morale), * Psychological Indicators (life events, locus of control, self-esteem) * Financial situation (financial status) * Memory (measures of cognitive functioning) * Interviewer observations (assessments of respondents) The NSJE was based on a national sample of 2,200 noninstitutionalized elderly aged 60+ in Japan. This cohort has been interviewed once every 3 years since 1987. To ensure that the data are representative of the 60+ population, the samples in 1990 and 1996 were refreshed to add individuals aged 60-62. In 1999, a new cohort of Japanese adults aged 70+ was added to the surviving members of previous cohorts to form a database of 3,990 respondents 63+, of which some 3,000 were 70+. Currently a 6-wave longitudinal database (1987, 1990, 1993, 1996, 1999, & 2002) is in place; wave 7 began in 2006. Data Availability: Data from the first three waves of the National Survey of the Japanese Elderly are currently in the public domain and can be obtained from ICPSR. Additional data are being prepared for future public release. * Dates of Study: 1987-2006 * Study Features: Longitudinal, International * Sample Size: ** 1987: 2,200 ** 1990: 2,780 ** 1993: 2,780 ** 1996: ** 1999: 3,990 ** 2002: ** 2006: Links: * 1987 (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06842 * 1990 (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03407 * 1993 (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/04145 * 1996 (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/26621
Explore the dataset on midyear population statistics for 2015, including data on non-infectious diseases, infectious diseases, accidents, malnutrition, congenital diseases, and more. Gain insights on population health trends globally.
Non-infectious, Midyear population, Annual, Infectious disease, Accident/Trauma, Malnutrition, Congenital disease, Other (including ageing), Disease, Health, Population
China, Germany, India, Japan, Russia, United States Follow data.kapsarc.org for timely data to advance energy economics research.
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Data describing the development and survival of gypsy moths (Lymantria dispar L. (Lepidoptera: Erebidae)) from all three subspecies on 13 North American conifers and 3 broad leaf hosts were collected (Keena and Richards 2020). Populations from the United States and Greece served as the Lymantria dispar dispar controls for comparison with the Asian strains from the L. d. asiatica (populations from China, Russia, and South Korea) and L. d. japonica (population from Japan) subspecies. The hosts compared were Acer rubrum, Betula populifolia, Quercus velutina, Pinus strobus, Pseudotsuga menziesii, Abies balsamea, Abies concolor, Larix occidentalis, Picea glauca, Picea pungens, Pinus ponderosa, Pinus taeda, Pinus palustris, Pinus rigida, Tsuga canadensis, and Juniperus virginiana.Survival and developmental data (either to 14 day or to adult with reproductive traits also evaluated) are important for assessing whether there is variation between and/or within a subspecies in host utilization. Host utilization information is critical to managers for estimating the hosts at risk and potential geographic range for Asian gypsy moths from different geographic origins in North America. Since the lists of hosts that Asian gypsy moth is known to feed on in other countries is long and no broad evaluation of North American hosts has been done, without data like these it is difficult to evaluate how the hosts at risk in North America to the Asian and established gypsy moths may differ.For more information about these data, see Keena and Richards (2020, https://doi.org/10.3390/insects11040260).
These data were originally published on 04/17/2020. Minor metadata updates were made on 07/22/2022 and 04/25/2023.
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Japan JP: Refugee Population: by Country or Territory of Origin data was reported at 53.000 Person in 2016. This records a decrease from the previous number of 145.000 Person for 2015. Japan JP: Refugee Population: by Country or Territory of Origin data is updated yearly, averaging 21.000 Person from Dec 1994 (Median) to 2016, with 23 observations. The data reached an all-time high of 521.000 Person in 2007 and a record low of 2.000 Person in 1997. Japan JP: Refugee Population: by Country or Territory of Origin data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;
Cancer Registry Software Market Size 2025-2029
The cancer registry software market size is forecast to increase by USD 121.9 million, at a CAGR of 14% between 2024 and 2029.
The market is witnessing significant growth due to the escalating prevalence of cancer cases worldwide. The increasing incidence of various types of cancer necessitates the implementation of advanced registry software solutions to manage and analyze patient data more efficiently. Moreover, the burgeoning clinical research in oncology further drives the demand for these systems, as they facilitate data collection, management, and analysis for research purposes. However, the market faces challenges in the form of stringent data privacy and security concerns. With the growing amount of sensitive patient information being stored and shared digitally, ensuring robust data security becomes crucial. The potential risks of data breaches and unauthorized access can significantly impact both patients and healthcare providers, necessitating the adoption of advanced security measures. Companies in the market must prioritize data security and privacy to gain the trust of healthcare organizations and patients alike.
What will be the Size of the Cancer Registry Software Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market is a dynamic and evolving landscape, continually adapting to advancements in healthcare technology and the growing demand for comprehensive cancer data management. This market encompasses various applications, including disease registry management, cancer staging system, data warehousing, cancer incidence tracking, registry software architecture, data integration platform, clinical data capture, case reporting system, statistical reporting, cancer screening programs, and more. These tools play a crucial role in cancer surveillance systems, enabling the collection, analysis, and reporting of epidemiological data for public health surveillance. They facilitate data encryption for patient data privacy, ensuring HIPAA compliance. Data interoperability and data quality metrics are essential components, allowing for seamless integration of various health informatics tools.
Real-time data updates and database management systems are integral to maintaining accurate and up-to-date information. Predictive modeling tools and data mining techniques contribute to risk factor identification and mortality data analysis. Data visualization tools offer valuable insights into the complexities of cancer data. Cancer registry software architecture supports population-based registry initiatives, ensuring secure data storage and registry reporting features. Oncology data management tools enable clinical data capture, case reporting, and statistical reporting, enhancing overall patient care. The ongoing development and refinement of these tools reflect the continuous unfolding of market activities and evolving patterns in cancer data management.
How is this Cancer Registry Software Industry segmented?
The cancer registry software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userGovernment and third partyPharma biotech and medical device companiesHospitals and medical practicePrivate payersResearch institutesTypeStand-alone softwareIntegrated softwareDeploymentOn-premisesCloud-basedGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyItalySpainUKAPACChinaJapanRest of World (ROW)
By End-user Insights
The government and third party segment is estimated to witness significant growth during the forecast period.Cancer registry software solutions play a vital role in assisting government and third-party agencies in managing and analyzing data related to cancer cases. These systems enable the tracking of cancer incidence, prevalence, and mortality rates, providing essential information for public health planning, resource allocation, and policy development. Analyzing trends and patterns in registry data helps identify high-risk populations, geographic disparities, and emerging cancer types. Governments utilize cancer registry software to monitor and improve the quality of cancer care. By evaluating variations in treatment practices and adherence to clinical guidelines, they can benchmark outcomes against national or international standards. Additionally, these software solutions facilitate data interoperability, ensuring data quality metrics and HIPAA compliance. Data encryption, data visualization tools, and predictive modeling capabilities enhance the functionality of cancer registry software. Epidemiological data analysis and risk factor identificatio
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Japan JP: Life Expectancy at Birth: Total data was reported at 83.985 Year in 2016. This records an increase from the previous number of 83.794 Year for 2015. Japan JP: Life Expectancy at Birth: Total data is updated yearly, averaging 78.484 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 83.985 Year in 2016 and a record low of 67.666 Year in 1960. Japan JP: Life Expectancy at Birth: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision, or derived from male and female life expectancy at birth from sources such as: (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
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Japan JP: Life Expectancy at Birth: Male data was reported at 80.980 Year in 2016. This records an increase from the previous number of 80.750 Year for 2015. Japan JP: Life Expectancy at Birth: Male data is updated yearly, averaging 75.630 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 80.980 Year in 2016 and a record low of 65.310 Year in 1960. Japan JP: Life Expectancy at Birth: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
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Japan JP: Population: Growth data was reported at -0.164 % in 2017. This records a decrease from the previous number of -0.115 % for 2016. Japan JP: Population: Growth data is updated yearly, averaging 0.396 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.606 % in 1961 and a record low of -0.185 % in 2011. Japan JP: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;