Receive notifications about changes to a patient's demographic details, including birth, death, change of address and change of GP using the Fast Healthcare Interoperability Resources (FHIR) standard for health and care data exchange.

Personal demographics including name(s) , addresse(s) and telecommunication contact details.

The graph displays the demographic distribution of various virtual digital assistant users in the United States, as of December 2016. In December 2016, ** percent of Siri users were ** or older.

By 2024, the share of the global population to be covered under modern privacy regulations is projected to reach 75 percent. The forecast for the year 2023 was 65 percent. Additionally, in 2020, only ten percent of the global population's privacy was protected by modern laws.

Survey on Equipment and Use of Information and Communication Technologies in Households: Internet services used for personal reasons in the last 3 months by demographic characteristics and nature of the service. National.

aValues are means (standard deviations) unless noted otherwise.

List of NYPD members of service

The POPUM database contains personal records entered from parish registers from the areas around Linköping, Sundsvall, large parts of the Västerbotten county and the inland of Norrland. The database covers parish registers from the end of the 17th century until the end of the 19th century. The personal records stem from different types of parish registers such as catechetical registers, birth and baptism registers, banns and marriage registers, migrations registers, and death registers. These datasets, ranging from birth to death, provides possibilities to link together individuals and generations. The life stories of individuals as well as family histories can be tracked. Moreover, the dataset offers the possibility to study demographical and socio-economic changes over time across different regions and parishes. The purpose of the POPUM database is to provide detailed individual records from church books between the late 1600s and around 1910 for research. It enables studies on demography, social structures, and historical development in Sweden. POPUM offers data on, among other things, population development, migration patterns, economic changes, industrialization, agricultural communities, small-scale farming, Sámi history, and urbanization.

Contains property crime victimizations. Property crimes include burglary, theft, motor vehicle theft, and vandalism. Households that did not report a property crime victimization are not included on this file. Victimizations that took place outside of the United States are excluded from this file.

In August of 2018, FSSA’s Office of Healthy Opportunities deployed a social risk assessment survey. The 10-question survey was made available to anyone applying online through FSSA for health coverage, the Supplemental Nutritional Assistance Program or Temporary Assistance for Needy Families. The results of this survey are aggregated and presented below and can help communities better understand the social risk factors affecting the health of those applying for our services. Please read and review the following information regarding the use of this data prior to viewing the tool. This survey was made available to those individuals who applied online ONLY and does not represent anyone who applied in-person, by telephone, by mail or any other method. In 2018, online applications accounted for 79% of those who applied for SNAP, TANF or health coverage. Survey completion is voluntary and does not impact eligibility for SNAP, TANF or health coverage. Applications are filed at a household level and may represent several individuals. The application process identifies a primary contact person for the household, and that individual’s demographics are represented on the dashboard; for example, person’s gender, race and education level. An individual who completes more than one application and survey over any given time period is represented once for each instance, and the survey answers and demographic details are based on each application’s responses. For example, an applicant’s age, education level and survey answers can change over time, and the reporting reflects any such changes. All information is presented in aggregate to ensure personally identifiable information is protected. To protect the privacy of individuals, data representing 20 or less individuals in any county will not be displayed. I.e. it will show as blank

Survey on Equipment and Use of Information and Communication Technologies in Households: Use of e-commerce for personal reasons by demographic characteristics and frequency of use of the purchase. National.

aParticipants transitioned from Tanner 1 to 2 at 10 years (n = 5), 11 years (n = 6), and 12 years (n = 5).bParticipants transitioned from Tanner 1 to 3 at 11 years (n = 1).cParticipants transitioned from Tanner 2 to 3 at 12 years (n = 1) and 13 years (n = 1).dParticipants transitioned from Tanner 3 to 4 at 11 years (n = 2), 13 years (n = 1), and 15 years (n = 1).eParticipants transitioned from Tanner 3 to 5 at 11 years (n = 2).fParticipants transitioned from Tanner 4 to 5 at 15 years (n = 3) and 16 years (n = 1).Notes: if more than one Morningness/Eveningness score was collected at each age, then the mean score was used; Tanner stage was unavailable for 1 participant at ages 9, 11, and 13 years, and for 2 participants at age 15 years.Demographics by individual at each age in the younger and older cohorts.

Personal contact or interaction with public administrations or services via a website or applications provided by these entities in the last 12 months by demographic characteristics and type of contact. National.

Absolute and relative frequencies of respondents’ personal demographics, totals and segmented by year.b

This dataset is comprised of 1-year estimate data from the American Community Survey published as of 2021.

The National Medical Expenditure Survey (NMES) series provides information on health expenditures by or on behalf of families and individuals, the financing of these expenditures, and each person's use of services. The Institutional Population Component (IPC) is a survey of nursing and personal care homes and facilities for the mentally retarded and residents admitted to those facilities. Information was collected on facilities and their residents at several points during 1987. Use and expenditure estimates for institutionalized persons can be combined with those from the Household Component for composite estimates covering most of the civilian population. Information on facilities and residents was collected from facility administrators and caregivers, with additional information collected from next-of-kin or other knowledgeable respondents. These data were supplemented by Medicare claims information for covered sample persons. Research File 19R provides information collected from two IPC questionnaires, the Personal History Questionnaire (PHQ) and the End-of-Year Questionnaire (EYQ). The PHQ was administered once as part of the surveys of next-of-kin. These data are primarily concerned with the characteristics of the sample person just prior to admission. The EYQ was administered once in either the surveys of next-of-kin or the surveys of institutions and focuses on health status. Research File 19R also includes items from the Baseline Questionnaire and the Baseline Questionnaire Supplement. Data from these questionnaires were released on NMES Public Use Tapes 8, 17, and 22R (ICPSR 9677, 6158, and 6467). Part 1 of this collection, Summary Data, includes demographic characteristics such as age, race, sex, date of admission to sampled facility, and vital status. Part 2, 1987 Personal History Questionnaire (PHQ) Data, supplies information on condition prior to admission to facility, chronic disease history, whether respondent needed help with activities of daily living (ADLs) and/or instrumental activities of daily living (IADLs), usage of assistive technology, and behavioral history. Part 3, End-of-Year Questionnaire (EYQ) Data, includes characteristics of the sample person, limitations and help with ADLs and IADLs, health and behavioral history, and condition codes reported by either the respondent or the facility medical records.

Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated

The dataset contains information on California’s Medical Service Study Areas (MSSA). MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data for 2000. Medical Service Study Areas are a geographic analysis unit defined by the California Office of Statewide Health Planning and Development. MSSA are a good foundation for needs assessment analysis, healthcare planning, and healthcare policy development.

Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the Personal Demographics Service (PDS) system. This release is an accurate snapshot as at 1 February 2025. GP Practice; Primary Care Network (PCN); Sub Integrated Care Board Locations (SICBL); Integrated Care Board (ICB) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive PCN; SICBL; ICB and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations.