The National Sample Survey of Registered Nurses (NSSRN) Download makes data from the survey readily available to users in a one-stop download. The Survey has been conducted approximately every four years since 1977. For each survey year, HRSA has prepared two Public Use File databases in flat ASCII file format without delimiters. The 2008 data are also offerred in SAS and SPSS formats. Information likely to point to an individual in a sparsely-populated county has been withheld. General Public Use Files are State-based and provide information on nurses without identifying the County and Metropolitan Area in which they live or work. County Public Use Files provide most, but not all, the same information on the nurse from the General Public Use File, and also identifies the County and Metropolitan Areas in which the nurses live or work. NSSRN data are to be used for research purposes only and may not be used in any manner to identify individual respondents.

Abstract (en): The Newly Licensed Registered Nurse New Cohort 2 Survey, 2012 is the second wave of a multi-wave panel survey that studied newly licensed registered nurses who obtained their first license to practice between August 1, 2010 and July 31, 2011. It was conducted as part of the RN Work Project, a national study of new nurses funded by the Robert Wood Johnson Foundation. The survey interviewed the nurses about their jobs, turnover, education, intentions and attitudes--including intent, satisfaction, organizational commitment, and preferences about work. The Newly Licensed Registered Nurse New Cohort 2 Survey, 2012 and the full series sought to accomplish three main objectives:

Describe newly licensed registered nurses' changes in work patterns and factors associated with those changes over an extended time period by following the panel from our current Robert Wood Johnson Foundation funded study for an additional six years.; Compare educational background, work setting, and work satisfaction among three different cohorts of NLRN.; Describe the training about patient safety of NLRNs employed in hospitals. The primary advantage of cohort data is to find out how groups graduating in different years are more or less similar. That information provides with an indication of changes in the environment or in those people who choose nursing as a career. Collecting data on two additional cohorts will help us separate the threats to internal validity of history versus maturational effects.; Panel data was used for this study and all others in the series because it made it possible to determine the similarities and differencies in groups graduating in different years. That information provides an indication of changes in the environment or in those people who choose nursing as a career. Collecting data on two additional cohorts helped the researchers separate the threats to internal validity of history versus maturational effects. Princeton Survey Research Associates International (PSRAI) determined the distribution of nurses by site needed in order to achieve a minimum of 1,500 completed surveys. Each nurse was assigned a random number. This list was then organized by each of the 27 sites and sorted according to random numbers. The first N (number of respondents needed) were selected from each site. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Checked for undocumented or out-of-range codes.. Presence of Common Scales: Large variety of scales from literature and questions identical to HRSA National Sample Survey - RNs 2005. Response Rates: 47% Datasets:DS1: Dataset Newly licensed registered nurses who obtained their first license to practice between August 1, 2010 and July 31, 2011. Smallest Geographic Unit: Region The sample design for the New Cohort 2 study sampled new RNs residing in 22 MSAs and 2 rural counties in 14 states across the country. For additional information please refer to the User Guide. 2020-02-20 Online variable search capabilities have been added for this study. Funding institution(s): Robert Wood Johnson Foundation (51120). mail questionnaire

The Payroll Based Journal (PBJ) Nurse Staffing and Non-Nurse Staffing datasets provide information submitted by nursing homes including rehabilitation services on a quarterly basis. The View Data link above includes the hours staff are paid to work each day, for each facility, aggregated by staff reporting category. Examples of reporting categories include Director of Nursing, Administrative Registered Nurses, Registered Nursing, Administrative Licensed Practice Nurses, Licensed Practice Nurses, Certified Nurse Aides, Certified Medication Aides, and Nurse Aides in Training. There are also other non-nurse staff categories provided in the data such as Respiratory Therapist, Occupational Therapist, and Social Worker. The datasets also include a facility’s daily census calculated using the Minimum Data Set (MDS) submission. The Payroll Based Journal (PBJ) Employee Detail Nursing Home Staffing datasets and technical information have been moved to a new location. Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.

This dataset provides values for NURSES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Connecticut Nurses Census 1917

The Connecticut Nurses Census is a part of State Archives https://cslarchives.ctstatelibrary.org/repositories/2/resources/443">Record Group 029: Records of the Military Census Department. The census forms may give basic details such as birthplace, age, marital status, maiden name, and current residence, as well as more specific information such as the name of the nursing school attended, medical specialty, and year of licensure. This census included the registration of both female and male nurses.

This index includes the name, birthplace, age, current residence, form number and box number. If a field is left blank, it is because the person who submitted the form did not answer that question (e.g. age, anybody!) People may request a copy of a census form by contacting us by telephone (860) 757-6580 or email. Please include the name of the individual and form number.

Nurses in Germany increased to 14.41 per 1000 people in 2023 from 14.26 per 1000 people in 2022. This dataset includes a chart with historical data for Germany Nurses.

This dataset contains the custom geographies used to study the registered nurse workforce and identifies which areas are designated as registered nurse shortage areas (RNSA) as of the year labeled in the title.

240 nurses were recruited and completed an online survey. Demographic data included inpatient hospital nursing role, state of licensure, race and ethnicity, age, sexual orientation, previous year’s household income, most advanced academic nursing degree, years as a nurse, years working in a hospital, whether currently working in a hospital, whether currently working as a travel or contract nurse, primary type of adult inpatient practice area, and zip code of primary practice location. Nurse participants responded to three questions about each of eight factorial vignettes depicting a patient voicing a safety concern, consisting of unique combinations of eight patient and event factors (socioeconomic status, sexual orientation, race and ethnicity, gender, age, communication approach, type of event, and apparent harm). Questions about the vignettes addressed degree of report credibility, degree of nurse participant concern, and likelihood of communicating patient concern as an incident report. 234 nurses consented to sharing their survey responses.

Advances in wearable technologies provide the opportunity to monitor many physiological variables continuously. Stress detection has gained increased attention in recent years, especially because early stress detection can help individuals better manage health to minimize the negative impacts of long-term stress exposure. This paper provides a unique stress detection dataset created in a natural working environment in a hospital. This dataset is a collection of biometric data of nurses during the COVID-19 outbreak. Studying stress in a work environment is complex due to the influence of many social, cultural, and individuals experience in dealing with stressful conditions. In order to address these concerns, we captured both the physiological data and associated context pertaining to the stress events. We monitored specific physiological variables, including electrodermal activity, heart rate, skin temperature, and accelerometer data of the nurse subjects. A periodic smartphone-administered survey also captured the contributing factors for the detected stress events. A database containing the signals, stress events, and survey responses is available upon request.

This table provides an overview of the key figures on health and care available on StatLine. All figures are taken from other tables on StatLine, either directly or through a simple conversion. In the original tables, breakdowns by characteristics of individuals or other variables are possible. The period after the year of review before data become available differs between the data series. The number of exam passes/graduates in year t is the number of persons who obtained a diploma in school/study year starting in t-1 and ending in t.

Data available from: 2001

Status of the figures:

2024: Most available figures are definite. Figures are provisional for: - causes of death; - youth care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university).

2023: Most available figures are definite. Figures are provisional for: - perinatal mortality at pregnancy duration at least 24 weeks; - diagnoses known to the general practitioner; - hospital admissions by some diagnoses; - average period of hospitalisation; - supplied drugs; - AWBZ/Wlz-funded long term care; - physicians and nurses employed in care; - persons employed in health and welfare; - average distance to facilities; - profitability and operating results at institutions. Figures are revised provisional for: - expenditures on health and welfare.

2022: Most available figures are definite. Figures are revised provisional for: - expenditures on health and welfare.

2021: Most available figures are definite, Figures are revised provisional for: - expenditures on health and welfare.f

2020 and earlier: All available figures are definite.

Changes as of 4 July 2025: More recent figures have been added for: - causes of death; - life expectancy; - life expectancy in perceived good health; - self-perceived health; - hospital admissions by some diagnoses; - sickness absence; - average period of hospitalisation; - contacts with health professionals; - youth care; - smoking, heavy drinkers, physical activity; - overweight; - high blood pressure; - physicians and nurses employed in care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university); - expenditures on health and welfare; - profitability and operating results at institutions.

Changes as of 18 december 2024: - Distance to facilities: the figures withdrawn on 5 June have been replaced (unchanged). - Youth care: the previously published final results for 2021 and 2022 have been adjusted due to improvements in the processing. - Due to a revision of the statistics Expenditure on health and welfare 2021, figures for expenditure on health and welfare care have been replaced from 2021 onwards. - Due to the revision of the National Accounts, the figures on persons employed in health and welfare have been replaced for all years. - AWBZ/Wlz-funded long term care: from 2015, the series Wlz residential care including total package at home has been replaced by total Wlz care. This series fits better with the chosen demarcation of indications for Wlz care.

When will new figures be published? New figures will be published in December 2025.

The “Rio de Janeiro Wet-Nursing Database” (RJWND) comprises all advertisements for wet nurses for the year of 1850 in Rio de Janeiro, Brazil, extracted from the city’s main commercial newspaper, Jornal do Commercio. “Mercenary” wet nursing, what contemporaries called the practice of paying for other women to breastfeed their children, was a thriving market throughout the nineteenth century. Enslaved women comprised most wet nurses, with freed women of color and white immigrant women also working in the trade. More rarely, white Brazilian women whose newborns had died advertised their milk. We can draw several conclusions from this data. Most importantly, RJWND demonstrates the ubiquity of wet nursing in urban Brazil. All women participated in this activity, whether as elite mothers not breastfeeding their own children, or as free, freed, freed African, and enslaved women breastfeeding other women’s children. It also sheds light on how enslavers valued wet nurses both for their reproductive labors (wet nursing) and their productive outputs (cleaning, cooking).

Connecticut Nurses Census 1917 The Connecticut Nurses Census is a part of State Archives Record Group 029: Records of the Military Census Department. The census forms may give basic details such as birthplace, age, marital status, maiden name, and current residence, as well as more specific information such as the name of the nursing school attended, medical specialty, and year of licensure. This census included the registration of both female and male nurses. This index includes the name, birthplace, age, current residence, form number and box number. If a field is left blank, it is because the person who submitted the form did not answer that question (e.g. age, anybody!) People may request a copy of a census form by contacting us by telephone (860) 757-6580 or email. Please include the name of the individual and form number.

Context

This dataset simply combines publicly available data to characterise a country based on healthcare factors, economy, government and demographics.

Content

All data are given per 100.000 inhabitants where this is appropriate scores are given as absolute values and so are spending and demographics. Each row represents one country. Data that is included covers the following topics:

Healthcare: - Staff including: Nurses and Physicians per 100.000 inhabitants - Infrastructure including: Beds, Chnage of beds between 2018 and 2019 and the change of bed numbers since 2013, Intensive Care Unit (ICU) beds, ventilators and Extra Corporal Membrane Oxygenation (ECMO), machines per 100.000 inhabitants - Total spending on healthcare in US dollars per capita.

Demographics: - The median age for entire population and each gender - The percentage of the population within age brackets - Total population - Population per km2 - Population change between 2018 and 2019

Government The used scores are from the Economist intelligence unit and describe how democratic a country is and how the government works. These can be used to compare countries based on their government type.

Acknowledgements

All data is publicly available and just has been brought together in one place. The sources are:

• Population densities

• Populations

• ECMO machines

• Hospital beds

• Number of physicians

• Health expenditure per capita

• Democracy indexes

• Median age

• OECD nurses per capita

Inspiration

These data are meant as metadata to decide which countries are comparable. I am working on healthcare data so the inspiration is to compare health statistics between countries and make an informed decision about how comparable they are. Could be used for any non healthcare related task as well.

Forecast: Number of Nurses Graduates in the US 2024 - 2028 Discover more data with ReportLinker!

ABSTRACT Objectives: To identify the presence of occupational stress in nursing professionals of a university hospital in the inlands of the state of Minas Gerais and examine influence of sociodemographic and occupational characteristics in this disease. Methods: Cross-sectional, exploratory and quantitative study with 124 professional nurses from a university hospital in the inlands of the state of Minas Gerais. The adapted and validated Portuguese version of the Job Stress Scale (JSS) was used for the performance of the study. Results: Most professionals were women (87.9%) with a mean age of 40.2 years, 80.6% were nursing technicians and 71.8% of the sample had some degree of exposure to occupational stress. Conclusions: The occupational stress index was higher than that observed in previous studies. Data obtained in the study point to the need to implement institutional measures for the prevention of occupational stress, especially by strengthening social support at work.

JQ05 - Nurses. Published by Department of Health. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Nurses’ data is compiled by the Department of Health as part of the Non-Monetary Health Care Statistics, administered jointly by Eurostat, OECD and WHO in fulfilment of the European regulation (EU) 2022/2294. These statistics are compiled and published on an annual basis and refer to the number of practicing nurses and nurses licensed to practice in the Republic of Ireland, as at end of the referenced ending calendar year....

Forecast: Population Per Nurses Graduates in Germany 2024 - 2028 Discover more data with ReportLinker!

In 2022, of the 458,590 nursing assistants in nursing homes in the United States, roughly four in ten were white. Meanwhile, Black or African American accounted for another 37 percent. Nursing assistants were therefore made up of predominantly racial minorities.

Data set for the Assessment of Nurses Interventions in the Management of Clinical Alarms in the Critical Care Unit. This data set contains all the data collected from a larger study conducted to assess the management of clinical alarms in the nursing care of critically ill patients at the critical care unit, KNH. Some of the variables captured were used to assess the other specific objectives in the larger study. For this particular manuscript the variables that are relevant are; the social demographic variables such as, age, gender, professional qualification, years that the participant has worked as a nurse, years that the participant has worked in CCU, whether the participant is trained in Critical Care Nursing, if the participant has been trained on alarm management, the number of hours of training and the year he or she was trained. Another variable captured in the dataset that is applicable in this manuscript is alarms that the nurses are more likely to respond to, number of nurses that fill alarm checklists and reasons as to why the nurses do not fill alarm checklists. Nursing interventions or actions in the management of clinical alarms are also variables that give insight into the findings in this manuscript. The interventions include; ensuring proper skin preparation before placement of electrodes, daily change of electrodes, assessing the cause of the alarm beep, disabling alarms every time they beep, pausing alarms every time they beep, re-setting alarm limits every time they beep, ignoring alarms every time they beep, checking and assessing the patient’s condition every time the alarm beeps and re-setting of alarms each time a patient is admitted. (XLSX 29 kb)

This dataset, drawn from the WHO Policy Survey 2023, identifies whether a country recognises midwifery as a standalone occupational group separate from nursing. Distinct recognition is foundational to professional autonomy, regulation, and education. This indicator supports analysis of national frameworks that enable or limit the visibility and growth of the midwifery profession.Data Source:WHO Policy Survey 2023: https://www.who.int/publications/i/item/9789240100176Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.