This project investigated various routes of entry to the UK of labour migrants coming from a single source country. Additionally, face-to-face interviews were conducted with recruiters, experts and healthcare professionals involved in training and administration in the Philippines. A total of 73 transcripts were compiled, 19 from care home assistants/nurses, 19 from domestic workers, 18 from hospital nurses, 13 from Philippine fieldwork (including student nurses), 2 from UK based recruitment agencies, 1 from a migrant organisation and 1 from a UK care home. Data and literature on health worker emigration patterns were gathered from local research bodies. The mission of the Centre is to provide a strategic, integrated approach to understanding contemporary and future migration dynamics across sending areas and receiving contexts in the UK and EU. In 2003, Filipinos made up the largest and most visible group of internationally recruited nurses in the UK. Of roughly 13,000 overseas nationals registered with the Nursing and Midwifery Council (NMC) that year, around 5,600, or almost half, came from the Philippines. They also figured prominently in private care homes and in the provision of care in private households. While there are various nationalities contributing to the care workforce, this project narrowed its focus on care workers from the Philippines due to it being a sector that is heavily segmented by ‘race,’ nationality, as well as immigration status. Focusing on one nationality also allowed us to investigate various routes of entry in the UK of labour migrants coming from a single source country. Additionally, fieldwork was carried out in the Philippines between November and December 2004 in order to asses the effect of nursing and care work recruitment from the sending country perspective. A series of interviews were conducted with recruiters, academics, experts and healthcare professionals involved in training and administration. Data and literature on health worker emigration patterns were gathered from local research bodies. The following findings were observed: (1) Many care workers arrived in the UK via other countries, highlighting the wide scope of multinational recruitment agencies. (2) Filipino care workers arriving via Singapore and the Middle East tended to enter via student visas, but employers assigned them more work than their immigration status allowed (they worked 35-40 hours compared to the regulated 20 hours) (3) Nurses working in care homes experienced more difficulty applying for registration, and were in some cases discouraged by employers. (4) Regulatory conditions differ significantly between public and private care providers. Recruitment to private nursing homes is particularly unregulated. 73 face-to-face interviews were conducted and transcribed from 19 care home assistants/nurses, 19 domestic workers, 18 hospital nurses, 13 Philippine fieldwork (including student nurses), 2 UK based recruitment agencies, a migrant organisation and a UK care home. No sampling method was used, it was totally universe. Data and literature on health worker emigration patterns were gather from local research bodies.

BackgroundA growing body of research indicates that cross-cultural competence in nurses can improve migrant patients’ health-related outcomes, but little is known about the potential benefits of cross-cultural competence on the nurses’ own well-being.ObjectiveTo examine whether cross-cultural competence (empathy, skills, positive attitudes, and motivation) is associated with perceived time pressure at work, psychological distress, and sleep problems among registered nurses in Finland, and whether there are differences in these potential associations between native and foreign-born nurses.MethodsThe present cross-sectional study was based on a sample of 212 foreign-born nurses licensed to practice in Finland and a random sample of 744 native Finnish nurses. Data were collected with a questionnaire and analyzed using multiple linear regression and structural equation modeling (SEM).ResultsOf all four dimensions of cross-cultural competence, only empathy was associated with perceived time pressure (β = –0.13, p = .018), distress (β = –0.23, p < .001), and sleep problems (β = –0.14, p = .004) after the adjustment for gender, age, employment sector, and frequency of interacting with patients and colleagues from different cultures. There were no differences between native and foreign-born nurses in these observed associations (all ps > .05).ConclusionsCross-cultural empathy may protect against perceived time pressure, distress, and sleep problems in both native and foreign-born nurses. Thus, the promotion of this component of cross-cultural competence among nursing personnel should be encouraged.

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....

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The project sought to address the shortage of sexual assault forensic examiners (SAFE) by delivering and evaluating a comprehensive SAFE training program developed by the International Association of Forensic Nurses (IAFN). To assess if the training was effective, researchers conducted an outcome evaluation using a mixed methods approach, including quantitative pre-post training and qualitative interviews with instructors and students. The evaluation had three main components: 1) to assess training completion, including the percentage of students who completed the training and the factors that contributed to their completion; 2) to ascertain whether students attained knowledge through pre-test/post-tests and the factors that contributed to knowledge attainment; and 3) to determine whether students retained their knowledge using a post-training exam approximately three months following the training, and whether the students incorporated the core concepts of the training into their SAFE practice. The researchers divided the project into 3 studies. Study 1 examined how many students completed the training and what predicted training completion. Study 2a utilized a one-group pre-test post-test design where researchers assessed students' knowledge attainment for 12 online modules. Study 2b utilized a qualitative framework to understand the instructors' pedagogical approach to teaching clinical skills. In addition, researchers conducted qualitative interviews to examine the students' perceptions of the patient care and medical forensic exam skills gained from the clinical component in the SAFE training, and how the clinical training contributed to their skill development. Study 3a explored knowledge retention using an online post-training survey given to students three months following the training. Study 3b utilized the same qualitative framework as Study 2b. Only data for studies 1, 2a, and 3a are available with this collection. The data file has 198 cases and 675 variables. The qualitative interviews for Studies 2b and 3b are not available as part of this data collection at this time.

Analysis of ‘World Bank WDI 2.12 - Health Systems’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/danevans/world-bank-wdi-212-health-systems on 21 November 2021.

--- Dataset description provided by original source is as follows ---

World Bank - World Development Indicators: Health Systems

This is a digest of the information described at http://wdi.worldbank.org/table/2.12# It describes various health spending per capita by Country, as well as doctors, nurses and midwives, and specialist surgical staff per capita

Content

Notes, explanations, etc. 1. There are countries/regions in the World Bank data not in the Covid-19 data, and countries/regions in the Covid-19 data with no World Bank data. This is unavoidable. 2. There were political decisions made in both datasets that may cause problems. I chose to go forward with the data as presented, and did not attempt to modify the decisions made by the dataset creators (e.g., the names of countries, what is and is not a country, etc.).

Columns are as follows: 1. Country_Region: the region as used in Kaggle Covid-19 spread data challenges. 2. Province_State: the region as used in Kaggle Covid-19 spread data challenges. 3. World_Bank_Name: the name of the country used by the World Bank 4. Health_exp_pct_GDP_2016: Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.

1. Health_exp_public_pct_2016: Share of current health expenditures funded from domestic public sources for health. Domestic public sources include domestic revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, non-profit institutions serving households (NPISH) or enterprise financing schemes as well as compulsory prepayment and social health insurance contributions. They do not include external resources spent by governments on health.

2. Health_exp_out_of_pocket_pct_2016: Share of out-of-pocket payments of total current health expenditures. Out-of-pocket payments are spending on health directly out-of-pocket by households.

3. Health_exp_per_capita_USD_2016: Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.

4. per_capita_exp_PPP_2016: Current expenditures on health per capita expressed in international dollars at purchasing power parity (PPP).

5. External_health_exp_pct_2016: Share of current health expenditures funded from external sources. External sources compose of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country. External sources either flow through the government scheme or are channeled through non-governmental organizations or other schemes.

6. Physicians_per_1000_2009-18: Physicians include generalist and specialist medical practitioners.

7. Nurse_midwife_per_1000_2009-18: Nurses and midwives include professional nurses, professional midwives, auxiliary nurses, auxiliary midwives, enrolled nurses, enrolled midwives and other associated personnel, such as dental nurses and primary care nurses.

8. Specialist_surgical_per_1000_2008-18: Specialist surgical workforce is the number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100,000 population.

9. Completeness_of_birth_reg_2009-18: Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.

10. Completeness_of_death_reg_2008-16: Completeness of death registration is the estimated percentage of deaths that are registered with their cause of death information in the vital registration system of a country.

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Inspiration

Does health spending levels (public or private), or hospital staff have any effect on the rate at which Covid-19 spreads in a country? Can we use this data to predict the rate at which Cases or Fatalities will grow?

--- Original source retains full ownership of the source dataset ---

Number of Nurses: Registered: Kerala: General Nursing and Midwives data was reported at 329,492.000 Person in 2022. This records an increase from the previous number of 315,620.000 Person for 2021. Number of Nurses: Registered: Kerala: General Nursing and Midwives data is updated yearly, averaging 215,708.000 Person from Dec 2005 (Median) to 2022, with 15 observations. The data reached an all-time high of 329,492.000 Person in 2022 and a record low of 77,596.000 Person in 2005. Number of Nurses: Registered: Kerala: General Nursing and Midwives data remains active status in CEIC and is reported by Central Bureau of Health Intelligence. The data is categorized under India Premium Database’s Health Sector – Table IN.HLB005: Health Human Resources: Number of Nurses: Registered.

In recent years, Japan has experienced a significant increase in the number of foreign students and workers entering the country. This has resulted in a vast number of international patients in medical facilities. This shift emphasizes the immediate need for Japanese nurses who are both clinically proficient and culturally attuned. In response, our research developed and validated the Cross-cultural Competence Scale for Japanese Nurses (CCCSJN) to better equip nurses for diverse patient care. We conducted a cross-sectional study in Japan’s general hospitals using anonymous questionnaires with nurses and midwives. The scale, developed from data from 394 nurses, underwent both qualitative and quantitative evaluations to define its construct. We analyzed the data using exploratory factor analysis, criterion-related validity, internal consistency, and test-retest reliability, confirming the scale’s reliability and validity. The exploratory analysis revealed five factors: “cross-cultural understanding,” “cross-cultural communication ability,” “motivation for cross-cultural nursing,” “cooperation with multiple professions,” and “respect for foreign patients.” These factors explained 50.92% of the total variance. Cronbach’s α for the CCCSJN was 0.94, and the test-retest reliability correlation was 0.77. The construct validity, criterion-related validity, internal consistency, and test-retest reliability of the CCCSJN were verified. The CCCSJN can be used to assess the cross-cultural competencies of Japanese nurses and identify what skills need to be mastered, leading to improved cross-cultural competence and care.

The Supporting information is a dataset generated through numerical coding of the questionnaire survey data.

In a historical and developmental sense, the former one-year reporting on employees employed in healthcare grew during 1990/91. in the continuous collection and monitoring of data through the state Register of Health Professionals. The department maintains data on all healthcare workers and healthcare associates, and on administrative and technical staff for now only numerically, according to the number of permanent employees at the end of the year. In the future, it is intended to register employees who are not health-oriented and work in healthcare, and healthcare professionals who work outside the healthcare system can also be registered.

Data on health workers and health care associates are required to be submitted not only by state and county-owned health institutions, but also by all private institutions, health workers who independently perform private practice, as well as trading companies for the performance of health activities, regardless of whether they have a contract with the Croatian Institute for health insurance.

All employees are assigned a registration number (code) upon entry into the Registry's database on the day of employment. The connection with the Croatian Health Insurance Institute exists through the use of the registration number when registering, recognizing within the CEZIH system, as well as when registering prescriptions, referrals and other documents of the HZZO. that is, in monitoring and building the health information system.

As an integral part of the same, relational databases also include data on health organizational units, representing the Register of Health Institutions. Namely, in addition to data on employees, the Registry, based on the decision of the Ministry of Health on work authorization, also records basic data on health institutions, surgeries and all other types of independent health units, regardless of the contract with the Croatian Health Insurance Institute or the type of ownership. As for employees, received data on the opening, closing, change of name, address, type and activity of the health organizational unit is also updated daily.

Thus, the organizational structure of healthcare is monitored through the database, according to levels of healthcare, types of healthcare institutions, healthcare activities performed by institutions, divisions with regard to the type of ownership as well as territorial distribution.

In addition to the importance of data on human potential and space, that is, the units where health care is provided, medical equipment is also an important factor in management and planning. One part of the department's work is related to the collection of data on this material resource. In the near future, it is planned to form a Register of Medically Expensive Equipment, which would be technologically and functionally connected with the existing two registers into a whole register of resources in healthcare.

Also, the statistical research aims to include those entities that are not part of the health system, and in which health workers work, i.e. health activities are performed, such as long-term care homes, which means expanding the existing data of the Register of Health Institutions.

In the last decade, a new IT application of the Registry of Health Care Professionals was created and an even better connection with the Croatian Institute for Health Insurance, for example through the use of the so-called population register or the register of insured persons. The register continues to be the source of data and the authorized institution for the delivery of data to international bodies such as the WHO and the joint WHO/Eurostat/OECD database. Within the scope of the Department's activities are also activities in international initiatives and programs, and with regard to the problems of statistical monitoring, shortages and planning of health workers. Since 2012, we have been involved in the implementation of the "Global Code of Practice on International Recruitment of Health Personnel", a recommendation that is also an instrument in the regulation, improvement and establishment of standards in the migration process.

In the same year, the Department was involved in the work in the part of the program platform on the topic of Joint Action on European Health Workforce Planning and Forecasting.

Also, during the past years, there has been cooperation on the topic of health workers within the framework of the South-eastern Europe Health Network (SEEHN).