Purpose This study aimed to identify changes in the regional distribution of nurses from 2011 to 2020 and to measure the degree of geographic inequality in the distribution of nurses. Methods National statistics from 2011 to 2020 were used to analyze the distribution of practicing nurses and nursing graduates by region. The degree of geographic inequality in these distributions was measured using the Gini coefficient. Results Between 2011 and 2020, the number of nursing graduates increased significantly in the non-capital regions and medically underserved areas.
However, non-capital regions observed a smaller increase in the number of practicing nurses than in the number of nursing graduates produced, while capital regions experienced a larger increase in the number of practicing nurses than in the number of nursing graduates produced. Furthermore, the degree of geographic inequality in the distribution of practicing nurses worsened between 2011 and 2020. Conclusion Effective policies to prevent the outflow of rural nurses are necessary to mitigate geographical inequality in the distribution of nurses.
Purpose Nursing colleges are continuously being expanded to solve the problem of imbalance among regions, but the outflow of the provincial brain-drain to metropolitan regions continues. Therefore, this study aimed to identify the influencing factors on the regional outflow intention of nursing students. Methods This study employed a mixedmethod design, and 214 nursing students in the Honam region filled out a self-administered questionnaire. Eight participants recruited through random sampling were interviewed in depth. Data were analyzed using a t-test, x2 test and logistic regression. Results Among the total respondents, 161 students (75.2%) had intent to regional outflow. Influencing factors were significantly correlated with employment in tertiary general hospitals (OR=3.32, 95% CI=1.35~8.16), perception of job opportunities in the province (OR=0.52, 95% CI=0.31~0.87), intrinsic job values (OR=2.43, 95% CI=1.14~5.22), and voluntary employment preparation behaviors (OR=2.75, 95% CI=1.05~ 7.19). Through the interviews, themes related to regional outflow intentions were drawn into the following three categories: “recognition of working environment by region”, “aspiration for professional growth”, and “expectation for self-development and rich experience”. Conclusion This study’s results are expected to be used as strategic data for establishing plans for nurturing regional human resources and improving the local nursing workforce in non-metropolitan areas.
Purpose This study aimed to estimate the unmet demand for INCS and the number of needed beds for fulfillment.
Methods: Annual data from the Korea Health Panel (2015~2018), Health Insurance Statistical Yearbook (2015~ 2019), and published statistical data (2015~2019) were used. To measure the unmet demand, the utilization of informal nursing care services, which can be a market substitute for INCS, was used. The number of needed beds was calculated by dividing the demand by the bed occupancy rate multiplied by 365 days.
Results: The unmet demand decreased every year and was estimated to be 31~47 million person-day as of 2019. It was the highest in Gyeonggi (6~8 million) and the lowest in Jeju (160~220 thousand), while the fulfilled rate was the highest in Incheon (52~61%) and the lowest in Jeonbuk (6~8%). For each type, general hospitals showed the highest unmet demand (6~10 million), followed by hospitals (5~8 million) and tertiary hospitals (4~7 million). Gyeonggi province (37,212~48,882) and general hospitals (54,955~70,962) were most needed additional INCS beds.
Conclusion: Tailored bed expansion strategies are necessary to satisfy each region's and hospital’s demand. Considering the multi-layered causes of unmet demand, a healthcare system reform that increases the regional self-sufficiency of INCS is required.
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A Study on the Outflow Intention of Nursing Students in Non-Metropolitan Area: Honam Region Purum Kang, A Young Han Journal of Korean Academy of Nursing Administration.2023; 29(3): 234. CrossRef
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