Previous evaluation studies of the visiting nursing program explained an average change of the participants' health status, without considering socio-ecological characteristics and their impacts. However, these factors must affect individual health problems and lifestyles. For effective and appropriate community based programs, the Geographical Information System(GIS) can be utilized. GIS is a computer-based tool for mapping and analyzing things that happen on earth, and integrates statistical analysis with unique visualization. The purpose of this study was to evaluate visiting nursing care and to advocate the usefulness of planning and evaluating visiting nursing programs using Exploratory Spatial Data Analysis(ESDA) with GIS technology.

One hundred eighty-four elderly participants with cerebrovascular risk factors who lived in 13 areas of one community received visiting nursing care. The data analyzed characteristics of pre-post change and autocorrelation by ESDA using GIS technology.

Visiting nursing care showed an improvement in the participants' lifestyle habits, and family management ability and stress level, while the improvements were different depending on the regions. The change of family management ability and stress level correlated with neighborhoods (Morgan's I= 0.1841, 0.1675).

Community health providers need to consider the individual participant's health status as well as socio-ecological factors. Analysis using GIS technology will contribute to the effective monitoring, evaluation and design of a visiting nursing program.

To examine geographical imbalances by analyzing new graduate nurses' migration patterns among regions where they grew up, attended nursing school, and had their first employment and to identify factors related to working in non-metropolitan areas.

The sample consisted of 507 new graduates working in hospitals as full-time registered nurses in South Korea. Migration patterns were categorized into 5 patterns based on sequential transitions of "geographic origin-nursing school-hospital." Multiple logistic regression analysis was conducted to identify factors associated with working in non-metropolitan hospitals.

Nurses who grew up, graduated, and worked in the same region accounted for the greatest proportion (54%). Sixty-five percent had their first employment in the region where they graduated. Nurses tended to move from poor to rich regions and from non-metropolitan to metropolitan areas. Working in non-metropolitan hospitals was related to older age, the father having completed less than 4 years of college education, non-metropolitan origin, non-capital city school graduation, and a diploma (vs. baccalaureate) degree.

Admitting students with rural backgrounds, increasing rural nursing school admission capacities, and providing service-requiring scholarships, particularly for students from low-income families, are recommended to address geographical imbalances.