KR-20260067976-A - System for providing data on the correlation between local depopulation and medical service reduction

KR20260067976AKR 20260067976 AKR20260067976 AKR 20260067976AKR-20260067976-A

Abstract

A system for providing data on the interrelationship between regional population decline and the reduction of medical services is disclosed. The system for providing data on the interrelationship between regional population decline and the reduction of medical services according to an embodiment of the present invention comprises: a data input storage unit that receives and stores basic data for deriving a result value pre-set by an operator, and then provides it to a first analysis unit, a second analysis unit, and a third analysis unit; a first analysis unit that examines the spatial heterogeneity and spatial correlation of the risk of regional population extinction through LSA (Local Indicators of Spatial Autocorrelation) and quantitatively calculates the degree of correlation value; a second analysis unit that examines bidirectionally whether the past value of one variable influences the current value of another variable using a Granger-test and quantitatively calculates the degree of influence value; and a third analysis unit that quantitatively calculates the degree of spatial influence relationship value through a Spatial Error Model among Spatial panel modeling. The gist of the configuration is to include: a result output unit that stores result values calculated from the first analysis unit, the second analysis unit, and the third analysis unit in a data input storage unit and outputs them to an operator's PC or smart device.

Inventors

윤희연
이종표

Assignees

서울대학교산학협력단

Dates

Publication Date: 20260513
Application Date: 20250911
Priority Date: 20241106

Claims (5)

A device that operates by means of a stored program based on data input by an operator to derive a preset result value, A data input storage unit (101) that receives and stores basic data for deriving a result value pre-set by an operator, and then provides it to a first analysis unit (110), a second analysis unit (120), and a third analysis unit (130); A first analysis unit (110) that examines the spatial heterogeneity and spatial correlation of the risk of regional population extinction through LSA (Local Indicators of Spatial Autocorrelation) and quantitatively calculates the degree of correlation value; A second analysis unit (120) that examines in both directions whether the past value of one variable influences the current value of another variable using a Granger test and quantitatively calculates the degree of influence; A third analysis unit (130) that quantitatively calculates the degree of spatial influence relationship through a Spatial Error Model during spatial panel modeling; and A result output unit (140) that stores the result values calculated from the first analysis unit (110), the second analysis unit, and the third analysis unit (130) in a data input storage unit and outputs them to an operator's PC or smart device; A system for providing data on the interrelationship between regional population decline and reduction of medical services, characterized by including
In paragraph 1, The basic data input to the above data input storage unit (101) is, RPE value (Regional Population Extinction Index, an indicator measuring regional population decline), which is a depopulation measurement metric, PMI values (Primary Medical Institutions) and SAMI values (Specialized and Advanced Medical Institutions), which indicate the location of medical institutions, the quantity of medical institutions, and the grade of each medical institution for medical services. Indicators measuring demographic change, such as NPGR (Natural Population Growth Rate), PIR (Population Inflow Rate), POP_DEN (Population Density), and PIR*POP_DEN (Interaction term), FINSCAL_AUTO value (Fiscal Autonomy), a regional economy measurement indicator, The BASIC_RECIPIENTS value, which is a measurement indicator of the Vulnerable Class (Basic livelihood Recipients), Healthcare expenditure measurement indicators: INSURACE_PER (Health insurance expenditure per capita), HEALTH_BUDGET (Healthcare Budget), A system for providing data on the interrelationship between regional population decline and reduction of medical services, characterized by selecting one or more from a group that includes the URBAN value (Urbanization rate), which is a spatial characteristic measurement indicator.
In paragraph 2, The above first analysis unit (110) is, A data preprocessing module (111) that performs the task of converting input data into a form suitable for analysis, receives raw data from a data input storage unit (101), undergoes processes of missing value correction, outlier removal, and data standardization, processes missing values using mean values, median values, or regression-based imputation methods, and detects and removes outliers that exceed a pre-set allowable range to ensure the reliability of the data; A spatial correlation calculation module (112) that analyzes regional data using LSA (Local Indicators of Spatial Autocorrelation), calculates Moran's I, Geary's C, and global spatial correlation indicators to identify the overall spatial distribution pattern of the data, and calculates numerically whether specific regional data forms a clustered form overall or is randomly distributed; and A result visualization and output module (113) that generates intuitive and easy-to-understand visual output based on data generated by a spatial correlation calculation module (112), generates a heat map and a cluster map using GIS-based tools, expresses spatial correlation by region in colors and patterns, and then transmits the result value to a result output unit (140); A system for providing data on the interrelationship between regional population decline and reduction of medical services, characterized by including
In paragraph 3, The above second analysis unit (120) is, A data preprocessing and normality verification module (121) that performs a task to correct missing values in time series data, RPE values (population extinction risk index), PMI values (number of primary medical institutions), SAMI values (number of specialized medical institutions), and time series data received from a data input storage unit (101), as a configuration for converting input time series data into an analyzable form; A causal relationship analysis module (122) that uses data input from a data preprocessing and normality verification module (121) to quantitatively measure the influence of past values of specific variables on current values of other variables, analyzes the influence of regional population decline on the reduction of medical services, or conversely evaluates the influence of the reduction of medical services on population decline; and A result visualization and report generation module (123) that provides the results of the Granger Causality Test to the operator in an intuitive and highly readable form, is designed to allow the operator to comprehensively understand the analysis results by including visual representations and text-based summary results, expresses the strength and direction of the causal relationship in the form of a linear graph, histogram, or correlation network graph, and then transmits the result values to the result output unit (140); A system for providing data on the interrelationship between regional population decline and reduction of medical services, characterized by including
In paragraph 4, The above third analysis unit (130) is, A data input and spatial weight matrix generation module (131) configured to process data required for spatial analysis and generate a weight matrix, receiving data with spatial characteristics such as RPE values (population extinction risk index), PMI values (number of primary medical institutions), SAMI values (number of specialized medical institutions), and POP_DEN values (population density) from a data input storage unit (101), converting the input data into a GIS (Geographic Information System) format, and organizing it into a structure suitable for analysis; A spatial panel modeling and analysis module (132) that performs a Spatial Panel Model analysis based on input data and a weight matrix, and quantitatively evaluates spatial interactions using a Spatial Error Model (SEM), wherein the SEM includes spatial correlations and spatial residuals within the data to calculate the impact of changes in a specific region on neighboring regions; and A visualization and report generation module (133) that expresses the analysis results in an intuitively understandable form, uses a GIS-based visualization tool to represent the spatial distribution and interaction as a map, generates a heatmap of the spatial correlation between the risk of population extinction and the reduction of medical services in a specific region so that the operator can grasp the problem area at a glance, and then transmits the result value to the result output unit (140); A system for providing data on the interrelationship between regional population decline and reduction of medical services, characterized by including

Description

System for providing data on the correlation between local depopulation and medical service reduction The present invention relates to a system for providing data on the interrelationship between regional population decline and the reduction of medical services, and more specifically, to a system capable of revealing the impact and various relationships between the risk of regional population decline and the reduction of medical services in the era of regional extinction. The risk of population decline is emerging as an increasingly serious social issue at the city, county, and district levels in South Korea. Population decrease at the local level stems from various causes, among which population aging and declining birth rates act as major long-term factors. These demographic shifts are more pronounced in low-density areas, such as rural regions, posing a significant threat to the sustainability of local communities. Regarding economic factors, industrial restructuring and job shortages are accelerating the migration of residents to cities. This leads to a weakening of the economic foundation within local communities, triggering a vicious cycle. In particular, the deterioration of living environments and the quality of public services are driving residents out of their regions. As essential community infrastructure—such as healthcare, education, and transportation—deteriorates, there is a distinct tendency for residents to move to urban areas that offer better amenities and living conditions. This phenomenon widens regional disparities and exacerbates the risk of rural extinction. Medical services are one of the essential public services that directly determine the health and survival of residents. However, the shortage of medical institutions at the local level significantly restricts access to basic medical services. The lack of medical services leads to a decline in the health levels of local residents and an increase in mortality rates, which seriously undermines the sustainability of the local population. Furthermore, the absence of medical services discourages residents from staying in the area, resulting in a further acceleration of local population decline. Conversely, regional population decline causes serious problems in terms of the supply of medical services. The decrease in demand for medical services resulting from population decline exacerbates the financial difficulties of local medical institutions. This can lead to the downsizing or closure of medical facilities, resulting in a situation where local residents are unable to receive adequate medical care. This vicious cycle further increases the risk of population extinction in the local community. Not only in South Korea, but also globally, cities in developed nations have experienced population growth during periods of economic expansion, yet there is an increasing number of cases where they transition to population decline after reaching their peak. In particular, South Korea, China, and Japan in Northeast Asia experienced rapid population growth after the 1980s, followed by an unprecedented phase of population decline in the 2010s. In Japan, the term "population extinction" first emerged, and the method of calculating the extinction risk index based on the ratio of the elderly population to the female population of childbearing age became established as a major analytical method. This risk of population decline extends beyond a mere social phenomenon and has a severe impact on the maintenance of essential local infrastructure. In particular, the reduction of key infrastructure, such as medical services, is not limited to a local infrastructure issue but affects the sustainability of the entire nation. If medical services are reduced due to population decline, health inequalities among local residents intensify and have a detrimental effect on the public health system. Furthermore, the issue of population decline has established itself as a structural problem that can no longer be resolved through short-term policies aimed at population growth. Given the continuously decreasing population, it is crucial to quantitatively analyze the relationship between regional population extinction and the reduction of medical services to formulate policy responses. This analysis can serve as essential foundational data for setting national policy priorities, extending beyond a mere regional issue. The risk of regional population decline is closely linked to the reduction of healthcare services, and the interaction between the two significantly impacts community sustainability. Failure to analyze this interaction not only undermines the effectiveness of local policies but can also pose a serious obstacle to establishing national response strategies. In conclusion, conventional technology has failed to analyze the relationship between regional population decline and the reduction of medical services from multiple perspectives, and has not properly refle