Navigation data-based medical service supply and demand feature multi-scale analysis method

Abstract

The invention discloses a multi-scale analysis method for medical service supply and demand characteristics based on navigation data, and the method comprises the steps: obtaining the navigation OD data of all users using a target navigation map, generating a hospital range according to the information of an isolation belt and an entrance and exit, and carrying out the superposition analysis according to the navigation OD data and the hospital range, and obtaining a hospital access journey; constructing a population-hospital two-mode network, and generating sub-networks of different scales in the population-hospital two-mode network by adopting an aggregation method; and according to the sub-networks of different scales, constructing a measurement method of the cross-city supply and demand characteristics of the city scale, the cross-city demand characteristics of the street scale and the cross-city supply characteristics of the hospital scale, and outputting an evaluation result of the multi-scale supply and demand characteristics of the medical service. According to the invention, the medical service evaluation is more comprehensive and accurate.

Description

Technical Field

[0001] The present invention relates to the field of urban planning technology, and in particular to a multi-scale analysis method, system, terminal and computer-readable storage medium for medical service supply and demand characteristics based on navigation data. Background Art

[0002] The supply and demand of medical services include suppliers (such as hospitals, community health centers, clinics, pharmacies, etc.) and demanders (such as population). The characteristics of the supply and demand of medical services represent the relationship between the supply and demand sides, including quantity, proportion, interaction relationship, influence mechanism, time dimension, space dimension, etc. Common characteristics include: supply quantity, demand quantity, supply-demand ratio, spatial separation, time distribution, accessibility, equality, etc.

[0003] Multi-scale evaluation of the supply and demand characteristics of medical services is of great significance for assessing hospital demand and service scope, and can effectively guide the scientific planning of medical resources and the improvement of utilization efficiency. In urban agglomeration areas, cross-city population mobility and interactive services occur frequently, and each city maintains a relatively independent management system, making the supply and demand relationship of medical services more complicated. In the absence of public medical records, the analysis method based on navigation OD data (OD: origin-destination, starting and ending points, navigation OD data is provided by a navigation map, recording the starting point and destination of all trips navigated using the navigation map) provides a new perspective and can deeply analyze these complex supply and demand relationships. This not only provides key insights for improving existing medical service evaluation models, but also significantly improves the accuracy and effectiveness of medical service planning and management.

[0004] Compared with other travel data, navigation data has irreplaceable advantages. Among the existing data sources, medical records are often difficult to obtain, questionnaires and interviews are characterized by high costs and small sample sizes, mobile phone signaling data and bus card data are accompanied by positioning errors, and taxi GPS and online car-hailing trajectory data only include one mode of travel among motor vehicle trips. As an emerging type of travel data, navigation data covers a variety of motor vehicle types such as taxis, private cars, and online car-hailing. At the same time, the navigation destination is directly input by the user and has the characteristics of high positioning accuracy. Although navigation data may have a low sampling rate in short-distance travel, it still has important application value in hospital service scope evaluation and accessibility evaluation. At present, there is a lack of analytical methods for extracting facility visit itineraries and evaluating supply and demand characteristics based on navigation OD data.

[0005] In addition, most existing studies focus on the micro or macro scale. In micro-scale studies, a single city is usually used as the research area. Although some studies have compared the supply and demand characteristics of different cities, they usually regard cities as independent entities in the spatial dimension. At the macro scale, network analysis methods are usually used, with cities as nodes, ignoring the internal characteristics of cities. However, with the development of cities, urban agglomerations have become a new form of urban organization, characterized by mutual connection and communication between cities, but each city still retains a relatively independent management system. At present, there is still a lack of multi-scale analysis methods for the supply and demand characteristics of medical services in urban agglomerations.

[0006] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0007] The main purpose of the present invention is to provide a multi-scale analysis method, system, terminal and computer-readable storage medium for the supply and demand characteristics of medical services based on navigation data, aiming to solve the problem that the prior art lacks a multi-scale analysis method for the supply and demand characteristics of medical services in urban agglomerations based on navigation OD data, and is unable to effectively and comprehensively evaluate medical services.

[0008] To achieve the above object, the present invention provides a multi-scale analysis method for medical service supply and demand characteristics based on navigation data, and the multi-scale analysis method for medical service supply and demand characteristics based on navigation data comprises the following steps:

[0009] Obtain navigation OD data of all users using the target navigation map, generate a hospital range according to the isolation zone and the entrance and exit information, perform an overlay analysis based on the navigation OD data and the hospital range, and obtain a hospital visit itinerary;

[0010] constructing a population-hospital two-model network according to the hospital visit itinerary, and generating sub-networks of different scales in the population-hospital two-model network by using an aggregation method;

[0011] According to sub-networks of different scales, cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale are constructed, and the evaluation results of the multi-scale supply and demand characteristics of medical services are output.

[0012] In addition, to achieve the above-mentioned purpose, the present invention also provides a multi-scale analysis system of medical service supply and demand characteristics based on navigation data, wherein the multi-scale analysis system of medical service supply and demand characteristics based on navigation data includes:

[0013] A data acquisition module, used to acquire navigation OD data of all users using the target navigation map, generate a hospital range according to the isolation zone and the entrance and exit information, and perform an overlay analysis based on the navigation OD data and the hospital range to obtain a hospital visit itinerary;

[0014] A network construction module, used to construct a population-hospital two-model network according to the hospital visit itinerary, and to generate sub-networks of different scales in the population-hospital two-model network by using an aggregation method;

[0015] The service evaluation module is used to construct cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale based on sub-networks of different scales, and output the evaluation results of the multi-scale supply and demand characteristics of medical services.

[0016] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a multi-scale analysis program based on the medical service supply and demand characteristics of navigation data, which is stored in the memory and can be run on the processor, and when the multi-scale analysis program based on the medical service supply and demand characteristics of navigation data is executed by the processor, the steps of the multi-scale analysis method of the medical service supply and demand characteristics based on the navigation data as described above are implemented.

[0017] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a multi-scale analysis program for medical service supply and demand characteristics based on navigation data, and when the multi-scale analysis program for medical service supply and demand characteristics based on navigation data is executed by a processor, the steps of the multi-scale analysis method for medical service supply and demand characteristics based on navigation data as described above are implemented.

[0018] In the present invention, the navigation OD data of all users using the target navigation map is obtained, the hospital range is generated according to the isolation zone and the entrance and exit information, and the navigation OD data and the hospital range are overlaid and analyzed to obtain the hospital visit itinerary; a population-hospital two-model network is constructed according to the hospital visit itinerary, and sub-networks of different scales are generated in the population-hospital two-model network by using an aggregation method; according to the sub-networks of different scales, cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale are constructed, and the evaluation results of the multi-scale supply and demand characteristics of medical services are output. The technical method of the present invention for evaluating the supply and demand characteristics of medical services using navigation OD data is helpful to improve the medical service evaluation technology by taking advantage of navigation data, and the multi-scale evaluation index of the supply and demand characteristics of medical services based on the two-model network is evaluated from the two aspects of node characteristics and sub-network characteristics, so that the medical service evaluation is more comprehensive and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a preferred embodiment of the multi-scale analysis method of medical service supply and demand characteristics based on navigation data of the present invention;

[0020] Figure 2It is a schematic diagram of a multi-scale cross-city medical service process using a population-hospital bipartite network to depict multi-scale cross-city medical service in a preferred embodiment of the multi-scale analysis method of medical service supply and demand characteristics based on navigation data of the present invention;

[0021] Figure 3 It is a schematic diagram of arrival points and hospital polygons in a preferred embodiment of the multi-scale analysis method of medical service supply and demand characteristics based on navigation data of the present invention;

[0022] Figure 4 It is a structural diagram of a preferred embodiment of the multi-scale analysis system of medical service supply and demand characteristics based on navigation data of the present invention;

[0023] Figure 5 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0025] The multi-scale analysis method of medical service supply and demand characteristics based on navigation data described in the preferred embodiment of the present invention is as follows: Figure 1 and Figure 2 As shown, the multi-scale analysis method of medical service supply and demand characteristics based on navigation data includes the following steps:

[0026] Step S10: Obtain navigation OD data of all users using the target navigation map, generate a hospital range based on the isolation zone and entrance and exit information, perform overlay analysis based on the navigation OD data and the hospital range, and obtain a hospital visit itinerary.

[0027] Specifically, the navigation OD data of all users who use the target navigation map (for example, all people who use AutoNavi navigation) are obtained, and the navigation OD data is preprocessed. The data preprocessing includes: cleaning the navigation OD data, deleting duplicate data, eliminating outliers and missing values, and organizing the data storage format. According to the coordinates of the arrival location, an arrival point shp file is generated. The shp file refers to a file format used to represent geographic spatial data in a geographic information system (GIS). The shp file usually contains the geometric position information of geographic spatial elements, such as points, lines or polygons, and attribute information related thereto. Here, the arrival point coordinates are converted into a point format shp file.

[0028] Hospital range generation: Use the API service of the online map to obtain the hospital AOI (Area of ​​interest) and the geographic coordinates of the entrance, set a buffer zone around the hospital entrance (for example, generate a 30-meter buffer zone around the hospital entrance), if the buffer zone intersects with the road isolation zone, delete the part exceeding the isolation zone, merge the generated entrance buffer zone with the hospital AOI, and create a hospital polygon representing the hospital.

[0029] Itinerary extraction based on overlay analysis: Overlay analysis is performed on the hospital polygon and the arrival point shp file, and the itinerary OD with the arrival point within the hospital polygon is identified as the itinerary for visiting the hospital, and the hospital visit itinerary is obtained. Overlay Analysis is an important spatial analysis method in Geographic Information System (GIS), which involves superimposing two or more different geographic data layers according to their geographical locations to explore the relationship and interaction between them, thereby generating a new data layer.

[0030] By extracting the itinerary to the hospital, we can estimate the characteristics of the people who come to the hospital to get services, including their place of origin, departure time, arrival time, etc., and then calculate various subsequent characteristic indicators. Although the hospital visit itinerary is not completely equivalent to the patient's medical record, it has high temporal and spatial resolution characteristics and can be used to estimate the supply and demand characteristics of medical services.

[0031] like Figure 3 As shown, Figure 3 Taking the University of Hong Kong-Shenzhen Hospital as an example, the destination and hospital polygon of the navigation OD data on December 22, 2019 are displayed.

[0032] Step S20: construct a population-hospital two-model network according to the hospital visit itinerary, and generate sub-networks of different scales in the population-hospital two-model network using an aggregation method.

[0033] Specifically, a population-hospital two-model network G is constructed based on the hospital visit itinerary, denoted as G = (U, V, E). The network consists of two groups of nodes: population grid (U) and hospital (V), where U represents the population grid, V represents the hospital, and E represents the set of edges; i ∈U and node v j Each edge e between ∈V ij Represents the population grid u i To the hospital j The flow of the edge is represented by i, i represents the index of the population grid node U, j represents the index of the hospital node V, and the edge weight w ij byu i and v j The flow rate between them is determined.

[0034] In the population-hospital two-model network, the aggregation method is used to generate sub-networks of different scales, namely, the urban population-urban hospital sub-network, the street population-urban hospital sub-network, and the urban population-hospital sub-network;

[0035] The urban population-urban hospital subnetwork is denoted as G CC =(C1, E CC ), namely, the city (population)-city (hospital) subnetwork, where the node is the city, C1 represents the node set, and E CC represents the edge set between cities; the street population-city hospital subnetwork is denoted as G DC =(D, E DC， C2), that is, the street (population)-city (hospital) subnetwork, D represents the street where the population is located, C2 represents the city where the hospital is located, and E DC represents the set of edges between the street where the population is located and the city where the hospital is located; the city population-hospital subnetwork is denoted as G CH =(C3,E CH , V), namely the city (population)-hospital subnet, C3 represents the city where the population is located, V represents the hospital, E CH Represents the set of edges between the city where the population is located and the hospital.

[0036] The edge weights in the urban population-urban hospital subnetwork, the street population-urban hospital subnetwork, and the street population-urban hospital subnetwork are calculated as follows:

[0037]

[0038] Among them, m and n are city nodes, d is a street node, and j is a hospital node. represents the edge weight of the urban population-urban hospital sub-network, represents the edge weight of the street population-city hospital sub-network, represents the edge weight of the urban population-hospital sub-network, represents the population grid set located in city m, represents the population grid set of d streets, represents the set of hospitals in city m, represents the set of hospitals in city n.

[0039] Step S20 constructs a medical service supply and demand network at different spatial scales, supporting subsequent content to depict the characteristics of medical service supply and demand at different scales.

[0040] Step S30: Based on the sub-networks of different scales, construct cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale, and output the evaluation results of the multi-scale supply and demand characteristics of medical services.

[0041] Specifically, for the cross-city supply and demand characteristics at the city scale, based on the urban population-urban hospital sub-network, we constructed the node strength, isolation index, the cross-city demand index and the cross-city supply index at the city scale, and the regional cross-city supply index at the city scale. According to the node strength, isolation index, the cross-city demand index and the cross-city supply index at the city scale, and the regional cross-city supply index at the city scale, we characterized the cross-city hospital access characteristics at the city scale. For the cross-city demand characteristics at the street scale, based on the street population-urban hospital sub-network, we constructed the cross-city demand index at the street scale. For the cross-city supply characteristics at the hospital scale, based on the street population-urban hospital sub-network, we calculated the hospital-scale cross-city supply index and the hospital-scale cross-city regional supply index at the hospital level.

[0042] Cross-city supply and demand characteristics at the city scale: Based on the city (population)-city (hospital) sub-network, the following indicators are constructed to characterize the cross-city hospital access characteristics at the city scale.

[0043] (1) Node strength:

[0044] Node strength is a key indicator for evaluating the importance of nodes in a network. In a directed network, this indicator is broken down into in-degree strength and out-degree strength, which represent the inflow and outflow of a city, respectively, both of which can be classified as cross-city travel. Trips that start and end in the same city are called intra-city trips. Understanding the relationship between inflow (in-degree strength), outflow (out-degree strength), and intra-city travel is crucial for analyzing the phenomenon of cross-city medical treatment. The mathematical expressions of these concepts are as follows:

[0045]

[0046] in, represents the number of trips from city n to city m, N is the total number of cities in the urban agglomeration, and are the sum of the weights of all input edges and output edges, Represents the sum of the weights of each edge within the city.

[0047] (2) Isolation index:

[0048] Existing studies generally believe that inter-city travel is rare. This assumption is generally accepted in geographically dispersed cities, but has not been confirmed in urban agglomerations. This paper proposes an isolation index (ISO m ) is used to measure the proportion of cross-city travel. The calculation formula is as follows:

[0049]

[0050] Among them, the minimum value of the isolation index is zero, indicating that there is no inter-city travel. On the contrary, a high isolation index indicates a high degree of interaction between the city and other cities. In this case, using only the city as a study area may bias the evaluation of medical services.

[0051] (3) Inter-city demand index and inter-city supply index at the city scale:

[0052] In order to describe the proportion of cross-city travel in the medical services provided by a city, the present invention proposes the city cross-city demand index (CCDI) and the city cross-city supply index (CCSI), which are expressed as follows:

[0053]

[0054] in, represents the proportion of outflow hospital visit trips from a city to the total hospital visit trips from city m, It represents the proportion of inbound hospital visits in city m to the total number of visits to hospitals in that city; both indices range from 0 to 100%. Cities with higher CCDI values ​​may lack high-quality medical resources or have an uneven layout of facilities, resulting in a higher proportion of their residents seeking medical treatment in other cities, and vice versa. A higher CCSI value indicates that the city carries a larger proportion of regional medical services and needs to pay more attention to the impact of cross-city medical services.

[0055] (4) Regional cross-city supply index at the city level:

[0056] In order to characterize the proportion of cross-city medical services provided by a city to the overall cross-city medical demand in the region, the present invention proposes the Regional Cross-City Supply Index (RCCSI). , the expression is as follows:

[0057]

[0058] The city-scale RCCSI represents the proportion of inbound trips in a city relative to outbound trips in all other cities in the city cluster. The value range of RCCSI is 0-100%. Cities with high RCCSI values ​​provide a large number of regional medical services and have considerable appeal to other cities. In contrast, cities with low RCCSI values ​​may lack high-quality medical resources and may be less attractive to other cities.

[0059] Based on the street population-city hospital subnetwork, a street-scale cross-city demand index is constructed. Street-scale cross-city demand index: Based on the street (population)-city (hospital) subnetwork, CCDI can also be calculated at the street scale. Similar to the city-scale CCDI, the street-scale It represents the ratio of cross-city trips from this street to the total trips generated in this street. The expression is as follows:

[0060]

[0061] in, represents the weight of the edge between street d and city m, M represents the total number of cities in the urban agglomeration, the numerator is the total number of hospital visit trips from street d to all cities except the city to which street d belongs, and the denominator represents the total number of hospital visit trips generated from street d.

[0062] Cross-city supply characteristics at the hospital scale: Based on the city (population)-hospital sub-network, the cross-city supply index and regional supply index can be calculated at the hospital level.

[0063] Hospital-scale cross-city supply index Describes the proportion of cross-city medical services relative to the total services provided by hospitals, as follows:

[0064]

[0065] in, represents the cross-city supply index of hospital scale, represents the weight of the edge between city m and hospital j, city j represents the city where hospital j is located, the numerator represents the number of cross-city trips to hospital j, and the denominator represents the number of all trips to hospital j.

[0066] Hospital-scale cross-city regional supply index It represents the proportion of cross-city medical services provided by a hospital to the total cross-city demand of other cities. The expression is as follows:

[0067]

[0068] in, represents the cross-city regional supply index at the hospital scale, and the numerator represents the total number of cross-city trips to hospital j. In order to simplify the formula, the previously introduced city output intensity index is used.

[0069] Furthermore, based on the cross-city supply and demand characteristics at the city scale, the cross-city demand characteristics at the street scale, and the cross-city supply characteristics at the hospital scale, the evaluation results of the multi-scale supply and demand characteristics of medical services are output.

[0070] The technical method of evaluating the supply and demand characteristics of medical services using navigation OD data in the present invention is helpful to utilize the advantages of navigation data to improve the medical service evaluation technology. A multi-scale evaluation index of the supply and demand characteristics of medical services based on a two-mode network is proposed, and the evaluation is carried out from two aspects: node characteristics and sub-network characteristics, and the impact of using a single city data on the medical service evaluation is quantitatively measured.

[0071] Furthermore, if Figure 4 As shown, based on the above-mentioned multi-scale analysis method of medical service supply and demand characteristics based on navigation data, the present invention also provides a multi-scale analysis system of medical service supply and demand characteristics based on navigation data, wherein the multi-scale analysis system of medical service supply and demand characteristics based on navigation data includes:

[0072] The data acquisition module 51 is used to acquire navigation OD data of all users who use the target navigation map, generate a hospital range according to the isolation zone and the entrance and exit information, and perform an overlay analysis based on the navigation OD data and the hospital range to obtain a hospital visit itinerary;

[0073] A network construction module 52, for constructing a population-hospital two-model network according to the hospital visit itinerary, and generating sub-networks of different scales in the population-hospital two-model network by using an aggregation method;

[0074] The service evaluation module 53 is used to construct cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale according to sub-networks of different scales, and output evaluation results of multi-scale supply and demand characteristics of medical services.

[0075] Furthermore, if Figure 5 As shown, based on the above-mentioned multi-scale analysis method and system of medical service supply and demand characteristics based on navigation data, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 5 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0076] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a multi-scale analysis program 40 based on the supply and demand characteristics of medical services based on navigation data is stored on the memory 20, and the multi-scale analysis program 40 based on the supply and demand characteristics of medical services based on navigation data can be executed by the processor 10, thereby realizing the multi-scale analysis method of the supply and demand characteristics of medical services based on navigation data in this application.

[0077] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the multi-scale analysis method of the medical service supply and demand characteristics based on navigation data.

[0078] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0079] In one embodiment, when the processor 10 executes the multi-scale analysis program 40 based on medical service supply and demand characteristics of navigation data in the memory 20, the steps of multi-scale analysis based on medical service supply and demand characteristics of navigation data as described above are implemented.

[0080] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a multi-scale analysis program for medical service supply and demand characteristics based on navigation data, and when the multi-scale analysis program for medical service supply and demand characteristics based on navigation data is executed by a processor, the steps of the multi-scale analysis method for medical service supply and demand characteristics based on navigation data as described above are implemented.

[0081] In summary, the present invention provides a multi-scale analysis method, system, terminal and computer-readable storage medium for medical service supply and demand characteristics based on navigation data, the method comprising: obtaining navigation OD data of all users using the target navigation map, generating hospital ranges according to isolation belts and entrance and exit information, performing overlay analysis according to the navigation OD data and the hospital range, and obtaining hospital visit itineraries; constructing a population-hospital two-model network according to the hospital visit itinerary, and using an aggregation method to generate sub-networks of different scales in the population-hospital two-model network; constructing cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale and cross-city supply characteristics at the hospital scale according to the sub-networks of different scales, and outputting evaluation results of multi-scale supply and demand characteristics of medical services. The technical method of the present invention for evaluating medical service supply and demand characteristics using navigation OD data is helpful to improve medical service evaluation technology by utilizing the advantages of navigation data, and the multi-scale evaluation index of medical service supply and demand characteristics based on the two-model network is evaluated from the two aspects of node characteristics and sub-network characteristics, so that the medical service evaluation is more comprehensive and accurate.

[0082] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or terminal including the element.

[0083] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0084] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A multi-scale analysis method for medical service supply and demand characteristics based on navigation data, characterized in that: The multi-scale analysis method of medical service supply and demand characteristics based on navigation data includes: Obtain navigation OD data of all users using the target navigation map, generate a hospital range according to the isolation zone and the entrance and exit information, perform an overlay analysis based on the navigation OD data and the hospital range, and obtain a hospital visit itinerary; constructing a population-hospital two-model network according to the hospital visit itinerary, and generating sub-networks of different scales in the population-hospital two-model network by using an aggregation method; According to sub-networks of different scales, cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale are constructed, and the evaluation results of the multi-scale supply and demand characteristics of medical services are output.

2. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 1 is characterized in that: The step of obtaining navigation OD data of all users using the target navigation map, generating a hospital range according to isolation belts and entrance and exit information, and performing overlay analysis on the navigation OD data and the hospital range to obtain a hospital visit itinerary specifically includes: Obtain navigation OD data of all users using the target navigation map, clean the navigation OD data, delete duplicate data, remove outliers and missing values, organize the data storage format, and generate an arrival point shp file based on the arrival location coordinates; Use the API service of the online map to obtain the geographic coordinates of the hospital AOI and entrance, set a buffer zone around the hospital entrance, and if the buffer zone intersects with the road isolation zone, delete the part exceeding the isolation zone, merge the resulting entrance buffer zone with the hospital AOI, and create a hospital polygon representing the hospital; The hospital polygon and the arrival point shp file are overlaid for analysis, and the itinerary OD whose arrival point is within the hospital polygon is identified as a itinerary for visiting the hospital, thereby obtaining a hospital visiting itinerary.

3. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 1 is characterized in that: The step of constructing a population-hospital two-model network according to the hospital visit itinerary and generating sub-networks of different scales in the population-hospital two-model network by using an aggregation method specifically includes: According to the hospital visit itinerary, a population-hospital two-model network G is constructed, denoted as G = (U, V, E), where U represents the population grid, V represents the hospital, and E represents the set of edges; Among them, node u i ∈U and node v j Each edge e between ∈V ij Represents the population grid u i To the hospital j The flow of the edge is represented by i, i represents the index of the population grid node U, j represents the index of the hospital node V, and the edge weight w ij byu i and v j The flow rate between them is determined; In the population-hospital two-model network, the aggregation method is used to generate sub-networks of different scales, namely, the urban population-urban hospital sub-network, the street population-urban hospital sub-network, and the urban population-hospital sub-network; The urban population-urban hospital subnetwork is denoted as G CC =(C1, E CC ), the node is the city, C1 represents the node set, E CC represents the edge set between cities; Let the street population-city hospital subnetwork be G DC =(D, E DC , C2), D represents the street where the population is located, C2 represents the city where the hospital is located, E DC represents the set of edges between the street where the population is located and the city where the hospital is located; The city population-hospital subnetwork is denoted as G CH =(C3,E CH , V), C3 represents the city where the population is located, V represents the hospital, E CH represents the set of edges between the city where the population is located and the hospital; The edge weights in the urban population-urban hospital subnetwork, the street population-urban hospital subnetwork, and the street population-urban hospital subnetwork are calculated as follows: Among them, m and n are city nodes, d is a street node, and j is a hospital node. represents the edge weight of the urban population-urban hospital sub-network, represents the edge weight of the street population-city hospital sub-network, represents the edge weight of the urban population-hospital sub-network, represents the population grid set located in city m, represents the population grid set of d streets, represents the set of hospitals in city m, represents the set of hospitals in city n.

4. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 3 is characterized in that: According to the sub-networks of different scales, the cross-city supply and demand characteristics at the city scale, the cross-city demand characteristics at the street scale, and the cross-city supply characteristics at the hospital scale are constructed, specifically including: For the cross-city supply and demand characteristics at the city scale, based on the city population-city hospital sub-network, we constructed the node strength, isolation index, city-scale cross-city demand index and cross-city supply index, and city-scale regional cross-city supply index. Based on the node strength, isolation index, city-scale cross-city demand index and cross-city supply index, and city-scale regional cross-city supply index, we characterized the cross-city hospital access characteristics at the city scale. For the cross-city demand characteristics at the street level, a cross-city demand index at the street level is constructed based on the street population-city hospital sub-network; For the cross-city supply characteristics at the hospital scale, the hospital-scale cross-city supply index and the hospital-scale cross-city regional supply index were calculated at the hospital level based on the street population-city hospital sub-network.

5. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 4 is characterized in that: The node strength includes in-degree strength and out-degree strength, which represent the inflow and outflow of the city respectively, and the expression is: in, represents the number of trips from city n to city m, N is the total number of cities in the urban agglomeration, and are the sum of the weights of all input edges and output edges, represents the sum of the weights of the edges within the city; The isolation index is used to measure the proportion of cross-city travel, and the expression is: Among them, ISO m represents the isolation index; The inter-city demand index and inter-city supply index at the city scale are used to describe the proportion of inter-city travel in the medical services provided by a city, and the expression is: in, represents the proportion of outflow hospital visit trips from a city to the total hospital visit trips from city m, It represents the proportion of the inflow hospital visit trips in city m to the total trips to the hospitals in that city; The regional inter-city supply index at the city scale is used to characterize the proportion of inter-city medical services provided by a city to the overall regional inter-city medical demand, and is expressed as: Among them, RCCSI m Represents the ratio of inbound trips to a city relative to outbound trips to all other cities in the city cluster.

6. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 5, characterized in that: The inter-city demand index at the street level is used to indicate the proportion of inter-city trips from the street to the total trips generated in the street, and is expressed as: in, It represents the ratio of cross-city trips from this street to the total trips generated in this street. represents the weight of the edge between street d and city m, M represents the total number of cities in the urban agglomeration, the numerator is the total number of hospital visit trips from street d to all cities except the city to which street d belongs, and the denominator represents the total number of hospital visit trips generated from street d.

7. The multi-scale analysis method for medical service supply and demand characteristics based on navigation data according to claim 6, characterized in that: The hospital-scale inter-city supply index is used to describe the proportion of inter-city medical services relative to the total services provided by the hospital, and is expressed as: in, represents the cross-city supply index of hospital scale, represents the weight of the edge between city m and hospital j, city j represents the city where hospital j is located, the numerator represents the number of cross-city trips to hospital j, and the denominator represents the number of all trips to hospital j; The hospital-scale inter-city regional supply index is used to indicate the proportion of inter-city medical services provided by a hospital to the total inter-city demand of other cities, and is expressed as: in, Represents the cross-city regional supply index of hospital scale.

8. A multi-scale analysis system for medical service supply and demand characteristics based on navigation data, characterized in that: The multi-scale analysis system for medical service supply and demand characteristics based on navigation data includes: A data acquisition module, used to acquire navigation OD data of all users using the target navigation map, generate a hospital range according to the isolation zone and the entrance and exit information, and perform an overlay analysis based on the navigation OD data and the hospital range to obtain a hospital visit itinerary; A network construction module, used to construct a population-hospital two-model network according to the hospital visit itinerary, and to generate sub-networks of different scales in the population-hospital two-model network by using an aggregation method; The service evaluation module is used to construct cross-city supply and demand characteristics at the city scale, cross-city demand characteristics at the street scale, and cross-city supply characteristics at the hospital scale based on sub-networks of different scales, and output the evaluation results of the multi-scale supply and demand characteristics of medical services.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a multi-scale analysis program based on navigation data's medical service supply and demand characteristics, which is stored in the memory and can be run on the processor. When the multi-scale analysis program based on navigation data's medical service supply and demand characteristics is executed by the processor, the steps of the multi-scale analysis method based on navigation data's medical service supply and demand characteristics are implemented as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a multi-scale analysis program for medical service supply and demand characteristics based on navigation data, and when the multi-scale analysis program for medical service supply and demand characteristics based on navigation data is executed by a processor, the steps of the multi-scale analysis method for medical service supply and demand characteristics based on navigation data as described in any one of claims 1-7 are implemented.

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