Method and device for measuring resident travel time to hospital based on grid map

Abstract

The application provides a resident medical treatment travel time calculation method and device based on a grid map, comprising the following steps: creating a time cost grid map of an area to be analyzed; obtaining location information of medical service institutions in the area to be analyzed, performing geographic coding to make the location information have latitude and longitude information, superimposing the location information on the time cost grid map, and forming a medical service institution spatial distribution data set; according to the time cost grid map and the medical service institution spatial distribution, using a minimum cost method to draw a medical service institution travel time map; and according to the medical service institution travel time map, obtaining a medical treatment travel time of each residential area in the area to be analyzed. The application can provide a reference for calculating the time of residents in different regions to different types of medical institutions, provide a basis for effectively formulating medical resource allocation policies, and increase the population coverage under different time thresholds.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical data processing, and particularly relates to a resident medical travel time calculation method and device based on a grid map. BACKGROUND

[0002] The medical system has gradually improved through the reform of the health system and the improvement of medical quality. Therefore, in the past decade, the overall public health level of people has been significantly improved. In addition, people's life expectancy has been extended due to the more affordable and better quality medical care. However, despite these commendable achievements, distance and time are important obstacles to people's access to medical care. People need to spend a long time to go to medical institutions when they are sick and seek medical care. Generally speaking, due to the underdeveloped economy and the unfavorable geographical location, rural and remote areas are at a disadvantage in the distribution of medical resources. However, in densely populated cities, due to the lack of sufficient health infrastructure in some areas, the cost of medical facilities will also be high, which brings challenges to improve the community health life. This technology helps to determine the scattered or clustered distribution of medical resources, which makes it possible to strengthen the effective allocation of medical resources and achieve sustainable development goals.

[0003] Therefore, the current calculation method of the resident medical travel time still needs to be improved. SUMMARY

[0004] Therefore, the present application provides a resident medical travel time calculation method based on a grid map, a device and a readable storage medium, which solves the problem of calculating the time of residents in different areas to different types of medical institutions.

[0005] The technical scheme of the present application is as follows:

[0006] On the one hand, the present application provides a resident medical travel time calculation method based on a grid map, comprising:

[0007] creating a time cost grid map of the area to be analyzed;

[0008] obtaining the location information of the medical service institutions in the area to be analyzed, geocoding the location information to have latitude and longitude information, and then superimposing the time cost grid map to form a medical service institution spatial distribution data set;

[0009] According to the time cost grid map and the spatial distribution of medical service institutions, a medical service institution travel time map is drawn by using the minimum cost method;

[0010] According to the medical service institution travel time map, the medical travel time of each resident point in the area to be analyzed is obtained.

[0011] Further, the cost grid map creation includes the following steps:

[0012] Determine the region to be analyzed, collect the road network, railway, land use, water area and terrain basic geographic information data of the region to be analyzed;

[0013] Based on the basic geographic information data of the region to be analyzed, the speed of different types of data is assigned, and the geographic information data set with speed attribute is composed;

[0014] According to the geographic information data set with speed attribute, the rasterization processing is carried out, and the unit grid driving speed data set is composed;

[0015] According to the unit grid driving speed data set, the resistance factor of the unit grid is calculated, the resistance factor is multiplied by the driving speed of the unit grid, and the driving speed of the unit grid is corrected.

[0016] Further preferably, the resistance factor calculation formula is as follows:

[0017] F=6e -3.5|tan(0.01745×slopeangle)+0.05| / 5.0

[0018] Wherein, F is the resistance factor, slopeangle is the slope value, the size of the slope is extracted according to the terrain, the resistance factor of each unit grid is calculated, and each grid resistance factor is multiplied by the corresponding grid speed to form the corrected unit grid driving speed data set.

[0019] According to the corrected unit grid driving speed data set, the time cost calculation formula is used to create the unit time cost grid map.

[0020] Further preferably, according to the time cost calculation formula:

[0021]

[0022] Wherein, Cost is the time cost; v is the corrected unit grid driving speed.

[0023] Further, the position information of the medical service institutions in the region to be analyzed is obtained, and the geographic coding is carried out to have the latitude and longitude information, which is superimposed with the time cost grid map to form the medical service institution spatial distribution data set, including the following steps:

[0024] Obtain the address position information of the medical service institutions in the region to be analyzed;

[0025] According to the address position information of the medical service institutions in the region to be analyzed, the address position is converted to latitude and longitude information by using geographic coding;

[0026] According to the longitude and latitude information of the medical service institutions in the region to be analyzed, the time cost grid map is overlaid to form a medical service institution spatial distribution data set.

[0027] Further, according to the time cost grid map and the medical service institution spatial distribution, a medical service institution travel time map is drawn by using the minimum cost method, including the following steps:

[0028] According to the unit time cost grid map, the medical service institution is taken as a starting position, and the minimum time cost of each grid to the starting position is identified.

[0029] The position of the minimum time cost on the time cost grid map is marked, and the minimum cumulative travel time cost of all grids to the nearest medical institution is iteratively calculated. The iteration result is the medical service institution travel time map.

[0030] Further, the minimum cumulative travel time cost of all grids to the nearest medical institution is calculated in the following manner:

[0031] T 旅行 =T 起始 +T 计算 ,

[0032] wherein T 起始 is the minimum time cost on the time cost grid map, and T 计算 is the minimum cumulative travel time cost required by other adjacent grids to the starting position.

[0033] The calculation manner of T 起始 is as follows:

[0034] T 起始 =a×(1+b),

[0035] wherein a is the minimum cumulative time cost, and b is the resistance ratio.

[0036] The calculation manner of T 计算 is as follows:

[0037] T 计算 =(a2×c2)+(a3×c3) / 2×d×e×f

[0038] wherein a2 and a3 are the time costs of adjacent pixels other than the starting point, c2 and c3 are the horizontal direction coefficients of adjacent pixels other than the starting point, d is the horizontal distance of adjacent pixels other than the starting point, e is the vertical coefficient of adjacent pixels other than the starting point, and f is the cost multiplier.

[0039] Further preferably, the calculation manner of the starting time cost a is as follows:

[0040] a=(a1+a2) / 2×f

[0041] wherein a1 is the minimum cumulative time cost.

[0042] Further, according to the medical service institution travel time map, the travel time of each resident point in the to-be-analyzed region to a hospital is obtained, including the following steps:

[0043] Obtaining spatial distribution data of the resident points in the to-be-analyzed region;

[0044] According to the medical service institution travel time map, the resident points in the to-be-analyzed region are superimposed on the medical service institution travel time map, and a multi-value extraction point tool is used to obtain the travel time of each resident to a hospital. In a second aspect, the present application also provides a resident travel time to a hospital based on a grid map, which is run through the resident travel time to a hospital based on a grid map in the first aspect, and includes:

[0045] A creating module is configured to create a cost grid map of the to-be-analyzed region;

[0046] An obtaining module is configured to obtain road network, railway, land use, water area and terrain data; and obtain medical institution spatial distribution data set;

[0047] A processing module is configured to combine the medical institution spatial distribution data and the cost grid map, and use a minimum cost method to draw a medical service institution travel time map;

[0048] An analyzing module is configured to obtain the travel time of each resident point in the to-be-analyzed region to a hospital according to the position of the resident point on the travel time map.

[0049] In a third aspect, the present application provides a computing device, including: one or more processors;

[0050] A storage device is configured to store one or more programs, when the one or more programs are executed by the one or more processors, so that the one or more processors implement the resident travel time to a hospital based on a grid map in the first aspect.

[0051] The resident travel time to a hospital based on a grid map of the present application has the following beneficial effects compared with the prior art:

[0052] By providing a resident travel time to a hospital based on a grid map, the calculation of the travel time of residents in different regions to different types of medical institutions can provide a reference for the effective medical resource allocation policy. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0054] Figure 1 The flow chart of the resident medical travel time calculation method based on the grid map provided for Embodiment 1 of the present application is shown in the figure.

[0055] Figure 2 The device diagram of the resident medical travel time calculation device based on the grid map provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0057] Those skilled in the art can understand that, unless otherwise defined, all the terms (including technical terms and scientific terms) used herein have the same meaning as the general understanding of those skilled in the art to which the present application belongs. It should also be understood that, such as those defined in the general dictionary, should be understood as having the same meaning as in the context of the prior art, and unless specifically defined as here, should not be interpreted as idealized or overly formal.

[0058] The technical solutions will be further described by the description of the embodiments in combination with the specific embodiments.

[0059] The present embodiment proposes a resident medical travel time calculation method based on a grid map, as shown in the figure, the method comprises the following steps: Figure 1

[0060] Step 11, selecting a to-be-analyzed area where the resident medical travel time needs to be calculated, creating a to-be-analyzed area time cost grid map;

[0061] Step 12, obtaining the location information of the medical service institutions in the to-be-analyzed area, performing geographic coding to make the location information have latitude and longitude information, and then superimposing with the time cost grid map to form a medical service institution spatial distribution data set;

[0062] ​Step 13, according to the time cost grid map and the spatial distribution of medical service institutions, a medical service institution travel time map is drawn by using the minimum cost method;

[0063] Step 14, according to the medical service institution travel time map, the travel time of each residential point in the region to be analyzed is obtained.

[0064] In the preferred embodiment, in the above step 11, the basic geographic information data of the region to be analyzed can be obtained by satellite remote sensing and the like, and the time cost grid refers to the time cost paid by each grid. In the above step 12, the spatial distribution data set of medical institutions in the region to be analyzed can be obtained by public medical information websites, questionnaire surveys and the like, and the detailed address information of medical institutions is geocoded to obtain the spatial distribution of medical institutions in the region to be analyzed, which is helpful to provide a data basis for subsequent evaluation. Further, by using step 13, a medical service institution travel time map can be formed. In the above step 14, according to the medical service institution travel time map of step 13, the travel time of each residential point in the region to be analyzed is obtained.

[0065] In the preferred embodiment, the step 11 further includes:

[0066] Step 111, the region to be analyzed is determined, and the road network, railway, land use, water area and terrain basic geographic information data of the region to be analyzed are collected;

[0067] Step 112, based on the basic geographic information data of the region to be analyzed, the driving speeds of different types of data are set to form a geographic information data set with speed attributes;

[0068] Step 113, according to the geographic information data set with speed attributes, a rasterization process is performed to form a driving speed data set of unit grids;

[0069] Specifically, according to the geographic information data set with speed attributes, a driving speed data set of 1km×1km unit grids is formed by using a raster embedding tool in GIS;

[0070] Step 114, according to the 1km×1km grid driving speed data set, the resistance factor of each unit grid is calculated, which is multiplied by the driving speed of each grid to correct the grid driving speed. The speed resistance factor calculation formula is:

[0071] F=6e -3.5|tan(0.01745×slopeangle)+0.05| / 5.0

[0072] Wherein, F is the resistance factor, slopeangle is the slope value, the resistance factor of each 1km*1km grid is obtained, and each grid resistance factor is multiplied by the corresponding grid speed by using the grid calculator in the GIS platform to form the corrected 1km*1km grid driving speed data set.

[0073] Step 115, the time cost grid map is obtained by using the cost calculation formula.

[0074]

[0075] In the formula, Cost is the travel time cost; and v is the driving speed of each grid after correction.

[0076] In the preferred embodiment, the driving speed setting and data source are the road network and railway speed, which need to refer to the Chinese Urban Road Traffic Facilities Design Specification (CJJ 37-2012) and the Chinese High-speed Railway Design Specification (TB10621-2014) for setting, and the land use and water area speed are set according to the commonly used standards. The reference for setting the time cost value is the average travel time of 1km. The specific data source and speed setting are shown in Table 1.

[0077] Table 1: Speed setting and source of road network, railway, land use, water area and terrain

[0078]

[0079]

[0080] In the preferred embodiment, the step 12 further comprises:

[0081] Step 121, obtaining the address position information of medical service institutions in the region to be analyzed

[0082] Step 123, according to the address position information of the medical service institutions, converting the address position into data with latitude and longitude attributes by using geographic coding;

[0083] Step 124, according to the medical service institution data with latitude and longitude attributes, superimposing the time cost grid map in the GIS platform to form the medical service institution spatial distribution data set of the region to be analyzed.

[0084] In the preferred embodiment, the medical service institution position in the region to be analyzed needs to be collected, and the spatial distribution characteristics of the medical institutions in the region can be obtained after completing the geographic coding.

[0085] In the preferred embodiment, the step 13 further comprises:

[0086] Step 131, converting the medical service institution spatial distribution dataset into a grid on the vector-to-grid tool of the GIS platform, the size of the grid being consistent with the size of the time cost grid, i.e. 1 km x 1 km.

[0087] Step 132, according to the 1 km x 1 km time cost grid map, taking the medical service institution as the starting position, identifying the minimum time cost of each grid to the starting position by using the GIS cost distance tool.

[0088] Step 133, according to the minimum time cost, marking the position on the time cost grid map, iteratively calculating the minimum cumulative travel time cost of all grids to the nearest medical institution, and the iterative calculation result is the medical service institution travel time map.

[0089] In the preferred embodiment, the calculation method of the minimum cumulative travel time cost of all grids to the nearest medical institution is as follows:

[0090] T 旅行 = T 起始 + T 计算

[0091] wherein T 起始 is the minimum time cost of the starting position, and T 计算 is the time cost required by other adjacent grids to the starting position.

[0092] The calculation method of T 起始 is as follows:

[0093] T 起始 = a x (1 + b),

[0094] wherein a is the minimum time cost, and b is the resistance ratio.

[0095] The calculation method of T 计算 is as follows:

[0096] T 计算 = (a2 x c2) + (a3 x c3) / 2 x d x e x f

[0097] wherein a2 and a3 are the time costs of the adjacent pixels other than the starting point, c2 and c3 are the horizontal direction coefficients of the adjacent pixels other than the starting point, d is the horizontal distance of the adjacent pixels other than the starting point, e is the vertical coefficient of the adjacent pixels other than the starting point, and f is the cost multiplier.

[0098] Further preferably, the calculation method of the starting time cost a is as follows:

[0099] a = (a1 + a2) / 2 x f

[0100] wherein a1 is the minimum cumulative time cost.

[0101] In a preferred embodiment, the step 14 further comprises:

[0102] Step 141, obtaining spatial distribution data of residential areas in the region to be analyzed;

[0103] Step 142, superimposing the residential areas in the region to be analyzed on the travel time map of medical service institutions, and using the GIS extraction value to point tool to obtain the medical travel time of each resident.

[0104] In this embodiment, the residential area data of the region to be analyzed is collected, and the medical travel time of each residential area is obtained by GIS extraction value to point according to the position of the residential area on the travel time map of medical service institutions.

[0105] In this embodiment, the present application can provide a reference for the calculation of the time of residents in different regions to different types of medical institutions, and can also provide a basis for the effective medical resource allocation policy making to increase the population coverage under different time thresholds.

[0106] As shown in Figure 2 the embodiment also provides a resident medical travel time measuring device 20 based on a grid map, comprising:

[0107] A creating module 21 is configured to create a cost grid map of the region to be analyzed;

[0108] An obtaining module 22 is configured to obtain road network, railway, land use, water area and terrain data, and obtain medical institution spatial distribution data set;

[0109] A processing module 23 is configured to combine the medical institution spatial distribution data and the cost grid map, and draw a medical institution travel time map by using the minimum cost method;

[0110] An analysis module 24 is configured to obtain the medical time of each residential area in the region to be analyzed according to the position of the residential area on the travel time map.

[0111] In a preferred embodiment, the creating of the time cost grid map of the region to be analyzed comprises:

[0112] Determining the region to be analyzed, collecting the road network, railway, land use, water area and terrain basic geographic information data of the region;

[0113] Based on the basic geographic information data of the region to be analyzed, the driving speed of different types of data is assigned to form a geographic information data set with speed attribute;

[0114] According to the geographical information data set with the driving speed attribute, rasterization processing is performed to form a 1km*1km grid driving speed data set;

[0115] According to the 1km*1km grid driving speed data set, a resistance factor of each unit grid is calculated, which is multiplied by the driving speed of each grid to correct the grid driving speed.

[0116] Optionally, the resistance factor calculation formula is as follows:

[0117] F=6e -3.5|tan(0.01745×slopeangle)+0.05| / 5.0

[0118] Wherein, F is the resistance factor, slopeangle is the slope value, the size of the slope is extracted according to the terrain, the resistance factor of each unit grid is calculated, and the resistance factor of each grid is multiplied by the corresponding grid speed by using the grid calculator in GIS to form the corrected 1km*1km grid driving speed data set;

[0119] According to the corrected 1km*1km grid driving speed data set, a time cost calculation formula is used to create a 1km*1km time cost grid map.

[0120] Optionally, the time cost calculation formula is as follows:

[0121]

[0122] Wherein, Cost is the time cost; v is the corrected driving speed of each grid.

[0123] In a preferred embodiment, the position information of the medical service institutions in the region to be analyzed is obtained, and the geographic coding is performed to have the latitude and longitude information, which is superimposed with the time cost grid map to form a medical service institution spatial distribution data set, including the following steps:

[0124] The address position information of the medical service institutions in the region to be analyzed is obtained;

[0125] According to the address position information of the medical service institutions in the region to be analyzed, the address position is converted to latitude and longitude information by using geographic coding;

[0126] According to the latitude and longitude information of the medical service institutions in the region to be analyzed, the cost grid map is superimposed on the GIS platform to form a medical service institution spatial distribution data set of the region to be analyzed.

[0127] In a preferred embodiment, according to the cost grid map and the spatial distribution of medical service institutions, a medical service institution travel time map is drawn by using the minimum cost method, including the following steps:

[0128] According to the 1km*1km cost grid map, taking the medical service institution as the starting position, the minimum time cost of each grid to the starting position is identified by using the GIS cost distance tool.

[0129] According to the minimum time cost, the position of each grid on the time cost grid map is marked, and the minimum cumulative travel time cost of all grids to the nearest medical service institution is iteratively calculated, and the iterative calculation result is the medical service institution travel time map.

[0130] Optionally, the minimum cumulative travel time cost of all grids to the nearest medical service institution is calculated in the following manner:

[0131] T 旅行 =T 起始 +T 计算

[0132] Wherein, T 起始 is the minimum time cost on the time cost grid map, and T 计算 is the minimum cumulative travel time cost required by other adjacent grids to the starting position.

[0133] Optionally, the calculation manner of T 起始 is as follows:

[0134] T 起始 =a×(1+b)

[0135] Wherein a is the minimum time cost, and b is the resistance ratio.

[0136] Optionally, the calculation manner of T 计算 is as follows:

[0137] T 计算 =(a2×c2)+(a3×c3) / 2×d×e×f

[0138] Wherein, a2 and a3 are the time costs of adjacent pixels except the starting point, c2 and c3 are the horizontal direction coefficients of adjacent pixels except the starting point, d is the horizontal distance of adjacent pixels except the starting point, e is the vertical coefficient of adjacent pixels except the starting point, and f is the cost multiplier.

[0139] Optionally, the calculation manner of the starting time cost a is as follows:

[0140] a=(a1+a2) / 2×f

[0141] Wherein, a1 is the minimum cumulative time cost.

[0142] In a preferred embodiment, according to the medical service institution travel time map, the travel time of each resident point in the region to be analyzed is obtained. The method comprises the following steps:

[0143] Obtain the spatial distribution data of the residential area in the region to be analyzed;

[0144] According to the medical service institution travel time map, the residential area in the region to be analyzed is superimposed with the medical service institution travel time map, and the travel time of each resident to a hospital is obtained by using the GIS value-to-point tool.

[0145] In a preferred embodiment, a computing device is also provided, comprising a processor, a memory storing a computer program, the computer program being executed by the processor to perform the method as described above. All implementation manners in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0146] In a preferred embodiment, a computer readable storage medium is also provided, storing instructions, when the instructions are executed on a computer, causing the computer to perform the method as described above. All implementation manners in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0147] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0148] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0149] In the embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. The division of the units is only a logical function division. There can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between the units can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0150] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0151] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0152] If the functions are realized in the form of software functional units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk, and various program code storage media.

[0153] In addition, it should be noted that in the device and method of the present application, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombination should be regarded as equivalent solutions of the present application. Moreover, the steps of executing the above series of processes can naturally be executed in time sequence according to the order of description, but do not necessarily have to be executed in time sequence, and some steps can be executed in parallel or independently of each other. It can be understood by those skilled in the art that all or any steps or components of the method and device of the present application can be realized in hardware, firmware, software or their combination in any computing device (including processor, storage medium, etc.) or network of computing devices, which can be realized by those skilled in the art using their basic programming skills after reading the description of the present application.

[0154] Therefore, the object of the present application can also be achieved by running a program or a set of programs on any computing device. The computing device can be a commonly known general purpose device. Therefore, the object of the present application can also be achieved by providing only a program product containing program code implementing the method or device. That is, such a program product also constitutes the present application, and a storage medium storing such a program product also constitutes the present application. Obviously, the storage medium can be any commonly known storage medium or any storage medium developed in the future. It is also pointed out that in the device and method of the present application, obviously, the components or steps can be decomposed and / or recombined. These decompositions and / or recombination should be considered as equivalent solutions of the present application. Moreover, the steps of performing the above series of processes can naturally be executed in time sequence according to the order of description, but do not necessarily have to be executed in time sequence. Some steps can be executed in parallel or independently of each other.

[0155] In summary, the present application proposes a resident medical travel time calculation method based on grid map, creates a time cost grid map of the area to be analyzed; obtains the location information of medical service institutions in the area to be analyzed, and performs geographic coding to make it have latitude and longitude information, superimposes it with the time cost grid map, and forms a medical service institution spatial distribution data set; according to the cost grid map and the spatial distribution of medical service institutions, a medical service institution travel time map is drawn by using the minimum cost method; according to the medical service institution travel time map, the medical travel time of each residential point in the area to be analyzed is obtained, which can provide a reference for the calculation of the time of residents in different areas to different types of medical institutions, and provide a basis for effective medical resource allocation policy making.

[0156] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for calculating residents' travel time to medical care based on a grid map, characterized in that, Includes the following steps: Create a time cost raster map of the area to be analyzed; The location information of medical service institutions in the area to be analyzed is obtained, and geocoding is performed to give the location information latitude and longitude information. Then, it is overlaid with the time cost raster map to form a spatial distribution dataset of medical service institutions. Based on the time cost grid map and the spatial distribution of medical service institutions, a travel time map of medical service institutions is drawn using the minimum cost method. Based on the travel time map of medical service institutions, obtain the medical travel time for each residential point in the area to be analyzed; Create a time cost raster map of the area to be analyzed, including: Determine the area to be analyzed and collect basic geographic information data on the road network, railways, land use, water areas and topography of the area to be analyzed. Based on the basic geographic information data of the area to be analyzed, driving speed values ​​are assigned to different types of data to form a geographic information dataset with speed attributes. Based on the geographic information dataset with speed attributes, a rasterization process is performed to form a driving speed dataset with cell grids. Based on the driving speed dataset of the cell grid, the drag factor of the cell grid is calculated, and the drag factor is multiplied by the driving speed of the cell grid to correct the driving speed of the cell grid. Based on the corrected driving speed dataset of the cell grid, a cell time cost raster map is created using the time cost calculation formula. The formula for calculating the drag factor is as follows: in, F As a resistance factor, slopeangle The slope value is extracted based on the terrain. The drag factor of each cell grid is calculated, and the drag factor of each cell grid is multiplied by the corresponding cell speed to form the corrected cell grid driving speed dataset. Based on the time cost raster map and the spatial distribution of healthcare service providers, a travel time map for healthcare service providers is created using the minimum cost method, including the following steps: Based on the aforementioned time cost grid map, with the medical service institution as the starting location, the minimum time cost from each grid to the starting location is identified. Mark the position of the minimum time cost on the time cost grid map, iteratively calculate the minimum cumulative travel time cost from all grids to the nearest medical service institution, and the iterative calculation result is the medical service institution travel time map; The minimum cumulative travel time cost from all grids to the nearest medical facility is calculated as follows: T 旅行 =T 起始 +T 计算 Where T 起始 T represents the minimum time cost on the time cost raster map. 计算 The minimum cumulative travel time cost required for other adjacent grid cells to reach the starting position.

2. The method for calculating residents' medical travel time based on grid maps as described in claim 1, characterized in that, The formula for calculating the time cost is as follows: in, Cost For time cost; v The corrected cell grid travel speed.

3. The method for calculating residents' medical travel time based on grid maps as described in claim 1, characterized in that, The process of obtaining location information of medical service institutions in the area to be analyzed, geocoding them to include latitude and longitude information, and overlaying them with the time cost raster map to form a spatial distribution dataset of medical service institutions includes the following steps: Obtain the address and location information of medical service institutions in the area to be analyzed; Based on the address and location information of medical service institutions in the area to be analyzed, the address and location are converted into latitude and longitude information using geocoding. Based on the latitude and longitude information of medical service institutions within the analysis area, and overlaid with the time cost raster map, a spatial distribution dataset of medical service institutions in the area to be analyzed is formed.

4. The method for calculating residents' medical travel time based on grid maps as described in claim 1, characterized in that, Based on the travel time map of medical service institutions, obtain the travel time for medical treatment for each residential point in the area to be analyzed, including the following steps: Obtain spatial distribution data of settlements within the area to be analyzed; Based on the travel time map of medical service institutions, the residential points in the area to be analyzed are overlaid with the travel time map of medical service institutions. Using a multi-value extraction point tool, the travel time of each resident to seek medical treatment is obtained.

5. A device for calculating residents' travel time to medical care based on a grid map, characterized in that, The method for calculating residents' medical travel time based on grid maps as described in any one of claims 1-4 is operated as follows: Create a module to create a cost raster map of the area to be analyzed; The acquisition module is used to acquire road network, railway, land use, water area and topography data; and to acquire spatial distribution datasets of medical service institutions. The processing module is used to combine spatial distribution data of medical service institutions with cost grid maps and use the minimum cost method to draw travel time maps of medical service institutions. The analysis module is used to obtain the medical treatment time for each residential point within the area to be analyzed, based on the location of the residential point on the travel time map.

6. A computing device, characterized in that, include: One or more processors; And a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method for calculating residents' medical travel time based on a grid map as described in any one of claims 1-4.

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