Hospital grade evaluation statistical index monitoring and early warning method and system and storage medium

Abstract

The invention discloses a hospital grade evaluation statistical index monitoring and early warning method and system and a storage medium. The method comprises the steps of obtaining a preset index system; when an index evaluation request of a target person is detected, determining a target evaluation result corresponding to the target person according to a preset index system; judging that the target evaluation result belongs to a first-class result, a second-class result or a third-class result; when it is judged that the target evaluation result belongs to the first-class result, a preliminary early warning template corresponding to the first-class result is obtained; generating a preliminary early warning report according to the target evaluation result in combination with the preliminary early warning template; determining an abnormal item coefficient set according to the target evaluation result when the target evaluation result is judged to belong to the second-class result; generating a warning report according to the abnormal item coefficient set; the problem of monitoring and early warning of statistical indexes of a complex index system in a hospital grade review environment is solved. There is no need to set a monitoring threshold for each index. And the risk index can be found.

Description

Technical Field

[0001] The present application relates to the field of monitoring and early warning of statistical indicators for hospital grade assessment, and in particular to a method, system and storage medium for monitoring and early warning of statistical indicators for hospital grade assessment. Background Art

[0002] In the tertiary hospital grade review, hospital data statistical evaluation and management, the existing technology is mainly based on set thresholds for monitoring and early warning. The basic principle is to set the monitoring thresholds in advance every year, quarter, and month, and give early warning information when there is a deviation from the threshold. 2. Main problems: a) There are currently a large number of indicators in the grade assessment, with 1000-1200 indicators. In practice, it is impossible to set thresholds for each indicator on an annual, quarterly, or monthly basis. b) Hospitals are required to have a continuous monitoring and analysis process for relevant indicators, so there needs to be a set of methods to quickly identify potential risk indicators and issue early warnings.

[0003] Therefore, how to monitor and warn of statistical indicators of complex indicator systems in the hospital grading evaluation environment has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] In order to solve the problem of monitoring and early warning of statistical indicators of a complex indicator system in a hospital grade evaluation environment, the present application provides a hospital grade assessment statistical indicator monitoring and early warning method, system and storage medium.

[0005] In the first aspect, the present application provides a hospital grade assessment statistical indicator monitoring and early warning method using the following technical solutions: A hospital grade assessment statistical indicator monitoring and early warning method, comprising: Get the preset indicator system; When an indicator evaluation request of a target person is detected, determining a target evaluation result corresponding to the target person according to the preset indicator system; Determine whether the target evaluation result belongs to the first category, the second category or the third category; When it is determined that the target evaluation result belongs to the first type of result, obtaining a preliminary warning template corresponding to the first type of result; Generate a preliminary warning report based on the target evaluation results and the preliminary warning template; When it is determined that the target evaluation result belongs to the second type of result, determining a set of abnormal item coefficients according to the target evaluation result; Generate a warning report based on the abnormal item coefficient set; When it is determined that the target evaluation result belongs to the three categories of results, no warning operation is performed.

[0006] Optionally, before the step of obtaining the preset indicator system, the step further includes: Get the preset factor set; Obtaining the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency in the preset factor set; A preset indicator system is established according to the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency.

[0007] Optionally, when an indicator evaluation request of a target person is detected, the step of determining a target evaluation result corresponding to the target person according to the preset indicator system includes: When an indicator evaluation request of a target person is monitored, a determination tag set is determined according to the evaluation request; Determine whether the screening condition corresponding to the determination tag set meets the preset screening condition; If not, obtaining a screening range condition in the preset screening condition and updating the determination tag set according to the screening range condition; The current judgment tag set is obtained and combined with the preset indicator system to determine the target evaluation result corresponding to the target person.

[0008] Optionally, the step of obtaining a screening range condition in the preset screening condition and updating the determination tag set according to the screening range condition includes: Obtaining the screening range in the preset screening condition; Determine the screening category and the screening details corresponding to the screening category in the screening range; The determination tag set is updated according to the screening category and the screening criteria corresponding to the screening category.

[0009] Optionally, the step of determining whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result includes: Obtaining a warning safety value from the target evaluation result; Obtaining a preset warning interval, and determining, according to the warning safety value, the location information of the target evaluation result belonging to the preset warning interval; It is determined according to the location information whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result.

[0010] Optionally, the step of generating a preliminary warning report according to the target evaluation result in combination with the preliminary warning template includes: determining a target deviation value in the target evaluation result; Determining a deviation category set in the preset indicator system according to the target deviation value; A preliminary warning report is generated according to the deviation category set and the preliminary warning template.

[0011] Optionally, the step of determining a set of abnormal item coefficients according to the target evaluation result includes: Determine an abnormal alarm item according to the target evaluation result; Determining data trend information in the alarm exception item; A set of abnormal item coefficients is determined according to the data trend information.

[0012] In a second aspect, the present application provides a hospital grade assessment statistical indicator monitoring and early warning system, the hospital grade assessment statistical indicator monitoring and early warning system comprising: A preset indicator system module is used to obtain a preset indicator system; A target evaluation result module is used to determine the target evaluation result corresponding to the target person according to the preset indicator system when an indicator evaluation request of the target person is detected; A result determination module, used to determine whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result; A type of result module, used for obtaining a preliminary warning template corresponding to the type of result when it is determined that the target evaluation result belongs to the type of result; A preliminary warning report module, used to generate a preliminary warning report according to the target evaluation result and the preliminary warning template; A second-category result module, for determining an abnormal item coefficient set according to the target evaluation result when it is determined that the target evaluation result belongs to the second-category result; A warning report module, used to generate a warning report according to the abnormal item coefficient set; The three-category result module is used to not perform a warning operation when it is determined that the target evaluation result belongs to the three categories of results.

[0013] In a third aspect, the present application provides a computer device, comprising: a memory and a processor, wherein the processor executes any of the methods described above when running computer instructions stored in the memory.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute the method described above.

[0015] In summary, the present application includes the following beneficial technical effects: This application obtains a preset indicator system; when an indicator evaluation request of a target person is detected, the target evaluation result corresponding to the target person is determined according to the preset indicator system; it is determined that the target evaluation result belongs to a first-class result, a second-class result, or a third-class result; when it is determined that the target evaluation result belongs to a first-class result, a preliminary warning template corresponding to the first-class result is obtained; a preliminary warning report is generated based on the target evaluation result combined with the preliminary warning template; when it is determined that the target evaluation result belongs to a second-class result, a set of abnormal item coefficients is determined according to the target evaluation result; a warning report is generated based on the set of abnormal item coefficients; it solves the monitoring and early warning of statistical indicators of complex indicator systems in the hospital grade review environment. There is no need to set a monitoring threshold for each indicator. Risk indicators can be discovered. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application; Figure 2 This is a flow chart of the first embodiment of the hospital grade assessment statistical indicator monitoring and early warning method of the present application; Figure 3 It is a structural block diagram of the first embodiment of the hospital grade assessment statistical indicator monitoring and early warning system of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] Reference Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0019] like Figure 1As shown, the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0020] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0021] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a hospital grade assessment statistical indicator monitoring and early warning program.

[0022] exist Figure 1 In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the computer device of the present application can be set in the computer device, and the computer device calls the hospital grade assessment statistical indicator monitoring and early warning program stored in the memory 1005 through the processor 1001, and executes the hospital grade assessment statistical indicator monitoring and early warning method provided in the embodiment of the present application.

[0023] The present application embodiment provides a hospital grade assessment statistical indicator monitoring and early warning method, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the hospital grade assessment statistical indicator monitoring and early warning method of the present application.

[0024] In this embodiment, the hospital grade assessment statistical indicator monitoring and early warning method includes the following steps: Step S10: Obtain a preset indicator system.

[0025] It should be noted that the existing technology mainly monitors and warns based on set thresholds. The basic principle is to set monitoring thresholds in advance every year, quarter, and month, and give warning information when there is a deviation from the threshold. 2. Main problems: a) There are currently a large number of indicators in the rating, with 1,000-1,200 indicators. In practice, it is impossible to set thresholds for each indicator on an annual, quarterly, or monthly basis. b) Hospitals are required to have a continuous monitoring and analysis process for relevant indicators, so a set of methods is needed to quickly identify potential risk indicators and issue warnings.

[0026] Furthermore, in order to achieve the establishment of a preset indicator system, before the step of obtaining the preset indicator system, it also includes: obtaining a preset factor set; obtaining the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency in the preset factor set; establishing the preset indicator system according to the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency.

[0027] It should be noted that the construction of the indicator system includes the following elements: indicator name (unique identifier), unit, monitoring category, statistical frequency (annual, quarterly, monthly, daily), correlation coefficient (specifically refers to the number of times similar indicators appear in the indicator system), and statistical data of the indicator name at the statistical frequency.

[0028] Step S20: When an indicator evaluation request of a target person is detected, a target evaluation result corresponding to the target person is determined according to a preset indicator system.

[0029] In the specific implementation, for unit-statistical data identification, generally each unit has its own acceptable range of values, such as: percentages should be between 0% and 100%, the number of people should be an integer, and most units should not have negative numbers. For monitoring category-statistical data identification: generally, each indicator has a fixed monitoring method: continuous rise, continuous decline, and continuous monitoring. It is particularly noted that when three consecutive data do not meet the monitoring method, they are identified as abnormal. For threshold-statistical data monitoring: the default threshold is set to a deviation of the average value within three periods of less than 5% as normal. The monitoring and early warning formula is calculated to form an early warning evaluation value for each indicator with the correlation coefficient for unit-statistical data, monitoring category-statistical data, and threshold-statistical data, and the top 20% of the core indicators of concern are taken.

[0030] In a specific implementation, when an indicator evaluation request of a target person is detected, the target evaluation result corresponding to the target person is determined according to a preset indicator system by collecting the corresponding data of the target person and inputting it into a preset port, wherein the collected data can be imported from a database or manually input.

[0031] Furthermore, in order to improve the accuracy of determining the target evaluation results, when an indicator evaluation request of the target person is detected, the step of determining the target evaluation result corresponding to the target person according to the preset indicator system includes: when the indicator evaluation request of the target person is monitored, determining a judgment label set according to the evaluation request; judging whether the filtering conditions corresponding to the judgment label set meet the preset filtering conditions; if not, obtaining the filtering range conditions in the preset filtering conditions and updating the judgment label set according to the filtering range conditions; obtaining the current judgment label set and combining it with the preset indicator system to determine the target evaluation result corresponding to the target person.

[0032] It should be noted that the steps of obtaining the filtering range conditions in the preset filtering conditions and updating the judgment label set according to the filtering range conditions include: obtaining the filtering range in the preset filtering conditions; determining the filtering category and the filtering details corresponding to the filtering category in the filtering range; and updating the judgment label set according to the filtering category and the filtering details corresponding to the filtering category.

[0033] It is understandable that the purpose of updating the screening range is to solve the problem caused by a range that is too small or too large. Among them, a screening range that is too small will result in a small number of sample data and the selected data will not be referenceable, while a screening range that is too large will result in too much sample data, wasting computing resources and causing inaccurate results.

[0034] Step S30: Determine whether the target evaluation result belongs to the first category, the second category or the third category.

[0035] Furthermore, in order to realize the judgment of the classification of the target evaluation results, the steps of judging whether the target evaluation results belong to the first category, the second category or the third category include: obtaining a warning safety value in the target evaluation results; obtaining a preset warning interval, and determining the position information of the target evaluation results in the preset warning interval according to the warning safety value; judging whether the target evaluation results belong to the first category, the second category or the third category according to the position information.

[0036] In a specific implementation, positioning is performed in a preset warning interval according to the specific value of the warning safety value and the position information is obtained, and the position information can be used to determine the result classification.

[0037] Step S40: When it is determined that the target evaluation result belongs to a type of result, a preliminary warning template corresponding to the type of result is obtained.

[0038] It should be noted that the preliminary warning template in this embodiment relies on the calibration of the growth of indicators, classifies the growth range of specific indicators, monitors continuous growth or continuous decline, and issues a warning if the growth attribute does not match the load value corresponding to the hospital or fluctuates abnormally. Therefore, the preliminary warning template mainly provides preliminary warnings for data with hidden dangers.

[0039] Step S50: Generate a preliminary warning report based on the target evaluation results and the preliminary warning template.

[0040] Furthermore, in order to realize the generation of a preliminary warning report, the steps of generating a preliminary warning report based on the target evaluation results in combination with the preliminary warning template include: determining a target deviation value in the target evaluation results; determining a deviation category set in a preset indicator system based on the target deviation value; and generating a preliminary warning report based on the deviation category set and the preliminary warning template.

[0041] Step S60: When it is determined that the target evaluation result belongs to the second category result, a set of abnormal item coefficients is determined according to the target evaluation result.

[0042] Furthermore, in order to improve the accuracy of determining abnormal item coefficients, the step of determining a set of abnormal item coefficients based on target evaluation results includes: determining alarm abnormal items based on target evaluation results; determining data trend information in the alarm abnormal items; and determining a set of abnormal item coefficients based on the data trend information.

[0043] Step S70: Generate a warning report based on the abnormal item coefficient set.

[0044] Step S80: When it is determined that the target evaluation result belongs to the third category, no warning operation is performed.

[0045] This embodiment obtains a preset indicator system; when an indicator evaluation request of a target person is detected, the target evaluation result corresponding to the target person is determined according to the preset indicator system; it is determined that the target evaluation result belongs to a first-class result, a second-class result, or a third-class result; when it is determined that the target evaluation result belongs to a first-class result, a preliminary warning template corresponding to the first-class result is obtained; a preliminary warning report is generated according to the target evaluation result combined with the preliminary warning template; when it is determined that the target evaluation result belongs to a second-class result, an abnormal item coefficient set is determined according to the target evaluation result; a warning report is generated according to the abnormal item coefficient set; it solves the monitoring and early warning of statistical indicators of complex indicator systems in the hospital grade review environment. There is no need to set a monitoring threshold for each indicator. Risk indicators can be found.

[0046] In addition, an embodiment of the present application also proposes a computer-readable storage medium, on which is stored a program for monitoring and warning of statistical indicators for hospital grade assessment. When the program for monitoring and warning of statistical indicators for hospital grade assessment is executed by a processor, the steps of the method for monitoring and warning of statistical indicators for hospital grade assessment as described above are implemented.

[0047] Reference Figure 3 , Figure 3 This is a structural block diagram of the first embodiment of the hospital grade assessment statistical indicator monitoring and early warning system of this application.

[0048] like Figure 3 As shown, the hospital grade assessment statistical indicator monitoring and early warning system proposed in the embodiment of the present application includes: The preset indicator system module 10 is used to obtain the preset indicator system; The target evaluation result module 20 is used to determine the target evaluation result corresponding to the target person according to the preset indicator system when detecting the indicator evaluation request of the target person; A result determination module 30, for determining whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result; A type one result module 40 is used to obtain a preliminary warning template corresponding to the type one result when it is determined that the target evaluation result belongs to the type one result; A preliminary warning report module 50 is used to generate a preliminary warning report based on the target evaluation results and the preliminary warning template; The second-category result module 60 is used to determine the abnormal item coefficient set according to the target evaluation result when it is determined that the target evaluation result belongs to the second-category result; A warning report module 70, configured to generate a warning report according to the abnormal item coefficient set; The three-category result module 80 is used to not perform a warning operation when it is determined that the target evaluation result belongs to the third category result.

[0049] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present application. In specific applications, technicians in this field can make settings as needed, and the present application does not impose any limitation on this.

[0050] This embodiment obtains a preset indicator system; when an indicator evaluation request of a target person is detected, the target evaluation result corresponding to the target person is determined according to the preset indicator system; it is determined that the target evaluation result belongs to a first-class result, a second-class result, or a third-class result; when it is determined that the target evaluation result belongs to a first-class result, a preliminary warning template corresponding to the first-class result is obtained; a preliminary warning report is generated according to the target evaluation result combined with the preliminary warning template; when it is determined that the target evaluation result belongs to a second-class result, an abnormal item coefficient set is determined according to the target evaluation result; a warning report is generated according to the abnormal item coefficient set; it solves the monitoring and early warning of statistical indicators of complex indicator systems in the hospital grade review environment. There is no need to set a monitoring threshold for each indicator. Risk indicators can be found.

[0051] In one embodiment, the preset indicator system module 10 is also used to obtain a preset factor set; obtain the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name under the statistical frequency in the preset factor set; establish a preset indicator system based on the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name under the statistical frequency.

[0052] In one embodiment, the target evaluation result module 20 is also used to determine a judgment label set according to the evaluation request when an indicator evaluation request of a target person is monitored; determine whether the filtering conditions corresponding to the judgment label set meet the preset filtering conditions; if not, obtain the filtering range conditions in the preset filtering conditions and update the judgment label set according to the filtering range conditions; obtain the current judgment label set and combine it with the preset indicator system to determine the target evaluation result corresponding to the target person.

[0053] In one embodiment, the target evaluation result module 20 is also used to obtain the filtering range in the preset filtering conditions; determine the filtering category and the filtering details corresponding to the filtering category in the filtering range; and update the judgment label set according to the filtering category and the filtering details corresponding to the filtering category.

[0054] In one embodiment, the result determination module 30 is also used to obtain a warning safety value in the target evaluation result; obtain a preset warning interval, and determine the position information of the target evaluation result in the preset warning interval based on the warning safety value; and determine whether the target evaluation result belongs to a first-class result, a second-class result, or a third-class result based on the position information.

[0055] In one embodiment, the preliminary warning report module 50 is also used to determine the target deviation value in the target evaluation result; determine the deviation category set in the preset indicator system according to the target deviation value; and generate a preliminary warning report according to the deviation category set and the preliminary warning template.

[0056] In one embodiment, the second type result module 60 is further used to determine an alarm abnormal item according to the target evaluation result; determine data trend information in the alarm abnormal item; and determine an abnormal item coefficient set according to the data trend information.

[0057] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present application. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0058] In addition, for technical details not fully described in this embodiment, please refer to the method for monitoring and early warning of hospital grade assessment statistical indicators provided in any embodiment of the present application, which will not be repeated here.

[0059] In addition, 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 system 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 system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0060] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0061] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned implementation methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a disk, or an optical disk), including a number of instructions to enable a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0062] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A hospital grade assessment statistical indicator monitoring and early warning method, characterized in that: include: Get the preset indicator system; When an indicator evaluation request of a target person is detected, determining a target evaluation result corresponding to the target person according to the preset indicator system; Determine whether the target evaluation result belongs to the first category, the second category or the third category; When it is determined that the target evaluation result belongs to the first type of result, obtaining a preliminary warning template corresponding to the first type of result; Generate a preliminary warning report based on the target evaluation results and the preliminary warning template; When it is determined that the target evaluation result belongs to the second type of result, determining a set of abnormal item coefficients according to the target evaluation result; Generate a warning report based on the abnormal item coefficient set; When it is determined that the target evaluation result belongs to the three categories of results, no warning operation is performed.

2. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 1 is characterized in that: Before the step of obtaining the preset indicator system, the method further includes: Get the preset factor set; Obtaining the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency in the preset factor set; A preset indicator system is established according to the indicator name, unit, monitoring category, statistical frequency, correlation coefficient and statistical data of the indicator name at the statistical frequency.

3. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 1 is characterized in that: The step of determining the target evaluation result corresponding to the target person according to the preset indicator system when an indicator evaluation request of the target person is detected includes: When an indicator evaluation request of a target person is monitored, a determination tag set is determined according to the evaluation request; Determine whether the screening condition corresponding to the determination tag set meets the preset screening condition; If not, obtaining a screening range condition in the preset screening condition and updating the determination tag set according to the screening range condition; The current judgment tag set is obtained and combined with the preset indicator system to determine the target evaluation result corresponding to the target person.

4. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 3 is characterized in that: The step of obtaining a screening range condition in the preset screening condition and updating the determination tag set according to the screening range condition includes: Obtaining the screening range in the preset screening condition; Determine the screening category and the screening details corresponding to the screening category in the screening range; The determination tag set is updated according to the screening category and the screening criteria corresponding to the screening category.

5. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 1 is characterized in that: The step of determining whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result comprises: Obtaining a warning safety value from the target evaluation result; Obtaining a preset warning interval, and determining, according to the warning safety value, the location information of the target evaluation result belonging to the preset warning interval; It is determined according to the location information whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result.

6. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 1 is characterized in that: The step of generating a preliminary warning report according to the target evaluation result and the preliminary warning template comprises: determining a target deviation value in the target evaluation result; Determining a deviation category set in the preset indicator system according to the target deviation value; A preliminary warning report is generated according to the deviation category set and the preliminary warning template.

7. The hospital grade assessment statistical indicator monitoring and early warning method according to claim 1 is characterized in that: The step of determining a set of abnormal item coefficients according to the target evaluation result comprises: Determine an abnormal alarm item according to the target evaluation result; Determining data trend information in the alarm exception item; A set of abnormal item coefficients is determined according to the data trend information.

8. A hospital grade assessment statistical indicator monitoring and early warning system, characterized in that: The hospital grade assessment statistical indicator monitoring and early warning system includes: A preset indicator system module is used to obtain a preset indicator system; A target evaluation result module is used to determine the target evaluation result corresponding to the target person according to the preset indicator system when an indicator evaluation request of the target person is detected; A result determination module, used to determine whether the target evaluation result belongs to a first-category result, a second-category result, or a third-category result; A type of result module, used for obtaining a preliminary warning template corresponding to the type of result when it is determined that the target evaluation result belongs to the type of result; A preliminary warning report module, used to generate a preliminary warning report according to the target evaluation result and the preliminary warning template; A second-category result module, for determining an abnormal item coefficient set according to the target evaluation result when it is determined that the target evaluation result belongs to the second-category result; A warning report module, used to generate a warning report according to the abnormal item coefficient set; The three-category result module is used to not perform a warning operation when it is determined that the target evaluation result belongs to the three categories of results.

9. A computer device, characterized in that: The device comprises: a memory and a processor, and when the processor runs the computer instructions stored in the memory, the processor executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 7.

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