CN117409940A - Clinical data path generation method and system based on hospital clinical big data - Google Patents

Clinical data path generation method and system based on hospital clinical big data Download PDF

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CN117409940A
CN117409940A CN202311513023.8A CN202311513023A CN117409940A CN 117409940 A CN117409940 A CN 117409940A CN 202311513023 A CN202311513023 A CN 202311513023A CN 117409940 A CN117409940 A CN 117409940A
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data
diagnosis
coefficient
user
path
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范婷
龚兰娟
江季君
邓兴锋
刘其武
廖展云
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Gaozhou Peoples Hospital
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    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract

The invention discloses a clinical data path generation method and a clinical data path generation system based on hospital clinical big data, which relate to the technical field of medical service platforms, wherein after a diagnosis name and a diagnosis ID are input by a user, the user diagnosis data is obtained through a data processing module, then the user diagnosis data is calculated and judged through the data processing module to obtain whether the user diagnosis data meets the path generation requirement, if not, the data which specifically has problems in the user diagnosis data is positioned according to the judgment result, then the data which has problems is subjected to flow checking judgment, if yes, whether the path can be generated is judged by further analysis through a data analysis module, if not, the examination judgment can be carried out on the nursing data which has problems, if yes, the diagnosis path is generated, and the function of generating the path after carrying out multiple analysis processing on the data before diagnosis is realized.

Description

Clinical data path generation method and system based on hospital clinical big data
Technical Field
The invention relates to the technical field of medical service platforms, in particular to a clinical data path generation method and a clinical data path generation system based on clinical big data of a hospital.
Background
The clinical pathway was the standardized pattern of diagnosis and treatment proposed by the united states for quality and cost management of a single condition in the last 90 th century. The clinical path refers to a standardized workflow written in advance, which enables the arrangement of the sequence and time of critical treatment, examination, and nursing activities of a disease or treatment to be optimized as much as possible by professionals of various disciplines according to the principles of evidence-based medicine, so that most patients suffering from the disease or implementing the treatment can receive medical treatment and nursing from the hospital to the discharge according to the flow. At present, china is greatly promoting the implementation of clinical paths. However, due to the fact that the medical behaviors and the medical treatment activities related to the medical path are more, the symptoms of patients appearing in medical treatment are more complex, the coupling among multiple symptoms is stronger, the symptoms appear in the process of symptom promotion, and a diagnosis and treatment standardized mode of single symptom quality and cost management is difficult to form. If the fixed clinical path is hard, the disease is possibly repeated, the treatment process is hard, and the conditions of delay treatment, excessive medical treatment and the like are easy to occur.
At present, in hospitals at home and abroad, diagnosis and treatment schemes and diagnosis and treatment paths for providing diseases for users are analyzed and summarized, and are mainly treated by doctors manually. This approach may be applied to cases where disease characteristics are low and diagnostic protocols are simple. However, under the condition that the disease diagnosis nodes are more and the diagnosis scheme is complex, the existing process of processing and analyzing the used data of the diagnosis and treatment path is simpler, so that the generated diagnosis and treatment path is not in line with the use of a patient, and the medical experience of the patient is affected.
Disclosure of Invention
In order to solve the above-mentioned shortcomings in the background art, the present invention aims to provide a method and a system for generating a clinical data path based on clinical big data of a hospital.
The aim of the invention can be achieved by the following technical scheme: a clinical data path generation system based on hospital clinical big data, comprising:
and a user input module: the diagnosis system comprises a data processing module, a diagnosis module and a diagnosis module, wherein the data processing module is used for inputting diagnosis names and visit IDs by users and sending the diagnosis names input by the users to the data processing module for processing;
and a data processing module: the diagnosis system comprises a database, a user input diagnosis name, a diagnosis data acquisition module, a data analysis module, a diagnosis module, a data analysis module and a data analysis module, wherein the diagnosis name is input by the user and is subjected to discrimination matching with a medical data set stored in the database to obtain user diagnosis data, the user diagnosis data comprises diagnosis data, treatment data, medication data, inspection data and nursing data, the user diagnosis data is marked, a comprehensive diagnosis coefficient is calculated according to the marked diagnosis data, the treatment data and the medication data, the comprehensive diagnosis coefficient is used for carrying out difference calculation with the inspection data, the obtained difference is subjected to proportion judgment with a set difference threshold value, whether the user diagnosis data has a problem or not is analyzed according to a judgment result, if the user diagnosis data has the problem, the problem data with the problem is positioned according to the proportion, a problem signal of the problem data is sent to the execution module, and if the problem does not exist, the comprehensive diagnosis coefficient and the nursing data are sent to the data analysis module;
and a data analysis module: calculating a path judgment coefficient by utilizing the comprehensive diagnosis coefficient and the nursing data, setting a path generation judgment value, carrying out path judgment on the path judgment coefficient and the path generation judgment value to obtain a path generation coefficient, comparing the path generation coefficient with the path generation judgment value, judging whether the path generation requirement is met according to the comparison result, if not, sending a nursing problem signal to an execution module, and if so, sending a generation signal to the path generation module;
and a path generation module: the diagnosis and treatment path generation module is used for receiving the diagnosis and treatment ID sent by the user input module, and generating a path according to the user diagnosis and treatment data corresponding to the diagnosis and treatment ID after receiving the generation signal;
the execution module: the system comprises a data processing module, a data analysis module, a data processing module and a data analysis module, wherein the data processing module is used for receiving various problem signals, executing different operations according to the received various different problem signals, and sending a problem-free signal to the data processing module or the data analysis module after executing the operations;
database: for storing a medical data set.
Preferably, the data processing module performs matching searching in the medical data set according to the diagnosis type of the diagnosis name entered by the user, so as to obtain the diagnosis data of the user.
Preferably, the process of calculating the comprehensive diagnosis coefficient by the data processing module is as follows:
marking diagnosis data as Zi, treatment data as Si, medication data as Yi, inspection data as Ji and nursing data as Hi, wherein i is the number of input times of a user input module, and i=1, 2, 3, & gt, n and n are the total number of input times of the user input module;
using the formulaAnd calculating to obtain a comprehensive diagnosis coefficient Zi, wherein Z0 is a diagnosis influence coefficient, S0 is a treatment influence coefficient, Y0 is a medication influence coefficient, a is a diagnosis correlation coefficient, b is a treatment correlation coefficient, c is a medication correlation coefficient, a+bc=1, and alpha is a preset coefficient.
Preferably, the difference value is calculated by using the calculated comprehensive diagnosis coefficient and the test data, so as to obtain a difference value, which is marked as Czi, and the calculation formula is as follows: czi =k|zi-ji|, k is a preset factor, a difference threshold Cz0 is set, and the calculated difference Czi and the difference threshold Cz0 are subjected to proportion judgment, wherein the process is as follows:
if it isJudging that the user diagnosis data has no problem at the moment, and sending the comprehensive diagnosis coefficient and the nursing data to a data analysis module;
if it isDetermining that the user diagnosis data has a problem at the moment, locating the problem in the user diagnosis data as diagnosis data, and sending a diagnosis problem signal to the executionA module;
if it isJudging that the user treatment data has problems at the moment, locating that the problems in the user treatment data are treatment data, and sending a treatment problem signal to an execution module;
if it isAnd judging that the user diagnosis data has problems at the moment, locating that the user diagnosis data has problems as medication data, and sending medication problem signals to the execution module.
Preferably, the data analysis module utilizes a formulaCalculating a path judgment coefficient Li, wherein q 1 To comprehensively diagnose the correlation coefficient, q 2 And t is a preset proportionality coefficient for nursing related coefficient.
Preferably, the data analysis module sets a path generation determination value L, calculates using the calculated path determination coefficient Li and the path generation determination value L, and calculates the path generation determination value L by the formulaCalculating a path generation coefficient L0, wherein P1 and P2 are preset generation factors; comparing the path generation coefficient L0 with the path generation determination value L:
if L0 is more than or equal to L, judging that the path generation process meets the requirement, and sending a generation signal to a path generation module for path generation;
if L0 is less than L, judging that the path generation process does not meet the requirement at the moment, positioning the problem in the nursing data Hi, and sending a nursing problem signal to the execution module.
Preferably, the process of acquiring the medical data set by the database comprises the following steps:
acquiring medical related data by using a data acquisition unit in a database, wherein the medical related data comprises patient treatment data and patient ID;
and combining the patient treatment data with a patient ID mapping model to obtain corresponding medical related data, and integrating the medical related data to generate a medical data set, wherein the patient ID mapping model is trained based on an artificial intelligence model.
In a second aspect, in order to achieve the above object, the present invention discloses a clinical data path generating method based on clinical big data of a hospital, the method comprising the steps of:
receiving a diagnosis name and a diagnosis ID input by a user, and judging and matching the diagnosis name input by the user to obtain user diagnosis data, wherein the user diagnosis data comprises diagnosis data, treatment data, medication data, inspection data and nursing data;
marking the user diagnosis data, calculating to obtain a comprehensive diagnosis coefficient by using the marked user diagnosis data, calculating to obtain a difference value by using the comprehensive diagnosis coefficient and the checking data, performing proportion judgment on the difference value and a set difference value threshold value, analyzing whether the user diagnosis data has problems according to the judgment result, if so, positioning the corresponding data with the problems according to the proportion, and performing analysis and judgment on the corresponding flow according to the corresponding data;
if the problem does not exist, calculating a path judgment coefficient by using the comprehensive diagnosis coefficient and the nursing data, setting a path generation judgment value, and calculating a path generation coefficient by using the path judgment coefficient and the path generation judgment value;
and comparing the path generation coefficient with a path generation judgment value, judging whether the path generation requirement is met or not according to the comparison result, if the path generation coefficient is not met, judging that nursing data has problems, analyzing and judging a corresponding nursing flow, and if the path generation coefficient is met, generating a path according to the user diagnosis data corresponding to the diagnosis ID to obtain a diagnosis path.
The invention has the beneficial effects that:
according to the invention, after the diagnosis name and the diagnosis ID are input by a user, the user diagnosis data are obtained through the data processing module, then the data processing module is used for calculating and judging to obtain whether the user diagnosis data meet the path generation requirement, if not, the data with specific problems in the user diagnosis data are positioned according to the judging result, then the flow checking and judging are carried out on the data with problems, if yes, the data analysis module is used for further analyzing and judging whether the path can be generated, if not, the checking and judging are carried out on the nursing data with problems, if yes, the diagnosis path is generated, and the function of carrying out path generation after carrying out repeated analysis processing on the data before diagnosis is realized.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort;
FIG. 1 is a schematic diagram of a system architecture of the present invention;
FIG. 2 is a schematic flow chart of the method of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a clinical data path generation system based on clinical big data of a hospital, comprising:
the system comprises a user input module, a data processing module, a data analysis module, a path generation module, an execution module and a database;
the user input module is used for inputting a diagnosis name and a diagnosis ID by a user and sending the diagnosis name input by the user to the data processing module for processing;
it should be further explained that the diagnosis ID entered by the user input module is a mark representing the user when the user makes a diagnosis, and the diagnosis ID corresponds to the diagnosis name entered by the user one by one and is associated with the diagnosis name entered by the user, so that a later hospital can find a diagnosis path corresponding to the diagnosis name entered by the user after generation according to the diagnosis ID, thereby playing a role of convenient finding.
The data processing module is used for carrying out data processing after receiving the diagnosis name input by the user, and specifically, the processing process of the data processing module comprises the following steps:
judging and matching the diagnosis name input by the user according to the received diagnosis name input by the user to obtain user diagnosis data, wherein the user diagnosis data comprise diagnosis data, treatment data, medication data, inspection data and nursing data;
it should be further explained that, in the specific implementation process, the data processing module performs the discrimination matching on the diagnosis name input by the user through the medical data set stored in the database, and performs the matching search in the medical data set according to the diagnosis type to which the diagnosis name input by the user belongs, so as to obtain the diagnosis data of the user;
the application data includes various types of application, in this embodiment, taking an acute gastroenteritis patient as an example, according to the application name, the application data is divided into seven sets of norfloxacin, simida, quick-acting antidiarrheal capsule, gentamicin, compound berberine tablet, weichang kang and yanning;
marking the obtained user visit data, wherein the diagnosis data is marked as Zi, the treatment data is marked as Si, the medication data is marked as Yi, the inspection data is marked as Ji, and the nursing data is marked as Hi, wherein i is the number of times of input of a user input module, and i=1, 2, 3, & gt, n and n are the total number of times of input of the user input module;
calculating by using the marked user visit data:
using the formulaCalculating to obtain a comprehensive diagnosis coefficient Zi, wherein Z0 is a diagnosis influence coefficient, S0 is a treatment influence coefficient, Y0 is a medication influence coefficient, a is a diagnosis correlation coefficient, b is a treatment correlation coefficient, c is a medication correlation coefficient, a+bc=1, and alpha is a preset coefficient;
and (3) carrying out difference calculation by using the calculated comprehensive diagnosis coefficient and the test data to obtain a difference value, which is marked as Czi, and calculating the formula: czi =k|zi-ji|, k is a preset factor, a difference threshold Cz0 is set, the calculated difference Czi and the difference threshold Cz0 are subjected to proportional judgment, whether the user treatment data has a problem or not is analyzed according to the judgment result, so that a treatment path cannot be generated, if the user treatment data has the problem, the data with the problem is positioned according to the ratio, and in this embodiment, the specific judgment process comprises the following steps:
if it isJudging that the user diagnosis data has no problem at the moment, generating a diagnosis and treatment path, and sending the comprehensive diagnosis coefficient and the nursing data to a data analysis module for data analysis;
if it isJudging that the user diagnosis data has problems at the moment, locating that the problems in the user diagnosis data are diagnosis data, sending a diagnosis problem signal to an execution module, and checking the diagnosis flow by the execution module;
if it isJudging that the user treatment data has problems at the moment, locating that the problems in the user treatment data are treatment data, sending a treatment problem signal to an execution module, and checking the treatment flow by the execution module;
if it isJudging that the user treatment data has problems at the moment, locating that the problems in the user treatment data are medication data, sending medication problem signals to an execution module, and performing problem investigation on medication types by the execution module;
the data analysis module performs data analysis after receiving the comprehensive diagnosis coefficient Zi and the nursing data Hi sent by the data processing module, and specifically, the analysis process of the data analysis module comprises the following steps:
based on the integrated diagnostic factor Zi and the care data Hi;
using the formulaCalculating a path judgment coefficient Li, wherein q 1 To comprehensively diagnose the correlation coefficient, q 2 T is a preset proportional coefficient for nursing related coefficients;
setting a path generation determination value L, calculating by using the calculated path determination coefficient Li and the path generation determination value L, and determining whether the requirement of generating the path is met according to the calculation result, wherein the process of calculating and determining according to the calculation result comprises the following steps:
the path judgment coefficient Li and the path generation judgment value L are utilized to pass through a formulaCalculating a path generation coefficient L0, wherein P1 and P2 are preset generation factors;
the calculated path generation coefficient L0 is judged, the path generation coefficient L0 is compared with a path generation judgment value L, and whether the generated path requirement is met is judged according to the comparison result:
if L0 is more than or equal to L, judging that the path generation process meets the requirement at the moment, and sending a generation signal to a path generation module by a data analysis module to generate a path;
if L0 is less than L, judging that the path generation process does not meet the requirement at the moment, positioning the problem in the nursing data Hi, sending a nursing problem signal to an execution module, and checking the problem in the nursing process by the execution module;
the path generation module is used for receiving the diagnosis ID sent by the user input module, acquiring corresponding user diagnosis data according to the diagnosis ID after receiving the generation signal, and then generating a path according to the user diagnosis data corresponding to the diagnosis ID, so as to finally obtain a diagnosis and treatment path;
it should be further noted that, in this embodiment, after the path generation module generates the diagnosis path, the diagnosis ID and the corresponding user diagnosis data are sent to the hospital system for storage, so that the later checking and use are facilitated.
The database is used for storing a medical data set, and further description is needed that the acquisition process of the medical data set by the database comprises the following steps:
acquiring medical related data by using a data acquisition unit in a database, wherein the medical related data comprises patient treatment data and patient ID;
and combining the patient treatment data with a patient ID mapping model to obtain corresponding medical related data, and integrating the medical related data to generate a medical data set, wherein the patient ID mapping model is trained based on an artificial intelligence model.
The execution module executes different operations according to the received various different problem signals and different types of problem signals, and sends a problem-free signal to the data processing module or the data analysis module after executing the operations, so that the data processing module and the data analysis module perform calculation or analysis again; specifically, the execution operation process of the execution module is as follows:
after receiving the diagnosis problem signal sent by the data processing module, the execution module analyzes and judges the diagnosis flow of the patient, and takes acute gastroenteritis as an example, judges whether the patient causes symptoms of nausea, vomit, abdominal pain and diarrhea or even possibly generates fever, so as to judge whether the patient is acute gastroenteritis, and if the judgment is wrong, the patient needs to be subjected to pathological judgment again;
after receiving the treatment problem signals sent by the data processing module, analyzing and judging the treatment flow of the patient, taking acute gastroenteritis as an example, wherein the treatment types comprise general treatment, drug treatment and diet therapy, and selecting different treatment modes according to the symptoms of the patient, so as to judge whether the treatment process has problems, and if the problems occur, adopting the treatment modes again for the patient;
after receiving the medication problem signal sent by the data processing module, analyzing and judging the medication flow of the patient, taking acute gastroenteritis as an example, and taking the medication types including norfloxacin, simida, quick-acting antidiarrheal capsules, gentamicin, compound berberine tablets, changweikang and yanning as well as selecting different medication according to the symptoms and sensitivity of the patient, and if the medication is problematic, replacing the medication used by the patient.
After receiving the nursing problem signal sent by the data analysis module, analyzing and judging the nursing flow of the patient, taking acute gastroenteritis as an example, nursing types including diet, warmth retention and light salt water drinking, selecting different nursing types for nursing according to the receiving degree of the patient, and changing the nursing flow if the nursing process has problems.
On the other hand, as shown in fig. 2, the embodiment of the invention also discloses a clinical data path generating method based on clinical big data of a hospital, which comprises the following steps:
receiving a diagnosis name and a diagnosis ID input by a user, and judging and matching the diagnosis name input by the user to obtain user diagnosis data, wherein the user diagnosis data comprises diagnosis data, treatment data, medication data, inspection data and nursing data;
marking the user diagnosis data, calculating to obtain a comprehensive diagnosis coefficient by using the marked user diagnosis data, calculating to obtain a difference value by using the comprehensive diagnosis coefficient and the checking data, performing proportion judgment on the difference value and a set difference value threshold value, analyzing whether the user diagnosis data has problems according to the judgment result, if so, positioning the corresponding data with the problems according to the proportion, and performing analysis and judgment on the corresponding flow according to the corresponding data;
if the problem does not exist, calculating a path judgment coefficient by using the comprehensive diagnosis coefficient and the nursing data, setting a path generation judgment value, and calculating a path generation coefficient by using the path judgment coefficient and the path generation judgment value;
and comparing the path generation coefficient with a path generation judgment value, judging whether the path generation requirement is met or not according to the comparison result, if the path generation coefficient is not met, judging that nursing data has problems, analyzing and judging a corresponding nursing flow, and if the path generation coefficient is met, generating a path according to the user diagnosis data corresponding to the diagnosis ID to obtain a diagnosis path. A clinical data path generation system based on hospital clinical big data.
Based on the same inventive concept, the present invention also provides a computer apparatus comprising: one or more processors, and memory for storing one or more computer programs; the program includes program instructions and the processor is configured to execute the program instructions stored in the memory. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application SpecificIntegrated Circuit, ASIC), field-Programmable gate arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computational core and control core of the terminal for implementing one or more instructions, in particular for loading and executing one or more instructions within a computer storage medium to implement the methods described above.
It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which when executed by a processor performs the above method. The storage media may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing has shown and described the basic principles, principal features, and advantages of the present disclosure. It will be understood by those skilled in the art that the present disclosure is not limited to the embodiments described above, which have been described in the foregoing and description merely illustrates the principles of the disclosure, and that various changes and modifications may be made therein without departing from the spirit and scope of the disclosure, which is defined in the appended claims.

Claims (8)

1. A clinical data path generation system based on hospital clinical big data, comprising:
and a user input module: the diagnosis system comprises a data processing module, a diagnosis module and a diagnosis module, wherein the data processing module is used for inputting diagnosis names and visit IDs by users and sending the diagnosis names input by the users to the data processing module for processing;
and a data processing module: the diagnosis system comprises a database, a user input diagnosis name, a diagnosis data acquisition module, a data analysis module, a diagnosis module, a data analysis module and a data analysis module, wherein the diagnosis name is input by the user and is subjected to discrimination matching with a medical data set stored in the database to obtain user diagnosis data, the user diagnosis data comprises diagnosis data, treatment data, medication data, inspection data and nursing data, the user diagnosis data is marked, a comprehensive diagnosis coefficient is calculated according to the marked diagnosis data, the treatment data and the medication data, the comprehensive diagnosis coefficient is used for carrying out difference calculation with the inspection data, the obtained difference is subjected to proportion judgment with a set difference threshold value, whether the user diagnosis data has a problem or not is analyzed according to a judgment result, if the user diagnosis data has the problem, the problem data with the problem is positioned according to the proportion, a problem signal of the problem data is sent to the execution module, and if the problem does not exist, the comprehensive diagnosis coefficient and the nursing data are sent to the data analysis module;
and a data analysis module: calculating a path judgment coefficient by utilizing the comprehensive diagnosis coefficient and the nursing data, setting a path generation judgment value, carrying out path judgment on the path judgment coefficient and the path generation judgment value to obtain a path generation coefficient, comparing the path generation coefficient with the path generation judgment value, judging whether the path generation requirement is met according to the comparison result, if not, sending a nursing problem signal to an execution module, and if so, sending a generation signal to the path generation module;
and a path generation module: the diagnosis and treatment path generation module is used for receiving the diagnosis and treatment ID sent by the user input module, and generating a path according to the user diagnosis and treatment data corresponding to the diagnosis and treatment ID after receiving the generation signal;
the execution module: the system comprises a data processing module, a data analysis module, a data processing module and a data analysis module, wherein the data processing module is used for receiving various problem signals, executing different operations according to the received various different problem signals, and sending a problem-free signal to the data processing module or the data analysis module after executing the operations;
database: for storing a medical data set.
2. The clinical data path generating system based on clinical big data of the hospital according to claim 1, wherein the data processing module performs matching search in the medical data set according to the diagnosis type to which the user input diagnosis name belongs, so as to obtain the diagnosis data of the user.
3. The hospital clinical big data based clinical data path generating system according to claim 2, wherein the process of calculating the comprehensive diagnostic coefficients by the data processing module is as follows:
marking diagnosis data as Zi, treatment data as Si, medication data as Yi, inspection data as Ji and nursing data as Hi, wherein i is the number of input times of a user input module, and i=1, 2, 3, & gt, n and n are the total number of input times of the user input module;
using the formulaAnd calculating to obtain a comprehensive diagnosis coefficient Zi, wherein Z0 is a diagnosis influence coefficient, S0 is a treatment influence coefficient, Y0 is a medication influence coefficient, a is a diagnosis correlation coefficient, b is a treatment correlation coefficient, c is a medication correlation coefficient, a+bc=1, and alpha is a preset coefficient.
4. A clinical data path generating system based on clinical big data of a hospital according to claim 3, wherein the difference value is calculated by using the calculated comprehensive diagnosis coefficient and the test data, and the difference value is marked as Czi, and the calculation formula is: czi =k|zi-ji|, k is a preset factor, a difference threshold Cz0 is set, and the calculated difference Czi and the difference threshold Cz0 are subjected to proportion judgment, wherein the process is as follows:
if it isJudging that the user diagnosis data has no problem at the moment, and sending the comprehensive diagnosis coefficient and the nursing data to a data analysis module;
if it isJudging that the user diagnosis data has problems at the moment, locating that the problems in the user diagnosis data are diagnosis data, and sending a diagnosis problem signal to an execution module;
if it isJudging that the user treatment data has problems at the moment, locating that the problems in the user treatment data are treatment data, and sending a treatment problem signal to an execution module;
if it isAnd judging that the user diagnosis data has problems at the moment, locating that the user diagnosis data has problems as medication data, and sending medication problem signals to the execution module.
5. The hospital clinical big data based clinical data path generating system according to claim 1, wherein the data analysis module uses a formulaCalculating a path judgment coefficient Li, wherein q 1 To comprehensively diagnose the correlation coefficient, q 2 And t is a preset proportionality coefficient for nursing related coefficient.
6. The clinical data path generating system based on clinical big data of hospital according to claim 5, wherein the data analysis module sets a path generation determination value L, calculates using the calculated path determination coefficient Li and the path generation determination value L, and calculates the path generation determination value by the formulaCalculating a path generation coefficient L0, wherein P1 and P2 are preset generation factors; comparing the path generation coefficient L0 with the path generation determination value L:
if L0 is more than or equal to L, judging that the path generation process meets the requirement, and sending a generation signal to a path generation module for path generation;
if L0 is less than L, judging that the path generation process does not meet the requirement at the moment, positioning the problem in the nursing data Hi, and sending a nursing problem signal to the execution module.
7. The hospital clinical big data based clinical data path generating system according to claim 1, wherein the database acquisition process for the medical data set comprises the steps of:
acquiring medical related data by using a data acquisition unit in a database, wherein the medical related data comprises patient treatment data and patient ID;
and combining the patient treatment data with a patient ID mapping model to obtain corresponding medical related data, and integrating the medical related data to generate a medical data set, wherein the patient ID mapping model is trained based on an artificial intelligence model.
8. The clinical data path generation method based on the hospital clinical big data is characterized by comprising the following steps:
receiving a diagnosis name and a diagnosis ID input by a user, and judging and matching the diagnosis name input by the user to obtain user diagnosis data, wherein the user diagnosis data comprises diagnosis data, treatment data, medication data, inspection data and nursing data;
marking the user diagnosis data, calculating to obtain a comprehensive diagnosis coefficient by using the marked user diagnosis data, calculating to obtain a difference value by using the comprehensive diagnosis coefficient and the checking data, performing proportion judgment on the difference value and a set difference value threshold value, analyzing whether the user diagnosis data has problems according to the judgment result, if so, positioning the corresponding data with the problems according to the proportion, and performing analysis and judgment on the corresponding flow according to the corresponding data;
if the problem does not exist, calculating a path judgment coefficient by using the comprehensive diagnosis coefficient and the nursing data, setting a path generation judgment value, and calculating a path generation coefficient by using the path judgment coefficient and the path generation judgment value;
and comparing the path generation coefficient with a path generation judgment value, judging whether the path generation requirement is met or not according to the comparison result, if the path generation coefficient is not met, judging that nursing data has problems, analyzing and judging a corresponding nursing flow, and if the path generation coefficient is met, generating a path according to the user diagnosis data corresponding to the diagnosis ID to obtain a diagnosis path.
CN202311513023.8A 2023-11-14 2023-11-14 Clinical data path generation method and system based on hospital clinical big data Pending CN117409940A (en)

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