Intelligent Management Method, System and Readable Storage Medium for Case Information

Abstract

The present application relates to the technical field of medical information data processing, and discloses an intelligent management method, system and readable storage medium for case information. The method includes: obtaining patient case information and parsing and extracting case data therefrom, and inserting each case data into a standard template to form a standard information page; identifying and extracting treatment plan data and its directly corresponding treatment effect data in the case data, and storing them as a data reference queue; obtaining and responding to a data query or storage request, outputting the standard information page or the data reference queue, or receiving the input case information and converting it into the standard information page and / or the data reference queue for storage. In addition, according to the treatment plan data included in the case data, the sampling time point corresponding to the subsequent treatment effect data is inferred, and data is automatically collected or a prompt message is output. The above solution ensures that relevant data can be accurately collected and processed through an intelligent case data acquisition and display method, assisting doctors in diagnosis and treatment and improving the treatment effect.

Description

Technical Field

[0001] This application relates to the technical field of medical data information processing, and in particular, to an intelligent management method, system and readable storage medium for case information. Background Art

[0002] For certain diseases, such as diabetes, coronary heart disease, cancer, etc., patients need to experience a long treatment cycle from diagnosis to recovery. During the entire treatment cycle, different doctors may be involved in the diagnosis and treatment process of the patient, and the treatment plan usually changes with the change of the attending doctor.

[0003] Currently, in order to enable doctors to understand the patient's condition more clearly, patients usually need to provide materials such as previous prescription forms and diagnostic reports to the doctor. However, the problem is that different doctors have different recording methods for the condition and treatment plan, and there may even be omissions in the records, which directly makes it difficult for subsequent doctors to comprehensively and clearly understand the treatment plan and treatment effect of the patient at different stages, causing trouble in accurately formulating subsequent treatment plans.

[0004] Obviously, improving the management of case information plays a crucial role in enhancing the patient's later treatment effect. Summary of the Invention

[0005] Aiming at the problem in practical applications that the case information during the patient's treatment cycle is difficult to be effectively managed and utilized, resulting in new doctors having difficulty obtaining comprehensive and clear condition information after the replacement of the attending doctor, which brings trouble to the accurate formulation of subsequent treatment plans, the first object of this application is to propose and protect an intelligent management method for case information, which classifies and integrates the data in the case information, analyzes the case data in combination with big data, provides the current doctor with the patient's previous treatment data and also provides diagnostic assistance for the doctor; in addition, it also ensures that all data related to the condition during the treatment cycle can be accurately collected through an intelligent case data acquisition method, providing strong data support for the accurate formulation of treatment plans. To implement the above intelligent management method for case information, the second object of this application is to provide an intelligent management system for case information, which can provide a hardware foundation for the smooth implementation of the above method. Finally, this application also proposes to protect a computer-readable storage medium to protect the computer-readable storage medium loaded with a program module for implementing the above management method when executed. The specific solutions are as follows:

[0006] An intelligent management method for case information, comprising:

[0007] Setting and storing a standard template for recording each case data;

[0008] Obtain various disease data, corresponding treatment plan data, and corresponding treatment effect data of the current case from the large case database and store them. The treatment plan data includes medical actions and corresponding action times, and the treatment effect data includes the responses of various disease data to the above medical actions and response times;

[0009] Obtain the case information of each diagnosis and treatment of the patient;

[0010] Parse and extract case data from the case information to represent the patient type, treatment plan, and treatment effect. After inserting each case data into the set positions of the standard template, form a standard information page and store it in association with the diagnosis and treatment times information;

[0011] Divide the case data of each diagnosis and treatment into different data groups according to the treatment means category to which they belong. Identify and extract the treatment plan data and its directly corresponding treatment effect data from the case data in the same data group, and store them in association as a data reference queue;

[0012] Obtain and respond to a data query request, and output the corresponding standard information page and / or data reference queue;

[0013] Obtain and respond to a data storage request, receive the input case information, parse and extract the case data therein, convert it into the standard information page and / or data reference queue and store it;

[0014] If the parsed case data contains treatment plan data, find the corresponding treatment effect data according to the treatment plan data, obtain the optimal sampling time point of the disease data according to the corresponding treatment effect data, generate a data sampling request at the above sampling time point and / or link an external sampling device to automatically complete data sampling and storage.

[0015] In the above technical solution, first, the case information input from the outside is used to extract case data. While simplifying the data for easy access, it can also exclude the interference of irrelevant data. Secondly, the case data is automatically inserted into a standard template to generate a formatted standard information page, which is convenient for doctors or patients to access the case information of previous diagnoses and treatments. By grouping the case data according to different treatment methods, the specific treatment plan and achieved treatment effect corresponding to a certain treatment method during the treatment process can be visually presented, which is convenient for doctors to understand the advantages and disadvantages of various treatment methods from a more macroscopic level. By associatively storing the specific treatment plan data in a certain treatment method with its corresponding treatment effect, it helps doctors to know the impact of each treatment plan data on the treatment effect at the detail level, and helps doctors to select appropriate treatment methods and medical actions in subsequent treatments. Finally, while storing the case information input from the outside, the case information is also analyzed. According to the newly input case information, the sampling time point of subsequent associated data is automatically determined, and when the sampling time point arrives, the patient or doctor is prompted to collect and input data, or the relevant data sampling is automatically completed. Thus, the risk of data omission during the entire treatment process can be minimized, ensuring that all data related to the condition during the treatment cycle can be accurately collected, providing strong data support for the accurate formulation of treatment plans.

[0016] Furthermore, the management method further includes:

[0017] Constructing the association relationship between each disease data and each treatment plan based on the case big database;

[0018] Configuring multiple treatment plans for each disease data and assigning a reliability reference value to each treatment plan according to the strength of the above association relationship;

[0019] After obtaining and responding to the data storage request, receiving the input case information and parsing and extracting the case data therein, it further includes:

[0020] If the case data obtained by parsing contains treatment plan data, then obtain the disease data in the case data;

[0021] Search for the reliability reference value corresponding to the treatment plan data for the above disease data;

[0022] If the above reliability reference value is lower than the set threshold, output a prompt message to the external input end;

[0023] Among them, the determination criterion for the strength of the association relationship between disease data and treatment plans is: the proportion of the number of each treatment plan corresponding to the same disease data in the case big database.

[0024] Through the above technical solution, when the reliability value of the correspondence between the treatment plan input by the doctor or patient and the disease data is low, that is, when the treatment plan does not match the disease data, the system will automatically output a prompt message to confirm whether there are errors or omissions in the input treatment plan data, improving the treatment effect.

[0025] Further, the data types of the case data include text, characters, and pictures;

[0026] Parse and extract case data from the case information to represent the patient type, treatment plan, or treatment effect, including:

[0027] Obtain or connect to an external semantic large model and a feature image database, and based on natural language extraction tools and image recognition algorithms, parse and extract case data from the input case information and classify and store it according to the semantics of each case data;

[0028] Inserting each case data into the set positions of the standard template includes:

[0029] Retrieve and store a standard template, find the insertion positions reserved for each case data in the standard template, use a data insertion tool to identify the data required for the insertion positions and insert the corresponding case data into them and save.

[0030] Through the above technical solution, it is possible to quickly parse the input case information by means of the disease diagnosis and treatment semantic large model and the feature image database deployed in the external server, and at the same time clean and format the data therein, transforming the case information in different styles input by different doctors into a unified format and document, facilitating subsequent doctors to comprehensively and clearly understand the treatment plan and treatment effect during the patient's diagnosis and treatment process.

[0031] Further, the management method further includes:

[0032] Based on the case big data combined with the case data already stored for the current patient, according to the medical actions and the corresponding action times, estimate and generate the variation law of specific data in the case data over time, or

[0033] According to the doctor-specified case data, based on the storage time sequence of each case data, search for and extract specific data from the case data already stored for the current patient, and generate the variation law of the above specific data over time, or

[0034] According to the storage time sequence of each case data in the standard information page, extract the same type of data from the case data already stored for the current patient and temporarily store it, and analyze and generate the variation law of the above same type of data over time;

[0035] Set a data security threshold according to the nature of the above specific data or similar data;

[0036] Combined with the current value of the above specific data or similar data and its corresponding change law, estimate the time point when the value of the above specific data or similar data reaches the data security threshold;

[0037] Generate a sampling request for the above specific data or similar data at the above time point, and / or link with an external sampling device to automatically complete data sampling and storage.

[0038] Through the above technical solution, specific data in case data can be monitored, and the above specific data can be collected and stored at an appropriate time point according to its change law, which is convenient for doctors to understand the change trend of patients' conditions; by monitoring the change trend of similar data in case data, similar data with a set change law can be identified, which helps doctors pay attention to case data with specific change laws over time, and is convenient for doctors to make more reasonable and accurate treatment plans in subsequent diagnosis and treatment processes, improving the treatment effect.

[0039] Furthermore, the management method further includes:

[0040] Based on case big data and correlation analysis method, evaluate the correlation between each case data, and store the associated case data with a correlation coefficient exceeding a set value associated with each case data in an associated database;

[0041] After obtaining and responding to a data storage request, receiving the input case information and parsing and extracting the case data therein, it further includes:

[0042] Based on the currently parsed case data, query its associated case data according to the associated database;

[0043] If the currently parsed case data does not include the sampling data corresponding to the above associated case data, generate and output a sampling request for the above associated case data, and / or link with an external sampling device to automatically complete the sampling and storage of the above associated case data.

[0044] Through the above technical solution, the risk of missing case data can be further reduced, ensuring that all relevant data during the treatment process can be collected and stored, which helps doctors propose more accurate treatment plans in subsequent treatment processes.

[0045] Furthermore, the management method further includes:

[0046] Extract the set disease data, its corresponding treatment plan data, and treatment effect data from the already stored case data of the current patient and store them in association with the data generation time;

[0047] Taking the set symptom data as a node, generating a therapeutic effect path for representing the set symptom data based on the time sequence of each data, and storing and generating a path query index in association with the name or number of the set symptom data;

[0048] Acquire and output the above-mentioned efficacy path in response to the input index information.

[0049] Through the above technical solution, doctors or patients can directly retrieve the efficacy path of a certain disease data by entering keywords, and then have a more intuitive understanding of previous treatment plans and their treatment effects, which will help doctors make accurate adjustments to subsequent treatment plans.

[0050] An intelligent management system for case information, comprising a system end and a user end connected with the system end;

[0051] The user terminal includes a data input and output display module, which is used to receive user input information, obtain information data fed back by the system terminal and display it;

[0052] The system end includes:

[0053] A data interaction unit, configured to receive data information or instruction requests input by a user terminal, and output corresponding data information or perform specific operations in response;

[0054] A data analysis unit is connected to the data interaction unit, receives case information input by the user, and analyzes and extracts case data representing the patient type, treatment plan or treatment effect from the case information;

[0055] A standard information page generating unit, configured to be data-connected to the data parsing unit, and used to insert each case data into a set position of the standard template to form a standard information page;

[0056] A reference cohort generation unit is configured to be data-connected to the data analysis unit, divide the case data of each diagnosis and treatment into different data groups according to the treatment method category to which it belongs, identify and extract the treatment plan data and its directly corresponding treatment effect data from each case data in the same data group, and generate a data reference cohort;

[0057] A data sampling monitoring unit is configured to be data-connected to the data parsing unit, obtain the parsed treatment plan data, search for corresponding treatment effect data according to the treatment plan data, obtain the best sampling time point of the symptom data according to the corresponding treatment effect data, generate a data sampling request at the above sampling time point and / or link an external sampling device to automatically complete data sampling;

[0058] A data storage unit configured to store a standard template for recording each case data, a standard information page and its associated diagnosis and treatment times information, a data reference queue, a sampling time point and corresponding sampling data, and various symptom data of the current case and its corresponding treatment plan data and corresponding treatment effect data;

[0059] The data request processing unit is configured to be data-connected to the data interaction unit, obtain and respond to the data query request input by the user end, output the corresponding standard information page and / or data reference queue, or obtain and respond to the data storage request input by the user end, receive the input case information and parse and extract the case data therein, convert it into the standard information page and / or data reference queue and store it.

[0060] Through the above technical solution, the system can respond quickly to data queries or input requests from the user. While clearly presenting previous case information, it can determine the case data that needs to be further collected based on the case information input by the user, ensuring that all data related to the disease during the treatment cycle can be accurately collected, providing strong data support for the accurate formulation of treatment plans.

[0061] Furthermore, the data storage unit also stores:

[0062] Each symptom data and a plurality of corresponding treatment plans, and a reliability reference value used to characterize the strength of the association between the treatment plan and the symptom data; and

[0063] Setting the disease data and its corresponding treatment plan data, treatment effect data and the generation time of the above data;

[0064] The management system also includes:

[0065] The treatment plan reliability determination unit is data-connected to the data analysis unit, obtains the analyzed disease data and the corresponding treatment plan data, searches for the reliability reference value of the treatment plan data corresponding to the disease data, and outputs the reliability determination result information to the external input terminal according to the size relationship between the reliability reference value and the set threshold value;

[0066] The efficacy path query unit uses the set symptom data as a node, generates a efficacy path based on the time sequence of each data, associates and stores the path query index with the name or number of the set symptom data, and retrieves and outputs the efficacy path in response to the index information input by the user.

[0067] Through the above technical solution, the reliability of the treatment plan input by the client can be evaluated and corresponding prompt information can be output to ensure that there are no major mistakes in the treatment plan. At the same time, an efficacy path with disease data as the core node is established and a query index is provided. Users can query the corresponding treatment plan and effect according to specific disease data, which is concise and clear and helps doctors make more accurate and reliable diagnoses and treatments for patients' conditions.

[0068] Further, the management system further includes:

[0069] A data linkage acquisition unit, including multiple monitors and / or wearable devices for collecting patients' physiological parameter data, configured to be signal-connected to the data sampling and monitoring unit, receive and respond to the sampling time points output by the sampling and monitoring unit, collect corresponding disease data and output it to the data analysis unit.

[0070] Through the above technical solution, the disease data required for diagnosis and treatment can be independently collected and input into the data analysis unit, and after being processed, it is stored as standard information for doctors to consult later, which can effectively reduce the omission rate of data collection.

[0071] A computer-readable storage medium, on which a program module for implementing the case intelligent management method as described above is loaded.

[0072] Through the above technical solution, it helps to promote the application of the above case intelligent management method.

[0073] In summary, the beneficial technical effects of the solution of the present application include:

[0074] (1) Analyze and extract case data from externally input case information, simplify the data for easy reference, and at the same time exclude the interference of irrelevant data;

[0075] (2) Automatically insert case data into a standard template to generate a formatted standard information page, which is convenient for doctors or patients to consult the case information of previous diagnoses and treatments;

[0076] (3) Group each case data according to different treatment means, which can intuitively present the specific treatment plan and achieved treatment effect corresponding to a certain treatment means during the treatment process, facilitating doctors to understand the advantages and disadvantages of various treatment means from a more macroscopic level. By associatively storing the specific treatment plan data in a certain treatment means with its corresponding treatment effect, it helps doctors know the impact of each treatment plan data on the treatment effect at the detailed level, and helps doctors select appropriate treatment means and medical actions in subsequent treatments;

[0077] While storing the input case information, the case information is also parsed, the sampling time points of subsequent associated data are automatically determined according to the newly input case information, and the patient or doctor is prompted to collect and enter the data when the sampling time point arrives, or the relevant data sampling is automatically completed, thereby maximizing the risk of data omission during the entire treatment process, ensuring that all disease-related data within the treatment cycle can be accurately collected, and providing strong data support for the accurate formulation of treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 is an overall schematic diagram of the information management method of the present application.

[0079] Figure 2 is a schematic diagram of the method for determining the reliability of the input treatment plan.

[0080] Figure 3 is a schematic diagram of the efficacy path.

[0081] Figure 4 is a schematic diagram of the function framework of the information management system of the present application.

[0082] Reference numerals: 1, data interaction unit; 2, data parsing unit; 3, standard information page generation unit; 4, reference queue generation unit; 5, data sampling monitoring unit; 6, data storage unit; 7, data request processing unit; 8, treatment plan reliability determination unit; 9, efficacy path query unit; 10, data linkage collection unit. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0083] The following details the embodiments of the present application, and the examples of the embodiments are shown in the drawings.

[0084] In the description of this specification, the descriptions referring to terms such as "certain embodiments", "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiments or examples. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0085] The embodiments of the present application disclose an intelligent management method for case information, mainly including a basic information configuration step and a data storage and retrieval step.

[0086] The basic information configuration step includes:

[0087] P100 sets and stores a standard template for recording the data of each case.

[0088] P200 obtains various disease data, corresponding treatment plan data and corresponding treatment effect data of the current case from the large case database and stores them.

[0089] In the above step P100, the standard template is mainly used to clearly present patient type data, disease data, treatment plan data and treatment effect data, facilitating patients or different doctors to access the data information. The above standard template is a word document or a PDF document.

[0090] In step P200, the disease data includes the patient's basic information data, clinical symptom data, diagnostic data, etc. For example, for prostate cancer, the above disease data includes the patient's age data, family medical history data, living habit data, various urination data, prostate specific antigen (such as PSA) screening data in the blood, imaging data such as ultrasound or MRI, biopsy data, etc. Through the above disease data, the patient's condition can be inversely deduced.

[0091] The treatment plan data mainly includes medical actions and the corresponding action times, that is, the specific treatment steps for the disease, such as the specific implementation steps of the operation, radiotherapy steps, drug taking plan and its corresponding time, etc.

[0092] The treatment effect data mainly includes the response of various disease data to the above medical actions and the response time. In specific practice, it includes the changes in relevant disease data and the time when the changes occur after the patient takes a specific drug, undergoes a specific operation or radiotherapy, including positive effects and side effects. For example, the body temperature change of the patient within a set time after taking an antipyretic, the incontinence frequency of the patient within a set time after the operation, the number of vomiting and diarrhea of the patient within a set time after radiotherapy, etc.

[0093] In the implementation mode of the present application, the data types of case data include text, characters and pictures.

[0094] To make the description of the implementation mode of the present application clearer, the meanings of each noun appearing in the specification are explained below. In the implementation mode of the present application, the disease data is defined as a part of the case data. In addition to the above disease data in the case data, there are also other data information such as treatment plan data. The case data is defined as a part of the case information. The case information is a data form in which various data are combined in a specific way to convey a certain meaning representation, and it also includes data information such as medical institution name information, patient name information, doctor evaluation information, etc. that has no direct association with the treatment plan.

[0095] In the embodiments of the present application, medical actions and action times are the refined implementation processes of treatment plans, and treatment plans are the specific refinements of treatment means. For example, the treatment means for prostate cancer include surgical treatment, chemotherapy, radiotherapy, hormone therapy, immunotherapy, etc., and different treatment means correspond to different treatment plans. For example, in the chemotherapy process, there are treatment plans such as taking docetaxel, cabazitaxel or other drugs; medical actions refer to the specific implementation processes of taking the above drugs, such as when to take them and how to take them.

[0096] Data storage and retrieval steps, such as Figure 1 shown, including:

[0097] S100, obtaining the case information of each diagnosis and treatment of the patient;

[0098] S200, parsing and extracting from the case information the case data used to characterize the patient type, treatment plan or treatment effect

[0099] S210, inserting each case data into the set position of the standard template to form a standard information page, and associating and storing it with the diagnosis and treatment times information;

[0100] S220, dividing the case data of each diagnosis and treatment into different data groups according to the treatment means category to which they belong, identifying and extracting the treatment plan data and its directly corresponding treatment effect data from the case data of the same data group, and associating and storing them as a data reference queue;

[0101] S310, obtaining and responding to a data query request, and outputting the corresponding standard information page and / or data reference queue;

[0102] S320, obtaining and responding to a data storage request, receiving the input case information, parsing and extracting the case data therein, and converting it into the standard information page and / or data reference queue for storage.

[0103] S321, if the parsed case data contains treatment plan data, then finding the corresponding treatment effect data according to the treatment plan data, obtaining the optimal sampling time point of the disease data according to the corresponding treatment effect data, generating a data sampling request at the above sampling time point and / or automatically completing data sampling by linking an external sampling device and storing it.

[0104] In the above step S100, a doctor or a patient inputs the case information to be stored through the information interaction interface of the user terminal.

[0105] In the embodiments of the present application, the presentation of case data includes two methods. One is the method of presenting using a standard information page as described in step S210, and the other is the presentation based on treatment plan data and its corresponding direct treatment effect as described in step S220. Since there may be multiple treatment methods during the treatment of a disease. For example, cancer patients can receive traditional Chinese medicine physiotherapy such as acupuncture while undergoing radiotherapy. Therefore, using a standard information page allows doctors to understand the patient's treatment situation from a macroscopic level, such as the improvement of the condition after radiotherapy and traditional Chinese medicine physiotherapy. And using a data reference cohort can enable doctors to know the direct treatment effect corresponding to each treatment plan from a detailed level. For example, for the treatment plan of taking a certain antidiarrheal adjuvant drug to improve the patient's diarrhea, the corresponding direct treatment effect is the change in the number of times the patient has diarrhea. By storing and displaying similar data in the form of a data reference cohort, it can provide more accurate diagnosis and treatment assistance for doctors.

[0106] Specifically, in step S200, case data used to characterize the patient type, treatment plan, or treatment effect is parsed and extracted from the case information, including: obtaining or connecting to an external semantic large model and a feature image database, and based on a natural language extraction tool and an image recognition algorithm, parsing and extracting case data from the input case information and classifying and storing it according to the semantics of each case data. The specific implementation steps are as follows:

[0107] S201, identify the format of the input case information, such as formats like EXCEL, PDF, word, png, etc., and select the corresponding parsing tool. For example, use tools like pdfminer to extract text and use an OCR recognition tool to extract text information from pictures.

[0108] S202, based on the parsed text data, extract the target case data. If the target case data has a fixed format, use regular expressions to extract it, or natural language processing can also be performed using NLP tools. Preferably, an external semantic large model related to medical diagnosis is used for recognition processing to improve the accuracy of data parsing.

[0109] S203, temporarily store the extracted case data above.

[0110] In step S210, inserting each case data into the set position of the standard template includes: retrieving and storing a standard template, finding the insertion positions reserved for each case data in the standard template, using a data insertion tool to identify the data required for the insertion position and inserting the corresponding case data into it and saving.

[0111] Based on the above technical solution, case information in different styles input by different doctors can be transformed into a unified format and document, which is convenient for doctors to comprehensively and clearly understand the treatment plan and treatment effect during the patient's diagnosis and treatment process later.

[0112] In the implementation manner of the present application, the basic information configuration step of the management method further includes:

[0113] P300, based on the large case database, constructs the association relationship between each disease data and each treatment plan, configures multiple treatment plans for each disease data, and assigns a reliability reference value to each treatment plan according to the strength of the above association relationship and stores it. The determination criterion for the strength of the association relationship between the above disease data and the treatment plan is: the proportion of the number of treatment plans corresponding to the same disease data in the large case database. For example, for a disease data, there are 5,000 corresponding treatment plans stored in the large case database, and the proportion of the number of different treatment plans is counted, which is used as the determination criterion for the strength of the association relationship between the treatment plan and the disease data.

[0114] Based on the above basic information configuration step, in step S200, after obtaining and responding to a data storage request, receiving the input case information and parsing and extracting the case data therein, as Figure 2 shown, it further includes:

[0115] S230, determining whether there is treatment plan data in the parsed case data;

[0116] S231, if there is treatment plan data in the parsed case data, obtaining the disease data in the case data;

[0117] S232, looking up the reliability reference value corresponding to the above disease data for the treatment plan data;

[0118] S233, if the above reliability reference value is lower than the set threshold, outputting a prompt message to the external input terminal.

[0119] Through the above setting, when the correspondence reliability value between the treatment plan input by the doctor and the disease data is low, that is, when the treatment plan and the disease data do not match, the system will automatically output a prompt message to confirm whether there are errors or omissions in the input treatment plan data, improving the treatment effect. In a specific implementation manner, the system can directly push the treatment plan with the highest association relationship strength with the current disease data in the large case database for the doctor's reference.

[0120] In the above step S321, the system obtains the corresponding treatment effect data according to the analysis of the treatment plan data. The above treatment effect data includes the response to the medical action and the response time. According to the above response time and the time when the medical action is made (obtained from the treatment plan data), the time point when the treatment effect appears can be calculated. Collecting relevant disease data at the above time point can make the treatment effect data more complete.

[0121] Optimally, in the implementation manner of the present application, the management method further includes:

[0122] A110, based on the case big data in combination with the case data already stored for the current patient, according to the medical actions and the corresponding action times, estimates and generates the variation law of specific data in the case data over time, or

[0123] A120, according to the case data specified by the doctor, based on the storage time sequence of each case data, searches for and extracts specific data from the case data already stored for the current patient, and generates the variation law of the above specific data over time, or

[0124] A130, in accordance with the storage time sequence of each case data in the standard information page, extracts the same type of data from the case data already stored for the current patient and temporarily stores it, and analyzes and generates the variation law of the above same type of data over time.

[0125] A200, sets a data security threshold according to the nature of the above specific data or the same type of data;

[0126] A300, in combination with the value of the above specific data or the same type of data and the corresponding variation law, estimates the time point when the value of the above specific data or the same type of data reaches the data security threshold;

[0127] A400, generates a sampling request for the above specific data or the same type of data at the above time point, and / or links an external sampling device to automatically complete data sampling and storage.

[0128] The above steps A110 - A130 can be implemented simultaneously, or only one or two combinations of them can be implemented.

[0129] The same type of data in step A110 refers to the data used to represent the same disease condition located on different standard information pages or at different positions on the same standard information page, such as body temperature data, blood lipid content, PSA level, etc.

[0130] The above technical solution can monitor specific data in the case data, such as monitoring the PSA level, collect and store the above specific data at an appropriate time point according to its variation law, which is convenient for doctors to understand the change trend of the patient's condition. By monitoring the variation trend of the same type of data in the case data, the same type of data with a set variation law can be identified, which helps doctors pay attention to the case data with a specific variation law over time, and is convenient for doctors to make a more reasonable and accurate treatment plan in the subsequent diagnosis and treatment process, and improve the treatment effect.

[0131] In the implementation manner of this application, the basic information configuration step of the management method further includes:

[0132] P400, based on case big data and correlation analysis method, evaluates the correlation between each case data, and associates each case data with the case data whose correlation coefficient exceeds the set value and stores it as an associated database.

[0133] In step S200, after obtaining and responding to the data storage request, receiving the input case information and parsing and extracting the case data therein, the method further includes:

[0134] S240, based on the case data currently parsed and obtained, query the associated case data according to the associated database;

[0135] S241, if the case data currently parsed and obtained does not include the sampling data corresponding to the above-mentioned associated case data, a sampling request for the above-mentioned associated case data is generated and output, and / or an external sampling device is linked to automatically complete the sampling and storage of the above-mentioned associated case data.

[0136] For example, when the parsed case data contains PSA level data but does not contain digital rectal examination (DRE) data or transrectal ultrasound data, the system will output a prompt message to remind the doctor to complete the above data. The above technical solution can further reduce the risk of missing case data, ensure that relevant data during the treatment process can be collected and stored, and help doctors propose more accurate treatment plans during subsequent treatment.

[0137] In order to facilitate doctors to have a more intuitive understanding of the patient's previous treatment plans and their treatment effects, the case information intelligent management method described in this application is further optimized and further includes:

[0138] S330, extracting the set symptom data and its corresponding treatment plan data and treatment effect data from the stored case data of the current patient and storing them in association with the data generation time;

[0139] S331, taking the set symptom data as a node, generating a therapeutic effect path for representing the set symptom data based on the time sequence of each data, and storing and generating a path query index in association with the name or number of the set symptom data;

[0140] S332, acquiring and responding to the index information input from the user end, retrieving and outputting the above-mentioned efficacy path.

[0141] Combination Figure 3 As shown, taking diarrhea as the set symptom data, and setting the symptom data in the same data group as diarrhea as A, B, and C, the therapeutic effect of diarrhea and its corresponding treatment plan can be highlighted through the efficacy path, and the changes in other symptom data can also be seen from the above efficacy path, thereby intuitively presenting the possible impact of the diarrhea treatment plan on other symptom data.

[0142] In specific practice, in addition to the above implementation steps, the intelligent management method for case information further includes user permission management, login setting management, etc. Many public security verification steps for the above permissions already exist in the prior art and will not be elaborated here.

[0143] To implement the above intelligent management method for case information, an embodiment of the present application also discloses an intelligent management system for case information, including a system terminal and a user terminal that is data-connected thereto. The system terminal is preferably configured in a cloud server to facilitate the collection of various information data and the access of the user terminal. The user terminal is configured as a smart phone, a tablet computer or a PC with network communication functions, and is used to receive and send information input by the user, obtain the information data fed back by the system terminal and display it.

[0144] As Figure 4 shown, the system terminal mainly includes: a data interaction unit 1, a data parsing unit 2, a standard information page generation unit 3, a reference queue generation unit 4, a data sampling and monitoring unit 5, a data storage unit 6, a data request processing unit 7, a treatment plan reliability determination unit 8, a treatment effect path query unit 9, and a data linkage collection unit.

[0145] The data interaction unit 1 is configured to receive data information or instruction requests input by the user terminal, and respond and output corresponding data information or perform specific operations. The data parsing unit 2 is data-connected to the data interaction unit 1, receives the case information input by the user terminal, and calls a semantic large model and a feature image database to parse and extract case data representing the patient type, treatment plan or treatment effect from the case information. The standard information page generation unit 3 is configured to be data-connected to the data parsing unit 2, and is used to insert each case data into a set position of a standard template to form a standard information page and output it to the data storage unit 6. The reference queue generation unit 4 is configured to be data-connected to the data parsing unit 2, divide the case data of each diagnosis and treatment into different data groups according to the category of the treatment means to which they belong, identify and extract treatment plan data and the directly corresponding treatment effect data from the case data of the same data group, generate a data reference queue and output it to the data storage unit 6.

[0146] The data sampling and monitoring unit 5 is configured to be data-connected to the data parsing unit 2, obtain the parsed treatment plan data, find the corresponding treatment effect data according to the treatment plan data, and then obtain the best sampling time point of the disease data according to the corresponding treatment effect data, generate a data sampling request at the above sampling time point and / or link an external sampling device to automatically complete data sampling. In specific practice, the above data sampling and monitoring unit 5 cooperates with the data linkage collection unit to collect relevant data.

[0147] Specifically, the data linkage acquisition unit includes multiple monitors and / or wearable devices for collecting patients' physiological parameter data, such as smart bracelets with heart rate and blood pressure monitoring functions, configured to be connected to the cloud server through a mobile communication network or the like with the data sampling and monitoring unit 5, receive and respond to the sampling time points output by the sampling and monitoring unit, collect corresponding disease data and output and upload it to the data analysis unit 2.

[0148] The data storage unit 6 is configured to store standard templates, standard information pages for recording each case data, and their associated diagnosis and treatment times information, data reference queues, sampling time points and corresponding sampling data, various disease data of the current case and their corresponding treatment plan data and corresponding treatment effect data, reliability reference values of the association strength between each disease data and multiple corresponding treatment plans, as well as set disease data and their corresponding treatment plan data, treatment effect data, and the generation times of the above-mentioned various data. In practical applications, the above data storage unit 6 is configured as an independent database system to facilitate the retrieval and storage of information data.

[0149] The data request processing unit 7 is configured to be data-connected to the data interaction unit 1, obtain and respond to the data query request input by the user terminal, output the corresponding standard information page and / or data reference queue, or obtain and respond to the data storage request input by the user terminal, receive the input case information and parse and extract the case data therein, and convert it into the standard information page and / or data reference queue and store it.

[0150] The treatment plan reliability determination unit 8 is data-connected to the data analysis unit 2, obtains the parsed disease data and its corresponding treatment plan data, looks up the reliability reference value of the treatment plan data corresponding to the above disease data, and outputs the reliability determination result information to the external input terminal according to the size relationship between the above reliability reference value and the set threshold. The treatment effect path query unit 9 generates a treatment effect path based on the time sequence of each data with the set disease data as the node, associates and stores it with the name or number of the above set disease data and generates a path query index, and retrieves and outputs the above treatment effect path in response to the index information input by the user terminal.

[0151] Finally, in order to facilitate the further popularization and use of the display method based on time-division multiplexing described in this application, the embodiment of this application also discloses a computer-readable storage medium, on which a program module for implementing the case intelligent management method as described above is loaded.

[0152] The above computer-readable storage medium includes but is not limited to disk memories, CD-ROMs, optical memories, etc.

[0153] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limitations on the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An intelligent management method for case information, characterized in that, Including: Setting and storing a standard template for recording case data of each case; Obtaining, storing various disease data, corresponding treatment plan data, and corresponding treatment effect data of the current case based on a large case database, where the treatment plan data includes medical actions and corresponding action times, and the treatment effect data includes the responses of various disease data to the above medical actions and response times; Obtaining the case information of each diagnosis and treatment of the patient; Parsing and extracting case data from the case information to characterize the patient type, treatment plan, and treatment effect; Inserting each case data into the set position of the standard template to form a standard information page, and storing it in association with the diagnosis and treatment times information; Dividing the case data of each diagnosis and treatment into different data groups according to the treatment means category to which they belong, identifying and extracting treatment plan data and their directly corresponding treatment effect data from the case data in the same data group, and storing them in association as a data reference queue; Obtaining and responding to a data query request, and outputting the corresponding standard information page and / or data reference queue; Obtaining and responding to a data storage request, receiving the input case information, parsing and extracting the case data therein, converting it into the standard information page and / or data reference queue, and storing it; If the parsed case data contains treatment plan data, then searching for the corresponding treatment effect data from the data storage unit according to the treatment plan data, obtaining the optimal sampling time point of the disease data according to the corresponding treatment effect data, generating a data sampling request at the above sampling time point and / or automatically completing data sampling by linking an external sampling device and storing it.

2. The intelligent management method for case information according to claim 1, wherein The data types of the case data include text, characters, and pictures; Parsing and extracting case data from the case information to characterize the patient type, treatment plan, and treatment effect, including: Obtaining or connecting to an external semantic large model and a feature image database, parsing and extracting case data from the input case information based on natural language extraction tools and image recognition algorithms, and classifying and storing the case data according to the semantics of each case data; Inserting each case data into the set position of the standard template includes: Retrieving and storing a standard template, searching for the insertion positions reserved for each case data in the standard template, using a data insertion tool to identify the data required for the insertion positions, and inserting the corresponding case data therein and saving it.

3. The intelligent management method for case information according to claim 2, wherein The management method further includes: Constructing the association relationship between each disease data and each treatment plan based on the large case database; Configuring multiple treatment plans for each disease data and assigning a reliability reference value to each treatment plan according to the strength of the above association relationship; After obtaining and responding to a data storage request, receiving the input case information and parsing and extracting the case data therein, it further includes: If the parsed case data contains treatment plan data, then obtaining the disease data in the case data; Searching for the reliability reference value corresponding to the above disease data of the treatment plan data; If the above reliability reference value is lower than the set threshold, then outputting a prompt message to the external input end; Wherein, the determination criterion for the strength of the association relationship between disease data and treatment plan is: the proportion of the number of each treatment plan corresponding to the same disease data in the large case database.

4. The intelligent management method for case information according to claim 3, wherein The management method further includes: Based on case big data combined with the case data already stored for the current patient, according to medical actions and corresponding action times, estimating and generating the variation law of specific data in the case data over time, or According to the case data specified by the doctor, based on the storage time sequence of each case data, searching and extracting specific data from the case data already stored for the current patient to generate the variation law of the above-mentioned specific data over time, or According to the storage time sequence of each case data in the standard information page, extracting and temporarily storing the same-type data in the case data already stored for the current patient, and analyzing and generating the variation law of the above-mentioned same-type data over time; Setting a data security threshold according to the nature of the above-mentioned specific data or same-type data; Combining the value of the above-mentioned specific data or same-type data and the corresponding variation law, estimating the time point when the value of the above-mentioned specific data or same-type data reaches the data security threshold; Generating a sampling request for the above-mentioned specific data or same-type data at the above-mentioned time point, and / or linking an external sampling device to automatically complete data sampling and storage.

5. The intelligent management method for case information according to claim 4, wherein The management method further includes: Based on case big data and the correlation analysis method, evaluating the correlation between each case data, and associatively storing each case data and the case data with a correlation coefficient exceeding a set value with it as an association database; After obtaining and responding to a data storage request, receiving the input case information and parsing and extracting the case data therein, it further includes: Based on the case data currently obtained by parsing, querying its associated case data according to the association database; If the sampling data corresponding to the above-mentioned associated case data is not included in the case data currently obtained by parsing, generating and outputting a sampling request for the above-mentioned associated case data, and / or linking an external sampling device to automatically complete the sampling and storage of the above-mentioned associated case data.

6. The intelligent management method for case information according to claim 5, wherein The management method further includes: Extracting the set disease data, its corresponding treatment plan data, and treatment effect data from the case data already stored for the current patient, and associatively storing them with the data generation time; Taking the set disease data as a node, generating a curative effect path for representing the set disease data based on the time sequence of each data, associatively storing it with the name or number of the set disease data, and generating a path query index; Obtaining and responding to the input index information to retrieve and output the above-mentioned curative effect path.

7. An intelligent management system for case information, characterized in that, Used to implement the intelligent management method for case information according to any one of claims 1-6, including a system terminal and a user terminal data-connected thereto; Among them, the user terminal includes a data input and output display module, configured to receive the input information of the user, obtain the information data fed back by the system terminal and display it; The system terminal includes: A data interaction unit (1), configured to receive the data information or instruction request input by the user terminal, and respond and output the corresponding data information or perform a specific operation; A data parsing unit (2), data-connected to the data interaction unit (1), receiving the case information input by the user terminal, and parsing and extracting the case data for representing the patient type, treatment plan, and treatment effect from the case information; A standard information page generation unit (3), configured to be connected to the data parsing unit (2) for data connection, and is used to insert each case data into a set position of a standard template to form a standard information page; A reference queue generation unit (4), configured to be connected to the data parsing unit (2) for data connection, divides the case data of each diagnosis and treatment into different data groups according to the category of the treatment means to which they belong, identifies and extracts treatment plan data and the directly corresponding treatment effect data from the case data of the same data group, and generates a data reference queue; A data sampling and monitoring unit (5), configured to be connected to the data parsing unit (2) for data connection, obtains the parsed treatment plan data, looks up the corresponding treatment effect data from the data storage unit (6) according to the treatment plan data, obtains the optimal sampling time point of the disease data according to the corresponding treatment effect data, generates a data sampling request at the above sampling time point and / or links an external sampling device to automatically complete data sampling; A data storage unit (6), configured to store a standard template for recording each case data, a standard information page and its associated diagnosis and treatment times information, a data reference queue, a sampling time point and the corresponding sampling data, and various disease data of the current case and their corresponding treatment plan data and corresponding treatment effect data; A data request processing unit (7), configured to be connected to the data interaction unit (1) for data connection, obtains and responds to a data query request input by the user terminal, outputs the corresponding standard information page and / or data reference queue, or obtains and responds to a data storage request input by the user terminal, receives the input case information and parses and extracts the case data therein, and converts it into the standard information page and / or data reference queue and stores it.

8. The intelligent management system for case information according to claim 7, wherein The following are also associated and stored in the data storage unit (6): Each disease data and multiple corresponding treatment plans, as well as a reliability reference value used to characterize the strength of the association between the treatment plan and the disease data; And Set disease data and its corresponding treatment plan data, treatment effect data, and the generation time of the above data; The management system further includes: A treatment plan reliability determination unit (8), connected to the data parsing unit (2) for data connection, obtains the parsed disease data and its corresponding treatment plan data, looks up the reliability reference value of the treatment plan data corresponding to the above disease data, and outputs a reliability determination result information to an external input end according to the size relationship between the above reliability reference value and a set threshold; A treatment effect path query unit (9), uses the set disease data as a node, generates a treatment effect path based on the time sequence of each data, is associated and stored with the name or number of the above set disease data and generates a path query index, and responds to the index information input by the user terminal to retrieve and output the above treatment effect path.

9. The intelligent management system for case information according to claim 7, wherein The management system further includes: A data linkage acquisition unit, including multiple monitors and / or wearable devices for collecting patient physiological parameter data, configured to be connected to the data sampling and monitoring unit (5) for signal connection, receive and respond to the sampling time point output by the sampling and monitoring unit, collect the corresponding disease data and output it to the data parsing unit (2).

10. A computer-readable storage medium, characterized in that, A program module for implementing the case intelligent management method according to any one of claims 1-6 is loaded thereon.

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