Case information intelligent management method and system and readable storage medium

Abstract

The invention relates to the technical field of medical information data processing, and discloses a case information intelligent management method and system and a readable storage medium, and the method comprises the steps: obtaining patient case information, analyzing and extracting case data from the patient case information, and inserting each piece of case data into a standard template to form a standard information page; identifying and extracting treatment scheme data and treatment effect data directly corresponding to the treatment scheme data in the case data, and storing the treatment scheme data and the treatment effect data as a data reference queue; a data query or storage request is obtained and responded, a standard information page or a data reference queue is output, or input case information is received and converted into the standard information page and / or the data reference queue for storage, in addition, sampling time points corresponding to follow-up treatment effect data are deduced according to treatment scheme data contained in case data, and the sampling time points are stored. And automatically collecting data or outputting a prompt message. According to the scheme, through an intelligent case data acquisition and display method, it is ensured that all related data can be accurately collected and processed, doctors are assisted in diagnosis and treatment, and the treatment effect is improved.

Description

Technical Field

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

[0002] For some diseases, such as diabetes, coronary heart disease, cancer, etc., patients need to go through a long treatment cycle from diagnosis to recovery. During the entire treatment cycle, different doctors may participate in the diagnosis and treatment process of the patient, and the diagnosis and treatment plan will usually change with the change of the attending physician.

[0003] Currently, in order for doctors to understand the patient's condition more clearly, patients are usually required to provide doctors with previous prescriptions, diagnosis reports and other materials. However, the problem is that different doctors have different ways of recording the condition and treatment plan, and there may even be omissions in the records, which directly leads to subsequent doctors having difficulty in fully and clearly understanding the patient's treatment plan at different stages and the effect after treatment when making a diagnosis and treatment, which brings troubles to the subsequent accurate formulation of treatment plans.

[0004] Obviously, improving the management of case information plays a vital role in improving the patient's subsequent treatment outcomes. Summary of the invention

[0005] In view of the problem that case information during the patient's treatment cycle is difficult to be effectively managed and utilized in actual applications, which makes it difficult for the new doctor to obtain comprehensive and clear information about the condition after the attending physician is replaced, causing trouble for the accurate formulation of subsequent treatment plans, the first purpose of this application is to propose and protect a method for intelligent management of case information, which classifies and integrates the data in the case information, analyzes the case data in combination with big data, and provides the current doctor with the patient's previous treatment data while also providing the doctor with diagnostic assistance; in addition, through an intelligent case data acquisition method, it ensures that all data related to the condition during the treatment cycle can be accurately collected, providing strong data guarantee for the accurate formulation of treatment plans. In order to realize the above-mentioned method for intelligent management of case information, the second purpose of this application is to provide a case information intelligent management system, which can provide a hardware foundation for the smooth implementation of the above-mentioned 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 used to implement the above-mentioned management method when executed. The specific scheme is as follows:

[0006] A case information intelligent management method, comprising:

[0007] Set up and store standard templates for recording data for each case;

[0008] Based on the case database, various symptom data of the current case, corresponding treatment plan data and expected treatment effect data are acquired and stored. The treatment plan data includes medical actions and corresponding action times. The treatment effect data includes responses of various symptom data to the above medical actions and response times.

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

[0010] Analyze and extract case data used to characterize patient types, treatment plans or treatment effects from the case information, insert each case data into a set position of the standard template to form a standard information page, and store it in association with the diagnosis and treatment number information;

[0011] The case data of each diagnosis and treatment are divided into different data groups according to the category of treatment methods to which they belong, and the treatment plan data and the directly corresponding treatment effect data are identified and extracted from the case data of each case in the same data group, and the data are associated and stored as a data reference queue;

[0012] Obtaining and responding to data query requests, outputting corresponding standard information pages and / or data reference queues;

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

[0014] If the analyzed case data contains treatment plan data, the expected treatment effect data is searched based on the treatment plan data, and the optimal sampling time point of the symptom data is obtained based on the expected treatment effect data. A data sampling request is generated at the above sampling time point and / or an external sampling device is linked to automatically complete data sampling and storage.

[0015] In the above technical scheme, firstly, case data is extracted from externally input case information, which simplifies the data for easy reference and eliminates interference from irrelevant data; secondly, the case data is automatically inserted into the standard template to generate a formatted standard information page, which is convenient for doctors or patients to review case information of previous diagnoses and treatments; by grouping the case data according to different treatment methods, the specific treatment plan and the treatment effect achieved corresponding to a certain treatment method in the treatment process can be intuitively presented, which is convenient for doctors to understand the advantages and disadvantages of various treatment methods from a more macro level; by associating and storing the specific treatment plan data in a certain treatment method with its corresponding treatment effect, it is helpful for doctors to know the impact of each treatment plan data on the treatment effect at the detailed level, which is helpful for doctors to choose appropriate treatment methods and medical actions in subsequent treatments. Finally, while storing the externally input case information, the case information will also be analyzed. The sampling time point of subsequent related data will be automatically determined based on the newly input case information, and the patient or doctor will be prompted to collect and enter the data when the sampling time point is reached, or the relevant data sampling will be automatically completed. This can minimize the risk of data omission during the entire treatment process, ensure that all disease-related data during the treatment cycle can be accurately collected, and provide strong data support for the accurate formulation of treatment plans.

[0016] Furthermore, the management method also includes:

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

[0018] Configure multiple treatment plans for each disease data and assign a reliability reference value to each treatment plan according to the strength of the above-mentioned association;

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

[0020] If the case data obtained by analysis contains treatment plan data, the symptom data in the case data is obtained;

[0021] Finding a reliability reference value of the treatment plan data corresponding to the disease data;

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

[0023] Among them, the criterion for judging the strength of the correlation between symptom data and treatment plans is: the proportion of treatment plans corresponding to the same symptom data in the case 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 symptom data is low, that is, the treatment plan and the symptom data are not compatible, the system will automatically output a prompt message to confirm whether there are errors or omissions in the input treatment plan data, thereby improving the treatment effect.

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

[0026] Parsing and extracting case data from the case information to characterize the patient type, treatment regimen, or treatment effect, including:

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

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

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

[0030] Through the above technical solution, with the help of the disease diagnosis and treatment semantic big model and feature image database deployed in the external server, the input case information can be quickly parsed using document parsing tools combined with regular expressions, NLP tools, etc., and the data therein can be cleaned and formatted at the same time, and the case information of different styles entered by different doctors can be converted into a unified format and document, so that subsequent doctors can fully and clearly understand the treatment plan and treatment effect during the patient's diagnosis and treatment process.

[0031] Furthermore, the management method also includes:

[0032] Based on the big case data combined with the existing case data of the current patient, according to the medical actions and the corresponding action time, the change pattern of specific data in the case data over time is estimated, or

[0033] According to the case data specified by the doctor, based on the storage time sequence of each case data, search and extract specific data from the case data already stored for the current patient, and generate the change pattern 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 stored case data of the current patient and temporarily store it, and analyze and generate the change pattern of the above-mentioned same type of data over time;

[0035] According to the nature of the above-mentioned specific data or similar data, a data security threshold is set;

[0036] Based on the current values ​​of the above-mentioned specific data or data of the same type and the corresponding changing rules, estimate the time point when the values ​​of the above-mentioned specific data or data of the same type reach the data security threshold;

[0037] At the above time point, a sampling request for the above specific data or similar data is generated, and / or an external sampling device is linked to automatically complete data sampling and storage.

[0038] Through the above technical solution, specific data in the case data can be monitored, and the above specific data can be collected and stored at appropriate time points according to their changing patterns, so that doctors can understand the changing trends of patients' conditions; by monitoring the changing trends of similar data in the case data, similar data with set changing patterns can be identified, which helps doctors pay attention to case data with specific changing patterns over time, so that doctors can make more reasonable and accurate treatment plans in the subsequent diagnosis and treatment process, thereby improving the treatment effect.

[0039] Furthermore, the management method also includes:

[0040] Based on case big data and correlation analysis, the correlation between each case data is evaluated, and each case data and the case data with a correlation coefficient exceeding the set value are associated and stored as an associated database;

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

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

[0043] If the case data currently parsed and acquired does not include 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.

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

[0045] Furthermore, the management method also includes:

[0046] 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;

[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 expected treatment effect data according to the treatment plan data, obtain the best sampling time point for the symptom data according to the expected 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 frequency information, a data reference queue, a sampling time point and the corresponding sampling data, and various symptom data of the current case and its corresponding treatment plan data and expected 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 user can be evaluated and corresponding prompt information can be output to ensure that there are no major omissions in the treatment plan; at the same time, an efficacy path with symptom data as the core node is established and a query index is provided. Users can query the corresponding treatment plan and effect based on specific symptom data, which is concise and clear, and helps doctors make more accurate and reliable diagnosis and treatment of patients' conditions.

[0068] Furthermore, the management system also includes:

[0069] The data linkage acquisition unit includes multiple monitors and / or wearable devices for collecting patient physiological parameter data, which are 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 them to the data analysis unit.

[0070] Through the above technical solution, the disease data required for diagnosis and treatment can be collected independently and input into the data analysis unit. After processing, it is stored as standard information for subsequent reference by doctors, which can effectively reduce the omission rate of data collection.

[0071] A computer-readable storage medium loaded with a program module for implementing the above-mentioned intelligent case management method.

[0072] The above technical solution will help promote the application of the above-mentioned case intelligent management method.

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

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

[0075] (2) Automatically insert case data into a standard template to generate a formatted standard information page, making it easier for doctors or patients to review case information from previous diagnoses and treatments;

[0076] (3) Grouping case data according to different treatment methods can intuitively present the specific treatment plan and treatment effect achieved for a certain treatment method during the treatment process, which is convenient for doctors to understand the advantages and disadvantages of various treatment methods from a relatively macro level. By associating and storing the specific treatment plan data in a certain treatment method with its corresponding treatment effect, it is helpful for doctors to know the impact of each treatment plan data on the treatment effect at the detailed level, which helps doctors to choose appropriate treatment methods and medical actions in subsequent treatments;

[0077] (4) The input case information will be stored and analyzed at the same time. The sampling time point of the subsequent related data will be automatically determined based on the newly input case information. When the sampling time point arrives, the patient or doctor will be prompted to collect and enter the data, or the relevant data sampling will be automatically completed. This can minimize the risk of data omission during the entire treatment process, ensure that all data related to the condition during the treatment cycle can be accurately collected, and provide strong data support for the accurate formulation of treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0080] Figure 3 It is a schematic diagram of the therapeutic pathway.

[0081] Figure 4 It is a functional framework diagram of this application information management system.

[0082] Figure 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

[0083] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0084] In the description of this specification, the description with reference to the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0085] The embodiment of the present application discloses a method for intelligent management of case information, which mainly includes a basic information configuration step and a data storage and review step.

[0086] Basic information configuration steps include:

[0087] P100, set up and store standard templates for recording data for each case;

[0088] P200, based on the case database, obtains and stores various symptom data of the current case, the corresponding treatment plan data and its expected treatment effect data.

[0089] In the above step P100, the standard template is mainly used to clearly present the patient type data, disease data, treatment plan data and treatment effect data, so that patients or different doctors can consult 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, and diagnosis data. 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, blood prostate-specific antigen (such as PSA) screening data, ultrasound or MRI and other imaging data, puncture biopsy data, etc. The patient's condition can be reversely inferred through the above disease data.

[0091] Treatment plan data mainly includes medical actions and corresponding action times, that is, specific treatment steps for the disease, such as specific surgical implementation steps, radiotherapy steps, drug administration plans and their corresponding times, etc.

[0092] The treatment effect data mainly includes the response of various symptom data to the above medical actions and the response time. In specific practice, it includes the changes in relevant symptom data after patients take specific drugs, undergo specific operations or radiotherapy and the time when the changes occur, including positive effects and side effects, such as the change in the patient's body temperature within a set time after taking antipyretics, the frequency of incontinence of patients within a set time after surgery, and the number of vomiting and diarrhea of ​​patients within a set time after radiotherapy.

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

[0094] In order to make the description of the implementation mode of this application clearer, the meaning of each term appearing in the specification is explained below. In the implementation mode of this application, symptom data is defined as a part of case data, and in addition to the above-mentioned symptom data, the case data also includes other data information such as treatment plan data. Case data is defined as a part of case information, and case information is a data form composed of various data in a specific combination to convey a certain meaning, which also includes data information such as medical institution name information, patient name information, doctor evaluation information, etc. that are not directly related to the treatment plan.

[0095] In the implementation mode of this application, the medical action and action time are the detailed implementation process of the treatment plan, and the treatment plan is the specific refinement of the treatment method. For example, the treatment methods for prostate cancer include surgical treatment, chemotherapy, radiotherapy, hormone therapy, immunotherapy, etc., and different treatment methods correspond to different treatment plans, such as the plan of taking docetaxel, cabazitaxel or other drugs during chemotherapy; the medical action refers to the specific implementation process of taking the above drugs, such as when to take them and how to take them.

[0096] Data storage review steps, such as Figure 1 As shown, including:

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

[0098] S200, parsing and extracting case data for characterizing patient type, treatment plan or treatment effect from the case information

[0099] S210, 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 number information;

[0100] S220, dividing the case data of each diagnosis and treatment into different data groups according to the treatment method category to which it belongs, identifying and extracting the treatment plan data and the directly corresponding treatment effect data from each case data in the same data group, and storing them in association as a data reference queue;

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

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

[0103] S321, if the case data obtained by analysis contains treatment plan data, then the expected treatment effect data is searched according to the treatment plan data, and the optimal sampling time point of the symptom data is obtained according to the expected treatment effect data, and a data sampling request is generated at the above sampling time point and / or an external sampling device is linked to automatically complete data sampling and store it.

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

[0105] In the implementation mode of the present application, the presentation of case data includes two methods, one is the presentation using the standard information page as described in step S210, and the other is the presentation based on the treatment plan data and its corresponding direct treatment effect as described in step S220. Since there may be multiple treatment methods at the same time during the treatment of the disease, such as cancer patients can also receive acupuncture and other traditional Chinese medicine physiotherapy while receiving radiotherapy. To this end, the use of standard information pages can allow doctors to understand the patient's treatment situation from a macro level, such as the improvement of the condition after radiotherapy and traditional Chinese medicine physiotherapy, and the use of data reference queues can let doctors know the direct treatment effects corresponding to each treatment plan from a detailed level, such as taking a certain antidiarrhea auxiliary drug to improve the patient's diarrhea. The corresponding direct treatment effect is the change in the number of diarrhea times of the patient. By storing and displaying similar data in the form of data reference queues, doctors can be provided with more accurate diagnosis and treatment assistance.

[0106] Specifically, in step S200, case data used to characterize patient types, treatment plans or treatment effects are parsed and extracted from the case information, including: obtaining or connecting to an external semantic large model and 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. The specific execution steps are:

[0107] S201, identifying the format of the input case information, such as EXCEL, PDF, word, png and other formats, and selecting the corresponding parsing tool, such as using tools such as pdfminer to extract text, and using OCR recognition tools to extract text information in the image.

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

[0109] S203: temporarily storing the extracted case data.

[0110] In step S210, inserting each case data into the set position of the standard template includes: calling and storing a standard template, searching for the insertion position 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 it.

[0111] Based on the above technical solution, case information of different styles input by different doctors can be converted into a unified format and document, so that subsequent doctors can fully and clearly understand the treatment plan and treatment effect during the patient's diagnosis and treatment process.

[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 case database, builds the association between each symptom data and each treatment plan, configures multiple treatment plans for each symptom data, and assigns a reliability reference value to each treatment plan according to the strength of the above association and stores it. The strength of the association between the above symptom data and the treatment plan is determined by the proportion of the number of treatment plans corresponding to the same symptom data in the case database. For example, for a symptom data, there are 5,000 corresponding treatment plans in the case database. The proportion of different treatment plans is counted and used as the criterion for determining the strength of the association between the treatment plan and the symptom data.

[0114] Based on the above basic information configuration steps, 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, as shown in FIG. Figure 2 As shown, it also includes:

[0115] S230, determining whether the case data obtained by analysis contains treatment plan data;

[0116] S231, if the case data obtained by analysis contains treatment plan data, then obtain the symptom data in the case data;

[0117] S232, searching for a reliability reference value of the treatment plan data corresponding to the disease data;

[0118] S233: If the reliability reference value is lower than the set threshold, output a prompt message to the external input terminal.

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

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

[0121] Optimized, in the implementation mode of the present application, the management method further includes:

[0122] A110, based on the case big data combined with the existing case data of the current patient, according to the medical actions and the corresponding action time, estimates the change pattern of specific data in the case data over time, or

[0123] A120, according to the case data designated by the doctor, based on the storage time sequence of each case data, searches and extracts specific data from the case data already stored for the current patient, and generates a time-dependent change pattern of the specific data, or

[0124] A130, according to the storage time sequence of each case data in the standard information page, extract similar data from the stored case data of the current patient and temporarily store them, and analyze and generate the change pattern of the above similar data over time.

[0125] A200, according to the nature of the above-mentioned specific data or similar data, set a data security threshold;

[0126] A300, based on the current value of the specific data or the same type of data and the corresponding change pattern, estimates the time point when the value of the specific data or the same type of data reaches the data security threshold;

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

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

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

[0130] The above technical solution can monitor specific data in case data, such as monitoring PSA levels, and collect and store the above specific data at appropriate time points according to its changing rules, so that doctors can understand the changing trends of patients' conditions. By monitoring the changing trends of similar data in case data, similar data with set changing rules can be identified, which helps doctors pay attention to case data with specific changing rules over time, so that doctors can make more reasonable and accurate treatment plans in the subsequent diagnosis and treatment process, and improve the treatment effect.

[0131] In the implementation manner of the present 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 acquired does not include 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-mentioned implementation steps, the intelligent management method of case information also includes user authority management, login setting management, etc. The security verification steps of the above-mentioned authority have been disclosed in many prior arts and will not be repeated here.

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

[0144] like Figure 4 As shown, the system end mainly includes: a data interaction unit 1, a data analysis unit 2, a standard information page generation unit 3, a reference queue generation unit 4, a data sampling monitoring unit 5, a data storage unit 6, a data request processing unit 7, a treatment plan reliability determination unit 8, an efficacy 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 end, and respond to output corresponding data information or perform specific operations. The data analysis unit 2 is data-connected to the data interaction unit 1, receives case information input by the user end, and calls the semantic large model and feature image database to parse and extract case data used to characterize 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 analysis unit 2, and is used to insert each case data into the set position of the 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 analysis unit 2, 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 treatment plan data and its directly corresponding treatment effect data from each case data in the same data group, generate a data reference queue and output it to the value data storage unit 6.

[0146] The data sampling monitoring unit 5 is configured to be data-connected with the data analysis unit 2, obtain the analyzed treatment plan data, search for the expected treatment effect data according to the treatment plan data, and then obtain the optimal sampling time point of the symptom data according to the expected 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 monitoring unit 5 cooperates with the data linkage acquisition unit to collect relevant data.

[0147] As described in detail, the data linkage acquisition unit includes multiple monitors and / or wearable devices for collecting patient physiological parameter data, such as a smart bracelet with heart rate and blood pressure monitoring functions, which is configured to connect to the cloud server through a mobile communication network, etc., with the data sampling monitoring unit 5, receive and respond to the sampling time point output by the sampling 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 for recording each case data, standard information pages and their associated diagnosis and treatment times, data reference queues, sampling time points and corresponding sampling data, various symptom data of the current case and their corresponding treatment plan data and expected treatment effect data, reliability reference values ​​of the strength of association between each symptom data and multiple corresponding treatment plans, and set symptom data and their corresponding treatment plan data, treatment effect data, and the generation time of each of the above data. In practical applications, the 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, to obtain and respond to the data query request input by the user end, to output the corresponding standard information page and / or data reference queue, or to obtain and respond to the data storage request input by the user end, to receive the input case information and to parse and extract the case data therein, to convert it into the standard information page and / or data reference queue and to store it.

[0150] The treatment plan reliability determination unit 8 is connected to the data analysis unit 2, obtains the analyzed disease data and its corresponding treatment plan data, searches for 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 value. The efficacy path query unit 9 uses the set disease data as a node, generates an efficacy path based on the time sequence of each data, associates and stores it with the name or number of the set disease data, and generates a path query index, and retrieves and outputs the above efficacy path in response to the index information input by the user terminal.

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

[0152] The above-mentioned computer-readable storage media include but are not limited to disk storage, CD-ROM, optical storage, 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 cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for intelligent management of case information, characterized in that: include: Set up and store standard templates for recording data for each case; Based on the case database, various symptom data of the current case, corresponding treatment plan data and expected treatment effect data are acquired and stored. The treatment plan data includes medical actions and corresponding action times. The treatment effect data includes responses of various symptom data to the above medical actions and response times. Obtain case information of each patient's diagnosis and treatment; Parsing and extracting case data from the case information to characterize patient type, treatment regimen or treatment effect; After inserting each case data into the set position of the standard template, a standard information page is formed and stored in association with the diagnosis and treatment number information; The case data of each diagnosis and treatment are divided into different data groups according to the category of treatment methods to which they belong, and the treatment plan data and the directly corresponding treatment effect data are identified and extracted from the case data of each case in the same data group, and the data are associated and stored as a data reference queue; Obtaining and responding to data query requests, outputting corresponding standard information pages and / or data reference queues; Acquire and respond to data storage requests, receive input case information and parse and extract case data therein, convert it into the standard information page and / or data reference queue and store it; If the analyzed case data contains treatment plan data, the expected treatment effect data is searched based on the treatment plan data, and the optimal sampling time point of the symptom data is obtained based on the expected treatment effect data. A data sampling request is generated at the above sampling time point and / or an external sampling device is linked to automatically complete data sampling and storage.

2. The method for intelligent management of case information according to claim 1, characterized in that: 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 regimen, or treatment effect, including: Obtain or connect to an external semantic large model and feature image database, parse and extract case data from the input case information based on natural language extraction tools and image recognition algorithms, and classify and store each case data according to its semantics; Inserting each case data into the set position of the standard template includes: Retrieve and store a standard template, find the insertion position reserved for each case data in the standard template, use the data insertion tool to identify the data required for the insertion position, insert the corresponding case data into it and save it.

3. The method for intelligent management of case information according to claim 2, characterized in that: The management method also includes: Build the relationship between each disease data and each treatment plan based on the case database; Configure multiple treatment plans for each disease data and assign a reliability reference value to each treatment plan according to the strength of the above-mentioned association; After obtaining and responding to a data storage request, receiving input case information and parsing and extracting case data therein, it also includes: If the case data obtained by analysis contains treatment plan data, the symptom data in the case data is obtained; Finding a reliability reference value of the treatment plan data corresponding to the disease data; If the reliability reference value is lower than the set threshold, a prompt message is output to the external input terminal; Among them, the criterion for judging the strength of the correlation between symptom data and treatment plans is: the proportion of treatment plans corresponding to the same symptom data in the case database.

4. The method for intelligent management of case information according to claim 3, characterized in that: The management method also includes: Based on the big case data combined with the existing case data of the current patient, according to the medical actions and the corresponding action time, the change pattern of specific data in the case data over time is estimated, or According to the case data specified by the doctor, based on the storage time sequence of each case data, search and extract specific data from the case data already stored for the current patient, and generate the change pattern of the above specific data over time, or According to the storage time sequence of each case data in the standard information page, extract the same type of data from the stored case data of the current patient and temporarily store it, and analyze and generate the change pattern of the above-mentioned same type of data over time; According to the nature of the above-mentioned specific data or similar data, a data security threshold is set; Based on the current values ​​of the above-mentioned specific data or data of the same type and the corresponding changing rules, estimate the time point when the values ​​of the above-mentioned specific data or data of the same type reach the data security threshold; At the above time point, a sampling request for the above specific data or similar data is generated, and / or an external sampling device is linked to automatically complete data sampling and storage.

5. The method for intelligent management of case information according to claim 4, characterized in that: The management method also includes: Based on case big data and correlation analysis, the correlation between each case data is evaluated, and each case data and the case data with a correlation coefficient exceeding the set value are associated and stored as an associated database; After obtaining and responding to a data storage request, receiving input case information and parsing and extracting case data therein, it also includes: Based on the case data currently parsed and obtained, query the associated case data according to the associated database; If the case data currently parsed and acquired does not include 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.

6. The method for intelligent management of case information according to claim 5, characterized in that: The management method also includes: 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; 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; Acquire and output the above-mentioned efficacy path in response to the input index information.

7. An intelligent management system for case information, characterized in that: Including the system end and the user end connected to it by data; 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; The system end includes: A data interaction unit (1) is configured to receive data information or instruction requests input by a user terminal, and in response output corresponding data information or perform a specific operation; The data analysis unit (2) is connected to the data interaction unit (1) to receive case information input by the user, and analyze and extract case data used to characterize the patient type, treatment plan or treatment effect from the case information; A standard information page generating unit (3) is configured to be data-connected to the data analyzing unit (2) and is used to insert each case data into a set position of the standard template to form a standard information page; A reference queue generation unit (4) is configured to be data-connected to the data analysis unit (2), divide the case data of each diagnosis and treatment into different data groups according to the category of treatment methods to which they belong, identify and extract treatment plan data and directly corresponding treatment effect data from each case data in the same data group, and generate a data reference queue; A data sampling monitoring unit (5) is configured to be data-connected to the data analysis unit (2), obtain the analyzed treatment plan data, search for expected treatment effect data according to the treatment plan data, obtain the best sampling time point for the symptom data according to the expected 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; A data storage unit (6) is configured to store a standard template for recording each case data, a standard information page and its associated diagnosis and treatment frequency 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 expected treatment effect data; The data request processing unit (7) is configured to be data-connected to the data interaction unit (1), obtain and respond to a data query request input by a user terminal, output a corresponding standard information page and / or a data reference queue, or obtain and respond to a data storage request input by a user terminal, receive the input case information, parse and extract the case data therein, convert it into the standard information page and / or the data reference queue, and store it.

8. The intelligent management system for case information according to claim 7, characterized in that: The data storage unit (6) also stores in association: Each symptom data and the corresponding multiple treatment plans, as well as a reliability reference value used to characterize the strength of the association between the treatment plan and the symptom data; as well as Setting the disease data and its corresponding treatment plan data, treatment effect data and the generation time of the above data; The management system also includes: The treatment plan reliability determination unit (8) is data-connected to the data analysis unit (2), 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; The efficacy path query unit (9) 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 end.

9. The intelligent management system for case information according to claim 7, characterized in that: The management system also includes: The data linkage collection unit includes a plurality of monitors and / or wearable devices for collecting physiological parameter data of patients, and is configured to be connected to the data sampling monitoring unit (5) by signal, receive and respond to the sampling time point output by the sampling monitoring unit, collect corresponding disease data and output it to the data analysis unit (2).

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

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