Medical risk control method, server and storage medium

Abstract

The embodiment of the present application discloses a medical risk control method, server and storage medium, which involves data analysis technology, can avoid the misuse of drugs and ensure the safety and rationality of drug use. The method includes: obtaining the patient's diagnosis and treatment information to be tested, the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested; the diagnosis and treatment information to be tested carries a diagnosis and treatment label, the diagnosis and treatment label is the current symptom or the type of drug to be tested; according to the diagnosis and treatment label, the corresponding medical information is obtained in the medical knowledge database; the matching degree between the diagnosis and treatment information to be tested and the medical information is calculated; according to the matching degree, different levels of warning information are issued.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and in particular to a medical risk control method, a server and a storage medium. Background Art

[0002] With the continuous improvement of modern medicine, the number and types of clinical drugs have increased rapidly, and the forms of medication have diversified, which provides doctors with more treatment methods and brings good news to patients.

[0003] However, the variety of drugs and treatment methods also make it more difficult for medical staff to use drugs correctly. As a result, many patients suffer from drug-induced diseases due to drug misuse or irrational use. The situation of safe drug use is becoming increasingly severe and has become a complex task involving a wide range of areas and high difficulty. Summary of the invention

[0004] The embodiments of the present application provide a medical risk control method, a server, and a storage medium, which involve data analysis technology, and can avoid the misuse of drugs and ensure the safety and rationality of drug use.

[0005] In the first aspect, an embodiment of the present application provides a medical risk control method, which includes: obtaining the patient's diagnosis and treatment information to be tested, the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested; the diagnosis and treatment information to be tested carries a diagnosis and treatment label, and the diagnosis and treatment label is the current symptom or the type of drug to be tested; obtaining corresponding medical information in a medical knowledge database according to the diagnosis and treatment label; calculating the degree of match between the diagnosis and treatment information to be tested and the medical information; and issuing different levels of warning information according to the degree of match.

[0006] As a possible implementation manner, obtaining corresponding medical information in a medical knowledge database according to the diagnosis and treatment label includes: obtaining corresponding therapeutic drug varieties and therapeutic drug dosages in a medical knowledge database according to the current symptoms; calculating the degree of match between the diagnosis and treatment information to be tested and the medical information includes: respectively calculating the similarity between the drug variety to be tested and the therapeutic drug variety to obtain a first similarity, and calculating the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug to obtain a second similarity; and multiplying the first similarity and the second similarity by their respective weights and then adding them together to obtain the degree of match.

[0007] As a possible implementation, the obtaining of corresponding medical information in a medical knowledge database according to the diagnosis and treatment label includes: obtaining corresponding indications, and therapeutic drug types and dosages of therapeutic drugs corresponding to the indications in a medical knowledge database according to the drug to be tested; and calculating the matching degree between the diagnosis and treatment information to be tested and the medical information includes:

[0008] The similarity between the current disease and the indication is calculated to obtain a first similarity, the similarity between the drug type to be tested and the therapeutic drug type is calculated to obtain a second similarity, and the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug is calculated to obtain a third similarity; the first similarity, the second similarity and the third similarity are multiplied by their respective weights and then added to obtain the matching degree.

[0009] As a possible implementation manner, the obtaining of the patient's diagnosis and treatment information to be tested, wherein the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, includes:

[0010] The patient's diagnosis and treatment information to be tested is obtained, wherein the diagnosis and treatment information to be tested includes medical record information, current symptoms and prescription information to be tested, and the medical record information includes: basic personal information, disease status, physiological status, and drug allergy history.

[0011] As a possible implementation, after obtaining the corresponding medical information in the medical knowledge database according to the diagnosis and treatment label, the method also includes: determining the patient type to which the patient belongs based on the medical record information; if it is determined based on the medical information that the diagnosis and treatment information to be tested includes prohibited drugs for the patient type, issuing a corresponding warning message; or, if it is determined based on the medical information that a certain drug in the diagnosis and treatment information to be tested has reached a prohibited dose for the patient type, issuing a corresponding warning message.

[0012] As a possible implementation, obtaining corresponding medical information in a medical knowledge database based on the diagnosis and treatment label includes: inputting the diagnosis and treatment label into a medical knowledge model to obtain corresponding medical information; the medical knowledge model is an artificial neural network model, which is obtained by learning and training various indications and treatment plans for the various indications.

[0013] As a possible implementation, the method further includes: when the matching degree reaches an excellent threshold, storing the diagnosis and treatment information to be tested into the medical knowledge database.

[0014] In the second aspect, an embodiment of the present application provides a server, comprising: a diagnosis and treatment information acquisition module, a medical information acquisition module, a calculation module, and a warning module; the diagnosis and treatment information acquisition module is used to obtain the patient's diagnosis and treatment information to be tested, the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, and the prescription information to be tested includes the type of drugs to be tested and the dosage of the drugs to be tested; the diagnosis and treatment information to be tested carries a diagnosis and treatment label, and the diagnosis and treatment label is the current symptom or the type of drug to be tested; the medical information acquisition module is used to obtain corresponding medical information in a medical knowledge database according to the diagnosis and treatment label; the calculation module is used to calculate the degree of match between the diagnosis and treatment information to be tested and the medical information; the warning module is used to issue different levels of warning information according to the degree of match.

[0015] In the third aspect, an embodiment of the present application further provides a server, comprising: a processor, an input device, an output device and a memory, wherein the processor, input device, output device and memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the first aspect and any possible implementation manner thereof.

[0016] In a fourth aspect, an embodiment of the present application provides a computer storage medium, wherein the computer storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method of the above-mentioned first aspect and any possible implementation method thereof.

[0017] The embodiment of the present application searches for relevant medical information (i.e., relevant safe medication rules) in the medical knowledge database based on the diagnosis and treatment labels (such as current symptoms, drug types, etc.) in the patient's diagnosis and treatment information to be tested, and compares the diagnosis and treatment information to be tested with the medical information, and issues a warning of the corresponding level when the matching degree is low. That is, the embodiment timely judges the correctness of the patient's diagnosis and treatment information to be tested, avoids the misuse of drugs, and ensures the safety and rationality of drug use. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments.

[0019] Figure 1 It is a flowchart of a medical risk control method provided in the first embodiment of the present application;

[0020] Figure 2 is a flow chart of a medical risk control method provided by another embodiment of the present application;

[0021] Figure 3 It is a structural diagram of a server provided in an embodiment of the present application;

[0022] Figure 4 It is a structural diagram of another server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Mentioning "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0024] Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of this application.

[0025] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0026] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0027] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0028] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0029] In order to better understand the embodiments of the present application, the method of applying the embodiments of the present application will be introduced below.

[0030] The electronic devices mentioned in the embodiments of the present application may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices (such as smart watches, smart bracelets, pedometers, etc.), computing devices or other processing devices connected to wireless modems, and various forms of user equipment (UE), mobile stations (MS), terminal devices, etc. For the convenience of description, the above-mentioned devices are collectively referred to as electronic devices.

[0031] See also Figure 1 , is a schematic flow chart of a medical risk control method provided in the first embodiment of the present application. The method can be applied to equipment such as servers, such as Figure 1 The method may include:

[0032] 101. Obtain the patient's medical history information, current symptoms, and prescription information to be tested, wherein the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested.

[0033] In this embodiment, the patient's medical history information may specifically include: the patient's basic personal information (name, age, height and weight, etc.), disease status, physiological status, drug allergy history, patient attributes, examination data and results, treatment plan, etc. The patient's prescription information may specifically include: medication types, usage and dosage of the medication, etc.

[0034] In this embodiment, the user can obtain an account ID by registering to access the above-mentioned server, or log in to the account through his own terminal device such as a mobile phone and send a judgment request to the server to execute the above-mentioned medical risk control method; and the terminal device used by the doctor can also connect to the server for communication, and the doctor can input the patient's diagnosis and treatment information to be tested in real time to make a risk control judgment.

[0035] 102. According to the above current symptoms, obtain the corresponding therapeutic drug types and therapeutic drug dosages from the medical knowledge database.

[0036] In this embodiment, the medical knowledge database can be used to store safe medication rules, that is, it can include information data on various drugs and their corresponding indications, usage and dosage, package design, pharmacokinetic data, contraindications, adverse reactions, and pharmacology and toxicology. At the same time, the medical knowledge database can also include data on the usage and dosage of various drugs in existing clinical trials.

[0037] For example, if the patient is an oncologist and his current illness is a tumor-related disease, then medical information related to tumor-related diseases is obtained from the above-mentioned medical knowledge database, including drugs suitable for tumor-related diseases and their dosage and usage. For example, targeted drugs designed for specific environments such as tumor hypoxia, low pH, and dense new blood vessels can increase the drug concentration in tumor tissue and significantly improve the effect of tumor chemotherapy. Among them, targeted drugs (also called targeted preparations) refer to drugs or their preparations that are endowed with targeting capabilities. The purpose is to enable the drug or its carrier to target a specific lesion site and accumulate or release the active ingredient at the target site. Targeted preparations can make the drug form a relatively high concentration in the target area, thereby improving the efficacy while inhibiting toxic side effects and reducing damage to normal tissues and cells.

[0038] 103. Calculate the similarity between the drug to be tested and the therapeutic drug to obtain a first similarity, calculate the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug to obtain a second similarity; multiply the first similarity and the second similarity by their respective weights and then add them together to obtain a matching degree.

[0039] 104. Issue warning messages of different levels according to the matching degree.

[0040] In this embodiment, a higher matching degree indicates that the medication in the above-mentioned diagnosis and treatment information to be tested is more correct, and a lower matching degree indicates that the medication in the above-mentioned diagnosis and treatment information to be tested is more incorrect. Therefore, according to different matching degrees, different levels of warning information are issued to remind patients to use medication with caution.

[0041] It can be understood that this embodiment searches for relevant medical information (i.e., corresponding therapeutic drug types and therapeutic drug dosages) in the medical knowledge database based on the current symptoms in the patient's diagnostic information to be tested, and compares the diagnostic information to be tested with the medical information, and issues a corresponding level of warning when the matching degree is low. That is, this embodiment timely judges the correctness of the patient's diagnostic information to be tested, avoids the misuse of drugs, and ensures the safety and rationality of drug use.

[0042] As an optional implementation, after obtaining the corresponding medical information in the medical knowledge database according to the current symptoms, the method further includes: determining the patient type to which the patient belongs based on the medical record information; if it is determined based on the medical information that the prescription information to be tested includes prohibited drugs for the patient type, a corresponding warning message is issued; or, if it is determined based on the medical information that a certain drug in the prescription information to be tested has reached a prohibited dose for the patient type, a corresponding warning message is issued.

[0043] For example, some medicines are not suitable for pregnant women. Based on the patient's medical records, it can be analyzed whether the patient is a pregnant woman. If the patient is a pregnant woman and her prescription to be tested includes drugs that are prohibited for pregnant women, it can be determined that the prescription information to be tested includes the patient's prohibited drugs and is not suitable for the patient to use. Corresponding warning information can be issued in time to indicate that the medication is incorrect.

[0044] For example, taking antibiotics as an example, the medical knowledge database includes relevant regulations on the safe use of antibiotics: if the patient is an outpatient or emergency patient, only one combination of antibiotics can be used; if the patient is an inpatient, only two combinations of antibiotics are allowed to be used at the same time. The patient's type can be analyzed based on the case in the patient's prescription information to be tested. If the patient is an outpatient or emergency patient, and the dosage of antibiotics in the prescription to be tested is two combinations, which exceeds the patient's prohibited dosage, the corresponding warning information will be issued in time to indicate that the medication is incorrect.

[0045] It can be understood that the purpose of this embodiment is to timely determine whether the patient's prescription information to be tested contains a treatment plan that is contraindicated for the patient. If so, a warning message is issued in a timely manner to avoid harm to the patient after use.

[0046] As an optional implementation, the above-mentioned obtaining corresponding medical information in the medical knowledge database based on the above-mentioned current symptoms includes: inputting the above-mentioned current symptoms into a medical knowledge model to obtain corresponding medical information; the above-mentioned medical knowledge model is an artificial neural network model, which is obtained by learning and training various indications and treatment plans for the above-mentioned various indications.

[0047] In this embodiment, the medical knowledge model is an artificial neural network model, which has been trained and studied for various indications and treatment plans for the above-mentioned various indications. Therefore, when the above-mentioned diagnosis and treatment labels are input, for example, chronic tonsillitis is input, various treatment plans, treatment drugs and dosages, safe use regulations and other information suitable for chronic tonsillitis can be output, which is the medical information desired to be obtained.

[0048] As an optional implementation, the method further includes: when the similarity reaches an excellent threshold, storing the diagnosis and treatment information to be tested into the medical knowledge database.

[0049] It can be understood that the similarity reaching the excellent threshold value indicates that the diagnosis and treatment plan in the diagnosis and treatment information to be tested (i.e., the patient's current symptoms, prescription information to be tested, case information, etc.) is a better diagnosis and treatment plan. Storing its information in the above-mentioned medical knowledge database can enrich and update the content of the medical knowledge database, so that the entire medical risk control method can more accurately determine the drug usage in various diagnosis and treatment information to be tested in the next use. In this embodiment, the excellent threshold value can be set by a person skilled in the art according to the specific situation, and this embodiment is not limited.

[0050] See also Figure 2 , is a schematic flow chart of a medical risk control method provided in the third embodiment of the present application. The method can be applied to equipment such as servers, such as Figure 2 The method may include:

[0051] 201. Obtain the patient's medical history information, current symptoms, and prescription information to be tested, wherein the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested.

[0052] In this embodiment, the patient's medical history information may specifically include: the patient's basic personal information (name, age, height and weight, etc.), disease status, physiological status, drug allergy history, patient attributes, examination data and results, treatment plan, etc. The patient's prescription information may specifically include: medication types, usage and dosage of the medication, etc.

[0053] In this embodiment, the user can obtain an account ID by registering to access the above-mentioned server, or log in to the account through his own terminal device such as a mobile phone and send a judgment request to the server to execute the above-mentioned medical risk control method; and the terminal device used by the doctor can also connect to the server for communication, and the doctor can input the patient's diagnosis and treatment information to be tested in real time to make a risk control judgment.

[0054] 202. Obtain corresponding indications, as well as therapeutic drug types and therapeutic drug dosages corresponding to the indications from a medical knowledge database according to the drug types to be tested.

[0055] In this embodiment, the medical knowledge database can be used to store safe medication rules, that is, it can include information data on various drugs and their corresponding indications, usage and dosage, package design, pharmacokinetic data, contraindications, adverse reactions, and pharmacology and toxicology. At the same time, the medical knowledge database can also include data on the usage and dosage of various drugs in existing clinical trials.

[0056] For example, if the patient's drug to be tested is a targeted drug, medical information related to the targeted drug is obtained in the above-mentioned medical knowledge database, including: targeted drugs (also called targeted preparations) refer to drugs or their preparations that are endowed with targeting capabilities; the purpose is to enable the drug or its carrier to target a specific lesion site and accumulate or release the active ingredient at the target site. Targeted preparations can form a relatively high concentration of the drug in the target area, thereby improving the efficacy while inhibiting toxic side effects and reducing damage to normal tissues and cells; targeted drugs designed for specific environments such as tumor hypoxia, low pH, and dense new blood vessels can increase the drug concentration in tumor tissues and significantly improve the effect of tumor chemotherapy.

[0057] 203. Calculate the similarity between the current symptom and the indication to obtain a first similarity, calculate the similarity between the drug to be tested and the therapeutic drug to obtain a second similarity, and calculate the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug to obtain a third similarity; multiply the first similarity, the second similarity, and the third similarity by their respective weights and then add them together to obtain a matching degree.

[0058] 204. Issue warning messages of different levels according to the matching degree.

[0059] In this embodiment, a higher matching degree indicates that the medication in the above-mentioned diagnosis and treatment information to be tested is more correct, and a lower matching degree indicates that the medication in the above-mentioned diagnosis and treatment information to be tested is more incorrect. Therefore, according to different matching degrees, different levels of warning information are issued to remind patients to use medication with caution.

[0060] It can be understood that this embodiment searches for relevant medical information (i.e., corresponding indication information, therapeutic drug types, and therapeutic drug dosage) in the medical knowledge database based on the drug types to be tested in the patient's diagnostic information to be tested, and compares the diagnostic information to be tested with the medical information, and issues a warning of the corresponding level when the matching degree is low. That is, this embodiment timely judges the correctness of the patient's diagnostic information to be tested, avoids the misuse of drugs, and ensures the safety and rationality of drug use.

[0061] As an optional implementation, after obtaining corresponding medical information in the medical knowledge database according to the above-mentioned drug variety to be tested, the above-mentioned method further includes: determining the patient type to which the patient belongs according to the medical record information; if it is determined according to the above-mentioned medical information that the above-mentioned prescription information to be tested includes banned drugs for the above-mentioned patient type, a corresponding warning message is issued; or, if it is determined according to the above-mentioned medical information that a certain drug in the above-mentioned prescription information to be tested has reached a banned dose for the above-mentioned patient type, a corresponding warning message is issued.

[0062] For example, some medicines are not suitable for pregnant women. Based on the patient's medical records, it can be analyzed whether the patient is a pregnant woman. If the patient is a pregnant woman and her prescription to be tested includes drugs that are prohibited for pregnant women, it can be determined that the prescription information to be tested includes the patient's prohibited drugs and is not suitable for the patient to use. Corresponding warning information can be issued in time to indicate that the medication is incorrect.

[0063] For example, taking antibiotics as an example, the medical knowledge database includes relevant regulations on the safe use of antibiotics: if the patient is an outpatient or emergency patient, only one combination of antibiotics can be used; if the patient is an inpatient, only two combinations of antibiotics are allowed to be used at the same time. The patient's type can be analyzed based on the case in the patient's prescription information to be tested. If the patient is an outpatient or emergency patient, and the dosage of antibiotics in the prescription to be tested is two combinations, which exceeds the patient's prohibited dosage, the corresponding warning information will be issued in time to indicate that the medication is incorrect.

[0064] It can be understood that the purpose of this embodiment is to timely determine whether the patient's prescription information to be tested contains a treatment plan that is contraindicated for the patient. If so, a warning message is issued in a timely manner to avoid harm to the patient after use.

[0065] As an optional implementation, the above-mentioned obtaining corresponding medical information in the medical knowledge database based on the above-mentioned drug varieties to be tested includes: inputting the above-mentioned drug varieties to be tested into a medical knowledge model to obtain corresponding medical information; the above-mentioned medical knowledge model is an artificial neural network model, which is obtained by learning and training various indications and treatment plans for the above-mentioned various indications.

[0066] In this embodiment, the medical knowledge model is an artificial neural network model, which has been trained and studied for various indications and treatment plans for the above-mentioned various indications. Therefore, when the above-mentioned drug varieties to be tested are input, such as anti-inflammatory drugs for chronic tonsillitis, various treatment plans, therapeutic drugs and dosages, safe use regulations and other information suitable for chronic tonsillitis can be output, which is the medical information desired to be obtained.

[0067] As an optional implementation, the method further includes: when the similarity reaches an excellent threshold, storing the diagnosis and treatment information to be tested into the medical knowledge database.

[0068] It can be understood that the similarity reaching the excellent threshold value indicates that the diagnosis and treatment plan in the diagnosis and treatment information to be tested (i.e., the patient's current symptoms, prescription information to be tested, case information, etc.) is a better diagnosis and treatment plan. Storing its information in the above-mentioned medical knowledge database can enrich and update the content of the medical knowledge database, so that the entire medical risk control method can more accurately determine the drug usage in various diagnosis and treatment information to be tested in the next use. In this embodiment, the excellent threshold value can be set by a person skilled in the art according to the specific situation, and this embodiment is not limited.

[0069] See also Figure 3 , Figure 3 300 is a schematic diagram of the structure of a server provided in an embodiment of the present application, the server 300 includes: a diagnosis and treatment information acquisition module 301, a medical information acquisition module 302, a calculation module 303, and a warning module 304;

[0070] The diagnosis and treatment information acquisition module 301 is used to acquire the patient's diagnosis and treatment information to be tested, wherein the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, wherein the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested; the diagnosis and treatment information to be tested carries a diagnosis and treatment label, wherein the diagnosis and treatment label is the current symptom or the type of drug to be tested; the medical information acquisition module 302 is used to acquire corresponding medical information in the medical knowledge database according to the diagnosis and treatment label;

[0071] A calculation module 303 is used to calculate the matching degree between the diagnosis and treatment information to be tested and the medical information;

[0072] The warning module 304 is used to issue warning messages of different levels according to the matching degree.

[0073] As a possible implementation, the medical information acquisition module 302 is specifically used to obtain the corresponding therapeutic drug varieties and therapeutic drug dosages in the medical knowledge database according to the current symptoms; the calculation module 303 is specifically used to respectively calculate the similarity between the drug variety to be tested and the therapeutic drug variety to obtain a first similarity, and calculate the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug to obtain a second similarity; the first similarity and the second similarity are multiplied by their respective weights and then added to obtain the matching degree.

[0074] As a possible implementation, the medical information acquisition module 302 is specifically used to obtain the corresponding indications, the therapeutic drug varieties and therapeutic drug dosages corresponding to the indications in the medical knowledge database according to the drug varieties to be tested; the calculation module 303 is specifically used to respectively calculate the similarity between the current disease and the indication to obtain a first similarity, calculate the similarity between the drug varieties to be tested and the therapeutic drug varieties to obtain a second similarity, and calculate the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug to obtain a third similarity; the first similarity, the second similarity and the third similarity are multiplied by their respective weights and then added to obtain the matching degree. As a possible implementation, the server 300 also includes: a prohibited drug warning module 305, which is used to determine the patient type to which the patient belongs according to the medical record information; if it is determined according to the medical information that the diagnostic and treatment information to be tested includes prohibited drugs of the patient type, a corresponding warning message is issued; or, if it is determined according to the medical information that a certain drug in the diagnostic and treatment information to be tested has reached a prohibited dose of the patient type, a corresponding warning message is issued.

[0075] As a possible implementation, the medical information acquisition module 302 is specifically used to input the diagnosis and treatment label into the medical knowledge model to obtain corresponding medical information; the medical knowledge model is an artificial neural network model, which is obtained by learning and training various indications and treatment plans for the various indications.

[0076] As a possible implementation, the server 300 further includes: a storage module 306, which is used to store the diagnosis and treatment information to be tested into the medical knowledge database when the matching degree reaches an excellent threshold.

[0077] According to the specific implementation of the embodiment of this application, Figure 1-Figure 3 The steps involved in the medical risk control method shown can be Figure 3 The various modules in the server 300 shown are executed. For example, Figure 1 Steps 101 to 104 in the above example can be respectively performed by Figure 3 The diagnosis and treatment information acquisition module 301, medical information acquisition module 302, calculation module 303, and warning module 304 shown in are executed.

[0078] The server 300 of the embodiment of the present application can search for relevant medical information (i.e., relevant safe medication rules) in the medical knowledge database according to the diagnosis and treatment labels (such as current symptoms, drug types, etc.) in the patient's diagnosis and treatment information to be tested, and compare the diagnosis and treatment information to be tested with the medical information, and issue a warning of the corresponding level when the matching degree is low. That is, the present embodiment timely judges the correctness of the patient's diagnosis and treatment information to be tested, avoids the misuse of drugs, and ensures the safety and rationality of drug use.

[0079] See also Figure 4 , Figure 4 Schematic diagram of another server structure disclosed in the embodiment of the present application. Figure 4 As shown, the server 400 includes a processor 401 and a memory 402, wherein the server 400 may also include a bus 403, the processor 401 and the memory 402 may be connected to each other via the bus 403, and the bus 403 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus 403 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The bus 400 is represented by only one thick line, but it does not mean that there is only one bus or one type of bus. The server 400 may also include an input and output device 404, and the input and output device 404 may include a display screen, such as a liquid crystal display screen. The memory 402 is used to store one or more programs containing instructions; the processor 401 is used to call the instructions stored in the memory 402 to execute the above Figure 1-Figure 3 Some or all of the method steps mentioned in the examples.

[0080] It should be understood that in the embodiment of the present application, the processor 401 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0081] Input devices may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and output devices may include a display (LCD, etc.), a speaker, etc.

[0082] The memory 402 may include a read-only memory and a random access memory, and provide instructions and data to the processor 401. A portion of the memory 402 may also include a non-volatile random access memory. For example, the memory 402 may also store information about the device type.

[0083] The server 400 of the embodiment of the present application can search for relevant medical information (i.e., relevant safe medication rules) in the medical knowledge database according to the diagnosis and treatment labels (such as current symptoms, drug types, etc.) in the patient's diagnosis and treatment information to be tested, and compare the diagnosis and treatment information to be tested with the medical information, and issue a warning of the corresponding level when the matching degree is low. That is, the present embodiment timely judges the correctness of the patient's diagnosis and treatment information to be tested, avoids the misuse of drugs, and ensures the safety and rationality of drug use.

[0084] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the interface testing methods recorded in the above method embodiments.

[0085] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0086] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the modules, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or modules can be electrical or other forms.

[0087] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0088] If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, magnetic disk or optical disk, etc., various media that can store program codes.

Claims

1. A medical risk control method, It is characterized in that The method comprises: Obtain the patient's diagnosis and treatment information to be tested, the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested, the medical history information includes the patient's personal basic information, disease status, physiological status, drug allergy history, patient attributes, examination data and results, treatment plan, and the patient's personal basic information includes name, age, height, and weight; Acquire first medical information from a medical knowledge database according to the current symptom, wherein the first medical information includes corresponding therapeutic drug varieties and therapeutic drug dosages, and the medical knowledge database is used to store safe medication rules, and the medical knowledge database includes information data on various drugs and their corresponding indications, usage and dosage, package design, pharmacokinetic data, contraindications, adverse reactions, and pharmacology and toxicology, and the medical knowledge database also includes usage and dosage data of various drugs in existing clinical trials; Determining the patient type of the patient according to the medical record information, the patient type including at least one of a pregnant woman, an outpatient, an emergency patient, or an inpatient; If it is determined based on the first medical information that the diagnostic and treatment information to be tested includes prohibited drugs for the patient type, a corresponding warning message is issued; or, if it is determined based on the first medical information that a certain drug in the diagnostic and treatment information to be tested reaches a prohibited dose for the patient type, a corresponding warning message is issued; The similarity between the drug to be tested and the drug to be treated is calculated to obtain a first similarity, and the similarity between the dosage of the drug to be tested and the dosage of the drug to be treated is calculated to obtain a second similarity; the first similarity and the second similarity are multiplied by their respective weights and then added to obtain a first matching degree, and different levels of warning information are issued according to the magnitude of the first matching degree; If the first matching degree is greater than the excellent threshold, the diagnosis and treatment information to be tested is stored in the medical knowledge database, and the first matching degree being greater than the excellent threshold indicates that the diagnosis and treatment plan in the diagnosis and treatment information to be tested is a better diagnosis and treatment plan; Searching for relevant second medical information in a medical knowledge database according to the drug type to be tested in the diagnosis and treatment information to be tested, wherein the second medical information includes corresponding indications, therapeutic drug types and therapeutic drug dosages; The similarity between the current disease and the indication is calculated to obtain a first similarity, the similarity between the drug to be tested and the therapeutic drug is calculated to obtain a second similarity, and the similarity between the dosage of the drug to be tested and the dosage of the therapeutic drug is calculated to obtain a third similarity; the first similarity, the second similarity and the third similarity are multiplied by their respective weights and then added to obtain a second matching degree; issuing warning messages of different levels according to the magnitude of the second matching degree; When the second matching degree is greater than an excellent threshold, the diagnosis and treatment information to be tested is stored in the medical knowledge database.

2. The method according to claim 1, It is characterized in that The acquiring first medical information from a medical knowledge database according to the current symptom includes: The current symptom is input into a medical knowledge model to obtain corresponding first medical information; the medical knowledge model is an artificial neural network model obtained by learning and training various indications and treatment plans for the various indications.

3. The method according to claim 1, It is characterized in that The step of searching the medical knowledge database for relevant second medical information according to the drug to be tested in the diagnosis and treatment information to be tested includes: The drug variety to be tested is input into a medical knowledge model to obtain corresponding second medical information; the medical knowledge model is an artificial neural network model obtained by learning and training various indications and treatment plans for the various indications.

4. A server, It is characterized in that The server comprises a module for executing the method according to any one of claims 1 to 3, the server comprising: a diagnosis and treatment information acquisition module, a medical information acquisition module, a calculation module, and a warning module; The diagnosis and treatment information acquisition module is used to obtain the patient's diagnosis and treatment information to be tested, the diagnosis and treatment information to be tested includes medical history information, current symptoms and prescription information to be tested, the prescription information to be tested includes the type of drug to be tested and the dosage of the drug to be tested; the diagnosis and treatment information to be tested carries a diagnosis and treatment label, and the diagnosis and treatment label is the current symptom or the type of drug to be tested; The medical information acquisition module is used to acquire corresponding medical information in the medical knowledge database according to the diagnosis and treatment label; The calculation module is used to calculate the matching degree between the diagnosis and treatment information to be tested and the medical information; The warning module is used to issue warning messages of different levels according to the matching degree.

5. A server, It is characterized in that The method comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 1 to 3.

6. A computer storage medium, It is characterized in that The computer storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 3.

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