Doctor experience party management method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a doctor experience party management method and device, electronic equipment and a storage medium, and relates to the technical field of information processing. The physician experience party management method comprises the following steps: acquiring a plurality of historical experience parties issued by a user for a target disease, and acquiring target adverse reaction information fed back by a patient; wherein at least part of medicines in the plurality of historical experience prescriptions are the same; determining a target historical experience party from the plurality of historical experience parties; wherein the target historical experience prescription comprises a target drug associated with the target adverse reaction information; generating a modification prompt message of the target historical experience party according to the target medicine, and sending the modification prompt message to a user; and modifying the target historical experience party according to a modification instruction input by a user for the modification prompt message to obtain a modified target historical experience party. According to the embodiment of the invention, the technical effect of intelligently managing doctor experience parties can be realized.

Description

Technical Field

[0001] This application relates to the field of information processing technologies, and more particularly, to a method, apparatus, electronic device, and storage medium for managing physicians' empirical prescriptions. Background Art

[0002] During the process of traditional Chinese medicine (TCM) physicians' diagnosis and prescription writing, physicians of different schools often prescribe empirical prescriptions to patients based on their personal medical practice experience and medication habits. Since the TCM prescriptions preset for a certain disease condition in the TCM diagnosis and treatment platform usually cannot be compatible with the content of the empirical prescriptions prescribed by physicians of different schools for this disease condition, there is currently no setting and application of the empirical prescriptions of physicians of various schools in the TCM diagnosis and treatment platform, resulting in the inability to perform intelligent management such as unified review, calibration, and update on the multiple empirical prescriptions of physicians of various schools. Relying solely on manual management makes it easy for physicians' empirical prescriptions to face the risk of being lost. Summary of the Invention

[0003] The purpose of the embodiments of this application is to provide a method, apparatus, electronic device, and storage medium for managing physicians' empirical prescriptions, so as to achieve the technical effect of intelligent management of physicians' empirical prescriptions.

[0004] In a first aspect, the embodiments of this application provide a method for managing physicians' empirical prescriptions, including:

[0005] Obtain multiple historical empirical prescriptions issued by a user for a target disease condition, and obtain target adverse reaction information feedback by a patient; wherein, at least some of the drugs in the multiple historical empirical prescriptions are the same;

[0006] Determine a target historical empirical prescription from the multiple historical empirical prescriptions; wherein, the target historical empirical prescription includes a target drug associated with the target adverse reaction information;

[0007] Generate a modification prompt message for the target historical empirical prescription based on the target drug, and send the modification prompt message to the user;

[0008] Modify the target historical empirical prescription according to the modification instruction input by the user for the modification prompt message to obtain a modified target historical empirical prescription.

[0009] In the above implementation process, by obtaining multiple historical empirical prescriptions issued by a user for a target disease or syndrome, as well as target adverse reaction information feedback by a patient, a target historical empirical prescription including a target drug associated with the target adverse reaction information is determined from the multiple historical empirical prescriptions, a modification prompt message for the target historical empirical prescription is generated based on the target drug, the modification prompt message is sent to the user, and according to the modification instruction input by the user for the modification prompt message, the target historical empirical prescription is modified to obtain a modified target historical empirical prescription, which can audit multiple historical empirical prescriptions based on the patient feedback mechanism, determine problematic empirical prescriptions among the multiple historical empirical prescriptions, prompt the user to calibrate the problematic empirical prescriptions, and complete intelligent management such as unified auditing and calibration of multiple empirical prescriptions of the same physician, thereby realizing intelligent management of the physician's empirical prescriptions.

[0010] Further, the obtaining of the target adverse reaction information feedback by the patient includes:

[0011] Extracting adverse reaction information from the patient follow-up visit information corresponding to the multiple historical empirical prescriptions to obtain multiple types of adverse reaction information;

[0012] Determining the adverse reaction information that meets the first condition among the multiple types of adverse reaction information as the target adverse reaction information; wherein, the first condition includes that the occurrence frequency of the adverse reaction information in the patient follow-up visit information corresponding to the multiple historical empirical prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold.

[0013] In the above implementation process, by presetting the first condition and determining the adverse reaction information that meets the first condition in the patient follow-up visit information corresponding to the multiple historical empirical prescriptions as the target adverse reaction information, the target adverse reaction information can be quickly and accurately determined from the patient follow-up visit information corresponding to the multiple historical empirical prescriptions, and by presetting the first condition including that the occurrence frequency of the adverse reaction information in the patient follow-up visit information corresponding to the multiple historical empirical prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold, the target adverse reaction information indicating high-frequency adverse reactions and / or severe adverse reactions can be quickly and accurately determined from the patient follow-up visit information corresponding to the multiple historical empirical prescriptions, thereby better realizing the intelligent management of the physician's empirical prescriptions.

[0014] Further, before determining the target historical empirical prescription from the multiple historical empirical prescriptions, it further includes:

[0015] Determining one or more preselected historical empirical prescriptions from the multiple historical empirical prescriptions; wherein, the patient follow-up visit information corresponding to the one or more preselected historical empirical prescriptions includes the target adverse reaction information.

[0016] Extract drugs from the multiple historical empirical prescriptions to obtain multiple preliminary selected drugs;

[0017] Determine the preliminary selected drugs that meet the second condition among the multiple preliminary selected drugs; wherein, the second condition includes that the occurrence frequency of the preliminary selected drug in the multiple historical empirical prescriptions reaches a preset second frequency threshold;

[0018] If the preliminary selected historical empirical prescription including the re - selected drug meets the preset quantity condition, then determine the re - selected drug as the target drug.

[0019] In the above implementation process, by determining one or more preliminary selected historical empirical prescriptions from multiple historical empirical prescriptions, the patient follow - up visit information corresponding to the one or more preliminary selected historical empirical prescriptions includes the target adverse reaction information, determining the preliminary selected drugs that meet the second condition among the multiple historical empirical prescriptions as the re - selected drugs, and if the preliminary selected historical empirical prescription including the re - selected drug meets the preset quantity condition, then determining the re - selected drug as the target drug, it is possible to quickly and accurately determine the target drug that is exactly associated with the target adverse reaction information from multiple historical empirical prescriptions. And by setting the second condition that the occurrence frequency of the preliminary selected drug in the multiple historical empirical prescriptions reaches a preset second frequency threshold, it is possible to quickly and accurately determine the drugs frequently used by users from multiple historical empirical prescriptions, thus better realizing the intelligent management of physicians' empirical prescriptions.

[0020] Further, before determining the target historical empirical prescription from the multiple historical empirical prescriptions, it further includes:

[0021] Determine one or more preliminary selected historical empirical prescriptions from the multiple historical empirical prescriptions; wherein, the patient follow - up visit information corresponding to the one or more preliminary selected historical empirical prescriptions includes the target adverse reaction information;

[0022] Extract drugs from the one or more preliminary selected historical empirical prescriptions to obtain multiple preliminary selected drugs;

[0023] Determine the preliminary selected drugs that meet the third condition among the multiple preliminary selected drugs as the target drugs; wherein, the third condition includes that the occurrence frequency of the preliminary selected drug in the one or more preliminary selected historical empirical prescriptions reaches a preset third frequency threshold, and the preliminary selected drug is an auxiliary drug.

[0024] In the above implementation process, by determining one or more preselected historical experience parties from multiple historical experience parties, the patient follow-up visit information corresponding to the one or more preselected historical experience parties includes target adverse reaction information, and determining the preselected drugs that meet the third condition among the multiple preselected drugs of all the preselected historical experience parties as the target drugs, it is possible to more quickly determine the target drugs associated with the target adverse reaction information from multiple historical experience parties, and by setting the third condition to include that the occurrence frequency of the preselected drugs in one or more preselected historical experience parties reaches a preset third frequency threshold, and the preselected drugs are adjuvant drugs, it is possible to quickly and accurately determine the adjuvant drugs frequently used by the user from all the preselected historical experience parties, so as to better realize the intelligent management of doctors' experience prescriptions.

[0025] Further, generating the modified prompt message for the target historical experience prescription according to the target drug includes:

[0026] In the case where a preset update cycle arrives, generating a first modified prompt message for the target historical experience prescription according to the target drug; or,

[0027] In the case where a prescription request initiated by the user for the target historical experience prescription is obtained, generating a second modified prompt message for the target historical experience prescription according to the target drug.

[0028] In the above implementation process, by generating a first modified prompt message for the target historical experience prescription according to the target drug in the case where a preset update cycle arrives, or generating a second modified prompt message for the target historical experience prescription according to the target drug in the case where a prescription request initiated by the user for the target historical experience prescription is obtained, it is possible to prompt the user to calibrate the problematic experience prescription when the update cycle arrives or the user selects the target historical experience prescription for prescribing, so as to better realize the intelligent management of doctors' experience prescriptions.

[0029] Further, the modified prompt message carries the pharmaceutical information of the target drug; wherein, the pharmaceutical information includes efficacy information and / or pharmacological information.

[0030] In the above implementation process, by adding pharmaceutical information such as the efficacy information and / or pharmacological information of the target drug to the modified prompt message, it is possible to facilitate the user to view the pharmaceutical information of the target drug together, assist the user in quickly selecting whether to modify the target historical experience prescription, so as to better realize the intelligent management of doctors' experience prescriptions.

[0031] Further, the generating the second modified prompt message for the target historical experience prescription according to the target drug in the case where a prescription request initiated by the user for the target historical experience prescription is obtained includes:

[0032] In response to the prescription request, obtain the patient diagnosis and treatment information of the current patient; wherein, the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information;

[0033] Generate the second modification prompt message; wherein, the second modification prompt message carries the pharmaceutical information of the target drug and the alternative drugs corresponding to the patient diagnosis and treatment information; the pharmaceutical information includes efficacy information and / or pharmacological information.

[0034] In the above implementation process, by responding to the prescription request initiated by the user for the target historical empirical formula, obtain the patient diagnosis and treatment information of the current patient, where the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information, and add pharmaceutical information such as the efficacy information and / or pharmacological information of the target drug, as well as the alternative drugs corresponding to the patient diagnosis and treatment information, to the generated second modification prompt message, which can facilitate the user to view the pharmaceutical information of the target drug and the alternative drugs corresponding to the patient diagnosis and treatment information together, assist the user in prescribing the optimal prescription for the current patient's illness condition, and thus better realize the intelligent management of the physician's empirical formula.

[0035] In a second aspect, an embodiment of the present application provides a physician's empirical formula management device, including:

[0036] A historical data acquisition module, configured to acquire a plurality of historical empirical formulas prescribed by the user for the target disease condition, and acquire the target adverse reaction information feedback by the patient; wherein, at least some of the drugs in the plurality of historical empirical formulas are the same;

[0037] A target prescription acquisition module, configured to determine a target historical empirical formula from the plurality of historical empirical formulas; wherein, the target historical empirical formula includes a target drug associated with the target adverse reaction information;

[0038] A prescription modification prompt module, configured to generate a modification prompt message for the target historical empirical formula according to the target drug, and send the modification prompt message to the user;

[0039] A prescription modification and update module, configured to modify the target historical empirical formula according to the modification instruction input by the user for the modification prompt message, to obtain a modified target historical empirical formula.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor; when the processor executes the computer program, the above-mentioned method is implemented.

[0041] Fourthly, an embodiment of the present application provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a schematic flowchart of a method for managing a doctor's empirical prescription provided by the first embodiment of the present application;

[0044] Figure 2 It is a schematic structural diagram of a device for managing a doctor's empirical prescription provided by the second embodiment of the present application;

[0045] Figure 3 It is a schematic structural diagram of an electronic device provided by the third embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The following will describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0047] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions, and cannot be understood as indicating or implying relative importance.

[0048] Traditional Chinese medicine has complex schools, and the dialectical prescription ideas of each school are somewhat different. In the process of traditional Chinese medicine doctors' consultation and prescription, doctors of different schools often prescribe empirical prescriptions to patients according to their personal medical experience and medication habits.

[0049] In the related art, since the traditional Chinese medicine prescriptions preset for a certain disease syndrome in the traditional Chinese medicine diagnosis and treatment platform usually cannot be compatible with the content of the empirical prescriptions prescribed by doctors of different schools for this disease syndrome, there is currently no setting and application of the empirical prescriptions of doctors of each school in the traditional Chinese medicine diagnosis and treatment platform, resulting in the inability to conduct intelligent management such as unified review, calibration, and update of the multiple empirical prescriptions of doctors of each school. Relying solely on manual management easily risks the loss of doctors' experience.

[0050] To this end, the present application proposes a management method for physicians' empirical prescriptions. By obtaining multiple historical empirical prescriptions issued by a user for a target disease syndrome, and target adverse reaction information feedback by a patient, a target historical empirical prescription including a target drug associated with the target adverse reaction information is determined from the multiple historical empirical prescriptions, a modification prompt message for the target historical empirical prescription is generated based on the target drug, the modification prompt message is sent to the user, and according to the modification instruction input by the user for the modification prompt message, the target historical empirical prescription is modified to obtain a modified target historical empirical prescription, which can review multiple historical empirical prescriptions based on the patient feedback mechanism, determine the problematic empirical prescriptions among the multiple historical empirical prescriptions, prompt the user to calibrate the problematic empirical prescriptions, and complete intelligent management such as unified review and calibration of multiple empirical prescriptions of the same physician, thereby realizing intelligent management of physicians' empirical prescriptions.

[0051] The following combines Figure 1 to describe a management method for physicians' empirical prescriptions provided by the first embodiment of the present application. The management method for physicians' empirical prescriptions provided by the first embodiment of the present application can be executed by a terminal device deployed with a traditional Chinese medicine diagnosis and treatment platform, such as a user terminal held by a physician, such as a mobile phone, a tablet computer, or a computer. The following takes the user terminal as the execution subject for illustration.

[0052] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a management method for physicians' empirical prescriptions provided by the first embodiment of the present application. The first embodiment of the present application provides a management method for physicians' empirical prescriptions, including steps S101 to S104:

[0053] S101. Obtain multiple historical empirical prescriptions issued by a user for a target disease syndrome, and obtain target adverse reaction information feedback by a patient; wherein, at least some of the drugs in the multiple historical empirical prescriptions are the same.

[0054] Exemplarily, according to actual application requirements, any disease syndrome is pre-selected as the target disease syndrome.

[0055] It should be noted that a disease syndrome refers to a disease and its syndromes. The same disease has one or more syndromes. For example, for the disease of "constipation", there are multiple syndromes such as "syndrome of accumulated heat in the intestines and stomach"; for the disease of "cold", there are multiple syndromes such as "syndrome of wind-heat cold", "syndrome of wind-cold cold", and "syndrome of summer-damp cold".

[0056] The user terminal determines a preset target disease syndrome, obtains multiple historical empirical prescriptions issued by the user for the target disease syndrome, and obtains target adverse reaction information feedback by a patient, wherein at least some of the drugs in the multiple historical empirical prescriptions are the same.

[0057] It should be noted that each of the multiple historical empirical prescriptions is an empirical prescription previously prescribed by the user for each patient suffering from the target disease or syndrome. Since the multiple historical empirical prescriptions are prescribed by the same user for the same disease or syndrome, at least some of the drugs in the multiple historical empirical prescriptions are the same. After each patient treats the target disease or syndrome according to the respective obtained historical empirical prescription, one or more adverse reactions may occur. Different patients may have the same or different types of adverse reactions. The target adverse reaction information feedback by these patients is used to indicate one or more adverse reactions that occur in these patients.

[0058] S102. Determine a target historical empirical prescription from the multiple historical empirical prescriptions; wherein, the target historical empirical prescription includes target drugs associated with the target adverse reaction information.

[0059] Exemplarily, after obtaining the multiple historical empirical prescriptions and the target adverse reaction information, the user terminal determines the target drugs associated with the target adverse reaction information, and determines the target historical empirical prescription from the multiple historical empirical prescriptions, wherein the target historical empirical prescription includes the target drugs.

[0060] It should be noted that the target drugs are the drugs in the multiple historical empirical prescriptions that cause one or more adverse reactions in these patients.

[0061] In practical applications, for each historical empirical prescription among the multiple historical empirical prescriptions, the user terminal can retrieve the target drugs from this historical empirical prescription. If the target drugs are retrieved from this historical empirical prescription, it is confirmed that this historical empirical prescription includes the target drugs, and this historical empirical prescription is determined as the target historical empirical prescription; otherwise, no processing is performed, so as to determine the target historical empirical prescription from the multiple historical empirical prescriptions.

[0062] S103. Generate a modification prompt message for the target historical empirical prescription according to the target drugs, and send the modification prompt message to the user.

[0063] Exemplarily, after determining the target drugs and the target historical empirical prescription, the user terminal generates a modification prompt message for the target historical empirical prescription according to the target drugs, and sends the modification prompt message to the user, so that the user can view the modification prompt message and select whether to modify the target historical empirical prescription.

[0064] In practical applications, after generating the modification prompt message, the user terminal can visually display the modification prompt message, so that the user can directly view the modification prompt message on the user terminal and select whether to modify the target historical empirical prescription.

[0065] S104. Modify the target historical empirical prescription according to the modification instruction input by the user for the modification prompt message, and obtain the modified target historical empirical prescription.

[0066] Exemplarily, after receiving the modification prompt message, the user can, according to actual application requirements, select whether to modify the target historical experience prescription. If so, determine the modification content of the target historical experience prescription and input a corresponding modification instruction to the user terminal.

[0067] In actual applications, the user can directly view the modification prompt message on the user terminal, select whether to modify the target historical experience prescription. If so, continue to retrieve the target historical experience prescription on the user terminal, and according to the determined modification content of the target historical experience prescription, edit the target historical experience prescription, thereby inputting a corresponding modification instruction to the user terminal.

[0068] After the user terminal obtains the modification instruction input by the user for the modification prompt message, according to this modification instruction, modify the target historical experience prescription to obtain the modified target historical experience prescription.

[0069] In the embodiment of the present application, by obtaining multiple historical experience prescriptions issued by the user for the target disease condition and the target adverse reaction information feedback by the patient, determining the target historical experience prescription including the target drug associated with the target adverse reaction information from multiple historical experience prescriptions, generating a modification prompt message for the target historical experience prescription according to the target drug, sending the modification prompt message to the user, and modifying the target historical experience prescription according to the modification instruction input by the user for the modification prompt message to obtain the modified target historical experience prescription, it is possible to review multiple historical experience prescriptions based on the patient feedback mechanism, determine the problematic experience prescriptions among multiple historical experience prescriptions, prompt the user to calibrate the problematic experience prescriptions, and complete the intelligent management such as unified review and calibration of multiple experience prescriptions of the same physician, thereby realizing the intelligent management of the physician's experience prescriptions.

[0070] In an optional embodiment, the obtaining of the target adverse reaction information feedback by the patient includes: extracting adverse reaction information from the patient follow-up visit information corresponding to multiple historical experience prescriptions to obtain multiple types of adverse reaction information; determining the adverse reaction information that meets the first condition among the multiple types of adverse reaction information as the target adverse reaction information; where the first condition includes that the occurrence frequency of the adverse reaction information in the patient follow-up visit information corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold.

[0071] Exemplarily, after the user terminal obtains multiple historical experience prescriptions, it obtains the patient follow-up visit information corresponding to the multiple historical experience prescriptions.

[0072] It should be noted that the patient follow-up visit information corresponding to each historical experience prescription among the multiple historical experience prescriptions is the follow-up visit information of the patients suffering from the target disease condition and treated according to each historical experience prescription.

[0073] After obtaining the follow-up visit information of patients corresponding to multiple historical experience prescriptions, the user terminal extracts adverse reaction information from the follow-up visit information of patients corresponding to multiple historical experience prescriptions, and obtains multiple types of adverse reaction information.

[0074] For example, assume that the target disease syndromes are "constipation" and "syndrome of accumulated heat in the intestines and stomach". After the user terminal obtains multiple historical experience prescriptions prescribed by the user for "constipation" and "syndrome of accumulated heat in the intestines and stomach", and the follow-up visit information of patients corresponding to multiple historical experience prescriptions, for the follow-up visit information of patients corresponding to each historical experience prescription among the multiple historical experience prescriptions, semantic recognition is performed on the follow-up visit information of patients corresponding to this historical experience prescription, and adverse reaction information is extracted from the follow-up visit information of patients corresponding to this historical experience prescription, such as adverse reaction information such as "diarrhea after taking the medicine" and "abdominal pain after taking the medicine", and multiple types of adverse reaction information are obtained.

[0075] Since different patients may have the same or different types of adverse reactions, the adverse reaction information extracted from the follow-up visit information of patients corresponding to each historical experience prescription may be the same or different. Considering the actual application requirements, such as accurately selecting one or more of these adverse reactions that commonly occur in these patients, and / or preferentially selecting one or more serious adverse reactions that occur in these patients, a first condition can be preset, where the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold.

[0076] It should be noted that the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold, and there are the following several situations: the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold; the first condition includes that the severity level of the adverse reaction information reaches a preset level threshold; the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold, and the severity level of the adverse reaction information reaches a preset level threshold.

[0077] After the user terminal obtains multiple types of adverse reaction information, it determines the first condition, and determines the adverse reaction information that meets the first condition among the multiple types of adverse reaction information as the target adverse reaction information.

[0078] In a preferred implementation manner of this embodiment, the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions reaches a preset first frequency threshold; the determining the adverse reaction information that meets the first condition among multiple types of adverse reaction information as the target adverse reaction information includes: for each type of adverse reaction information among the multiple types of adverse reaction information, counting the occurrence frequency of this type of adverse reaction information in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions; in the case where the occurrence frequency reaches the first frequency threshold, determining this type of adverse reaction information as the target adverse reaction information.

[0079] It should be noted that in the case where the occurrence frequency does not reach the first frequency threshold, no processing is performed.

[0080] In practical applications, the first frequency threshold can be set according to the occurrence frequency of each type of adverse reaction information in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions.

[0081] For example, after the user terminal obtains multiple types of adverse reaction information, it is determined that the multiple types of adverse reaction information include two types of adverse reaction information: "diarrhea after taking medicine" and "abdominal pain after taking medicine". Count the occurrence frequency f1 of the adverse reaction information "diarrhea after taking medicine" in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions, and count the occurrence frequency f2 of the adverse reaction information "abdominal pain after taking medicine" in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions. Assuming that the first frequency threshold is set as f3, and f2 < f3 < f1, then only the occurrence frequency f1 of the adverse reaction information "diarrhea after taking medicine" in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions reaches the first frequency threshold f3, and only the adverse reaction information "diarrhea after taking medicine" with the highest occurrence frequency is determined as the target adverse reaction information.

[0082] In another preferred implementation manner of this embodiment, the first condition includes that the severity level of the adverse reaction information reaches a preset level threshold; the determining the adverse reaction information that meets the first condition among multiple types of adverse reaction information as the target adverse reaction information includes: for each type of adverse reaction information among the multiple types of adverse reaction information, determining the severity level of this type of adverse reaction information; in the case where the severity level reaches the level threshold, determining this type of adverse reaction information as the target adverse reaction information.

[0083] It should be noted that in the case where the severity level does not reach the level threshold, no processing is performed.

[0084] In the embodiments of the present application, by presetting a first condition, the adverse reaction information that meets the first condition in the follow-up visit information of patients corresponding to multiple historical experience prescriptions is determined as the target adverse reaction information, which can quickly and accurately determine the target adverse reaction information from the follow-up visit information of patients corresponding to multiple historical experience prescriptions. And by presetting the first condition to include that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical experience prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold, the target adverse reaction information indicating high-frequency adverse reactions and / or severe adverse reactions can be quickly and accurately determined from the follow-up visit information of patients corresponding to multiple historical experience prescriptions, so as to better realize the intelligent management of physicians' experience prescriptions.

[0085] In an alternative embodiment, before determining the target historical experience prescription from multiple historical experience prescriptions, it further includes: determining one or more preselected historical experience prescriptions from multiple historical experience prescriptions; wherein, the follow-up visit information of patients corresponding to one or more preselected historical experience prescriptions includes the target adverse reaction information; extracting drugs from multiple historical experience prescriptions to obtain multiple primary selected drugs; determining the primary selected drugs that meet the second condition among the multiple primary selected drugs as the secondary selected drugs; wherein, the second condition includes that the occurrence frequency of the primary selected drugs in multiple historical experience prescriptions reaches a preset second frequency threshold; if the preselected historical experience prescription including the secondary selected drugs meets the preset quantity condition, then the secondary selected drugs are determined as the target drugs.

[0086] As an example, after the user terminal obtains multiple historical experience prescriptions and the target adverse reaction information, for the follow-up visit information of patients corresponding to each historical experience prescription, it retrieves the target adverse reaction information from the follow-up visit information of patients corresponding to this historical experience prescription. If the target adverse reaction information is retrieved from the follow-up visit information of patients corresponding to this historical experience prescription, it is confirmed that the follow-up visit information of patients corresponding to this historical experience prescription includes the target adverse reaction information, and this historical experience prescription is determined as a preselected historical experience prescription, otherwise no processing is performed, so as to determine one or more preselected historical experience prescriptions from multiple historical experience prescriptions.

[0087] After the user terminal obtains multiple historical experience prescriptions, for each historical experience prescription among the multiple historical experience prescriptions, it extracts drugs from this historical experience prescription, and determines the extracted drugs as the primary selected drugs, so as to obtain multiple primary selected drugs.

[0088] Considering that at least some of the drugs in multiple historical empirical prescriptions are the same, these drugs that appear repeatedly in multiple historical empirical prescriptions may be the commonly used drugs for the user to prescribe for the target disease syndrome. To explore the correlation between the commonly used drugs for the user to prescribe for the target disease syndrome and the target adverse reaction information, it is necessary to accurately screen the commonly used drugs for the user to prescribe for the target disease syndrome from multiple preliminary selected drugs as the reselected drugs. Therefore, a second condition can be preset, where the second condition includes that the appearance frequency of the preliminary selected drugs in multiple historical empirical prescriptions reaches a preset second frequency threshold.

[0089] After the user terminal obtains multiple preliminary selected drugs, it determines that the second condition includes that the appearance frequency of the preliminary selected drugs in multiple historical empirical prescriptions reaches a preset second frequency threshold. For each preliminary selected drug among the multiple preliminary selected drugs, it counts the appearance frequency of this preliminary selected drug in multiple historical empirical prescriptions. When the appearance frequency reaches the second frequency threshold, it determines this preliminary selected drug as a reselected drug. When the appearance frequency does not reach the second frequency threshold, no processing is performed.

[0090] In practical applications, the second frequency threshold can be set according to the appearance frequencies of each preliminary selected drug in multiple historical empirical prescriptions.

[0091] For example, after the user terminal obtains multiple preliminary selected drugs, it determines that the multiple preliminary selected drugs include "rhubarb", " mirabilite ", " white peony root ", and " raw atractylodes macrocephala ". It respectively counts the appearance frequencies of these preliminary selected drugs "rhubarb", " mirabilite ", " white peony root ", and " raw atractylodes macrocephala " in multiple historical empirical prescriptions as f4, f5, f6, and f7. Assuming that the second frequency threshold is set as f8, and f7 < f8 < {f4, f5, f6}, then only the three preliminary selected drugs "rhubarb", " mirabilite ", and " white peony root " have their appearance frequencies {f4, f5, f6} reaching the second frequency threshold f8, and these three preliminary selected drugs "rhubarb", " mirabilite ", and " white peony root " are determined as reselected drugs.

[0092] Considering that usually only a certain drug or a certain drug pair can cause the adverse reaction indicated by the target adverse reaction information to occur commonly in patients, this drug or drug pair will have an exact correlation with the target adverse reaction information. Only some of the reselected drugs may have an exact correlation with the target adverse reaction information. If the reselected drugs are directly determined as the target drugs, for example, if the three reselected drugs "rhubarb", " mirabilite ", and " white peony root " are determined as the target drugs, then because the reselected drug " white peony root " actually does not cause the adverse reaction indicated by the target adverse reaction information to occur commonly in patients, it is easy to wrongly prompt the user that the medication of " white peony root " is improper subsequently.

[0093] In order to accurately determine the target drug associated with the target adverse reaction information, a quantity condition can be preset, and the quantity condition is used to further screen out the target drug that has an exact association with the target adverse reaction information from the selected drugs. Among them, the quantity condition includes: the number of preselected historical empirical formulas including the selected drugs reaches a preset quantity threshold, or the proportion of the preselected historical empirical formulas including the selected drugs in all preselected historical empirical formulas reaches a preset proportion threshold.

[0094] After the user terminal obtains the selected drugs, it determines the preselected historical empirical formulas including the selected drugs from one or more preselected historical empirical formulas, and judges whether these preselected historical empirical formulas including the selected drugs meet the quantity condition. If so, it confirms that the selected drugs are associated with the target adverse reaction information and determines the selected drugs as the target drugs; otherwise, it does not perform any processing.

[0095] In a preferred implementation manner of this embodiment, the quantity condition includes: the number of preselected historical empirical formulas including the selected drugs reaches a preset quantity threshold; the step of determining the selected drugs as the target drugs if the preselected historical empirical formulas including the selected drugs meet the preset quantity condition includes: determining the preselected historical empirical formulas including the selected drugs from one or more preselected historical empirical formulas; counting the number of preselected historical empirical formulas including the selected drugs; and determining the selected drugs as the target drugs when the number reaches the preset quantity threshold.

[0096] In a preferred implementation manner of this embodiment, the quantity condition includes: the proportion of the preselected historical empirical formulas including the selected drugs in all preselected historical empirical formulas reaches a preset proportion threshold; the step of determining the selected drugs as the target drugs if the preselected historical empirical formulas including the selected drugs meet the preset quantity condition includes: determining the preselected historical empirical formulas including the selected drugs from one or more preselected historical empirical formulas; counting the proportion of the preselected historical empirical formulas including the selected drugs in all preselected historical empirical formulas; and determining the selected drugs as the target drugs when the proportion reaches the preset proportion threshold.

[0097] In the embodiments of the present application, by determining one or more preselected historical experience parties from multiple historical experience parties, where the patient follow-up information corresponding to the one or more preselected historical experience parties includes target adverse reaction information, determining the primary drugs that meet the second condition among the multiple historical experience parties as the alternative drugs, and if the preselected historical experience parties including the alternative drugs meet the preset quantity condition, determining the alternative drugs as the target drugs, it is possible to quickly and accurately determine the target drugs that are exactly associated with the target adverse reaction information from multiple historical experience parties. And by setting the second condition to include that the appearance frequency of the primary drugs among the multiple historical experience parties reaches the preset second frequency threshold, it is possible to quickly and accurately determine the drugs frequently used by the user from multiple historical experience parties, so as to better realize the intelligent management of the doctor's experience prescriptions.

[0098] In an alternative embodiment, before determining the target historical experience parties from multiple historical experience parties, it further includes: determining one or more preselected historical experience parties from multiple historical experience parties; wherein, the patient follow-up information corresponding to the one or more preselected historical experience parties includes target adverse reaction information; extracting drugs from the one or more preselected historical experience parties to obtain multiple preselected drugs; determining the preselected drugs that meet the third condition among the multiple preselected drugs as the target drugs; wherein, the third condition includes that the appearance frequency of the preselected drugs among the one or more preselected historical experience parties reaches the preset third frequency threshold, and the preselected drugs are auxiliary drugs.

[0099] Exemplarily, in an actual scenario, a user usually determines the basic prescription for a disease syndrome according to the disease syndrome suffered by the patient. The basic prescription includes the main drugs for treating the disease syndrome, and according to the individual symptoms of the patient, adds auxiliary drugs for assisting the main drugs in treating the disease syndrome to the basic prescription of the disease syndrome to obtain an experience prescription. Therefore, the main drugs for treating the target disease syndrome are the same among multiple historical experience parties, and the auxiliary drugs for assisting the main drugs in treating the target disease syndrome are not completely the same.

[0100] After the user terminal obtains multiple historical experience parties and target adverse reaction information, for the patient follow-up information corresponding to each historical experience party, it retrieves the target adverse reaction information from the patient follow-up information corresponding to the historical experience party. If the target adverse reaction information is retrieved from the patient follow-up information corresponding to the historical experience party, it is confirmed that the patient follow-up information corresponding to the historical experience party includes the target adverse reaction information, and the historical experience party is determined as a preselected historical experience party, otherwise no processing is performed, so as to determine one or more preselected historical experience parties from multiple historical experience parties.

[0101] After the user terminal obtains one or more preselected historical experience parties, for each preselected historical experience party, it extracts the drugs from the preselected historical experience party as the preselected drugs, so as to obtain multiple preselected drugs.

[0102] Considering that the patient follow-up information corresponding to each preselected historical experience prescription includes target adverse reaction information, the drugs frequently used by the user among all the preselected historical experience prescriptions usually include the main drugs for treating the target disease syndrome and the auxiliary drugs for assisting the main drugs in treating the target disease syndrome. The auxiliary drugs frequently used by the user are closely related to the target adverse reaction information. To more quickly determine the target drug, a third condition can be preset, and the third condition is used to directly screen the target drug from all the preselected historical experience prescriptions. Among them, the third condition includes that the appearance frequency of the preselected drug in one or more preselected historical experience prescriptions reaches a third frequency threshold, and the preselected drug is an auxiliary drug.

[0103] After the user terminal obtains multiple preselected drugs, it determines that the third condition includes that the appearance frequency of the preselected drug in all the preselected historical experience prescriptions reaches a preset third frequency threshold, and the preselected drug is an auxiliary drug. For each preselected drug among the multiple preselected drugs, it counts the appearance frequency of the preselected drug in all the preselected historical experience prescriptions, and judges whether the preselected drug is an auxiliary drug. If the appearance frequency reaches the third frequency threshold and the preselected drug is an auxiliary drug, the preselected drug is determined as the target drug. If the appearance frequency does not reach the third frequency threshold or the preselected drug is not an auxiliary drug, no processing is performed.

[0104] In practical applications, the third frequency threshold can be set according to the appearance frequency of each preselected drug in all the preselected historical experience prescriptions.

[0105] In the embodiment of the present application, by determining one or more preselected historical experience prescriptions from multiple historical experience prescriptions, the patient follow-up information corresponding to the one or more preselected historical experience prescriptions includes target adverse reaction information, and the preselected drug that meets the third condition among the multiple preselected drugs of all the preselected historical experience prescriptions is determined as the target drug, which can more quickly determine the target drug associated with the target adverse reaction information from multiple historical experience prescriptions. And by setting the third condition to include that the appearance frequency of the preselected drug in one or more preselected historical experience prescriptions reaches a preset third frequency threshold, and the preselected drug is an auxiliary drug, it can quickly and accurately determine the auxiliary drugs frequently used by the user from all the preselected historical experience prescriptions, so as to better realize the intelligent management of the physician's experience prescriptions.

[0106] In an optional embodiment, the generating a modification prompt message for the target historical experience prescription according to the target drug includes: generating a first modification prompt message for the target historical experience prescription according to the target drug when a preset update period arrives; or generating a second modification prompt message for the target historical experience prescription according to the target drug when a prescription request initiated by the user for the target historical experience prescription is obtained.

[0107] Exemplarily, considering the actual application, it is usually necessary to regularly manage the physician's empirical prescriptions. An update cycle can be preset, such as one week.

[0108] After the user terminal determines the target drug and the target historical empirical prescription, it detects in real time whether the update cycle has arrived. When the update cycle arrives, a first modification prompt message for the target historical empirical prescription is generated based on the target drug, and the first modification prompt message is sent to the user, so that the user can view the first modification prompt message and choose whether to modify the target historical empirical prescription.

[0109] And considering the actual application, during the process of a physician prescribing for the target disease condition of the current patient, the physician may choose the target historical empirical prescription for prescribing. To prevent the physician from still prescribing according to the problematic empirical prescription, the user can be prompted to calibrate the target historical empirical prescription during the process of the user choosing the target historical empirical prescription for prescribing.

[0110] After the user terminal determines the target drug and the target historical empirical prescription, it monitors in real time the prescribing request initiated by the user for the target historical empirical prescription. When the prescribing request initiated by the user for the target historical empirical prescription is obtained, a second modification prompt message for the target historical empirical prescription is generated based on the target drug, and the second modification prompt message is sent to the user, so that the user can view the second modification prompt message, choose whether to modify the target historical empirical prescription, and choose the target historical empirical prescription or the modified target historical empirical prescription for prescribing.

[0111] In the embodiment of the present application, by generating a first modification prompt message for the target historical empirical prescription based on the target drug when the preset update cycle arrives, or generating a second modification prompt message for the target historical empirical prescription based on the target drug when the prescribing request initiated by the user for the target historical empirical prescription is obtained, it is possible to prompt the user to calibrate the problematic empirical prescription when the update cycle arrives or the user chooses the target historical empirical prescription for prescribing, thereby better realizing the intelligent management of the physician's empirical prescriptions.

[0112] In an optional embodiment, the modification prompt message carries the pharmaceutical information of the target drug; wherein, the pharmaceutical information includes efficacy information and / or pharmacological information.

[0113] Exemplarily, after the user terminal determines the target drug and the target historical empirical prescription, it determines the pharmaceutical information corresponding to the target drug and adds the pharmaceutical information to the generated modification prompt message, wherein the pharmaceutical information includes efficacy information and / or pharmacological information.

[0114] It should be noted that there are the following several situations for the pharmaceutical information including efficacy information and / or pharmacological information: the pharmaceutical information includes efficacy information; the pharmaceutical information includes pharmacological information; the pharmaceutical information includes both efficacy information and pharmacological information.

[0115] For example, after the user terminal determines the target drug and the target historical empirical formula, it detects in real time whether the update cycle has arrived. When the update cycle arrives, it uses big data technology to capture the efficacy information of the target drug from the knowledge base in the field of traditional Chinese medicine. For example, the efficacy information of "rhubarb" and "magnesium sulfate" is that "both rhubarb and magnesium sulfate belong to laxative drugs, both have the effect of purging and reducing accumulation, and their medicinal properties are drastic. Therefore, when used in combination, the purgative effect is enhanced". It captures the pharmacological information of the target drug from the knowledge base in the field of Western medicine. For example, the pharmacological information of "rhubarb" and "magnesium sulfate" is that "rhubarb can stimulate the large intestine and enhance intestinal peristalsis; magnesium sulfate can form a hypertonic saline solution in the intestine, which leads to hyperactivity and causes the intestine to retain a large amount of water. The intestinal volume increases, which will reflexively cause intestinal peristalsis and diarrhea". It adds the pharmacological information such as the efficacy information and pharmacological information of the target drug to the generated first modification prompt message. For example, the first modification prompt message is "a. The combination of rhubarb and magnesium sulfate may cause diarrhea after taking the medicine. It is recommended to use them separately or reduce the dosage; b. Both rhubarb and magnesium sulfate belong to laxative drugs, both have the effect of purging and reducing accumulation, and their medicinal properties are drastic. Therefore, when used in combination, the purgative effect is enhanced; c. Rhubarb can stimulate the large intestine and enhance intestinal peristalsis; magnesium sulfate can form a hypertonic saline solution in the intestine, which leads to hyperactivity and causes the intestine to retain a large amount of water. The intestinal volume increases, which will reflexively cause intestinal peristalsis and diarrhea", and sends the first modification prompt message to the user, so that the user can view the first modification prompt message and choose whether to modify the target historical empirical formula. If a modification instruction input by the user for the first modification prompt message is obtained subsequently, the target historical empirical formula is modified according to the modification instruction, and the target historical empirical formula is updated to the modified target historical empirical formula.

[0116] In the embodiment of the present application, by adding pharmacological information such as the efficacy information and / or pharmacological information of the target drug to the modification prompt message, it is convenient for the user to view the pharmacological information of the target drug together, assisting the user to quickly select whether to modify the target historical empirical formula, so as to better realize the intelligent management of the physician's empirical formula.

[0117] In an alternative embodiment, when obtaining a prescription request initiated by the user for the target historical empirical formula, generating a second modification prompt message for the target historical empirical formula according to the target drug includes: responding to the prescription request and obtaining the patient diagnosis and treatment information of the current patient; wherein the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information; generating a second modification prompt message; wherein the second modification prompt message carries the pharmacological information of the target drug and the alternative drugs corresponding to the patient diagnosis and treatment information; the pharmacological information includes efficacy information and / or pharmacological information.

[0118] Exemplarily, after determining the target drug and the target historical experience prescription, the user terminal monitors in real time the prescribing request initiated by the user for the target historical experience prescription. In the case of obtaining the prescribing request initiated by the user for the target historical experience prescription, it responds to the prescribing request, obtains the patient diagnosis and treatment information of the current patient, where the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information, determines the pharmaceutical information of the target drug, the pharmaceutical information includes efficacy information and / or pharmacological information, determines the candidate drugs corresponding to the patient diagnosis and treatment information, adds the pharmaceutical information and the candidate drugs to the generated second modification prompt message, and sends the second modification prompt message to the user, so that the user can view the second modification prompt message, select whether to modify the target historical experience prescription, and select whether to add the candidate drugs to the target historical experience prescription or the modified target historical experience prescription.

[0119] For example, after the user terminal determines the target drug and the target historical empirical formula, it monitors in real time the prescribing request initiated by the user for the target historical empirical formula. When the prescribing request initiated by the user for the target historical empirical formula is obtained, in response to the prescribing request, using big data technology, it extracts the efficacy information of the target drug from the traditional Chinese medicine domain knowledge base. For example, the efficacy information of "rhubarb" and "magnesium sulfate" is that "both rhubarb and magnesium sulfate belong to purgative drugs, both have the effect of purging accumulation, and their medicinal properties are drastic. Therefore, when used in combination, the purgative effect is enhanced". It extracts the pharmacological information of the target drug from the western medicine domain knowledge base. For example, the pharmacological information of "rhubarb" and "magnesium sulfate" is that "rhubarb can stimulate the large intestine and enhance intestinal peristalsis ability; magnesium sulfate can form a hypertonic saline solution in the intestine, which causes hyperactivity and keeps a large amount of water in the intestine, increasing the intestinal volume and reflexively causing intestinal peristalsis and diarrhea". At the same time, it obtains the patient diagnosis and treatment information of the current patient. Among them, the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information. According to the pre-set mapping relationship of "diagnosis and treatment information - syndrome element - drug", it determines the target syndrome element corresponding to the patient diagnosis and treatment information, and then determines the candidate drugs corresponding to the target syndrome element. For example, the candidate drugs are "1 - 3 herbs such as tangerine peel". It adds the pharmaceutical information and the candidate drugs to the generated second modification prompt message and sends the second modification prompt message to the user. For example, the second modification prompt message is: "a. The combination of rhubarb and magnesium sulfate may cause diarrhea after taking the medicine. It is recommended to use them separately or reduce the dosage; b. Both rhubarb and magnesium sulfate belong to purgative drugs, both have the effect of purging accumulation, and their medicinal properties are drastic. Therefore, when used in combination, the purgative effect is enhanced; c. Rhubarb can stimulate the large intestine and enhance intestinal peristalsis ability; magnesium sulfate can form a hypertonic saline solution in the intestine, which causes hyperactivity and keeps a large amount of water in the intestine, increasing the intestinal volume and reflexively causing intestinal peristalsis and diarrhea; d. According to the patient diagnosis and treatment information, it is recommended to add 1 - 3 herbs such as tangerine peel", so that the user can view the second modification prompt message, select whether to modify the target historical empirical formula, and select whether to add the candidate drugs to the target historical empirical formula or the modified target historical empirical formula.

[0120] It should be noted that the syndrome element is the basic unit of traditional Chinese medicine syndrome differentiation. By identifying the syndrome, that is, symptoms and signs, the disease location and disease nature of the disease are determined, thus constituting the syndrome name.

[0121] In the embodiment of the present application, by responding to the prescription request initiated by the user for the target historical experience prescription, the patient diagnosis and treatment information of the current patient is obtained. The patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information. The pharmacodynamic information and / or pharmacological information and other pharmaceutical information of the target drug, as well as the candidate drugs corresponding to the patient diagnosis and treatment information, are added to the generated second modification prompt message, which can facilitate the user to view the pharmaceutical information of the target drug and the candidate drugs corresponding to the patient diagnosis and treatment information together, assist the user in prescribing the optimal prescription for the current patient's illness condition, and thus better realize the intelligent management of the physician's experience prescription.

[0122] In an alternative embodiment, the method further includes: in the case where the target adverse reaction information is the new symptom information of the target disease syndrome, generating a configuration prompt message for prompting to add the symptoms of the target disease syndrome, and sending the configuration prompt message to the user; according to the configuration instruction input by the user for the configuration prompt message, adding the target syndrome symptoms specified by the user under the target disease syndrome; establishing a mapping relationship between the target syndrome symptoms and the new drugs according to the new drugs in the modified target historical experience prescription.

[0123] Exemplarily, the traditional Chinese medicine diagnosis and treatment platform supports the user to edit the experience prescriptions and disease syndrome types stored in the platform, as well as the relevant information such as the main symptoms, secondary symptoms, accompanying symptoms, treatment principles, and doctor's advice of the diseases.

[0124] After the user terminal obtains the target adverse reaction information, it compares the target adverse reaction information with the adverse reaction information of the target disease syndrome stored in the platform to determine whether the target adverse reaction information is the new symptom information of the target disease syndrome.

[0125] In the case where the target adverse reaction information is the new symptom information of the target disease syndrome, generating a configuration prompt message for prompting to add the symptoms of the target disease syndrome, and sending the configuration prompt message to the user, so that the user can view the configuration prompt message and select whether to edit the relevant information of the target disease syndrome.

[0126] In the case where the configuration instruction input by the user for the configuration prompt message is obtained, according to the configuration instruction, adding the target syndrome symptoms specified by the user under the target disease syndrome, and establishing a mapping relationship between the target syndrome symptoms and the new drugs according to the new drugs in the modified target historical experience prescription, and storing the target syndrome symptoms and the mapping relationship between the target syndrome symptoms and the new drugs in the traditional Chinese medicine diagnosis and treatment platform, so that the user can view this information for prescribing later.

[0127] For example, assume that the target adverse reaction information "diarrhea after eating cold food" is the newly added symptom information of the target disease syndrome, and the newly added drugs in the modified target historical empirical formula are "parched atractylodes macrocephala" and "dry ginger". Then, a configuration prompt message for prompting the addition of the symptoms of the target disease syndrome is generated and sent to the user. When the configuration instruction input by the user for the configuration prompt message is obtained, according to this configuration instruction, the target syndrome symptoms specified by the user are added under the target disease syndrome. For example, the accompanying symptom "diarrhea after eating cold food" is added under the target disease syndrome, and according to the newly added drugs in the modified target historical empirical formula, that is, "parched atractylodes macrocephala" and "dry ginger", a mapping relationship between the target syndrome symptoms and the newly added drugs is established, that is, the mapping relationship between the accompanying symptom "diarrhea after eating cold food" - "parched atractylodes macrocephala" and "dry ginger".

[0128] In the case where the target adverse reaction information is not the newly added symptom information of the target disease syndrome, no processing is performed.

[0129] In the embodiment of the present application, when the target adverse reaction information is the newly added symptom information of the target disease syndrome, a configuration prompt message for prompting the addition of the symptoms of the target disease syndrome is generated and sent to the user. According to the configuration instruction input by the user for the configuration prompt message, the target syndrome symptoms specified by the user are added under the target disease syndrome, and according to the newly added drugs in the modified target historical empirical formula, a mapping relationship between the target syndrome symptoms and the newly added drugs is established, which can ensure that the corresponding target syndrome symptoms are added under the target disease syndrome in a timely manner, and the mapping relationship between the target syndrome symptoms and the newly added drugs is updated in a timely manner, assisting the user to prescribe based on more comprehensive clinical experience, so as to better realize the intelligent management of the doctor's empirical formula.

[0130] Please refer to Figure 2 , Figure 2 FIG. 2 is a schematic structural diagram of a doctor's empirical formula management device provided by the second embodiment of the present application. The second embodiment of the present application provides a doctor's empirical formula management device, including: a historical data acquisition module 201, configured to acquire a plurality of historical empirical formulas prescribed by the user for the target disease syndrome, and acquire the target adverse reaction information fed back by the patient; wherein, at least some of the drugs in the plurality of historical empirical formulas are the same; a target prescription acquisition module 202, configured to determine a target historical empirical formula from the plurality of historical empirical formulas; wherein, the target historical empirical formula includes a target drug associated with the target adverse reaction information; a prescription modification prompt module 203, configured to generate a modification prompt message for the target historical empirical formula according to the target drug, and send the modification prompt message to the user; a prescription modification and update module 204, configured to modify the target historical empirical formula according to the modification instruction input by the user for the modification prompt message to obtain a modified target historical empirical formula.

[0131] In an alternative embodiment, the obtaining of the target adverse reaction information of the patient feedback includes: extracting adverse reaction information from the follow-up visit information of patients corresponding to multiple historical empirical prescriptions to obtain multiple types of adverse reaction information; determining the adverse reaction information that meets the first condition among the multiple types of adverse reaction information as the target adverse reaction information; wherein, the first condition includes that the occurrence frequency of the adverse reaction information in the follow-up visit information of patients corresponding to multiple historical empirical prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold.

[0132] In an alternative embodiment, the target prescription obtaining module 202 is further configured to determine one or more preselected historical empirical prescriptions from the multiple historical empirical prescriptions before determining the target historical empirical prescription from the multiple historical empirical prescriptions; wherein, the follow-up visit information of patients corresponding to the one or more preselected historical empirical prescriptions includes the target adverse reaction information; extracting drugs from the multiple historical empirical prescriptions to obtain multiple primary selected drugs; determining the primary selected drugs that meet the second condition among the multiple primary selected drugs as the alternative selected drugs; wherein, the second condition includes that the occurrence frequency of the primary selected drugs in the multiple historical empirical prescriptions reaches a preset second frequency threshold; if the preselected historical empirical prescription including the alternative selected drugs meets the preset quantity condition, then determining the alternative selected drugs as the target drugs.

[0133] In an alternative embodiment, the target prescription obtaining module 202 is further configured to determine one or more preselected historical empirical prescriptions from the multiple historical empirical prescriptions before determining the target historical empirical prescription from the multiple historical empirical prescriptions; wherein, the follow-up visit information of patients corresponding to the one or more preselected historical empirical prescriptions includes the target adverse reaction information; extracting drugs from the one or more preselected historical empirical prescriptions to obtain multiple preselected drugs; determining the preselected drugs that meet the third condition among the multiple preselected drugs as the target drugs; wherein, the third condition includes that the occurrence frequency of the preselected drugs in the one or more preselected historical empirical prescriptions reaches a preset third frequency threshold, and the preselected drugs are adjuvant drugs.

[0134] In an alternative embodiment, the generating of the modification prompt message for the target historical empirical prescription based on the target drug includes: generating a first modification prompt message for the target historical empirical prescription based on the target drug when a preset update period arrives; or generating a second modification prompt message for the target historical empirical prescription based on the target drug when a prescription request initiated by the user for the target historical empirical prescription is obtained.

[0135] In an alternative embodiment, the modification prompt message carries the pharmaceutical information of the target drug; wherein, the pharmaceutical information includes efficacy information and / or pharmacological information.

[0136] In an alternative embodiment, when a prescription request initiated by a user for a target historical experience prescription party is obtained, generating a second modification prompt message for the target historical experience prescription based on the target drug includes: in response to the prescription request, obtaining the patient diagnosis and treatment information of the current patient; wherein the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information, and palm diagnosis information; generating a second modification prompt message; wherein the second modification prompt message carries the pharmaceutical information of the target drug and the alternative drugs corresponding to the patient diagnosis and treatment information; the pharmaceutical information includes efficacy information and / or pharmacological information.

[0137] The implementation processes of the functions and roles of each module in the above device are specifically described in detail in the implementation processes of the corresponding steps in the above method, and will not be elaborated here.

[0138] Please refer to Figure 3 , Figure 3 FIG. 3 is a schematic structural diagram of an electronic device provided in the third embodiment of the present application. The third embodiment of the present application provides an electronic device 30, including a processor 301, a memory 302, and a computer program stored in the memory 302 and configured to be executed by the processor 301; when the processor 301 executes the computer program, it implements the method as described in the first embodiment of the present application and can achieve the same beneficial effects.

[0139] Wherein, when the processor 301 reads the computer program from the memory 302 through the bus 303 and executes the computer program, it can implement the method as described in the first embodiment of the present application.

[0140] The processor 301 can process digital signals and can include various computing architectures. For example, a complex instruction set computer architecture, a reduced instruction set computer architecture, or an architecture that implements a combination of multiple instruction sets. In some examples, the processor 301 can be a microprocessor.

[0141] The memory 302 can be used to store instructions executed by the processor 301 or data related to the execution of the instructions. These instructions and / or data can include code for implementing some or all of the functions of one or more modules described in the embodiments of the present application. The processor 301 in this embodiment can be used to execute the instructions in the memory 302 to implement the method as described in the first embodiment of the present application. The memory 302 includes dynamic random access memory, static random access memory, flash memory, optical memory, or other memories well known to those skilled in the art.

[0142] The fourth embodiment of the present application provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method as described in the first embodiment of the present application and can achieve the same beneficial effects.

[0143] In summary, the embodiments of the present application provide a management method, device, electronic device and storage medium for a physician's empirical formula. The management method for the physician's empirical formula includes: obtaining a plurality of historical empirical formulas prescribed by a user for a target disease or syndrome, and obtaining target adverse reaction information feedback by a patient; wherein at least some of the drugs in the plurality of historical empirical formulas are the same; determining a target historical empirical formula from the plurality of historical empirical formulas; wherein the target historical empirical formula includes a target drug associated with the target adverse reaction information; generating a modification prompt message for the target historical empirical formula according to the target drug, and sending the modification prompt message to the user; modifying the target historical empirical formula according to the modification instruction input by the user for the modification prompt message to obtain a modified target historical empirical formula. By obtaining a plurality of historical empirical formulas prescribed by a user for a target disease or syndrome and the target adverse reaction information feedback by a patient, determining a target historical empirical formula including a target drug associated with the target adverse reaction information from the plurality of historical empirical formulas, generating a modification prompt message for the target historical empirical formula according to the target drug, sending the modification prompt message to the user, and modifying the target historical empirical formula according to the modification instruction input by the user for the modification prompt message to obtain a modified target historical empirical formula, the embodiments of the present application can audit a plurality of historical empirical formulas based on the patient feedback mechanism, determine the problematic empirical formulas among the plurality of historical empirical formulas, prompt the user to calibrate the problematic empirical formulas, and complete the intelligent management such as unified auditing and calibration of a plurality of empirical formulas of the same physician, so as to realize the intelligent management of the physician's empirical formula.

[0144] The above embodiments are only illustrative examples, and the various embodiments of the present application can be combined or nested with each other, and the present application is not limited thereto.

[0145] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0146] In addition, each functional module in various embodiments of this application can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0147] If the described function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0148] The above are only the embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application. It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0149] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, and all of them should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0150] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

Claims

1. A method for managing physician experience prescriptions, characterized in that: include: Acquire multiple historical prescriptions prescribed by the user for the target disease, and obtain target adverse reaction information fed back by the patient; wherein at least some of the drugs in the multiple historical prescriptions are the same; Determining a target historical experience prescription from the plurality of historical experience prescriptions; wherein the target historical experience prescription includes a target drug associated with the target adverse reaction information; generating a modification prompt message of the target historical experience prescription according to the target drug, and sending the modification prompt message to the user; According to the modification instruction input by the user in response to the modification prompt message, the target historical experience formula is modified to obtain a modified target historical experience formula.

2. The method according to claim 1, characterized in that The target adverse reaction information obtained from patient feedback includes: Extracting adverse reaction information from the patient follow-up information corresponding to the multiple historical experience prescriptions to obtain multiple types of adverse reaction information; Adverse reaction information that meets a first condition among the multiple types of adverse reaction information is determined as the target adverse reaction information; wherein, the first condition includes that the frequency of occurrence of the adverse reaction information in the patient follow-up information corresponding to the multiple historical experience prescriptions reaches a preset first frequency threshold, and / or the severity level of the adverse reaction information reaches a preset level threshold.

3. The method according to claim 1, characterized in that Before determining the target historical experience method from the plurality of historical experience methods, the method further includes: Determine one or more pre-selected historical experience prescriptions from the multiple historical experience prescriptions; wherein the patient follow-up information corresponding to the one or more pre-selected historical experience prescriptions includes the target adverse reaction information; Extract drugs from the multiple historical experience prescriptions to obtain multiple preliminary selected drugs; Determine the primary selected drugs that meet the second condition among the multiple primary selected drugs as the re-selected drugs; wherein the second condition includes that the frequency of occurrence of the primary selected drugs in the multiple historical experience prescriptions reaches a preset second frequency threshold; If the pre-selected historical experience formula including the multiple-selected drug meets the preset quantity condition, the multiple-selected drug is determined as the target drug.

4. The method according to claim 1, characterized in that: Before determining the target historical experience method from the plurality of historical experience methods, the method further includes: Determine one or more pre-selected historical experience prescriptions from the multiple historical experience prescriptions; wherein the patient follow-up information corresponding to the one or more pre-selected historical experience prescriptions includes the target adverse reaction information; Extract drugs from the one or more preselected historical experience prescriptions to obtain a plurality of preselected drugs; A preselected drug among the multiple preselected drugs that meets a third condition is determined as the target drug; wherein the third condition includes that the frequency of occurrence of the preselected drug in the one or more preselected historical experience prescriptions reaches a preset third frequency threshold, and the preselected drug is an auxiliary drug.

5. The method according to claim 1, characterized in that The step of generating a modification prompt message of the target historical experience prescription according to the target drug includes: When a preset update cycle arrives, a first modification prompt message of the target historical experience prescription is generated according to the target drug; or, When a prescription request initiated by the user for the target historical experience prescription is obtained, a second modification prompt message of the target historical experience prescription is generated according to the target drug.

6. The method according to any one of claims 1 to 5, characterized in that: The modification prompt message carries pharmaceutical information of the target drug; wherein the pharmaceutical information includes efficacy information and / or pharmacological information.

7. The method according to claim 5, characterized in that In the case of obtaining a prescription request initiated by a user for the target historical experience prescription, generating a second modification prompt message of the target historical experience prescription according to the target drug, including: In response to the prescription request, obtaining patient diagnosis and treatment information of the current patient; wherein the patient diagnosis and treatment information includes one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information and palm diagnosis information; Generate the second modification prompt message; wherein, the second modification prompt message carries the pharmaceutical information of the target drug and the candidate drug corresponding to the patient's diagnosis and treatment information; the pharmaceutical information includes efficacy information and / or pharmacological information.

8. A physician's experience prescription management device, characterized in that: include: A historical data acquisition module is used to acquire multiple historical experience prescriptions prescribed by users for target diseases and symptoms, and to acquire target adverse reaction information fed back by patients; wherein at least some of the drugs in the multiple historical experience prescriptions are the same; A target prescription acquisition module, used to determine a target historical experience prescription from the multiple historical experience prescriptions; wherein the target historical experience prescription includes a target drug associated with the target adverse reaction information; A prescription modification prompt module, used to generate a modification prompt message of the target historical experience prescription according to the target drug, and send the modification prompt message to the user; The prescription modification and updating module is used to modify the target historical experience prescription according to the modification instruction input by the user in response to the modification prompt message to obtain a modified target historical experience prescription.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor; when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program; wherein, when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

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