CN113450892A

CN113450892A - Medication decision scheme generation method and device, computer equipment and storage medium

Info

Publication number: CN113450892A
Application number: CN202110142229.9A
Authority: CN
Inventors: 肖坚; 张露; 黄行行; 窦钰涛; 夏飞; 邹丹
Original assignee: Hunan Rongguan Intelligent Technology Co ltd; Xiangya Hospital of Central South University
Current assignee: Hunan Rongguan Intelligent Technology Co ltd; Xiangya Hospital of Central South University
Priority date: 2021-02-02
Filing date: 2021-02-02
Publication date: 2021-09-28

Abstract

The application relates to a medication decision scheme generation method, a medication decision scheme generation device, computer equipment and a storage medium. The method comprises the following steps: the method comprises the steps of obtaining patient related information of a current patient, wherein the patient related information comprises basic information and disease information of the current patient, generating evaluation data corresponding to the patient related information according to the patient related information, obtaining decision path related information from a preset medication knowledge graph according to the evaluation data, pushing the decision path related information to a selection interface of a preset medical staff terminal, constructing the preset medication knowledge graph based on the medication related information and historical disease clinical treatment data, responding to selection operations of different medication schemes, and obtaining a medication decision scheme for the current patient according to the selected medication scheme. By adopting the method, the relevant information of the decision path can be provided comprehensively, accurately and efficiently, different medication schemes can be represented visually, and the accurate and efficient medication decision can be generated.

Description

Medication decision scheme generation method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for generating a medication decision scheme, a computer device, and a storage medium

Background

Currently, the diseases in society are various, and for different diseases, the selection of drugs for the corresponding diseases is important. For example, in the case of cancer, as cancer morbidity and mortality have increased year by year, cancer has become a significant problem threatening public health in current diseases, with pain being one of the most common conditions for oncology patients. The correct selection of the analgesic drugs and the adjustment of the dosage for the cancer pain patients are particularly important for exerting the maximum analgesic effect and reducing the adverse reaction.

However, the available drug options are various and complicated, for example, the drug options in cancer drugs include non-steroidal anti-inflammatory drugs, acetaminophen, opioids, auxiliary analgesics (including anticonvulsants, antidepressants, glucocorticoids, local anesthetics, and bisphosphonates), and so on. The medicine is various in types, the titration of the opioid is complex, medical staff need to obtain accurate corresponding medicines or dosages, a large number of historical medical records need to be inquired, and a proper medication decision can be obtained by researching and analyzing the historical medical records, so that the whole process needs to consume a long time, and the accuracy is low and the efficiency is low.

Disclosure of Invention

In view of the above, there is a need to provide a medication decision scheme generation method, apparatus, computer device and storage medium that can be used accurately and efficiently.

A medication decision plan generation method, the method comprising:

acquiring patient-related information of a current patient, wherein the patient-related information comprises basic information and disease information of the current patient;

generating evaluation data corresponding to the patient-related information according to the patient-related information;

obtaining decision path related information from a preset medication knowledge graph according to the evaluation data, and pushing the decision path related information to a selection interface of a preset medical staff terminal, wherein the preset medication knowledge graph is constructed based on the medication related information and historical disease clinical treatment data, and the decision path related information comprises different selectable medication schemes;

and responding to the selection operation of different medication schemes, and obtaining a medication decision scheme for the current patient according to the selected medication scheme.

In one embodiment, obtaining the decision path related information from the pre-set medication knowledge graph according to the evaluation data comprises:

acquiring medication related information, wherein the medication related information comprises disease-to-medication information, disease consensus information, drug instruction information and open database related medication information;

generating a disease medication knowledge base according to medication related information;

carrying out term standardization processing on the disease medication knowledge base to obtain standardized disease medication knowledge base data;

carrying out natural language processing on the standardized disease medication knowledge base data to obtain disease medication coded data;

acquiring historical disease clinical treatment data, and generating electronic medical record data according to the historical disease clinical treatment data;

and constructing a medication knowledge map according to the disease medication coded data and the electronic medical record data.

In one embodiment, the assessment data comprises basic assessment data and condition assessment data;

generating, from the patient-related information, assessment data corresponding to the patient-related information includes:

generating basic evaluation data according to basic information in the patient-related information, wherein the basic information comprises at least one of identity information, historical clinical diagnosis information, auxiliary examination information, personal past medical history information, allergy information, treatment information and physical conditions;

and generating disease evaluation data according to disease information in the patient-related information, wherein the disease information comprises at least one of disease reason, disease part, disease property, disease intensity and disease neuropathic evaluation data.

In one embodiment, the evaluation data further comprises historical evaluation data, breakthrough pain evaluation data, and compliance evaluation data, and the obtaining patient-related information for the current patient further comprises:

judging whether the current patient is a patient taking medicine in the past or not;

when the judgment result is that the patient has taken medicine in the past, acquiring the past information, the outbreak pain information and the compliance information of the current patient, wherein the compliance information is the medication compliance information of the patient who has taken medicine in the past; generating, from the patient-related information, assessment data corresponding to the patient-related information further comprises:

adding the past information, the break-out pain information and the compliance information to the patient-related information;

obtaining historical evaluation data according to the previous information;

and generating burst pain evaluation data according to the burst pain information, and generating compliance evaluation data according to the compliance information.

In one embodiment, after obtaining a medication decision plan for the current patient based on the selected medication plan in response to the selection of the different medication plan, the method further comprises:

analyzing medicine related information of medicine used in the medicine decision according to the medicine decision, wherein the medicine related information comprises at least one of usage amount, medicine using time, adverse reaction, medicine interaction, medicine-food interaction and caution items of the medicine;

constructing a list table including medicine related information of medication;

and pushing the list clearing table to a preset medical staff terminal.

updating the current patient to a patient who has taken the previous medicine, and extracting relevant information, evaluation data and medicine taking decision of the patient who has taken the previous medicine;

and updating the extracted information serving as the past information to a preset medication knowledge map.

obtaining satisfaction information of a current medication patient to a medication decision;

generating satisfaction evaluation according to the satisfaction information;

and storing the satisfaction evaluation as feedback information into a preset medicine-taking knowledge map.

A medication decision determination device, the device comprising:

the information acquisition module is used for acquiring patient related information of the current patient, and the patient related information comprises basic information and disease information of the current patient;

the data generation module generates evaluation data corresponding to the patient-related information according to the patient-related information;

the decision path pushing module is used for obtaining decision path related information from a preset medication knowledge graph according to the evaluation data and pushing the decision path related information to a selection interface of a preset medical staff terminal, the preset medication knowledge graph is constructed based on the medication related information and the clinical treatment data of the historical symptoms, and the decision path related information comprises different selectable medication schemes;

and the decision selection module is used for responding to the selection operation of different medication schemes and obtaining the medication decision scheme of the current patient according to the selected medication scheme.

A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

The medication decision scheme generation method, the device, the computer equipment and the storage medium acquire the patient related information of the current patient, determine the effective and accurate decision path related information by processing the patient related information into comprehensive evaluation data, analyzing the decision path related information from the preset medication knowledge graph based on the evaluation data generated after processing, and analyzing and processing the evaluation data based on the preset medication knowledge graph, wherein the decision path related information comprises different selectable medication schemes and evidence for evidence for decision path, thereby enhancing the accuracy of scheme medication selection, responding to the selection operation of the decision path related information by pushing the decision path related information to a selection interface of a preset medical staff terminal, the medication decision of the current patient is determined, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be visually represented, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

Drawings

FIG. 1 is a diagram of an application environment of a medication decision plan generation method in one embodiment;

FIG. 2 is a schematic flow chart diagram illustrating a method for generating a medication decision plan in one embodiment;

FIG. 3 is a flow diagram illustrating the construction of a medication knowledge graph in a medication decision scheme generation method according to an embodiment;

FIG. 4 is a schematic flow chart diagram illustrating a method for generating a medication decision plan in accordance with another embodiment;

FIG. 5 is a schematic flow chart diagram illustrating a method for generating a medication decision plan in accordance with yet another embodiment;

FIG. 6 is a schematic flow chart diagram illustrating a medication decision plan generation method in accordance with yet another embodiment;

FIG. 7 is a flowchart illustrating a method for generating a medication decision plan in accordance with another embodiment;

FIG. 8 is a schematic flow chart diagram illustrating a method for generating a medication decision plan in one embodiment;

FIG. 9 is a diagram of construction of a medication decision plan generation method using a knowledge graph of medication in an application embodiment;

FIG. 10 is a diagram illustrating basic evaluation data in a medication decision making process according to an exemplary embodiment;

FIG. 11 is a diagram of pain cause of a medication decision plan generation method in an example application;

FIG. 12 is a diagram of a pain site generated by a medication decision making protocol generation method in an example application;

FIG. 13 is a diagram of the pain profile of the medication decision protocol generation method in one example of use;

FIG. 14 is a diagram of pain intensity of a medication decision making protocol generation method in an example application;

FIG. 15 is a diagram of pathological pain assessment in a medication decision making protocol generation method according to an example application;

FIG. 16 is a diagram illustrating historical evaluation of a medication decision making process in an embodiment;

FIG. 17 is a diagram illustrating compliance assessment in a medication decision protocol generation method in an example application;

FIG. 18 is a schematic diagram of a decision path in a medication decision making method according to an embodiment;

FIG. 19 is a diagram of a decision path of a patient not before a medication decision plan generation method in an application example;

FIG. 20 is a diagram of a previous patient decision path of a medication decision plan generation method in an application embodiment;

FIG. 21 is a diagram illustrating an inventory table in a medication decision plan generation method in an exemplary embodiment;

FIG. 22 is a block diagram showing the construction of a medication decision making apparatus according to an embodiment;

FIG. 23 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The medication decision scheme generation method provided by the application can be applied to the application environment shown in fig. 1. Wherein, the medication decision system 102 communicates with the preset medical staff terminal 104 through a network. The medication decision system 102 acquires patient-related information of the current patient, the patient-related information including basic information and condition information of the current patient; the medication decision system 102 generates evaluation data corresponding to the patient-related information based on the patient-related information; the medication decision system 102 obtains decision path related information from a preset medication knowledge graph according to the evaluation data, and pushes the decision path related information to a selection interface of a preset medical staff terminal 104, wherein the preset medication knowledge graph is constructed based on the medication related information and clinical treatment data of historical symptoms, and the decision path related information comprises different selectable medication schemes; the medication decision system 102 responds to the selection operation of different medication schemes from the preset medical staff terminal 104, and the medication decision system 102 obtains the medication decision scheme for the current patient according to the selected medication scheme. The medication decision system 102 may be a system including a terminal and a server, where the terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server may be implemented by an independent server or a server cluster formed by a plurality of servers.

In one embodiment, as shown in fig. 2, a medication decision scheme generation method is provided, which is illustrated by taking the example of the method applied to the medication decision system in fig. 1, and includes the following steps:

in step 202, patient-related information of the current patient is obtained, wherein the patient-related information comprises basic information and disease information of the current patient.

Specifically, the medication decision system acquires patient-related information of the current patient, wherein the patient-related information is information corresponding to the current patient, and the patient-related information includes basic information and disease information of the current patient. The current patient's basic information includes at least one of identity information, historical clinical diagnosis information, auxiliary examination information, personal past medical history information, allergy information, treatment information, and physical conditions, and the current patient's condition information refers to a symptom in which a condition occurs. For example, the current condition information of the patient includes at least one of the pain cause, pain site, pain nature, pain intensity, and neuropathic pain.

At step 204, evaluation data corresponding to the patient-related information is generated based on the patient-related information.

Specifically, the medication decision system generates evaluation data corresponding to the patient-related information according to the acquired patient-related information, and the generated evaluation data may be embedded in the medication decision system in a table form. And generating an evaluation data table corresponding to the patient-related information through the medication decision system, wherein the evaluation data is divided according to different content information in the patient-related information. For example, the patient-related information includes basic information and disease condition information of the current patient, and the evaluation data is also divided into basic information evaluation data and disease condition evaluation data.

And step 206, obtaining relevant information of the decision path from a preset medication knowledge graph according to the evaluation data, and pushing the relevant information of the decision path to a selection interface of a preset medical staff terminal, wherein the preset medication knowledge graph is constructed based on the relevant information of medication and clinical treatment data of historical diseases, and the relevant information of the decision path comprises different selectable medication schemes.

The evaluation data is generated according to the relevant information of the patient, corresponding different evaluation data is generated according to different contents in the relevant information of the patient, and the preset medication knowledge map is constructed on the basis of the medication relevant information and the clinical treatment data of the historical symptoms. Different data processing is respectively carried out on the medication related information and the clinical treatment data of the historical symptoms, and finally, a preset medication knowledge map is constructed on all the data obtained comprehensively. The decision path related information comprises different alternative medication schemes, evidence-based evidence corresponding to the different medication schemes is also included in the decision path related information, and the evidence-based evidence comprises the provenance of the different medication schemes recorded in the preset medication knowledge graph. For example, when the patient has bone pain or not, which is a tumor emergency, which is a special cancer pain, the system suggests that nonsteroidal anti-inflammatory drugs/acetaminophen/steroid/sodium diphosphate can be selected and evidence for the follow-up of the medication decision is given.

Specifically, the medication decision system obtains decision path related information from a preset medication knowledge graph according to the evaluation data. The decision path related information may be a decision path table including related information such as different medication schemes and evidence-based evidence. And pushing the relevant information of the decision path to a selection interface of a preset medical staff terminal, namely pushing the decision path table to the selection interface. The selection interface displays the decision path table and the relevant information of the decision path carried in the decision path table, namely the decision path table on the selection interface comprises different medication schemes, and each medication scheme corresponds to a selection item.

In response to the selection of the different medication options, a medication decision plan for the current patient is obtained based on the selected medication option, step 208.

The selection operation is an operation on a selection interface of a preset medical staff terminal, and the selection of different medication schemes can be a click operation of a selection button on the selection interface. Each medication scheme corresponds to a button of a selection item, the button can be a key or other modules which can be clicked and selected, the clicking of the button indicates that the medication scheme corresponding to the button is selected, the final determination derivation is triggered by the selected button, namely a confirmation button is arranged behind the selected button, the button is the selected button, the selected button can also be other modules which can be clicked and selected, such as the selected key, the selected button can also be matched with selected characters, and the display of the selected characters can be confirmation or indication characters for next operation and the like.

Specifically, when the medication decision system responds to the selection operation of different medication schemes, the medication decision scheme for the current patient is obtained according to the selected medication scheme fed back by the selection interface of the preset medical staff terminal.

In the medication decision scheme generation method, the patient-related information of the current patient is acquired, and the patient-related information comprises the basic information and the disease information of the current patient; by processing the current patient-related information into comprehensive assessment data. Analyzing the relevant information of the decision path from a preset medication knowledge graph based on the evaluation data generated after the processing, wherein the preset medication knowledge graph is constructed based on the medication relevant information and the clinical treatment data of the historical symptoms. Based on a preset medication knowledge map, the evaluation data is analyzed and processed, effective and accurate decision path related information is determined, the decision path related information comprises different selectable medication schemes and evidence for evidence, the different selectable medication schemes are provided, corresponding evidence for evidence for evidence for evidence including decision paths, and accuracy of scheme medication selection is enhanced. The decision path related information is pushed to a selection interface of a preset medical staff terminal, the selection operation of the decision path related information is responded, the medication decision of the current patient is determined, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be represented visually, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

In one embodiment, as shown in fig. 3, the step 206 of obtaining the decision-making path related information from the preset medication knowledge graph according to the evaluation data, and pushing the decision-making path related information to the selection interface of the preset medical staff terminal includes:

step 302, medication related information is obtained, wherein the medication related information comprises disease to medication information, disease consensus information, drug instruction information and open database related medication information.

Specifically, a medication decision system obtains medication related information. The medication related information comprises disease-to-medication information, disease consensus information, drug instruction information and open database related medication information. The information on the application of drugs and the information on the consensus of diseases, such as the national and foreign authoritative Guidelines and the consensus of Cancer, are exemplified by the national and foreign authoritative Guidelines and the consensus of Cancer, including NCCN Guidelines Version 1.2020Adult Cancer Pain (the national Integrated Cancer network (NCCN) Clinical Practice guideline for adults: Adult Cancer Pain), Management of Cancer Pain in adolt patients: ESMO Clinical Practice Guidelines for Adult Cancer Pain (2018 European Association of oncology Cancer of the common identification of Cancer of the related to the national Cancer of the reference of the national and the reference of Cancer of the national and consensus of the information of the reference of the national, of Cancer of the national, of the application of the information of the national, of the national and the application of the national, of the national and the public of the public knowledge of the national, of the public. The condition-to-medication information also includes clinical study information, which is obtained via a Clinical Decision Support System (CDSS), which is an interactive expert system that assists medical personnel in making medical decisions. The clinical decision support system can connect clinical observation and clinical knowledge, assist clinical decision and improve clinical results. The corresponding medicine application knowledge of cancer such as cancer pain related evaluation, medicine treatment and the like can be extracted from authoritative guidelines, consensus and clinical research information at home and abroad. The information of the cancer pain medicine specification corresponding to the cancer can comprise medicine specifications of medicines such as non-steroidal anti-inflammatory drugs, acetaminophen, opioid medicines, auxiliary analgesics (including anticonvulsant medicines, antidepressant medicines, glucocorticoids, local anesthetics, bisphosphonate medicines and the like), and at least one of medicine usage amount, adverse reactions, medicine interaction, medicine-food interaction, cautionary matters and the like can be extracted from the medicine specification. The open database stores drug related information. Drug interactions, drug-food interaction information, etc. may be collected in a database drugs (website providing medical information to U.S. healthcare workers and consumers, www.drugs.com). According to the PCNE classification system: during the working meeting of the European pharmaceutical Care alliance (PCNE) in 1 month 1999, a classification scheme of Drug Related Problems (DRPs) is constructed, and the classification system can be used for researching the nature, prevalence rate and incidence rate of the DRPs (drug related problems) and can also be used as an index in the process of researching pharmaceutical care results, and the supplementary instruction is that drug interaction and drug-food interaction exist in a drug instruction book, but the content of the drug instruction book is more comprehensive. Further extracting drug interaction, medicine-food interaction and the like from an open database.

And step 304, generating a disease medication knowledge base according to the medication related information.

Specifically, the medication decision system extracts the medication related knowledge such as cancer pain related assessment and medication from the disease corresponding medication information and the disease consensus information according to the acquired medication related information such as the disease corresponding medication information, the disease consensus information, the medicine specification information and the open database related medication information, extracts the knowledge such as cancer pain related assessment and medication from the clinical research information, extracts the drug usage amount, adverse reactions, drug interactions, drug-food interactions and cautionary matters and the like from the medicine specification, extracts the drug interactions, drug-food interactions and the like from the open database, and generates a disease medication knowledge base according to the medication related information and the corresponding information extracted from the medication related information.

And step 306, carrying out term standardization processing on the disease medication knowledge base to obtain standardized disease medication knowledge base data.

All terms involved in the knowledge map need to be standardized and processed by natural language, so that the term standardization processing needs to be carried out on the disease medication knowledge base firstly. Specifically, the medication decision system carries out term standardization processing on the disease medication knowledge base, wherein the term standardization processing can refer to ICD-10 classification for diagnosis and refers to MedDRA dictionary for adverse reaction terms for standardization coding, and the MedDRA dictionary refers to ICH international medical term dictionary.

And 308, performing natural language processing on the standardized disease medication knowledge base data to obtain disease medication coded data.

Since all terms in the knowledge map need to be standardized and processed in natural language, the standardized knowledge base for treating diseases needs to be processed in natural language after the term standardization. Specifically, the medication decision system performs natural language processing on the data of the standardized disease medication knowledge base to generate an updated standardized disease medication knowledge base. Natural Language Processing (NLP), i.e. accepting the input of the user in the form of natural language by the computer, and internally performing a series of operations such as processing and calculation by the algorithm defined by human, so as to simulate the understanding of the natural language by human, and return the result expected by the user. After the term standardized processing and natural language processing are performed, the disease medication coding data is obtained from the updated standardized disease medication knowledge base.

And 310, acquiring historical disease clinical treatment data, and generating electronic medical record data according to the historical disease clinical treatment data.

Specifically, the real-world clinical treatment data (electronic medical record system data) includes thousands of real and complete clinical cases. The medication decision system obtains historical disease clinical treatment data of different patients from the collated real-world clinical treatment data to obtain more detailed medication rules. Among them, Electronic Medical Record (EMR): the digital medical service work record of characters, figures, data, images and the like generated in the process of clinic diagnosis and treatment and guidance intervention of medical staff of a medical institution for outpatients and inpatients is a complete and detailed clinical information resource generated and recorded in the process of visiting a medical institution by resident individuals.

And step 312, constructing a medication knowledge map according to the disease medication coded data and the electronic medical record data.

Specifically, the medication decision system constructs a medication knowledge map according to the acquired disease medication coded data and the electronic medical record data. The knowledge graph is essentially a semantic network which reveals relationships among entities, and can formally describe real-world objects and their relationships. The knowledge map of medication is the knowledge map for establishing the correlation between symptoms and medication.

In this embodiment, by acquiring medication related information including information on medication for a disease, information on consensus of disease, information on a drug instruction manual, and information on medication related to an open database, a knowledge base for disease medication can be generated according to the medication related information. And obtaining the disease medication coding data by performing natural language processing on the standardized disease medication knowledge base data. The method comprises the steps of obtaining historical disease clinical treatment data of different patients, generating electronic medical record data according to the historical disease clinical treatment data, and constructing a medication knowledge map according to disease medication coded data and the electronic medical record data. The preset medication knowledge graph is constructed based on medication related information and historical disease clinical treatment data, and the analysis and the processing of the medication decision system are realized based on the preset medication knowledge graph. Based on a preset medicine-taking knowledge map, evaluation data can be analyzed and processed, and effective and accurate decision-making path related information can be determined. The decision path related information comprises different alternative medication schemes and evidence for evidence collection, not only provides different alternative medication schemes, but also provides corresponding evidence for evidence collection, and the evidence for evidence collection comprises the basis of the decision path, so that the accuracy of scheme medication selection is enhanced. The decision path related information is pushed to a selection interface of a preset medical staff terminal, the selection operation of the decision path related information is responded, the medication decision of the current patient is determined, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be represented visually, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

In one embodiment, as shown in FIG. 4, the assessment data includes basic assessment data and condition assessment data, step 204. Generating, from the patient-related information, assessment data corresponding to the patient-related information includes:

step 402, generating basic evaluation data according to basic information in the patient-related information, wherein the basic information comprises at least one of identity information, historical clinical diagnosis information, auxiliary examination information, personal past medical history information, allergy information, treatment information and physical conditions.

In particular, the medication decision system generates basic assessment data based on basic information in the patient-related information. The identity information includes the name, sex, age, ethnicity, height, weight, and medical record number of the patient. The basic information also includes general information including the cultural degree, occupation, marital status, home address, contact telephone, etc. of the patient. Taking cancer as an example, the historical clinical diagnostic information includes the primary tumor diagnosis and stage, metastatic status, tumor complications, and historical clinical diagnosis of underlying diseases. The auxiliary examination information includes laboratory examination results and imaging examination results, such as examination items for liver and kidney functions, and the examination items for kidney functions may include blood creatinine and creatinine clearance, for example, in the case of kidney functions. The personal past medical history information refers to personal habits and symptoms possibly brought by the personal habits, the personal habits comprise smoking, drinking, exercise, staying up night, eating habits and the like, and the eating habits comprise whether high salt, high sugar, high fat, high purine and the like are possibly suffered. The treatment information may be tumor-related treatment including surgical resection, radiation therapy, traditional Chinese medicine therapy, immunotherapy, chemotherapy, and targeted therapy. Allergy information is the individual's allergy history, which includes causes of allergy, drug allergy, food allergy, etc. The physical condition includes a score for the body, with different scores corresponding to different segments, each segment corresponding to a different physical condition. The basic evaluation data is the basic evaluation data finally obtained by integrating according to the personal conditions according to all the basic information, the obtained basic evaluation data can be a corresponding table generated and embedded into a medication decision system, and the corresponding table also corresponds to the recording person and the recording date.

Step 404, generating disease evaluation data according to disease information in the patient-related information, wherein the disease information comprises at least one of disease reason, disease position, disease property, disease intensity and disease neuropathic evaluation data.

Specifically, the medication decision system generates the disease evaluation data according to the disease information in the patient-related information, wherein the disease information comprises at least one of disease cause, disease part, disease property, disease intensity and disease neuropathic evaluation data. In the case of cancer, the disease condition is cancer pain, and the disease condition information may be cancer pain information, and the pain information includes at least one of pain cause, pain site, pain property, pain intensity, and neuropathic pain evaluation data. Pain causes include tumor-related pain causes, tumor therapy-related pain causes, and non-tumor-related pain causes, among others, and tumor-related pain may include tissue damage, tumor compression, tumor obstruction. Tumor tension, etc., and the pain associated with the anti-tumor therapy may include radiation therapy-induced, chemotherapy-induced, surgical therapy-induced, and unknown causes. The evaluation data generated according to the pain part is generated by directly embedding the human body diagram into the system and inputting by clicking of the medical staff terminal, the human body part in the human body diagram is subjected to labeling of different parts, the labels can be numerical labels according to the size sequence, and the evaluation data of the corresponding pain part is generated by matching according to the clicked labels. The pain properties include different types of pain, such as various types of pain, e.g., soreness, stinging, jumping, dull pain, and cramping, each type of pain being labeled, which may be numerical labels in order of magnitude. The pain intensity refers to grading the pain intensity, each intensity corresponds to a different grade, for example, NRS (Numerical Rating Scale) is embedded in a medication decision system, NRS is composed of 11 numbers from 0 to 10, the embedded NRS is slidable and provided with a slider, and the slider can be dragged to any number. The 11 numbers 0 to 10 in NRS describe the intensity of pain, and are used to assess the intensity of pain in patients, with greater numbers showing more and more severe pain. The numbers indicate the evaluation criterion that the number 0 represents no pain; numbers 1-3 represent mild pain (pain does not affect sleep); numbers 4-6 represent moderate pain; numbers 7-9 represent severe pain (inability to fall asleep or to wake during sleep); the numeral 10 represents severe pain. The neuropathic pain assessment data includes any of a number of pain condition data including whether a needle-prick pain condition, a burning or burning pain condition, a tingling pain condition, an electric shock pain condition, an aggravation due to contact with clothing or bed linen, and a joint pain condition.

In this embodiment, the relevant information of the patient is processed into comprehensive evaluation data, and the relevant information of the decision path is analyzed from the preset medication knowledge graph based on the evaluation data generated after the processing. And analyzing and processing the evaluation data based on a preset medicine-taking knowledge map to determine effective and accurate decision-making path related information. The decision path related information comprises different selectable medication schemes and evidence following, not only are the different selectable medication schemes provided, but also corresponding evidence following is provided, the evidence following comprises the basis of the decision path, the accuracy of scheme medication selection is enhanced, the decision path related information is pushed to a selection interface of a preset medical staff terminal to respond to the selection operation of the decision path related information, the medication decision of the current patient is determined, the pushed decision path related information provides comprehensive, accurate and efficient information, different medication schemes can be represented visually, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

In one embodiment, as shown in fig. 5, step 202, before acquiring the patient-related information of the current patient, further includes:

step 502, judging whether the current patient is a past medicine patient.

Specifically, the medication decision system responds to the judgment operation of the preset medical staff terminal to judge whether the current patient is the previous medication patient. And when the judgment result is that the patient is not the previous patient, directly carrying out the next step to acquire the patient related information of the current patient. If the determination result is that the patient is a drug-taking patient, it is necessary to acquire information such as past information of the current patient in addition to the patient-related information of the current patient. The former drug patient refers to a patient who has used the drug decision system before, and the patient can be stored in the drug decision system as the former patient after use.

And step 504, when the judgment result is that the patient has taken medicine in the past, acquiring the past information, the information of the outbreak pain and the compliance information of the current patient, wherein the compliance information is the medication compliance information of the patient having taken medicine in the past.

Specifically, when the judgment result is that the patient has taken the previous medicine, the previous information of the current patient stored in the medicine taking decision system is acquired, the medicine taking decision system acquires the information of the outbreak pain and the compliance information, and the compliance information is the medicine taking compliance information of the patient who has taken the previous medicine. The prior information is the prior data of the prior medication decision by using a medication decision system, and the outbreak pain refers to the pain condition of transient aggravation of pain which occurs spontaneously or suddenly under the induction of certain predictable or unpredictable factors on the premise that the background pain control is relatively stable and the analgesic is fully applied after the prior medication.

The assessment data also includes historical assessment data, breakthrough pain assessment data, and compliance assessment data.

Generating assessment data corresponding to the patient-related information based on the patient-related information, i.e. step 204 further comprises:

step 506, past information, break-out pain information, and compliance information are added to the patient-related information.

Specifically, the past information, the information on the outbreak pain and the compliance information are added into the patient related information, and the medication decision system obtains the updated patient related information, wherein the current patient is the past medication patient.

And step 508, obtaining historical evaluation data according to the past information.

Specifically, the medication decision system obtains historical evaluation data in the past information according to the obtained past information, wherein the historical evaluation data comprises the use condition of the past analgesic, and the use condition of the past analgesic comprises the name and dosage form of the past analgesic, the dose, the frequency, the medication time, the pain relief rate and the medication safety, wherein the medication safety comprises side effects of medication, such as nausea, vomiting, constipation, dizziness, disturbance of consciousness, dyspnea and the like.

And step 510, generating explosion pain evaluation data according to the explosion pain information, and generating compliance evaluation data according to the compliance information.

Specifically, the drug administration decision system generates explosive pain evaluation data according to the acquired explosive pain information, wherein the explosive pain refers to a pain condition of transient aggravation of spontaneous pain or suddenly appearing under the induction of certain predictable or unpredictable factors under the premise that the background pain control is relatively stable and the analgesic drug is fully applied after the previous drug administration, and the explosive pain evaluation data is generated by using the data related to the occurrence of the explosive pain. The medication decision system also generates compliance evaluation data according to the compliance information, and the compliance evaluation data can be obtained by taking compliance scoring as an example according to the acquired compliance information, for example, when the compliance is lower than 6, the compliance is medium between 6 and 7, and the compliance is high when the compliance is greater than or equal to 8.

In the embodiment, the evaluation data corresponding to the current existing medication patient is generated through the related information of the existing medication patient; obtaining decision path related information from a preset medication knowledge graph according to evaluation data, analyzing and processing the evaluation data based on the preset medication knowledge graph to determine effective and accurate decision path related information, wherein the decision path related information comprises different selectable medication schemes and evidence-based evidence, not only provides different selectable medication schemes, but also provides corresponding evidence-based evidence, the evidence-based evidence comprises the basis of the decision path, the accuracy of scheme medication selection is enhanced, the decision path related information is pushed to a selection interface of a preset medical staff terminal to respond to the selection operation of the decision path related information to determine the medication decision of the current patient, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be visually represented, and accurate medication path selection is provided, and a final medication decision is made in response to the selection request, so that a more accurate and efficient medication decision scheme can be generated.

In one embodiment, as shown in fig. 6, the step 208, in response to the selection of the different medication scheme, after obtaining the medication decision scheme for the current patient according to the selected medication scheme, further comprises:

step 602, analyzing relevant information of the medicine used in the medication decision according to the medication decision, wherein the relevant information of the medicine comprises at least one of usage amount of the medicine, medication time, adverse reaction, medicine interaction, medicine-food interaction and caution items.

Specifically, the medication decision system analyzes the relevant information of the medication in the medication decision according to the medication decision of the current patient, wherein the relevant information of the medication comprises at least one of usage amount, medication time, adverse reaction, drug interaction, drug-food interaction and caution items of the medication. Wherein, the time of administration is determined according to chronopharmacology. Taking the medicine used in the current medication decision as the pregabalin as an example, analyzing the medicine related information of the pregabalin, wherein the medicine related information comprises at least one of the usage amount, the medication time, the adverse reaction, the medicine interaction, the medicine-food interaction and the caution items of the medicine.

Step 604, build a checklist including information about drugs to be taken.

Specifically, the medication decision system constructs an inventory table including medication related information, and the medication decision system analyzes the analyzed medication related information and an inventory table of the drugs constructed by the corresponding drugs.

And 606, pushing the list to a preset medical staff terminal.

Specifically, the medication decision system derives a list table including medication related information, and pushes the list table to a preset medical staff terminal.

In this embodiment, the relevant information of the medicines to be taken in the medication decision is analyzed according to the medication decision, a list table including the relevant information of the medicines to be taken is constructed, and the list table is pushed to the preset medical staff terminal. The decision path related information is pushed to a selection interface of a preset medical staff terminal, the selection operation of the decision path related information is responded, the medication decision of the current patient is determined, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be represented visually, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

In one embodiment, as shown in fig. 7, the step 208, in response to the selecting operation of the different medication scheme, after obtaining the medication decision scheme for the current patient according to the selected medication scheme, further includes:

step 702, updating the current patient to the patient who has taken the previous medicine, and extracting the related information, evaluation data and medication decision of the patient who has taken the previous medicine.

Specifically, the medication decision system updates the current patient to the prior medication patient in the medication decision system, and extracts the related information, evaluation data and medication decision of the prior medication patient from the prior.

And step 704, updating the extracted information as the past information to a preset medication knowledge map.

Specifically, the medication decision system updates the extracted information as the past information to a medication knowledge map preset in the medication decision system.

In this embodiment, the current patient is updated to the previous medication patient, the relevant information, the evaluation data, and the medication decision of the previous medication patient are extracted, and the extracted information is updated to the preset medication knowledge map as the previous information, so that a more accurate and efficient medication decision can be generated.

In one embodiment, as shown in fig. 8, the step 208, in response to the selection of the different medication scheme, after obtaining the medication decision scheme for the current patient according to the selected medication scheme, further comprises:

and step 802, obtaining satisfaction information of a preset medical staff terminal to a medication decision.

Specifically, the medication decision system acquires satisfaction information of a preset medical staff terminal to a medication decision, the preset medical staff terminal can be the satisfaction information given by a doctor or a pharmacist, the satisfaction information is pushed to the preset medical staff terminal after a medication decision scheme for a current patient is obtained, and the medication decision system responds to the satisfaction information from the preset medical staff terminal.

And step 804, generating satisfaction evaluation according to the satisfaction information.

Specifically, a satisfaction evaluation is generated according to the obtained satisfaction information, and the satisfaction evaluation content comprises the following contents: the system decision-making system is simple and convenient to operate, whether a perfect or unnecessary evaluation item exists in the cancer pain medication decision-making process or not, and the decision-making result conforms to the judgment of a user according to self experience.

And 806, storing the satisfaction evaluation as feedback information into a preset medicine-taking knowledge graph.

Specifically, the medication decision system stores satisfaction evaluation generated according to the satisfaction information as feedback information to a preset medication knowledge map, wherein the satisfaction evaluation is generated according to the satisfaction information given by a doctor or a pharmacist, and the satisfaction information is obtained by immediately scoring the satisfaction after the medication decision of the current patient using the once-used medication decision system is finished.

In the embodiment, the satisfaction degree information of the preset medical staff terminal for the medication decision is obtained, and the satisfaction degree evaluation is generated according to the satisfaction degree information, so that the satisfaction degree evaluation can be stored as the feedback information to the preset medication knowledge map, and the medication decision system can be continuously perfected according to the feedback information, so that the information provided by the pushed relevant information of the decision path is comprehensive, accurate and efficient.

In one application example, the application also provides an application scenario, as shown in fig. 10, which applies the above medication decision scheme generation method. Specifically, taking cancer pain medication of cancer as an example, the method is applied to a cancer pain medication decision system for explanation, and the application of the medication decision scheme generation method in the application scenario is as follows:

in one embodiment, the cancer pain medication decision system obtains cancer pain medication-related information including cancer pain-to-medication information and cancer pain consensus information, drug instruction information, and open database-related medication information. And the cancer pain medication decision system generates a cancer pain medication knowledge base according to the cancer pain medication related information. And (4) carrying out term standardization processing on the cancer pain medication knowledge base to obtain standardized cancer pain medication knowledge base data. And the cancer pain medication decision system carries out natural language processing on the data of the standardized cancer pain medication knowledge base to obtain cancer pain medication coded data. The cancer pain medication decision system acquires different historical cancer pain clinical treatment data, and generates electronic medical record data according to the historical cancer pain clinical treatment data. And constructing a cancer pain medication knowledge map according to the cancer pain medication coded data and the electronic medical record data, wherein the process is shown in fig. 9.

In one embodiment, the cancer pain medication decision system is operated to determine whether the current patient is a previously taken cancer pain patient in response to the determination of the preset medical staff terminal. When the judgment result is that the cancer pain patient is the cancer pain patient who uses the traditional medicine, the cancer pain medicine decision system obtains the previous information, the outbreak pain information and the compliance information of the current cancer pain patient, and the compliance information is the medicine compliance information of the cancer pain patient who uses the traditional medicine. The cancer pain medication decision system adds the past information, the break-out pain information and the compliance information to the cancer pain patient related information.

In one embodiment, the cancer pain medication decision system acquires cancer pain patient-related information of a current patient, wherein the cancer pain patient-related information comprises basic information and pain information of the current cancer pain patient, and when the current patient is a cancer pain patient who has taken a previous medicine, the cancer pain patient-related information further comprises previous information, break-out pain information and compliance information. The cancer pain medication decision system generates evaluation data corresponding to the information related to the cancer pain patient based on the information related to the cancer pain patient, wherein the evaluation data includes basic evaluation data and pain evaluation data, specifically, the basic evaluation data is generated as shown in fig. 10, and the pain evaluation data includes at least one of pain cause (fig. 11), pain part (fig. 12), pain property (fig. 13), pain intensity (fig. 14) and neuropathic pain evaluation data (fig. 15). When the current cancer pain patient is a previously-administered cancer pain patient, the evaluation data further includes historical evaluation data, breakthrough pain evaluation data, and compliance evaluation data. The cancer pain medication decision system obtains historical evaluation data according to the past information, and specifically, fig. 16 exemplifies the use of the past analgesic medication of cancer pain. And generating blasting pain evaluation data according to the blasting pain information and generating compliance evaluation data according to the compliance information, wherein the compliance evaluation is embedded into a cancer pain medication decision system in a table form as shown in fig. 17.

In one embodiment, the cancer pain medication decision system obtains decision path-related information from a pre-defined cancer pain medication knowledge map based on the evaluation data (see fig. 18). The information related to the decision path is divided into information related to the decision path of a non-existing drug-taking cancer pain patient (for example, fig. 19) and information related to the decision path of an existing drug-taking cancer pain patient (for example, fig. 20), and the existing drug-taking cancer pain patient adds a process of analyzing problems and causes of existing drugs. And pushing the relevant information of the decision path to a selection interface of a preset medical staff terminal, wherein a preset cancer pain medication knowledge graph is constructed based on the relevant information of cancer pain medication and historical cancer pain clinical treatment data, and the relevant information of the decision path comprises different selectable medication schemes.

In one embodiment, in response to selection of a different dosage regimen, the cancer pain medication decision system derives a medication decision for the current cancer pain patient based on the selected dosage regimen. According to the medication decision, the cancer pain medication decision system analyzes the medication related information of the medication in the medication decision, wherein the medication related information comprises the usage amount, the medication time, the adverse reaction, the drug interaction, the drug-food interaction and the caution items of the medication. The cancer pain medication decision system constructs a list table including information related to the medication, and takes the cancer pain medication such as pregabalin as an example, and the list table of pregabalin is shown in fig. 21. And pushing the list clearing table to a preset medical staff terminal. When the current cancer pain patient is a cancer pain patient who has been taken with a previous medicine, the problem and reason existing in the previous medicine are analyzed, the problem analysis and reason analysis are carried out according to a PCNE (pharmaceutical Care Network Europe) classification system, and finally the problem and reason analysis is displayed in the medicine taking decision path related information. The PCNE classification system is a classification scheme for constructing Drug Related Problems (DRPs) during a working meeting of the European pharmaceutical Care alliance (PCNE) in 1 month 1999, and can be used for researching the nature, prevalence and incidence of the DRPs and also used as an index in the process of researching pharmaceutical care results.

In one embodiment, the current cancer pain patient is updated to the previous cancer pain patient in the cancer pain medication decision system, and the related information, evaluation data and medication decision of the previous cancer pain patient are extracted. And updating the extracted information serving as the past information to a preset cancer pain medication knowledge map.

In one embodiment, the cancer pain medication decision system obtains information of satisfaction degree of a preset medical staff terminal to a medication decision. And generating satisfaction evaluation according to the satisfaction information. And storing the satisfaction evaluation as feedback information into a preset cancer pain medication knowledge map.

In this embodiment, comprehensive evaluation data is generated by acquiring patient-related information of a current patient and processing the patient-related information according to the patient-related information. And analyzing the relevant information of the decision path from a preset medication knowledge graph based on the evaluation data generated after the processing. The preset medication knowledge graph is constructed based on medication related information and historical disease clinical treatment data, and evaluation data are analyzed and processed based on the preset medication knowledge graph to determine effective and accurate decision-making path related information. The decision path related information comprises different alternative medication schemes and evidence for evidence collection, not only provides different alternative medication schemes, but also provides corresponding evidence for evidence collection, and the evidence for evidence collection comprises the basis of the decision path, so that the accuracy of scheme medication selection is enhanced. The decision path related information is pushed to a selection interface of a preset medical staff terminal, the selection operation of the decision path related information is responded, the medication decision of the current patient is determined, the information provided by the pushed decision path related information is comprehensive, accurate and efficient, different medication schemes can be represented visually, accurate medication path selection is provided, the final medication decision is made in response to the selection request, and a more accurate and efficient medication decision scheme can be generated.

It should be understood that the steps in the flowcharts in the above embodiments are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in each flowchart may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

In one embodiment, as shown in fig. 22, there is provided a medication decision determination apparatus including: an information obtaining module 2202, a data generating module 2204, a decision path pushing module 2206, and a decision selecting module 2208, wherein:

In one embodiment, the medication decision determining apparatus further includes a medication knowledge map construction module, where the medication knowledge map construction module is configured to obtain medication related information, and the medication related information includes information of medication for a disease, information of consensus of disease, information of drug specification, and information of medication related to an open database; generating a disease medication knowledge base according to medication related information; carrying out term standardization processing on the disease medication knowledge base to obtain standardized disease medication knowledge base data; carrying out natural language processing on the standardized disease medication knowledge base data to obtain disease medication coded data; acquiring historical disease clinical treatment data, and generating electronic medical record data according to the historical disease clinical treatment data; and constructing a medication knowledge map according to the disease medication coded data and the electronic medical record data.

In one embodiment, the assessment data comprises basic assessment data and disease assessment data, and the data generation module is further configured to generate the basic assessment data according to basic information in the patient-related information, wherein the basic information comprises at least one of identity information, historical clinical diagnosis information, auxiliary examination information, personal past medical history information, allergy information, treatment information and physical conditions; and generating disease assessment data according to disease information in the patient-related information, wherein the disease information comprises at least one of disease reason, disease part, disease property, disease intensity and disease neuropathic assessment data.

In one embodiment, the medication decision determination device further comprises a past medication patient judgment module, wherein the past medication patient judgment module is used for judging whether the current patient is a past medication patient based on a preset medication knowledge graph; when the judgment result is that the patient has taken medicine in the past, acquiring the past information, the outbreak pain information and the compliance information of the current patient, wherein the compliance information is the medication compliance information of the patient who has taken medicine in the past; the evaluation data further includes historical evaluation data, breakthrough pain evaluation data, and compliance evaluation data, and generating evaluation data corresponding to the patient-related information based on the patient-related information further includes: adding the past information, the break-out pain information and the compliance information to the patient-related information; obtaining historical evaluation data according to the previous information; and generating burst pain evaluation data according to the burst pain information, and generating compliance evaluation data according to the compliance information.

In one embodiment, the medication decision determining apparatus further includes a list construction module, where the list construction module is configured to analyze, according to the medication decision, information related to a medication used in the medication decision, where the information related to the medication includes at least one of a usage amount of the medication, a medication time, an adverse reaction, a drug interaction, a drug-food interaction, and a notice; constructing a list table including medicine related information of medication; and pushing the list clearing table to a preset medical staff terminal.

In one embodiment, the medication decision determination device further comprises a medication knowledge map update module,

the medication knowledge map updating module is used for updating the current patient into a past medication patient and extracting related information, evaluation data and medication decision of the past medication patient; and updating the extracted information serving as the past information to a preset medication knowledge map.

In one embodiment, the medication decision determining apparatus further includes a satisfaction evaluation generating module, and the satisfaction evaluation generating module is configured to obtain satisfaction information of the current medication patient for the medication decision; generating satisfaction evaluation according to the satisfaction information; and storing the satisfaction evaluation as feedback information into a preset medicine-taking knowledge map.

For specific limitations of the medication decision determination device, reference may be made to the above limitations of the medication decision scheme generation method, which are not described herein again. The modules of the medication decision making apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 23. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is for storing medication use knowledge map data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a medication decision scheme generation method.

Those skilled in the art will appreciate that the architecture shown in fig. 23 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A medication decision plan generation method, the method comprising:

and responding to the selection operation of the different medication schemes, and obtaining the medication decision scheme of the current patient according to the selected medication scheme.

2. The method of claim 1, wherein obtaining decision path-related information from a pre-defined medication knowledge graph based on the assessment data comprises:

generating a disease medication knowledge base according to the medication related information;

3. The method of claim 1, wherein the assessment data comprises basic assessment data and condition assessment data;

the generating, from the patient-related information, assessment data corresponding to the patient-related information comprises:

generating the disease assessment data according to disease information in the patient-related information, wherein the disease information comprises at least one of disease reason, disease position, disease property, disease intensity and disease neuropathic assessment data.

4. The method of claim 3, wherein the assessment data further comprises historical assessment data, breakthrough pain assessment data, and compliance assessment data, and wherein the obtaining patient-related information for the current patient further comprises:

when the judgment result is that the patient has taken the previous medicine, obtaining previous information, outbreak pain information and compliance information of the current patient, wherein the compliance information is the medication compliance information of the patient who has taken the previous medicine;

the generating assessment data corresponding to the patient-related information based on the patient-related information further comprises:

adding the past information, break-out pain information, and compliance information to the patient-related information;

obtaining historical evaluation data according to the past information;

and generating explosion pain evaluation data according to the explosion pain information, and generating compliance evaluation data according to the compliance information.

5. The method of claim 1, wherein, in response to the selecting of the different medication regimen, after deriving a medication decision plan for the current patient based on the selected medication regimen, further comprising:

analyzing relevant information of the medicine used in the medication decision according to the medication decision, wherein the relevant information of the medicine comprises at least one of usage amount, medication time, adverse reaction, medicine interaction, medicine-food interaction and caution items of the medicine;

constructing a list table including the relevant information of the medicines to be taken;

and pushing the list clearing table to the preset medical staff terminal.

6. The method of any one of claims 1 to 5, wherein, in response to the selecting of the different medication regimen, after deriving a medication decision plan for the current patient based on the selected medication regimen, further comprises:

updating the current patient to a prior medication patient, and extracting relevant information, evaluation data and medication decision of the prior medication patient;

and updating the extracted information serving as the past information to the preset medication knowledge map.

7. The method of claim 6, wherein, in response to the selecting of the different medication regimen, after deriving a medication decision plan for the current patient based on the selected medication regimen, further comprising:

obtaining satisfaction information of a preset medical staff terminal to the medication decision;

generating satisfaction evaluation according to the satisfaction information;

and storing the satisfaction evaluation as feedback information to the preset medication knowledge map.

8. A medication decision determination device, comprising:

the information acquisition module is used for acquiring patient-related information of a current patient, wherein the patient-related information comprises basic information and disease information of the current patient;

the data generation module is used for generating evaluation data corresponding to the patient-related information according to the patient-related information;

the decision path pushing module is used for obtaining decision path related information from a preset medication knowledge graph according to the evaluation data and pushing the decision path related information to a selection interface of a preset medical staff terminal, wherein the preset medication knowledge graph is constructed based on the medication related information and clinical treatment data of historical symptoms, and the decision path related information comprises different selectable medication schemes;

and the decision selection module is used for responding to the selection operation of the different medication schemes and obtaining the medication decision scheme of the current patient according to the selected medication scheme.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.