CN111599480A - Method, device, terminal and readable medium for evaluating adverse drug reactions - Google Patents

Abstract

A method for assessing adverse drug reactions, comprising: acquiring medical data of a patient; analyzing the medical data of the patient based on the assessment scale to obtain an analysis result for assessing the possibility that the disease of the patient is caused by adverse drug reactions.

Description

Evaluation method, device, terminal and readable medium for adverse drug reaction

technical field

This article relates to, but is not limited to, the technical field of data processing, and in particular, refers to a method, device, terminal and readable medium for evaluating adverse drug reactions.

Background technique

Adverse Drug Reaction (ADR) refers to various reactions that are unrelated to the purpose of the drug and unfavorable to the patient due to the effect of the drug itself or the interaction between the drugs during the use of commonly used doses of drugs. Adverse drug reactions can generally be divided into four categories: side effects, toxic reactions, allergic reactions and secondary infections. In real life, the incidence of adverse drug reactions is extremely high, especially when drugs are used for a long time or in large doses, adverse drug reactions can endanger human health, and even endanger human life in severe cases. With the development of the pharmaceutical market and the increasing variety of new drugs, it has increased the difficulty for the public to use drugs correctly. Unsafe drug use cannot be completely avoided in the world. ADR monitoring is the main means of monitoring drug safety. Carrying out ADR monitoring is conducive to understanding the occurrence of adverse reactions, facilitating timely adoption of safety precautions and preventing the expansion of the scope of ADR hazards.

However, the current ADR monitoring is mainly based on the spontaneous reporting model, which passively collects ADR case reports from medical institutions (monitoring subjects), drug manufacturers, and operating enterprises across the country. Among them, the current ADR monitoring work in medical institutions is mainly carried out by manually evaluating the medical record data and filling in the form, which greatly depends on the personal initiative of the reporting person, and the labor cost is high and it takes a long time. Moreover, the accuracy of manual evaluation is highly dependent on the evaluator's medical knowledge literacy and clinical diagnosis and treatment experience, and the evaluation results may be biased due to human subjective factors.

SUMMARY OF THE INVENTION

The present application provides an assessment method, device, terminal and readable medium for adverse drug reactions, which can realize automatic assessment of adverse drug reactions, thereby improving the accuracy and efficiency of assessment.

In one aspect, the present application provides a method for evaluating adverse drug reactions, comprising: obtaining medical data of a patient; analyzing the medical data of the patient based on an evaluation scale to obtain an analysis result, which is used to evaluate the patient's disease the possibility of adverse drug reactions.

In another aspect, the present application provides an evaluation device for adverse drug reactions, comprising: a data acquisition module configured to acquire medical data of a patient; an evaluation processing module configured to analyze the medical data of the patient based on an evaluation scale , and the analysis result is obtained, which is used to evaluate the possibility that the disease of the patient is caused by the adverse drug reaction.

In another aspect, the present application provides a terminal, comprising: a memory and a processor, the memory is configured to store a computer program, when the computer program is executed by the processor, the method for evaluating the adverse drug reaction described above is implemented. step.

In another aspect, the present application provides a computer-readable medium storing a computer program that, when executed, implements the steps of the method for evaluating an adverse drug reaction as described above.

The evaluation method for adverse drug reactions provided in this application is based on the evaluation scale, and the medical data of the patient is analyzed to obtain the analysis result, which is used to evaluate the possibility that the patient's disease is caused by the adverse drug reaction. In this way, it is possible to Realizing the automatic giving of the analysis results of adverse drug reactions not only reduces labor costs, but also accelerates the evaluation speed, and can eliminate the subjective interference factors of manual evaluation and improve the evaluation accuracy.

Other features and advantages of the present application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the present application. Other advantages of the present application may be realized and attained by the approaches described in the specification and drawings.

Description of drawings

The accompanying drawings are used to provide an understanding of the technical solutions of the present application, and constitute a part of the specification. They are used to explain the technical solutions of the present application together with the embodiments of the present application, and do not constitute a limitation on the technical solutions of the present application.

Fig. 1 is the flow chart of the evaluation method of the adverse drug reaction provided by the embodiment of this application;

2 is a schematic diagram of an evaluation device for adverse drug reactions provided by an embodiment of the present application;

FIG. 3 is an example diagram of a terminal provided by an embodiment of the present application.

Detailed ways

This application describes a number of embodiments, but the description is exemplary rather than restrictive, and it will be apparent to those of ordinary skill in the art that within the scope of the embodiments described in this application can be There are many more examples and implementations. Although many possible combinations of features are shown in the drawings and discussed in the embodiments, many other combinations of the disclosed features are possible. Unless expressly limited, any feature or element of any embodiment may be used in combination with, or may be substituted for, any other feature or element of any other embodiment.

This application includes and contemplates combinations with features and elements known to those of ordinary skill in the art. The embodiments, features and elements that have been disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions as defined by the claims. Any features or elements of any embodiment may also be combined with features or elements from other inventive arrangements to form another unique inventive arrangement defined by the claims. Accordingly, it should be understood that any of the features shown and/or discussed in this application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not to be limited except in accordance with the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

Furthermore, in describing representative embodiments, the specification may have presented a method or process as a particular sequence of steps. However, to the extent that the method or process does not depend on the specific order of steps described herein, the method or process should not be limited to the specific order of steps described. Other sequences of steps are possible, as will be understood by those of ordinary skill in the art. Therefore, the specific order of steps set forth in the specification should not be construed as limitations on the claims. Furthermore, the claims directed to the method and/or process should not be limited to performing their steps in the order written, as those skilled in the art will readily appreciate that these orders may be varied and still remain within the spirit and scope of the embodiments of the present application Inside.

The present application provides an evaluation method, device, terminal and readable medium for adverse drug reactions. By analyzing the medical data of a patient, an evaluation result can be obtained quickly and automatically, which not only reduces labor costs, but also speeds up evaluation and improves the efficiency of evaluation. The evaluation efficiency can be eliminated, and the subjective interference factors of manual evaluation can be excluded, and the evaluation accuracy can be improved.

FIG. 1 is a flowchart of the method for evaluating adverse drug reactions provided in the embodiment of the present application. As shown in Figure 1, the method for evaluating adverse drug reactions provided in this embodiment includes the following steps:

Step 101, obtaining medical data of a patient;

Step 102 , based on the evaluation scale, analyze the medical data of the patient to obtain an analysis result, which is used to evaluate the possibility that the patient's disease is caused by an adverse drug reaction.

The evaluation method provided in this embodiment can be applied to a client computing device (for example, a mobile terminal such as a portable computer, or a fixed terminal such as a desktop computer). Exemplarily, the client computing device may perform analysis based on locally stored medical data in combination with an assessment scale to obtain an analysis result. However, this application is not limited to this. In other implementation manners, the evaluation method provided in this embodiment may also be executed cooperatively by a client computing device and a server computing device (eg, a server); for example, the client computing device may acquire medical data and evaluation from the server computing device Alternatively, the client computing device may send an evaluation instruction to the server computing device, and after receiving the evaluation instruction, the server computing device analyzes the corresponding medical data based on the evaluation scale.

Taking the application of the evaluation method provided in this embodiment to a client computing device as an example, the client computing device may execute the above evaluation method after receiving a trigger instruction. For example, a doctor clicks an automatic evaluation button on the display interface of the client computing device. to issue a trigger instruction; or, the client computing device may execute the foregoing evaluation method according to a preset condition, for example, execute the foregoing evaluation method according to a set period. However, this application is not limited to this.

In an exemplary embodiment, in step 101, acquiring the patient's medical data may include: acquiring the patient's medical data from an electronic medical record database according to the patient's identification information; wherein the medical data may include: patient basic data, condition diagnosis data , Check test data and doctor's order medication data.

In this exemplary embodiment, medical data can be obtained from an electronic medical record database of a medical institution, and active monitoring of the electronic medical record data can be realized by using the electronic medical record data to evaluate adverse drug reactions.

In this exemplary embodiment, the identification information of the patient may be unique, for example, the identification information may be an ID number, a medical insurance number, a medical record number in a medical institution, a mobile phone number, and the like. The information database (for example, the electronic medical record database) of the medical institution is used to store all kinds of data of the patient in the process of seeing a doctor in real time. Through the identification information of the patient, each visit record of the patient in the medical institution can be found from the information database of the medical institution, and the medical data of the patient can be obtained from the patient's visit record. Among them, the basic data of the patient may include: age, gender, blood type, height, weight, whether there are special groups (such as children, women), whether there is an allergy history and other physiological characteristic data; disease diagnosis data may include the patient's medical treatment process given by the doctor The diagnostic data of the medical device; the inspection data includes the data of various inspections performed by the patient during the medical treatment; the doctor's order medication data includes the patient's medication data during the medical treatment.

In this exemplary embodiment, the patient's electronic medical record data can be obtained from the electronic medical record database of a medical institution according to the patient's identification information; then, the patient's electronic medical record data is desensitized to protect the patient's privacy; The desensitized electronic medical record data were analyzed based on the evaluation scale.

In an exemplary embodiment, the selection of the evaluation scale may be manually determined by a doctor, for example, for a certain patient, when the doctor initially concludes that the patient's disease is liver injury, the doctor may select the evaluation amount of drug-induced liver injury. The table performs automated analysis of the patient's medical data to assess the likelihood that the patient's liver damage was caused by a drug. Alternatively, the assessment scale can be automatically determined by a computer program. For example, by detecting disease diagnosis data, it is known that the patient is currently diagnosed with liver injury, and the computer program can automatically determine the medical treatment of the patient using the drug-induced liver injury assessment scale. The data were analyzed to assess the likelihood that the patient's liver injury was caused by a drug. However, this application is not limited to this.

In an exemplary embodiment, the assessment scale may include at least one assessment item, and by analyzing the patient's medical data, an assessment score of the patient's medical data in each assessment item may be obtained; all assessment items in the assessment scale The total score can reflect the possibility that the patient's disease is caused by adverse drug reactions. For example, for liver injury, the assessment scale for drug-induced liver injury can be used for scoring; for kidney injury, the assessment scale for drug-induced kidney injury can be used for scoring. It should be noted that the evaluation scale in this embodiment includes an existing authoritative and quantifiable analysis scale for adverse drug reaction diseases that have been relatively well-researched. In this way, the accuracy of adverse drug reactions can be ensured.

In an exemplary embodiment, step 102 may include: for any evaluation item in the evaluation scale, according to the question type to which the evaluation item belongs, determining an analysis strategy corresponding to the evaluation item; According to the analysis strategy, the medical data of the patient is analyzed to obtain the evaluation score of the medical data of the patient in the evaluation item; the analysis result is obtained according to the evaluation score of all the evaluation items in the evaluation scale. For example, by analyzing the medical data of the patient, scoring each evaluation item in the evaluation scale, and calculating the total score of all the evaluation items after completing the scoring, the final analysis result can be obtained.

In an exemplary embodiment, the question type may include: a first type of question for analysis by mapping data fields in medical data (eg, the first type of question includes at least one of the following types: for analysis by mapping medical data The field value of the data field in the data field, and the problem that is analyzed according to the calculation result of the field value; for the problem of analyzing by mapping the field value of the data field in the medical data), for at least the medical data and the drug description data. The second type of problem in one item is to extract data for analysis, and the third type of problem is used to analyze medical data by logical calculation.

In this exemplary embodiment, based on the current research on the impact of adverse drug reactions, the evaluation method for judging whether there is an adverse drug reaction usually includes the following aspects: the degree of overlap between the onset time and the time of using the corresponding drug, whether the patient itself has the Risk factors for such adverse effects, presence of concomitant medication or interference from other factors that can lead to adverse effects within the time frame to be evaluated, whether the drug has caused such adverse effects and the number of cases, etc. Based on this, in this exemplary embodiment, the questions to be analyzed in the evaluation scale can be classified into the above three types.

In an exemplary embodiment, the analysis strategy corresponding to the evaluation item belonging to the first type of question includes at least one of the following: searching the medical data for a data field mapped with the evaluation item, value, determine the evaluation score of the medical data on the evaluation item; look up the data field mapped with the evaluation item from the medical data, and calculate the field value of the found data field (for example, according to the setting The calculation formula or the field value of the found data field is required to be calculated), and according to the calculation result, the evaluation score of the medical data on the evaluation item is determined;

The analysis strategy corresponding to the evaluation item belonging to the second type of question includes: extracting data related to the evaluation item from at least one item of medical and drug description data according to a set format, or, through natural language analysis, from medical data and drug data. Extracting data related to the evaluation item from at least one item of the description data; determining the evaluation score of the medical data on the evaluation item according to the extracted data;

The analysis strategy corresponding to the evaluation item belonging to the third type of problem includes: extracting data related to the evaluation item from the medical data, performing logical calculation on the extracted data according to the set logical calculation rules, and obtaining the medical data in the The assessment score on the assessment item.

In this exemplary embodiment, the patient's medical data may be structured data; for the evaluation items belonging to the first type of questions, it may be directly mapped with the data field names in the medical data, according to the field values of the mapped data fields For the evaluation items that belong to the second type of questions, relevant data can be extracted from large paragraphs of text in medical data or drug description data (for example, drug instructions) for scoring; for the evaluation items that belong to the third type of questions, Multiple data fields can be extracted from medical data, and then logical calculations are performed on the field values to score.

In an exemplary embodiment, the evaluation method of this embodiment may further include: recording the data in the medical data for obtaining the analysis result into a database. In this exemplary embodiment, by recording the data used in the evaluation process of the evaluation scale, it can be ensured that the original data used to obtain the analysis result can be traced back, thereby ensuring the rigor of the automatic evaluation process.

In an exemplary implementation, the evaluation method of this embodiment may further include: recording the analysis process for obtaining the analysis result; and displaying the analysis process for obtaining the analysis result after receiving the control instruction. In this exemplary embodiment, when displaying the analysis process, for the evaluation items belonging to the first type of questions, the field names and field values of the data fields used can be directly displayed; for the evaluation items belonging to the second type of questions, you can Display the content of documents extracted from medical data or drug description data, and mark the relevant sentences in it (for example, marked in red); for the evaluation items belonging to the third type of problems, you can display the data fields extracted from medical data. Field name and field value, and then display the logical calculation process between field values according to the set format, so that the logical calculation process is clear at a glance. By displaying the analysis process, it is easy to trace the data, and it is convenient for manual review to ensure the rigor of the automatic evaluation process.

The evaluation method provided by the embodiment of the present application is illustrated below by using an example. In this example, the Roussel Uclaf Causality Assessment Method (RUCAM) scale is used as an example to evaluate hepatocellular drug-induced liver injury, that is, through the clinical, biochemical and , serological and radiological characteristics were scored, and finally a comprehensive total score was obtained, reflecting the possibility of liver injury caused by a certain drug. In this example, the RUCAM scale is shown below.

RUCAM scale

In the table above, Group I includes the following seven categories of etiology: Hepatitis A virus (HAV) infection; Hepatitis B virus (HBV) infection; Hepatitis C virus (HCV) infection; Hepatitis E virus (HEV) infection; Ultrasound imaging/hepatic vascular color Doppler imaging/intracavitary ultrasonography/CT/MRC; alcoholism (aspartate aminotransferase (AST)/ALT ≥2); recent history of acute hypotension (especially if underlying cardiac disease) .

Group II includes the following 5 etiologies: combined sepsis, metastatic malignancy, autoimmune hepatitis, chronic hepatitis B or C, primary biliary cholangitis or primary sclerosing cholangitis, and hereditary liver disease etc.; cytomegalovirus (CMV) infection; Epstein-Barr virus (EBV) infection; herpes simplex virus (HSV) infection; varicella-zoster virus (VZV) infection.

After scoring the seven evaluation items in the above table, the seven evaluation scores are added up to obtain the final score; where the final score is 0 or lower, it means that the drug is excluded as the cause of liver injury; A final score of 1 to 2 indicates that the drug is unlikely to be the cause of the liver injury; a final score of 3 to 5 indicates that the drug is likely to be the cause of the liver injury; the final score A score of 6 to 8 indicates that the drug is probable as the cause of liver injury; a final score greater than 8 indicates that the drug is highly probable as the cause of liver injury.

In this example, before the evaluation scale is automatically scored, the patient's electronic medical record data may be obtained from the electronic medical record database of the medical institution, and desensitization processing is performed to obtain the patient's medical data. Then, according to the above-mentioned RUCAM scale, through data extraction and analysis from the patient's medical data, the possibility of the patient having adverse drug reactions is evaluated. Among them, the information of the medicines taken by the patients can be determined according to the data of the patients' doctor's orders, and then the RUCAM scale score processing is performed on the medicines in turn, so as to judge the possibility of the medicines having adverse reactions to the patient according to the obtained scores. .

In this example, based on the RUCAM scale, the questions that need to be analyzed in the assessment items can be classified into the following three types: first type questions for analysis by mapping data fields in medical data, questions for analysis from medical data and The second type of problems for analysis by extracting data from at least one item of drug description data (for example, document materials such as drug instructions), and the third type of problems for analysis by logical calculation of medical data.

In this example, the RUCAM scale includes seven assessment items, of which the first assessment item (time from medication to onset), the second assessment item (duration after drug withdrawal), and the fourth assessment item (concomitant medication) , the seventh assessment item (drug restimulation) belongs to the first category of questions; the sixth assessment item (previous information) belongs to the second category of questions; the third assessment item (risk factors), the fifth assessment item (other reasons) ) belongs to the third category of problems. Among them, different options of each assessment item correspond to different scores, and the sum of the scores of all assessment items is the total score, which can be used as a criterion for judging whether there is drug-induced liver injury.

In this example, the first evaluation item is the judgment of the time from taking the medicine to the onset, which belongs to the first type of question. Among them, the medication time can be obtained by mapping to the relevant time field in the doctor's order medication data, and the onset time can be obtained by mapping to the relevant time field in the disease diagnosis data or inspection data. According to the difference between the field values of the above two time fields, The number of days from taking the medicine to the onset can be obtained, and then the options corresponding to the obtained days from taking the medicine to the onset can be determined and scored; for example, if the patient is taking the medicine for the first time and the number of days from taking the medicine to the onset is 20 days, then according to the amount of RUCAM The table determines that the first assessment item has a score of +2.

The second assessment item is the course of the disease after drug withdrawal, which is determined according to the decrease in the difference between the peak ALT and the upper limit of normal (ULN) in a certain period of time. The second assessment item belongs to the first category of questions. Among them, the percentage of ALT level reduction=100%*(ALT peak value-ALT value)/(ALT peak value-ULN); the data in the above formula can be obtained from the relevant data fields in the inspection data, and determined according to the calculation results The score for the second assessment item.

The third assessment item is whether the patient has risk factors for liver injury, which belongs to the third category of questions. Among them, age, gender and drinking information can be extracted from the basic information of the patient, and then logical calculation is performed on the extracted information to determine the corresponding options, and determine the score of the third evaluation item.

The fourth evaluation item is the consistency of concomitant medication and onset time, which belongs to the first category. Among them, the concomitant medication can be obtained by directly mapping the field value of the corresponding data field in the medical order medication data, and then the corresponding option is determined according to the mapped field value, and the score of the fourth evaluation item is determined.

The fifth assessment item is whether the patient has suffered from some specified diseases that can cause liver damage, which belongs to the third type of question. Among them, relevant data can be extracted from the disease diagnosis data of the patient (for example, HAV infection existed before), and the corresponding options can be determined by logical judgment according to the extracted data, and then the score can be obtained.

The sixth evaluation item is whether there is a precedent for causing liver damage in the drug instructions and other documents, which belongs to the second category of questions. Among them, by extracting data from the drug instructions of the used drugs, for example, structuring the drug instructions according to the format characteristics of the instructions, or using natural language analysis to extract data from the drug instructions, and according to the extracted data, determine the corresponding drug instructions. options and get points.

Among them, in addition to the description of adverse reactions, the drug insert usually also records the name of the drug, specifications, expiration date, main ingredients, indications or functions, usage, dosage, contraindications and precautions, etc., which can be recognized by text recognition technology. The adverse reaction descriptions in the drug inserts were extracted.

The seventh assessment item is the relationship between drug re-use and disease incidence, which belongs to the first category. Among them, the ALT before and after re-medication can be obtained by mapping to the relevant data fields in the inspection data, and the relationship between the re-medication and the disease can be judged according to the value obtained by the mapping, the corresponding options are determined, and the score is obtained.

In the above evaluation process, the data used in the patient's medical data can be recorded in the database, and the evaluation process and strategy can be traced back. In addition, the recorded data and evaluation process can be displayed. For example, for the analysis process of the first type of problems, the data field names and field values mapped from medical data can be directly displayed; for the analysis process of the second type of problems, the extracted specific sentences can be recorded, and the relevant information can be displayed when the document content is displayed. Statements are marked in red; for the third type of problem, multiple fields may be involved. After the names of the record fields are marked in red, the logical calculation process can be output to the display page in a fixed format, making the calculation process clear at a glance.

The evaluation method for adverse drug reactions provided by this embodiment realizes automatic evaluation and scoring through a computer program, which can improve the evaluation speed, eliminate the subjective interference factors of manual evaluation, and improve the evaluation accuracy. Moreover, classifying the problems to be analyzed in the evaluation and setting the corresponding automatic analysis strategy can improve the feasibility of automatic evaluation and the processing efficiency. In addition, by recording and displaying the analysis process, the evaluation process can be traced back, thereby making the automated evaluation more rigorous.

FIG. 2 is a schematic diagram of an evaluation device for adverse drug reactions provided by an embodiment of the present application. As shown in FIG. 2 , the evaluation device provided in this embodiment includes: a data acquisition module 201 configured to acquire medical data of a patient; an evaluation processing module 202 configured to analyze the medical data of the patient based on an evaluation scale , and the analysis result is obtained, which is used to evaluate the possibility that the disease of the patient is caused by the adverse drug reaction.

In an exemplary embodiment, the data acquisition module 201 is configured to acquire the medical data of the patient in the following manner: acquiring the medical data of the patient from the electronic medical record database according to the identification information of the patient; wherein the medical data includes: the basic information of the patient; Data, disease diagnosis data, inspection and test data, and doctor's order medication data.

In an exemplary embodiment, the assessment scale includes at least one assessment item;

The evaluation processing module 202 is configured to analyze the medical data of the patient based on the evaluation scale in the following manner to obtain an analysis result: for any evaluation item in the evaluation scale, according to the Question type, determine the analysis strategy corresponding to the evaluation item; use the analysis strategy corresponding to the evaluation item to analyze the medical data of the patient, and obtain the evaluation score of the patient's medical data in the evaluation item; According to the evaluation scores of all evaluation items in the evaluation scale, the analysis result is obtained.

In an exemplary embodiment, the question types include: a first type of question for analysis by mapping data fields in medical data, a first type of question for analysis by extracting data from at least one of medical data and drug description data. The second type of problem and the third type of problem are used to analyze the medical data by logical calculation.

In an exemplary embodiment, the analysis strategy corresponding to the evaluation item belonging to the first type of question includes at least one of the following: searching the medical data for a data field mapped with the evaluation item, value, determine the evaluation score of the medical data on the evaluation item; find the data field mapped with the evaluation item from the medical data, calculate the field value of the found data field, and according to the calculation result, determining the evaluation score of the medical data on the evaluation item;

The analysis strategy corresponding to the evaluation item belonging to the second type of question includes: extracting data related to the evaluation item from at least one of the medical data and the drug description data according to the set format, or, through natural language analysis, from the medical data and the drug description data. Extracting data related to the evaluation item from at least one item of the drug description data; determining the evaluation score of the medical data on the evaluation item according to the extracted data;

The analysis strategy corresponding to the evaluation item belonging to the third type of problem includes: extracting data related to the evaluation item from the medical data, performing logical calculation on the extracted data according to the set logical calculation rules, and obtaining the medical data in the The assessment score on the assessment item.

In an exemplary implementation, the evaluation apparatus provided in this embodiment may further include: a first storage module, configured to record the data in the medical data for obtaining the analysis result into a database.

In an exemplary implementation, the evaluation device provided in this embodiment may further include: a second storage module, configured to record the analysis process for obtaining the analysis result; and a display module, configured to display the obtained result after receiving the control instruction. The analysis process of the analysis result.

For the relevant description of the evaluation apparatus provided in this embodiment, reference may be made to the description of the above-mentioned embodiment of the evaluation method, so it will not be repeated here.

An embodiment of the present application further provides a terminal, including: a memory and a processor; the memory is configured to store a computer program, and when the computer program is executed by the processor, implements the steps of the above-mentioned method for evaluating adverse drug reactions.

FIG. 3 is an example diagram of a terminal provided by an embodiment of the present application. In an example, as shown in FIG. 3 , the terminal provided in this embodiment includes: a processor 31, a memory 32, and a bus system 33; wherein the processor 31 and the memory 32 are connected through the bus system 33; the memory 32 is configured as The instructions are stored, and the processor 31 is configured to execute the instructions stored by the memory 32 .

It should be noted that the structure of the terminal shown in FIG. 3 does not constitute a limitation on the terminal, and may include more or less components than shown, or combine some components, or provide different component arrangements.

It should be understood that the processor 31 may be a central processing unit (Central Processing Unit, “CPU” for short), and the processor 31 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf processors Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Memory 32 may include read only memory and random access memory, and provides instructions and data to processor 31 . A portion of memory 32 may also include non-volatile random access memory. For example, memory 32 may also store device type information.

In addition to the data bus, the bus system 33 may also include a power bus, a control bus, a status signal bus, and the like. However, for the sake of clarity, the various buses are designated as bus system 33 in FIG. 3 .

In the implementation process, the processing performed by the above-mentioned device for evaluating adverse drug reaction may be completed by an integrated logic circuit of hardware in the processor 31 or an instruction in the form of software. That is, the steps of the evaluation method disclosed in the embodiments of the present application may be embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media. The storage medium is located in the memory 32, and the processor 31 reads the information in the memory 32, and completes the steps of the above method in combination with its hardware. To avoid repetition, detailed description is omitted here.

In addition, the embodiments of the present application further provide a computer-readable medium storing a computer program, and when the computer program is executed, the steps of the above-mentioned method for evaluating an adverse drug reaction are implemented.

Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, functional modules/units in the systems, and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be composed of several physical components Components execute cooperatively. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those of ordinary skill in the art, the term computer storage media includes both volatile and nonvolatile implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules or other data flexible, removable and non-removable media. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, magnetic tape, magnetic disk storage or other magnetic storage devices, or may Any other medium used to store desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and can include any information delivery media, as is well known to those of ordinary skill in the art .

The above shows and describes the basic principles and main features of the present application and the advantages of the present application. The present application is not limited by the above-mentioned embodiments. The above-mentioned embodiments and descriptions only describe the principles of the present application. Without departing from the spirit and scope of the present application, the present application will also have various changes and improvements. These changes and improvements are within the scope of the claimed application.

Claims (10)

1. A method for assessing adverse drug reactions, comprising:

acquiring medical data of a patient;

analyzing the medical data of the patient based on an assessment scale to obtain an analysis result for assessing the possibility that the disease of the patient is caused by adverse drug reactions.

2. The assessment method of claim 1, wherein said obtaining medical data of a patient comprises: acquiring medical data of the patient from an electronic medical record database according to the identification information of the patient; wherein the medical data comprises: patient profile data, patient condition diagnostic data, examination and test data, and medical order medication data.

3. The assessment method according to claim 1, wherein said assessment scale comprises at least one assessment item;

analyzing the medical data of the patient based on the assessment scale to obtain an analysis result, comprising: aiming at any evaluation item in the evaluation scale, determining an analysis strategy corresponding to the evaluation item according to the problem type of the evaluation item; analyzing the medical data of the patient by adopting an analysis strategy corresponding to the evaluation item to obtain an evaluation score of the medical data of the patient in the evaluation item; and obtaining an analysis result according to the evaluation scores of all the evaluation items in the evaluation scale.

4. The evaluation method according to claim 3, wherein the question type includes: a first category of questions for analysis by mapping data fields in the medical data, a second category of questions for analysis by extracting data from at least one of the medical data and the drug description data, and a third category of questions for analysis by performing logical calculations on the medical data.

5. The evaluation method according to claim 4, wherein the analysis policy corresponding to the evaluation item belonging to the first category of questions comprises at least one of: searching a data field mapped with the evaluation item from the medical data, and determining an evaluation score of the medical data on the evaluation item according to the field value of the searched data field; searching a data field mapped with the evaluation item from the medical data, calculating the field value of the searched data field, and determining the evaluation score of the medical data on the evaluation item according to the calculation result;

the analysis strategy corresponding to the evaluation items belonging to the second type of problems comprises the following steps: extracting data related to the evaluation item from at least one of medical data and medicine description data according to a set format, or extracting data related to the evaluation item from at least one of medical data and medicine description data through natural language analysis; determining an evaluation score of the medical data on the evaluation item according to the extracted data;

the analysis strategy corresponding to the evaluation item belonging to the third type of problem comprises the following steps: and extracting data related to the evaluation items from the medical data, and performing logic calculation on the extracted data according to a set logic calculation rule to obtain the evaluation score of the medical data on the evaluation items.

6. The evaluation method according to claim 1, further comprising: and recording data used for obtaining an analysis result in the medical data to a database.

7. The evaluation method according to claim 1, further comprising: recording an analysis process for obtaining the analysis result; and after receiving the control instruction, displaying the analysis process of the analysis result.

8. An apparatus for evaluating adverse drug reactions, comprising:

a data acquisition module configured to acquire medical data of a patient;

and the evaluation processing module is configured to analyze the medical data of the patient based on the evaluation scale to obtain an analysis result for evaluating the possibility that the disease of the patient is caused by adverse drug reactions.

9. A terminal, comprising: a memory and a processor, the memory configured to store a computer program that, when executed by the processor, carries out the steps of the method of assessing an adverse drug reaction of any one of claims 1 to 7.

10. A computer-readable medium, characterized in that a computer program is stored which, when executed, carries out the steps of the method for assessing adverse drug reactions of any one of claims 1 to 7.

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