CN111599480A

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

Info

Publication number: CN111599480A
Application number: CN202010313239.XA
Authority: CN
Inventors: 宋海波
Original assignee: Drug Evaluation Center Of State Drug Administration
Current assignee: Drug Evaluation Center Of State Drug Administration
Priority date: 2020-04-20
Filing date: 2020-04-20
Publication date: 2020-08-28
Anticipated expiration: 2040-04-20
Also published as: CN111599480B

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

Method, device, terminal and readable medium for evaluating adverse drug reactions

Technical Field

The present disclosure relates to, but not limited to, the field of data processing technologies, and in particular, to a method, an apparatus, a terminal and a readable medium for evaluating adverse drug reactions.

Background

Adverse Drug Reactions (ADRs) refer to various reactions that are not related to the purpose of administration and are not beneficial to patients during the administration of a conventional dose of a Drug due to the action of the Drug itself or the interaction between drugs. Adverse drug reactions can be generally classified into four categories, namely side effects, toxic reactions, allergic reactions and secondary infections. In real life, the incidence rate of adverse drug reactions is extremely high, and particularly when the drug is used for a long time or the dosage is large, the adverse drug reactions can harm the health of human beings, and even endanger the life of human beings when the condition is serious. With the development of the medicine market and the continuous increase of new medicine varieties, the difficulty of the public in correctly using the medicine is increased. Unsafe medication is difficult to completely avoid in the world, ADR monitoring is a main means for monitoring medicine safety, ADR monitoring is developed to be beneficial to knowing adverse reaction occurrence conditions, safety precaution measures are convenient to take in time, and the condition range of ADR harm is prevented from being expanded.

However, the current ADR monitoring is mainly based on a spontaneous report mode, and ADR case reports from national medical institutions (monitoring subjects), pharmaceutical manufacturers, and business enterprises are passively collected. The ADR monitoring work in the existing medical institution is mainly carried out in a mode of manually evaluating medical record data and filling a form, greatly depends on the personal subjective activity of the reporter, and has high labor cost and long time consumption. Moreover, the accuracy of manual evaluation is highly dependent on the medical knowledge literacy and clinical experience of the evaluator, and the evaluation result may have deviation due to subjective factors of the evaluator.

Disclosure of Invention

The application provides a method, a device, a terminal and a readable medium for evaluating adverse drug reactions, which can realize automatic evaluation of adverse drug reactions, thereby improving evaluation accuracy and efficiency.

In one aspect, the present application provides 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.

In another aspect, the present application provides a device 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.

In another aspect, the present application provides a terminal, including: a memory and a processor, the memory being configured to store a computer program which, when executed by the processor, carries out the steps of the method of assessing adverse drug reactions as described above.

In another aspect, the present application provides a computer readable medium storing a computer program which, when executed, implements the steps of the method for assessing adverse drug reactions as described above.

According to the method for evaluating adverse drug reactions, the medical data of the patient are analyzed based on the evaluation scale to obtain the analysis result, and the analysis result is used for evaluating the possibility that the disease of the patient is caused by the adverse drug reactions.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. Other advantages of the present application may be realized and attained by the instrumentalities and combinations particularly pointed out in the specification and the drawings.

Drawings

The accompanying drawings are included to provide an understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the examples serve to explain the principles of the disclosure and not to limit the disclosure.

FIG. 1 is a flow chart of a method for assessing adverse drug reactions provided in the examples of the present application;

FIG. 2 is a schematic view of an apparatus for evaluating adverse drug reactions provided in the embodiments of the present application;

fig. 3 is an exemplary diagram of a terminal according to an embodiment of the present application.

Detailed Description

The present application describes embodiments, but the description is illustrative rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. 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. Any feature or element of any embodiment may be used in combination with or instead of any other feature or element in any other embodiment, unless expressly limited otherwise.

The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive concept as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive aspects to form yet another unique inventive aspect, as defined by the claims. Thus, 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 limited except as by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

Further, 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 rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other orders of steps are possible as will be understood by those of ordinary skill in the art. Therefore, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Further, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.

The application provides an evaluation method, an evaluation device, a terminal and a readable medium for adverse drug reactions, which can quickly and automatically obtain an evaluation result by analyzing medical data of a patient, thereby not only reducing the labor cost, accelerating the evaluation speed and improving the evaluation efficiency, but also eliminating subjective interference factors of manual evaluation and improving the evaluation accuracy.

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

step 101, acquiring medical data of a patient;

and 102, analyzing the medical data of the patient based on the evaluation scale to obtain an analysis result, wherein the analysis result is used for evaluating the possibility that the disease of the patient is caused by adverse drug reactions.

The evaluation method provided by the embodiment can be applied to client computing equipment (for example, a mobile terminal such as a portable computer, or a fixed terminal such as a desktop computer). Illustratively, the client computing device may perform an analysis in conjunction with the assessment scale based on the locally stored medical data to obtain an analysis result. However, this is not limited in this application. In other implementations, the evaluation method provided by this embodiment may also be executed by a client computing device and a server computing device (e.g., a server) in cooperation; for example, the client computing device may obtain medical data and assessment scales from the server computing device and then analyze the medical data and assessment scales; or, 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 evaluation method provided by the present embodiment as an example, the client computing device may execute the evaluation method after receiving the trigger instruction, for example, a doctor clicks an automatic evaluation button on a display interface of the client computing device to issue the trigger instruction; alternatively, the client computing device may execute the above evaluation method according to preset conditions, for example, according to a set period. However, this is not limited in this application.

In an exemplary embodiment, in step 101, acquiring medical data of a patient may include: acquiring medical data of a patient from an electronic medical record database according to the identification information of the patient; the medical data may include, among other things: patient profile data, patient condition diagnostic data, examination and test data, and medical order medication data.

In the exemplary embodiment, the medical data can be acquired from an electronic medical record database of a medical institution, and the electronic medical record data is used for evaluating adverse drug reactions, so that the electronic medical record data can be actively monitored.

In the exemplary embodiment, the identification information of the patient may have uniqueness, for example, the identification information may be an identification number, a medical care number, a medical record number in a medical institution, a mobile phone number, and the like. An information database (e.g., an electronic medical record database) of a medical institution is used for storing various types of data of patients during a treatment process in real time. Through the identification information of the patient, the medical record of each visit of the patient at the medical institution can be searched from the information database of the medical institution, and the medical data of the patient can be obtained from the visit record of the patient. Wherein the patient profile may include: age, sex, blood type, height, weight, whether special population (such as children and women) exists, whether allergy history exists, and other physiological characteristic data; the medical condition diagnostic data may include diagnostic data given by a physician during a medical procedure of the patient; the examination and verification data comprises data of various examinations carried out by the patient in the hospitalizing process; the prescription medication data comprises medication data of the patient during the hospitalization.

In the exemplary embodiment, the electronic medical record data of the patient can be acquired from an electronic medical record database of a medical institution according to the identification information of the patient; then, desensitizing the electronic medical record data of the patient to protect the privacy of the patient; analysis was performed based on assessment scales for desensitized electronic medical record data.

In an exemplary embodiment, the selection of the assessment scale may be manually determined by a physician, for example, when the physician preliminarily finds that the patient is suffering from liver injury, the physician may select a drug-induced liver injury assessment scale to automatically analyze the medical data of the patient to assess the possibility that the liver injury of the patient is caused by a drug. Alternatively, the assessment scale may be automatically determined by a computer program, for example, by detecting the disease diagnosis data to determine that the patient is currently diagnosed with liver damage, and the computer program may automatically determine to analyze the medical data of the patient using the assessment scale for drug-induced liver damage to assess the likelihood that the liver damage of the patient is caused by a drug. However, this is not limited in this application.

In an exemplary embodiment, the assessment scale may include at least one assessment item, and the assessment score of the medical data of the patient at each assessment item may be obtained by analyzing the medical data of the patient; the total score of all the assessment items in the assessment scale may reflect the likelihood that the patient's disease is caused by an adverse drug reaction. For example, for liver injury, an assessment scale for drug-induced liver injury can be used for scoring; for renal injury, a rating scale for drug-induced renal injury may be used for scoring. It should be noted that the assessment scale of the present embodiment includes a quantitative analysis scale for the existing authoritative presence of relatively well studied adverse drug reaction disease. Therefore, the accuracy of the adverse drug reactions can be ensured.

In an exemplary embodiment, step 102 may include: 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. For example, by analyzing the medical data of the patient, scoring each assessment item in the assessment scale, and calculating the total score of all assessment items after scoring, the final analysis result can be obtained.

In an exemplary embodiment, the issue types may include: a first category of questions for analysis by mapping data fields in the medical data (e.g., the first category of questions includes at least one type of questions for analysis by mapping field values of the data fields in the medical data and based on results of calculation of the field values; questions for analysis by mapping field values of the 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 calculation on the medical data.

In the present exemplary embodiment, based on the current research on the adverse drug reaction effect, the evaluation method for determining whether the adverse drug reaction exists generally includes the following aspects: the coincidence of the onset time with the time of administration of the corresponding drug, whether the patient himself has risk factors for such adverse effects, whether there is interference with concomitant medication or other factors which may lead to adverse effects in the time frame to be evaluated, whether the drug already has cases and the number of cases which lead to such adverse effects, etc. Based on this, in the present exemplary embodiment, the questions to be analyzed in the evaluation scale can be classified into the above-described three types.

In an exemplary embodiment, the analysis policy corresponding to the evaluation item belonging to the first category of questions includes 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 a field value of the searched data field (for example, calculating the field value of the searched data field according to a set calculation formula or a requirement), and determining an evaluation score of the medical data on the evaluation item according to a 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 drug description data according to a set format, or extracting data related to the evaluation item from at least one of medical data and drug 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.

In the present exemplary embodiment, the medical data of the patient may be structured data; for the evaluation items belonging to the first kind of problems, the data field names in the medical data can be directly mapped, and the evaluation items are scored according to the field values of the mapped data fields; for the evaluation items belonging to the second category of questions, relevant data can be extracted from a large text of medical data or drug instruction data (e.g., drug instruction manual) for scoring; for an evaluation item belonging to the third category of questions, a plurality of data fields may be extracted from the medical data, and then a logical calculation may be performed on the field values to score.

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

In an exemplary embodiment, the evaluation method of the present embodiment may further include: recording an analysis process for obtaining an analysis result; and after receiving the control instruction, displaying the analysis process of the obtained analysis result. In the present exemplary embodiment, in displaying the analysis process, for the evaluation items belonging to the first kind of questions, the field names and field values of the employed data fields may be directly displayed; for the evaluation items belonging to the second category of questions, document contents extracted from the medical data or the drug description data may be displayed, and related sentences therein may be labeled (for example, red-labeled); for the evaluation items belonging to the third category of questions, the field names and the field values of the data fields extracted from the medical data may be displayed, and then the logical calculation process between the field values may be displayed in a set format to make the logical calculation process clear at a glance. Data tracing can be facilitated through the display analysis process, manual searching is facilitated, and the rigor of the automatic evaluation process is guaranteed.

The evaluation method provided in the embodiments of the present application is illustrated by an example. In this example, the assessment scale is a Roussel u-leaf causal association Method (RUCAM) scale, which is used to assess drug-induced liver injury of hepatocyte type by scoring the clinical, biochemical, serological and radiological characteristics of liver injury, and finally obtaining a comprehensive score that reflects the possibility of liver injury caused by a certain drug. In this example, the RUCAM scale is shown below.

RUCAM scale

In the above table, group i includes the following 7 etiologies: hepatitis A Virus (HAV) infection; hepatitis B Virus (HBV) infection; hepatitis C Virus (HCV) infection; hepatitis E Virus (HEV) infection; hepatobiliary ultrasonic imaging/hepatic vascular color doppler imaging/intracavity ultrasound examination/CT/MRC; alcoholism (glutamic-oxaloacetic transaminase (AST)/ALT is not less than 2); there has been a recent history of acute hypotension (especially when there is underlying cardiac disease).

Group ii included the following 5 etiologies: combined sepsis, metastatic malignant tumor, autoimmune hepatitis, chronic hepatitis B or C, primary biliary cholangitis or primary sclerosing cholangitis, hereditary liver disease, etc.; cytomegalovirus (CMV) infection; EB virus (EBV) infection; herpes Simplex Virus (HSV) infection; varicella-zoster virus (VZV) infection.

After scoring is carried out on seven evaluation items in the table, the seven evaluation scores are added to obtain a final score; wherein, the final score of 0 or less than 0 indicates that the drug is excluded as the cause of liver damage; a final score of 1 to 2 indicates that the drug is unlikely (unlikely) to be the cause of liver injury; a final score of 3 to 5 indicates that the drug is likely (permissible) the cause of the liver injury; a final score of 6 to 8 points indicates that the drug is likely (capable) to be the cause of liver injury; a final score of greater than 8 indicates that the drug is highly likely (high likelihood) to be the cause of liver damage.

In this example, before automatically scoring the assessment scale, the electronic medical record data of the patient may be obtained from the electronic medical record database of the medical institution, and desensitization processing may be performed to obtain the medical data of the patient. The likelihood of the patient having an adverse drug reaction is then assessed by data extraction and analysis from the patient's medical data according to the above mentioned RUCAM scale. The information of the medicines taken by the patient can be determined according to the medical order data of the patient, and then the RUCAM scale scoring processing is sequentially carried out on the medicines in the medicine, so that the possibility that the medicine has adverse reaction on the patient is judged according to the obtained scoring value.

In this example, based on the RUCAM scale, the questions to be analyzed in the evaluation item can be classified into the following three types: 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 drug description data (e.g., bibliographic material such as a drug description), and a third category of questions for analysis by performing logical calculations on the medical data.

In this example, the RUCAM scale includes seven evaluation items, wherein the first evaluation item (dose to onset time), the second evaluation item (after drug withdrawal course), the fourth evaluation item (concomitant medication), the seventh evaluation item (drug re-stimulation) belong to the first category of questions; the sixth evaluation item (past information) belongs to the second category of questions; the third evaluation item (risk factor) and the fifth evaluation item (other reasons) belong to the third category of problems. Different options of each evaluation item correspond to different scores, and the total score is obtained by adding the scores of all the evaluation items, and can be used as a judgment standard for judging whether the drug-induced liver injury exists.

In this example, the first evaluation item is judgment of the time from taking a medicine to onset, and belongs to the first category of questions. The medicine taking time can be obtained by mapping to relevant time fields in the medical advice medicine taking data, the disease onset time can be obtained by mapping to relevant time fields in the disease condition diagnosis data or the examination and examination data, the days from medicine taking to disease onset can be obtained according to the difference of the field values of the two time fields, and then options corresponding to the obtained days from medicine taking to disease onset are determined and scored; for example, if the patient is initially taken and the number of days from administration to onset is 20 days, the score for the first assessment item can be determined to be +2 according to the RUCAM scale.

The second evaluation item is the disease course after drug withdrawal, and is determined according to the reduction amplitude of the difference value between the ALT peak value and the Upper Limit of Normality (ULN) in the disease course within a certain time, and the second evaluation item belongs to the first kind of problems. Wherein the percentage of ALT level reduction is 100%, (ALT peak-ALT value)/(ALT peak-ULN); the data in the above calculation formula may be obtained from examining the relevant data fields in the test data, and the score of the second assessment item may be determined based on the calculation result.

The third evaluation item is whether the patient has liver injury risk factors, and belongs to the third category of problems. Wherein, age, sex and drinking information can be extracted from the basic information of the patient, then the extracted information is logically calculated, the corresponding option is determined, and the score of the third evaluation item is determined.

The fourth evaluation item is the coincidence of concomitant medication and onset time, and belongs to the first category of problems. The concomitant medication can be obtained by directly mapping field values of corresponding data fields in the medication data of the order, then determining corresponding options according to the mapped field values, and determining the score of the fourth evaluation item.

The fifth evaluation item is whether the patient has suffered some specified diseases causing liver damage, and belongs to the third category of problems. Wherein relevant data (e.g., prior HAV infection) may be extracted from the patient's disease diagnosis data, a logical judgment is made based on the extracted data to determine the corresponding option, and a score is obtained.

The sixth evaluation item is whether the literature such as the drug instruction book mentions the precedent case of causing liver injury, and belongs to the second category of problems. The data extraction is performed on the medicine instruction manual using the medicine, for example, the medicine instruction manual is structured according to the format characteristics of the instruction manual, or the data extraction is performed on the medicine instruction manual in a natural language analysis mode, the corresponding option is determined according to the extracted data, and the score is obtained.

The medical instruction book is not only recorded with adverse reaction description information, but also generally recorded with the name, specification, expiration date, main components, indications or functional indications, usage, dosage, contraindications, cautionary matters and the like of the medicine, and the adverse reaction description in the medical instruction book can be extracted through a character recognition technology.

The seventh evaluation item is the relationship between the re-medication and the onset of disease, and belongs to the first category of problems. The ALT before and after the secondary medication can be obtained by mapping to relevant data fields in the inspection data, the relationship between the secondary medication and the morbidity is judged according to the numerical value obtained by mapping, the corresponding option is determined, and the score is obtained.

In the evaluation process, data used in the medical data of the patient can be recorded in a database, so that the evaluation process and the strategy can be traced. In addition, the recorded data and the evaluation process can be displayed. For example, for the analysis process of the first kind of questions, the data field names and field values mapped from the medical data may be directly displayed; for the analysis process of the second kind of problems, the extracted specific sentences can be recorded, and the related sentences are marked with red notes when the document content is displayed; for the third kind of problems, a plurality of fields may be involved, and after the recorded field names are respectively marked with red, the process of logic calculation can be output to a display page according to a fixed format, so that the calculation process is clear at a glance.

According to the method for evaluating adverse drug reactions, automatic evaluation and scoring are realized through a computer program, the evaluation speed can be increased, subjective interference factors of manual evaluation are eliminated, and the evaluation accuracy is improved. Moreover, the problems needing to be analyzed in the evaluation are classified and corresponding automatic analysis strategies are set, so that the feasibility of automatic evaluation and the processing efficiency can be improved. In addition, by recording and displaying the analysis process, the traceability of the evaluation process can be realized, so that the automatic evaluation is more rigorous.

Fig. 2 is a schematic view of an adverse drug reaction evaluation device provided in an embodiment of the present application. As shown in fig. 2, the evaluation apparatus 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 to obtain an analysis result for evaluating the possibility that the disease category of the patient is caused by adverse drug reactions.

In an exemplary embodiment, the data acquisition module 201 is configured to acquire medical data of a patient by: 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.

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

wherein the evaluation processing module 202 is configured to analyze the medical data of the patient based on the evaluation scale to obtain an analysis result by: 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.

In an exemplary embodiment, the issue types include: 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.

In an exemplary embodiment, the analysis policy corresponding to the evaluation item belonging to the first category of questions includes 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;

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

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

For the related description of the evaluation apparatus provided in this embodiment, reference may be made to the description of the embodiments of the evaluation method, and therefore, the description thereof is not repeated herein.

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 which, when executed by the processor, carries out the steps of the method for assessing adverse drug reactions as described above.

Fig. 3 is an exemplary diagram of a terminal according to 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 to store instructions and the processor 31 is configured to execute the instructions stored by the memory 32.

It should be noted that the configuration of the terminal shown in fig. 3 is not intended to be limiting, and may include more or fewer components than those shown, or may combine certain components, or provide a different arrangement of components.

It should be understood that the processor 31 may be a Central Processing Unit (CPU), and the processor 31 may be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs) 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.

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

The bus system 33 may include a power bus, a control bus, a status signal bus, and the like, in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 33 in fig. 3.

In implementation, the processing performed by the above evaluation device for adverse drug reactions may be performed by an integrated logic circuit of hardware or instructions in the form of software in the processor 31. That is, the steps of the evaluation method disclosed in the embodiments of the present application may be implemented by a hardware processor, or implemented by a combination of hardware and software modules in a processor. The software module may be located in a storage medium such as a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, etc. 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 method in combination with the hardware. To avoid repetition, it is not described in detail here.

In addition, the present application also provides a computer readable medium, which stores a computer program, and when the computer program is executed, the computer program implements the steps of the method for evaluating adverse drug reactions as described above.

It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable 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 performed by several physical components in cooperation. 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). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can 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 includes any information delivery media as known to those skilled in the art.

The foregoing shows and describes the general principles and features of the present application, together with the advantages thereof. The present application is not limited to the above-described embodiments, which are described in the specification and drawings only to illustrate the principles of the application, but also to provide various changes and modifications within the spirit and scope of the application, which are within the scope of the claimed application.

Claims

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;

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.