CN115240804A

Movatterモバイル変換

Info

Publication number: CN115240804A
Application number: CN202210659271.2A
Authority: CN
Inventors: 侯丹; 王爽; 刘昱菡
Original assignee: Shanghai Damou Intelligent Technology Co ltd
Current assignee: Shanghai Damou Intelligent Technology Co ltd
Priority date: 2022-06-10
Filing date: 2022-06-10
Publication date: 2022-10-25

Abstract

The invention discloses a patient information recording method, a patient information recording device, patient information recording equipment and a computer readable storage medium, and belongs to the field of medical treatment. According to the invention, the diagnosis information of the target patient is acquired, the disease category database of the patient group is confirmed according to the diagnosis information of the target patient, the target information is extracted from the diagnosis information of the target patient according to the index dimension required by disease category research, and the target information is stored as the first patient information of the target patient, so that the patient information can be efficiently extracted according to actual requirements, and the patient information can be recorded and stored.

Description

Patient information recording method, apparatus, device and computer readable storage medium

Technical Field

The present invention relates to the medical field, and in particular, to a method, an apparatus, a device and a computer-readable storage medium for recording patient information.

Background

Clinical information of patients has very important significance for the research of diseases, so that the collection of the information of the patients not only is beneficial to the treatment of the patients, but also can help researchers to deeply research the diseases.

In the prior art, the diagnosis and treatment information of a patient is stored mainly in a text type mode, and in addition, a plurality of important small-sized equipment for special examination are used for storing the information of the patient in a single-machine-version system or printing paper-version file records. However, the prior art has the problems that the information is stored dispersedly, extra time is needed for arranging the information of the patient after the patient goes out of the hospital, and usually, a lot of information is not recorded during the patient goes out of the hospital, and data unfortunately runs off, so that the data recording is incomplete.

Disclosure of Invention

The invention mainly aims to provide a patient information recording method, a patient information recording device, patient information recording equipment and a computer readable storage medium, and aims to completely acquire the diagnosis and treatment information of a patient.

To achieve the above object, the present invention provides a patient information recording method including the steps of:

acquiring diagnostic information of a target patient;

confirming a disease species database of the target patient to be grouped based on the diagnosis information, and grouping the target patient into the disease species database;

extracting target information from the diagnostic information of the target patient according to the index dimension required by the disease research;

storing the target information as first patient information for the target patient.

Optionally, the target information includes numerical information, and the step of storing the target information as first patient information of the target patient includes:

carrying out natural semantic analysis and numeralization on the initial text information to obtain numerical information;

and taking the numerical value information as the target information and storing the numerical value information as first patient information of the target patient.

Optionally, the target information includes image feature information, and the step of storing the target information as first patient information of the target patient includes:

performing image omics information extraction on the image information to obtain image characteristic information;

and taking the image characteristic information as the target information and storing the image characteristic information as the patient information of the target patient.

Optionally, the step of extracting target information from the information of the target patient based on the index dimension includes:

extracting the target information from the information of the target patient based on the index dimension, and judging whether the target information corresponding to the index dimension is completely collected;

if the doctor is missing, sending prompt information to the doctor in charge;

and acquiring missing information corresponding to the prompt information by the doctor in charge, and supplementing the missing information into the target information.

Optionally, after the step of storing the target information as the patient information of the target patient, the method further comprises:

according to a preset time period, circularly executing the steps of extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease type research, and storing the target information as first patient information of the target patient;

according to the first patient information of gathering in predetermineeing the time cycle, assess the state of an illness condition of target patient through mathematical model, obtain the assessment result, the state of an illness condition includes: infection, shock, resuscitation;

and predicting the condition of the target patient in the next preset time period through the mathematical model to obtain a prediction result.

Optionally, the method further comprises, after the step of storing the target information as first patient information of the target patient:

acquiring second patient information of the similar patients, wherein the second patient information is used for diagnosis and treatment reference;

and acquiring the diagnosis and treatment scheme of the similar patient and the public paper introduction of the effect of the diagnosis and treatment scheme for diagnosis and treatment reference.

Optionally, the step of validating the disease category database of the target patient grouping based on the diagnosis information and grouping the patient into the disease category database comprises:

acquiring a first diagnosis result in the diagnosis information;

and confirming a disease species database of the patient group based on the first diagnosis result, and grouping the patient into the disease species database.

Further, to achieve the above object, the present invention also provides a patient information recording apparatus comprising:

the acquisition module is used for acquiring the diagnostic information of the target patient;

the first storage module is used for confirming a disease species database of the target patient group based on the diagnosis information and grouping the patient into the disease species database;

the extraction module is used for extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease type research;

a second storage module for storing the target information as first patient information of the target patient.

Optionally, the second storage module is further configured to:

Optionally, the extraction module is further configured to:

extracting the target information from the information of the target patient based on the index dimension, and judging whether the target information corresponding to the index dimension is completely acquired;

if the doctor is missing, sending prompt information to a doctor in charge;

Optionally, the patient information recording device further comprises a processing module for:

according to first patient information collected in a preset time period, evaluating the condition of a target patient through a mathematical model to obtain an evaluation result, wherein the condition comprises: infection, shock, resuscitation;

Optionally, the processing module is further configured to:

Optionally, the first storage module is further configured to:

the step of confirming the disease species database of the target patient grouping based on the diagnosis information and grouping the patient into the disease species database comprises:

acquiring a first diagnosis result in the diagnosis information;

Further, to achieve the above object, the present invention also provides a patient information recording apparatus comprising: a memory, a processor, and a patient information recording program stored on the memory and executable on the processor, the patient information recording program configured to implement the steps of the patient information recording method as described above.

Further, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a patient information recording program which, when executed by a processor, realizes the steps of the patient information recording method as described above.

The patient information recording method provided by the invention is used in a patient information recording system, and is characterized in that the diagnosis information of a target patient is obtained, a disease category database of the target patient is confirmed according to the diagnosis information, the disease category database corresponding to the target patient is grouped to realize classification management, then the corresponding target information is extracted from the diagnosis information of the target patient according to the index dimension required by the disease category research of the patient, and the target information is stored as first patient information corresponding to the target patient, so that the patient information is obtained according to the requirement, and the patient information can be recorded in groups.

Drawings

Fig. 1 is a schematic diagram of a patient information recording device in a hardware operating environment according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a first embodiment of a patient information recording method according to the present invention;

FIG. 3 is a detailed flowchart of step S40 of the first embodiment of the patient information recording method according to the present invention;

FIG. 4 is a flowchart illustrating a third embodiment of a patient information recording method according to the present invention;

FIG. 5 is a functional block diagram of an embodiment of a patient information recording device according to the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to fig. 1, fig. 1 is a schematic diagram of a patient information recording device in a hardware operating environment according to an embodiment of the present invention.

As shown in fig. 1, the patient information recording apparatus may include: aprocessor 1001, such as a Central Processing Unit (CPU), acommunication bus 1002, auser interface 1003, anetwork interface 1004, and amemory 1005. Wherein acommunication bus 1002 is used to enable connective communication between these components. Theuser interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and theoptional user interface 1003 may also include a standard wired interface, a wireless interface. Thenetwork interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). TheMemory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. Thememory 1005 may alternatively be a storage device separate from theprocessor 1001 described previously.

Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the patient information recording apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

As shown in fig. 1, thememory 1005, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a patient information recording program.

In the patient information recording apparatus shown in fig. 1, thenetwork interface 1004 is mainly used for data communication with other apparatuses; theuser interface 1003 is mainly used for data interaction with a user; theprocessor 1001 and thememory 1005 in the raman spectrum data processing apparatus of the present invention may be provided in a patient information recording apparatus which calls a patient information recording program stored in thememory 1005 by theprocessor 1001 and executes the patient information recording method provided by the embodiment of the present invention.

An embodiment of the present invention provides a patient information recording method, and referring to fig. 2, fig. 2 is a schematic flowchart of a first embodiment of a patient information recording method according to the present invention.

In this embodiment, the patient information recording method includes:

step S10, acquiring diagnosis information of a target patient;

step S20, confirming a disease species database of the target patient to be grouped based on the diagnosis information, and grouping the target patient into the disease species database;

step S30, extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease species research;

step S40, storing the target information as first patient information of the target patient.

The patient information recording method of the present embodiment is used for a patient information recording system of a medical institution such as a hospital. During the hospital visit of the patient, the information required by the disease research related to the patient is collected and recorded,

the respective steps will be described in detail below:

step S10, obtaining the diagnosis information of a target patient;

in one embodiment, diagnostic information is obtained for a target patient. It is understood that in order to record the patient information, the diagnosis information of the patient needs to be obtained, and the diagnosis information at least comprises: one or more of personal information, medical records of inquiry, chief complaints, current medical history, past medical history, medical records of treatment, results of diagnosis of treatment and treatment schemes of treatment. The step collects the diagnosis information of the patient, and all the information of the patient usually exists in the hospital information management system in the form of electronic information, but is not effectively integrated and processed, so that the diagnosis information of the target patient can be obtained, and the corresponding diagnosis information can be obtained from the hospital information management system. It should be noted that some medical institutions do not convert the paper information into electronic archives, and the paper information needs to be recorded into a system for reading.

The target patient may be selected according to preset screening conditions, for example, one or more patients in departments may be selected as the target patient, or all patients admitted to the hospital may be selected as the target patient, and specifically, the confirmation of the target patient may be selected according to actual needs of the study of hospitals, doctors, and medical institutions. The target patient corresponding to the specific disease species can be selected to help establish a database of the specific disease species, and corresponding clinical information such as diagnosis information and treatment information can be obtained so as to better study the disease.

Step S20, confirming a disease species database of the target patient grouping based on the diagnosis information, and grouping the target patient into the disease species database;

in one embodiment, the disease category database of the target patient is confirmed according to the diagnosis information, and after the confirmation, the target patient is put into the corresponding disease category database. It can be understood that after the diagnostic information of the target patient is obtained, what disease the patient suffers from can be determined, and accordingly, the disease category to which the disease belongs can be determined, for example: acute appendicitis is usually clinically referred to as acute appendicitis, i.e., the case is the diagnosis of acute appendicitis. But in disease management refers to a group of Diseases that have the same clinical features as "acute appendicitis", consume the same clinical resources, and correspond to the International Classification of Diseases (ICD). Although the classification of the disease category is usually performed according to ICD, the classification method of the disease category may be set according to actual needs. Wherein the diagnostic information includes: first diagnosis, second diagnosis, etc., and the diagnostic information may be used to confirm the disease from which the patient is suffering. For example, the first diagnosis of the patient is lung cancer, the second diagnosis is hyperlipidemia, and screening principles can be set according to actual needs, for example, the patient is respectively put into lung cancer and hyperlipidemia disease databases, or the patient is only put into lung cancer disease database or hyperlipidemia disease database, so as to realize classification management of the patient.

Further, in one embodiment, the step of identifying the disease category database of the target patient grouping based on the diagnosis information and grouping the patient into the disease category database comprises:

step S21, acquiring a first diagnosis result in the diagnosis information;

and S22, confirming a disease species database of the patient group based on the first diagnosis result, and grouping the patient into the disease species database.

In one embodiment, a first diagnosis result in the diagnosis information is obtained, and it is understood that the diagnosis information includes various diagnosis information of the patient, personal information, and the like, and the first diagnosis is a main disease of the patient, and the need of treatment is more urgent in general. For example, the first diagnosis of a patient is lung cancer, and the second diagnosis is hyperlipidemia, it is understood that, for example, the patient is lung cancer just examined in the hospital admission, the cancer is more threatening to the life of the patient, and hyperlipidemia is a disease suffered by the patient throughout the year, and the disease condition is relatively stable. Therefore, the patient is first grouped into the disease type database corresponding to the first diagnosis, and the target patient can be treated with reference to the condition of the other patients in the disease type database. By obtaining the first diagnosis result and putting the target patient into the corresponding disease database according to the first diagnosis, the study of the disease and the treatment of the patient are better facilitated.

Step S30, extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease type research;

in one embodiment, the index dimension is researched by acquiring disease types corresponding to the disease type database, and the target information is extracted from the diagnosis information of the target patient. Wherein, the index dimension required by the disease research is also the index related to a certain disease. It will be appreciated that there is a great deal of diagnostic information for a target patient, but not all of that information is usually required, and the index dimensions are those determined by professional medical personnel, such as doctors, who are available to study and treat the disease.

For example, the important indicators for diabetes research are blood sugar, urine sugar, insulin, and glycated hemoglobin, and the data is extracted from the diagnostic information of the patient. The index dimensions for different disease species are different, for example, the indices required for pneumonia are total white blood cell count, neutrophils, procalcitonin, C-reactive protein. In addition, there are some data that cannot be extracted directly, requiring the system to make inferences, such as: if the patient has respiratory tract infection, the occupation is a construction worker, the worker is 6 years old, the reason of the respiratory tract infection can be inferred to be excessive dust inhalation, the severity degree can be correspondingly inferred according to the working age, and the inferred information is obtained and used as target information. The target information acquired according to the index dimension can meet diagnosis and treatment requirements, and the inference model can be obtained through machine learning and neural network method training.

In one embodiment, the target information obtained according to the index dimension is stored as first patient information of the patient. And storing the extracted target information in a disease category database corresponding to the target information, wherein the target information corresponds to the target patients one by one.

In this embodiment, the diagnosis information of the target patient is obtained, the disease category database of the target patient is determined according to the diagnosis information, the target patient is classified into the corresponding disease category database, the corresponding target information is extracted from the diagnosis information of the target patient according to the index dimension required by the disease category research of the target patient, and the target information is stored as the first patient information corresponding to the target patient, so that the patient information is obtained according to the requirement, and the patient information can be recorded in a grouped manner.

Further, based on the first embodiment of the patient information recording method of the present invention, a second embodiment of the patient information recording method of the present invention is proposed.

Referring to fig. 3, fig. 3 is a flowchart illustrating a step S40 of the first embodiment of the patient information recording method of the present invention, and in the second embodiment, the target information includes initial text information, and the step of storing the target information as the first patient information of the target patient includes:

s41, carrying out natural semantic analysis and digitization on the initial text information to obtain numerical information;

in an embodiment, the acquired initial text information is subjected to natural semantic analysis and numerical processing to obtain numerical information. The extracted target information further includes initial text information, the initial text information may be composed of extracted text information of multiple dimensions, and natural semantic analysis is performed on the text information, that is, text classification is performed, for example, the daily smoking amount of a patient is 1 pack and half (30), 45 years old, smoking starts from 25 years old, the daily smoking amount of a patient B is 1 pack (20), 26 years old, and smoking starts from 20 years old, so that the disease conditions of the patient a and the patient B are classified, the patient with smoking history of 20 years and the patient with smoking history of 6 years old are classified, without considering the influence of other factors, the pneumonia severity of the patient a is definitely higher, the corresponding disease condition after natural semantic analysis obtains the severity level of the patient, the patient a may be level 5, and the patient B may be level 2, and these information cannot be used as an exact diagnosis result, and only serve as auxiliary data.

The digitization is to convert the text information into a vector form, a one-hot coding format, and other numerical forms, for example, "yes" and "no" are converted into "0" and "1" respectively. By carrying out natural semantic analysis and numerical storage on the initial text information, the method is not only convenient to store and not easy to generate character messy codes, but also convenient to use the information for model training in the follow-up process,

and step S42, taking the numerical value information as the target information and storing the numerical value information as first patient information of the target patient.

In one embodiment, the obtained numerical information is stored as first patient information of the target patient. I.e. in a disease species database corresponding to the patient grouping. In addition, calls can be made from the disease database when such data is needed. Specifically, the calling may be performed by searching for the patient name, number, bed number, etc., or may input corresponding features, such as: the age of the disease and the degree of the disease are searched.

Further, in an embodiment, the target information includes image feature information, and the step of storing the target information as the first patient information of the target patient includes:

step S43, performing image omics information extraction on the image information to obtain image characteristic information;

in one embodiment, image information is obtained, and the image information is subjected to image omics information extraction to obtain image feature information. It should be noted that the image information may be extracted from a PACS system, which is an abbreviation of Picture Archiving and Communication Systems and means an image Archiving and Communication system. The system is applied to a hospital image department, and mainly aims to store various medical images (including images generated by equipment such as nuclear magnetism, CT, ultrasound, various X-ray machines, various infrared instruments, microscopes and the like) which are generated daily in a digital mode through various interfaces (analog, DICOM and network), can be quickly called back for use under certain authorization when needed, and is added with auxiliary diagnosis management functions. The image omics features are to extract a large amount of image information from images (CT, MRI, PET, and the like) at high flux, realize tumor segmentation, feature extraction and model establishment, and assist doctors to make the most accurate diagnosis by means of deeper mining, prediction and analysis of the mass image data information. Imaging omics can be intuitively understood as converting visual image information into deep features for quantitative research. And using the extracted information as image characteristic information.

And step S43, taking the image characteristic information as the target information and storing the image characteristic information as the patient information of the target patient.

In one embodiment, after the image characteristic information is obtained, the information is stored as patient information for the target patient. It is understood that the image characteristic information may be used for patient disease prediction, treatment, diagnosis, etc., however, in many cases, the image information may not be associated with other diagnosis information of the patient, resulting in incomplete information storage, and therefore, the image characteristic information is stored together with other target information of the target patient as the first patient information of the patient. According to the embodiment, more complete patient information can be obtained by acquiring the image information and extracting the imaging omics information, so that the diagnosis and treatment of the patient diseases are more facilitated.

Further, the step of extracting target information from the information of the target patient based on the index dimension includes:

step S31, extracting the target information from the information of the target patient based on the index dimension, and judging whether the target information corresponding to the index dimension is completely collected;

in an embodiment, after the target information is extracted, it is further determined whether the target information is completely acquired, that is, it is determined whether the target information corresponding to the index dimension is missing, for example, the index dimension to be acquired includes blood sugar, blood pressure, blood fat, and CT, but the acquired information only includes blood pressure, blood fat, and blood sugar, so that the information of CT is less, the target information is incompletely acquired, and the incomplete acquisition of the target information may cause inaccurate subsequent determination, so it is necessary to determine whether the target information is completely acquired. It can be understood that, after the information is obtained, the information is correspondingly filled or stored in a storage location corresponding to the dimension of the index, for example, stored in a form, and if it is detected that the form corresponding to the value to be filled in the blood glucose is blank, it may also be determined that the index is not obtained.

Step S32, if the doctor is missing, prompt information is sent to the doctor in charge;

in one embodiment, when the target information is judged to be missing, prompt information is sent to the doctor in charge. The system acquisition module may also be used, and it can be understood that missing information may be an error in the acquisition process, or the information may be missing, and a doctor in charge needs to determine the missing information, for example, the index is an index of a certain examination, and the doctor in charge determines which examinations the patient has performed, so that it can be determined whether the examinations have not been performed or the system has not acquired. Therefore, the missing item information is prompted.

And S33, acquiring missing information corresponding to the prompt information by the doctor in charge, and supplementing the missing information into the target information.

In one embodiment, according to the prompt information, missing information corresponding to the prompt information is collected, and the missing information is supplemented to the target information. It can be understood that, after the prompt message is sent, if the corresponding examination is not done or the patient is not queried, the doctor in charge supplements and stores the corresponding examination as an electronic file, and then obtains the corresponding information again according to the prompt message. If the acquisition is wrong, the acquisition is tried again, the previous problem cannot occur, and if the acquisition is not available after the doctor in charge supplements the information, whether the code has the problem or not can be considered, and related personnel can be informed to diagnose the problem. And sending prompt information until all target information corresponding to the index dimension is completely acquired as long as the acquisition is not complete, so that the target information of the index dimension corresponding to the disease research is completely acquired.

In the embodiment, the classification of the text information is realized by acquiring the initial text information and performing natural semantic analysis and numerical processing, so that the text information is classified more effectively, the initial text information of the patient is utilized to the maximum extent, and the initial text information can be stored in the system after being digitized; in addition, image information is collected and the imaging omics information is extracted, so that image characteristic information beneficial to diagnosis and treatment of patients is obtained. And whether the target information corresponding to the index dimension is completely acquired is judged, and when the target information is not completely acquired, prompt information is sent, so that the completeness of acquiring the patient information is guaranteed.

Referring to fig. 4, fig. 4 is a schematic flowchart illustrating steps of a third embodiment of the patient information recording method of the present invention, and further, based on the previous embodiment of the patient information recording method of the present invention, the third embodiment of the patient information recording method of the present invention is proposed, in this embodiment, after the step of storing the target information as the patient information of the target patient, the method further includes:

step S51, according to a preset time period, circularly executing the steps of extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease type research, and storing the target information as first patient information of the target patient;

step S52, evaluating the state of an illness of the target patient through a mathematical model according to first patient information acquired within a preset time period to obtain an evaluation result, wherein the state of the illness comprises: infection, shock, resuscitation;

and S53, predicting the disease condition of the target patient in the next preset time period through the mathematical model to obtain a prediction result.

In the embodiment, first patient information of the target patient is periodically acquired, and after the first patient information of the target patient is acquired, the first patient information is used for disease condition assessment and prediction.

The respective steps will be described in detail below:

in one embodiment, during the hospitalization period, the step of extracting the target information from the diagnosis information of the target patient according to the index dimension required by the disease type research and storing the target information as the first patient information of the target patient is executed circularly according to a preset time period, that is, the above process is executed circularly by taking a specified time length as a unit, for example, every day, and the information of the same day is collected. The preset time period can be set according to actual conditions, and is every day, every three days and every week. It will be appreciated that the first patient information of the patient is collected over a predetermined time period, since the patient's condition is not constant, and changes in the patient's condition need to be attended to in a timely manner, particularly during the hospital stay. In addition, the preset time period is used as a routine setting, when the patient has special conditions, collection can be additionally carried out, for example, the patient has just performed an operation today, or the patient has performed examinations today, and the newly obtained data plays an important role in subsequent disease judgment.

Step S52, according to the first patient information acquired within a preset time period, the condition of the target patient is evaluated through a mathematical model to obtain an evaluation result, where the evaluation result includes, but is not limited to: infection, shock, resuscitation;

in one embodiment, the first patient information collected within a preset time period is input into a mathematical model, and the condition of the target patient is evaluated through the mathematical model to obtain an evaluation result. It can be understood that after information of each dimension of a patient is acquired, the information of the patient can be deeply mined, some information which cannot be acquired only by a doctor is acquired by using the information, usually, the information can be acquired only by a large amount of calculation, so that target information corresponding to the acquired index dimension is input into a pre-constructed mathematical model as an independent variable, historical patient data can be adopted for training of the mathematical model, and a prediction model is constructed by methods such as decision trees, support vector machine regression (SVR), back propagation neural networks, combined prediction models and the like.

And S53, predicting the state of an illness of the target patient in the next preset time period through the mathematical model to obtain a prediction result.

In one embodiment, after obtaining the evaluation result of the disease condition of the target patient, the patient is further predicted for the next preset time period to obtain the prediction result. Specifically, the disease state of the patient is predicted by one or more indexes, for example, the weight of the diabetic patient is obtained by an indexing method, and the weight is input into a prediction model to predict the progression of the disease state of the diabetic patient. The specific required index number can be set according to different disease types and parameters required by the prediction model, and the disease development of the patient is predicted in advance through the prediction model, so that the countermeasures are taken in advance, and the disease condition of the patient is improved. It should be noted that the prediction and evaluation may be performed by one mathematical model, or may be performed by two models.

Further, in an embodiment, the method further comprises, after the step of storing the target information as the first patient information of the target patient:

step S54, matching similar patients of the target patient based on the first patient information;

in an embodiment, similar patients are matched based on the first patient information of the target patient. Specifically, the similarity of the index dimensions in the first patient information can be determined, and similar ages, disease types, sexes, medical histories, and the like can be matched. For example: today a patient, 30 years old, female, with diabetes, has a history of 2 years, then the corresponding matching rules can be set, for example: first screening patients with diabetes, then screening women between 20-40 years of age, then screening patients with history of 1-3 years to obtain similar patients, and then screening similar patients with the age closest to 30 years of age and the age of history closest to each other to obtain the highest similarity.

And step S55, acquiring second patient information of the similar patients, wherein the second patient information is used for diagnosis and treatment reference.

In an embodiment, after the similar patient is found, second patient information, such as age, medical history, clinical symptoms and the like, of the similar patient is acquired, and after the second patient information is acquired, diagnosis and treatment information can be accurately recommended for a target patient, so that a doctor is helped to judge the state of an illness and confirm a diagnosis and treatment scheme, and therefore diagnosis and treatment accuracy is improved. It should be noted that the number of similar patients is not limited, and may be one or more.

And S56, acquiring the diagnosis and treatment scheme of the similar patient and the public paper introduction of the effect of the diagnosis and treatment scheme for diagnosis and treatment reference.

The embodiment realizes effective utilization of patient information by acquiring a preset time period and acquiring first patient information of a target patient in the preset time period and performing disease condition evaluation and prediction of a next preset time period according to the first patient information, can also match similar patients according to the first patient information, acquires related information for reference according to the similar patients, can assist doctors in diagnosis and treatment, and is favorable for improving the accuracy of diagnosis and treatment.

The invention also provides a patient information recording device. Fig. 5 is a schematic diagram of functional modules of an embodiment of a patient information recording apparatus according to the present invention.

The patient information recording apparatus of the present invention includes:

an obtainingmodule 10, configured to obtain diagnostic information of a target patient;

afirst storage module 20, configured to confirm a disease category database of the target patient grouping based on the diagnosis information, and group the patient into the disease category database;

anextraction module 30, configured to extract target information from the diagnostic information of the target patient according to an index dimension required for the disease research;

asecond storage module 40, configured to store the target information as first patient information of the target patient.

Optionally, the second storage module is further configured to:

Optionally, the extraction module is further configured to:

if the doctor is missing, sending prompt information to a doctor in charge;

Optionally, the processing module is further configured to:

and acquiring the diagnosis and treatment scheme of the similar patients and the public thesis introduction of the effect of the diagnosis and treatment scheme for diagnosis and treatment reference.

Optionally, the first storage module is further configured to:

acquiring a first diagnosis result in the diagnosis information;

The invention also provides a computer readable storage medium.

The computer-readable storage medium of the present invention has stored thereon a patient information recording program which, when executed by a processor, implements the steps of the patient information recording method as described above.

The method implemented when the patient information recording program running on the processor is executed may refer to each embodiment of the patient information recording method of the present invention, and details thereof are not repeated here.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A patient information recording method, characterized by comprising the steps of:

acquiring diagnostic information of a target patient;

2. The patient information recording method according to claim 1, wherein the target information includes initial text information, and the step of storing the target information as first patient information of the target patient includes:

3. The patient information recording method according to claim 1, wherein the target information includes image feature information, and the step of storing the target information as first patient information of the target patient includes:

4. The patient information recording method according to claim 1, wherein the step of extracting target information from the information of the target patient based on the index dimension includes:

if the doctor is missing, sending prompt information to the doctor in charge;

5. The patient information recording method according to claim 1, wherein after the step of storing the target information as the patient information of the target patient, the method further comprises:

according to the first patient information of gathering in the preset time period, assess the state of an illness condition of target patient through mathematical model, obtain the assessment result, the state of an illness condition includes: infection, shock, resuscitation;

and predicting the disease condition of the target patient in the next preset time period through the mathematical model to obtain a prediction result.

6. The patient information recording method of claim 1, wherein the step of storing the target information as first patient information for the target patient is followed by the method further comprising:

7. The patient information recording method according to claim 1, wherein the step of confirming the disease species database of the target patient grouping based on the diagnosis information and grouping the patient into the disease species database comprises:

acquiring a first diagnosis result in the diagnosis information;

8. A patient information recording apparatus, characterized in that the apparatus comprises:

the acquisition module is used for acquiring the diagnosis information of the target patient;

the first storage module is used for confirming a disease species database of the target patient to be grouped based on the diagnosis information and grouping the patient into the disease species database;

the extraction module is used for extracting target information from the diagnosis information of the target patient according to the index dimension required by the disease research;

9. A patient information recording apparatus, characterized in that the apparatus comprises: a memory, a processor, and a patient information recording program stored on the memory and executable on the processor, the patient information recording program configured to implement the steps of the patient information recording method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that a patient information recording program is stored thereon, which when executed by a processor implements the steps of the patient information recording method according to any one of claims 1 to 7.