Intelligent shift handover method, device and equipment

Abstract

The present invention discloses an intelligent handover method, device and equipment. The intelligent handover method includes: obtaining the medical record information of all patients from the hospital information system; for each first patient, obtaining the attention tag of the medical record information of the first patient; if the attention tag is yes, outputting the first handover log of the first patient. The present application automatically identifies the patients who need attention based on the medical record information of the patients, and automatically outputs the necessary medical record information of the patients who need attention, so as to avoid the problem of wasting the energy of medical staff and delaying clinical work due to completing the handover log during the handover, and the problem of unclear description and unreadable handover log.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medical information technology, and in particular to an intelligent shift handover method, device and equipment. Background Art

[0002] The handover system is one of the main contents of the 18 core medical systems. It plays an important role in ensuring medical safety and quality, and is a work norm that medical staff must abide by. The main content of the handover record is the patient's condition and treatment during the shift, which is an important record document to ensure the continuity of doctors' diagnosis and treatment activities. With the improvement of medical standards, the continuous expansion of hospital business, and the gradual increase in ward beds, doctors have to spend a lot of time writing handover records while performing routine handover work. The traditional writing process and heavy writing tasks have gradually become a burden for doctors to diagnose and treat diseases.

[0003] Moreover, in the actual work process, the handover process that mainly relies on written records brings the following problems:

[0004] 1. The content is not standardized and lacks necessary information. The key patients in the ward, including critically ill patients, postoperative patients, newly admitted patients, and patients with critical values, must write a handover record. The handover record book needs to fill in a lot of content. The duty staff sometimes only writes the handover outline, lacking a description of the patient's condition, etc.;

[0005] 2. The handwriting is illegible and difficult to discern. Everyone has their own writing habits. In the busy work environment of doctors, in order to pursue speed, it is inevitable that "hellish handwriting" will appear, which is not conducive to the successor doctor to check the patient's condition, and is not conducive to supervision and quality management. Summary of the invention

[0006] In view of the above, the present invention aims to provide an intelligent handover method, device and equipment, and accordingly proposes a computer-readable storage medium, which automatically identifies patients who need attention based on their medical records, and automatically outputs the necessary medical records of patients who need attention, so as to avoid wasting the energy of medical staff and delaying clinical work due to completing the handover log during the handover, and the problem of unclear description and unreadable handover log.

[0007] The technical solution adopted by the present invention is as follows:

[0008] In a first aspect, the present invention provides an intelligent shift handover method, comprising:

[0009] Obtain all patients' medical records from the hospital information system;

[0010] For each first patient, obtain the attention tag of the medical record information of the first patient;

[0011] If the attention tag is yes, the first shift log of the first patient is output.

[0012] In one possible implementation, obtaining the attention tag of the medical record information of the first patient specifically includes:

[0013] Extract the patient type of the first patient from the medical record information;

[0014] Obtaining a maximum matching degree between the medical record information and a first medical record template in a medical record database corresponding to the patient type;

[0015] If the maximum matching degree is higher than the threshold, obtaining the attention tag of the second medical record template corresponding to the maximum matching degree;

[0016] The attention tag of the second medical record template is used as the attention tag of the medical record information.

[0017] In one possible implementation, outputting a first shift handover log of a first patient specifically includes:

[0018] Determine the shift type based on the current time information;

[0019] Extract data corresponding to the indicators in the handover list corresponding to the handover type in the medical record template from the medical record information to form a first handover log;

[0020] Output the first shift handover log.

[0021] In one possible implementation, before obtaining the maximum matching degree, the step further includes obtaining a target object;

[0022] and,

[0023] The medical record database is a medical record database corresponding to the patient type in the target database corresponding to the target object.

[0024] In one possible implementation, an intelligent handover method is implemented through a neural network model based on deep learning, wherein the medical record information of all patients is used as input information of the neural network model, and the first handover log of the first patient is used as output information of the neural network model.

[0025] In one possible implementation, if the attention tag is yes, then the basic information of the first patient is output;

[0026] In addition, the intelligent shift handover method also includes:

[0027] Receive the basic information of the newly added second patient, whose attention tag is yes;

[0028] and,

[0029] Output the first shift log for the first patient and the second patient.

[0030] In one possible implementation, the method further includes:

[0031] Receive the second shift log for the first patient and / or the second patient;

[0032] Merge the first shift handover log and the second shift handover log of the same patient and output them.

[0033] In one possible implementation, the method further includes:

[0034] Receive the reason for the second patient being concerned and the second shift log;

[0035] The reason why the second patient was paid attention to and the second shift log were input into the training set of the neural network model.

[0036] In a second aspect, the present invention provides an intelligent shift handover device, including a medical record information acquisition module, a focus tag acquisition module, and a shift handover log output module;

[0037] The medical record information acquisition module is used to obtain the medical record information of all patients from the hospital information system;

[0038] The attention tag acquisition module is used to obtain the attention tag of the medical record information of the first patient;

[0039] The shift handover log output module is used to output the first shift handover log of the first patient.

[0040] In a third aspect, the present invention provides an intelligent shift handover device, comprising:

[0041] One or more processors, a memory and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, and when the instructions are executed by the intelligent shift handover device, the intelligent shift handover device executes the above-mentioned intelligent shift handover method.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored, and when the computer-readable storage medium is run on a computer, the computer executes the above-mentioned intelligent shift handover method.

[0043] The idea of ​​the present invention is to automatically identify patients who need attention based on their medical records, and automatically output the necessary medical records of patients who need attention, so as to avoid wasting the energy of medical staff and delaying clinical work during handovers, and problems such as unclear descriptions and unreadable handover logs. In addition, a unified handover list is set for different target objects, different patient types, and different handover types in this application, and the necessary information is included to ensure the pertinence of the handover information. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described below with reference to the accompanying drawings, in which:

[0045] Figure 1 A flow chart of the intelligent shift handover method provided by the present invention;

[0046] Figure 2 A flow chart of obtaining a focus tag of the medical record information of a first patient provided by the present invention;

[0047] Figure 3 A flow chart of outputting a first shift log of a first patient provided by the present invention;

[0048] Figure 4 A schematic diagram of the structure of the intelligent shift handover device provided by the present invention;

[0049] Figure 5 A structural diagram of a focus tag acquisition module provided by the present invention;

[0050] Figure 6 A structural diagram of a shift log output module provided by the present invention;

[0051] Figure 7 This is a structural schematic diagram of the intelligent shift handover device provided by the present invention. DETAILED DESCRIPTION

[0052] Embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0053] In view of the aforementioned core concept, the present invention provides at least one embodiment of an intelligent shift handover method, such as Figure 1 As shown, the following steps may be included:

[0054] S110: Obtain medical record information of all patients from the hospital information system.

[0055] Hospital Information System (HIS) generally consists of three parts: one is the management information system that meets management requirements; the second is the medical information system that meets medical requirements; and the third is the information service system that meets the above two requirements.

[0056] In step S110, the intelligent handover system provided in the present application obtains the medical record information of all patients from the medical information system for use in subsequent steps.

[0057] Specifically, medical record information includes the patient's hospitalization information (including number of days in hospital, whether it is postoperative, hospitalization number, etc.), general condition (including name, gender, etc.), vital signs (including heart rate, blood pressure, respiratory rate, body temperature, etc.), test results, diagnosis results, treatment methods, medication, nursing level, changes in indicators, disease progression, patient type, etc.

[0058] S120: For each first patient, obtain a focus tag of the medical record information of the first patient.

[0059] It should be noted that the intelligent handover system of the present application includes a medical record database, which stores multiple medical record templates. The medical record templates are representative medical record information of various types obtained by analyzing the collected medical record information of various patients.

[0060] As an embodiment, the intelligent handover system also includes a label correspondence table, in which the attention label corresponding to each medical record template is recorded. The attention label is used to indicate whether the information of the medical record template needs to be paid special attention to by subsequent medical staff (i.e., the target object) during the handover. If it needs to be paid special attention to, the attention label is "yes", otherwise, the attention label is "no".

[0061] As another embodiment, each medical record template has a field regarding an attention tag, and whether the medical record template needs attention is determined by identifying the field.

[0062] On the basis of the above, if Figure 2 As shown, the attention tags for obtaining the medical record information of the first patient specifically include:

[0063] S1201: Extract the patient type of the first patient from the medical record information. The patient types include new patients, critically ill patients, postoperative / invasive operation patients, special treatment (such as chemotherapy, isotope therapy) patients, etc.

[0064] S1202: Obtain the maximum matching degree between the medical record information of the first patient and the first medical record template in the medical record database corresponding to the patient type. For example, if the first patient is a new patient, match the medical record information of the first patient with each medical record template in the medical record database of new patients, and obtain the maximum value of the matching degrees with all medical record templates as the maximum matching degree.

[0065] S1203: Determine whether the maximum matching degree is higher than a threshold, if so, execute S1204. Otherwise, execute S1206.

[0066] If the maximum matching degree is higher than the threshold (e.g., 0.9), it means that there is a medical record template in the medical record database that is highly similar to the medical record information of the first patient, and the handover process can be performed according to the medical record template. Otherwise, there is no medical record template in the medical record database that is highly similar to the medical record information of the first patient.

[0067] S1204: Obtain the attention tag of the second medical record template corresponding to the maximum matching degree.

[0068] As described above, for the intelligent shift handover system with a label correspondence table, the label correspondence table is queried to obtain the attention label corresponding to the second medical record template.

[0069] For the intelligent shift handover system having a field regarding the attention tag, the attention tag corresponding to the second medical record template is obtained by reading the field.

[0070] S1205: Use the attention tag of the second medical record template as the attention tag of the medical record information.

[0071] S1206: Output a matching failure message, so that the user manually inputs a focus tag for the medical record information. If the manually input focus tag is yes, the user also needs to input a handover log for the medical record information.

[0072] It should be noted that the intelligent handover system can be a system solely for doctors (target objects) or a system solely for nurses (target objects). Both independent systems obtain attention tags according to the above method. The intelligent handover system can also be a system that takes both doctors and nurses into consideration. In this case, it is necessary to obtain the target object (doctor or nurse) before S1202 and obtain the maximum match in the target database corresponding to the target object and the medical record database corresponding to the patient type.

[0073] S130: Determine whether the attention tag is yes, if yes, execute S150. Otherwise, the case information does not need attention, and the intelligent handover system does not need to output the attention tag and / or handover log of the first patient.

[0074] S150: Outputting the first shift handover log of the first patient.

[0075] As an embodiment, the first shift handover log is all medical record information of the first patient.

[0076] In the above embodiment, the patient's medical record information contains multiple indicators, some of which do not require special attention. Therefore, there is information with a lower importance level in the medical record information, which makes it impossible for the target object to obtain the patient's important information at the fastest speed when handing over the shift.

[0077] Based on the above considerations, in a preferred implementation, the first shift handover log includes multiple important indicators, and discards indicator information with a lower importance level.

[0078] Specifically, the medical record template of the medical record database includes a handover list corresponding to each handover type, and the handover list includes the above-mentioned multiple important indicators. Among them, the handover types include early handover, evening handover, holiday handover, etc. Different handover types require different indicators.

[0079] In this embodiment, if Figure 3 As shown, the first shift log of the first patient is output, specifically including:

[0080] S310: Determine the handover type according to the current time information.

[0081] Specifically, the current time can be obtained through network time, or through the time of the intelligent shift handover system.

[0082] The shift type is determined based on whether the current time is a holiday, morning or afternoon.

[0083] S320: Extracting data corresponding to the indicators in the handover list corresponding to the handover type in the medical record template from the medical record information to form a first handover log.

[0084] S330: Output the first shift handover log.

[0085] In a preferred embodiment, if the attention tag is yes, before step S150, it also includes S140: outputting basic information of the first patient to take the first patient as a patient requiring attention. This step allows the user to check whether there are any missed patients requiring attention. If so, the user manually inputs the information.

[0086] As an embodiment, the basic information includes the patient's general condition, patient type, hospitalization number and other information, which are used to confirm the patient's identity.

[0087] On the basis of the above, in order to gradually improve the accuracy of the handover log, in a preferred embodiment, an intelligent handover method is implemented through a neural network model based on deep learning, that is, the intelligent handover system adopts a neural network model based on deep learning, for example, a BERT (Bidirectional Encoder Representations from Transformers) model, etc. Among them, the medical record information of all patients obtained from the HIS system is used as the input information of the neural network model, and the basic information of the patient with the attention label as yes and the handover log of the patient are used as the output information of the neural network model.

[0088] In the training phase of the neural network model, first, a certain amount of medical record information is collected, and a focus label is attached to each medical record information. For the medical record information that needs attention, a handover list is made according to the standard format of handover (determined by the handover type, target object and patient type). The medical record information, focus label and handover list form the data set of the model. Secondly, the information in the data set is annotated with text to form a training set for model learning.

[0089] An example of text annotation is shown below:

[0090] Medical Record Information:

[0091] Bed 23, male, 45 years old, 2021XXXXXX, 2021-10-21, new patient

[0092] Diagnosis: Coronary heart disease, heart function, type 2 diabetes

[0093] Admitted to hospital due to "chest tightness for 1 day". The patient had chest tightness without obvious cause 1 day ago, which was persistent, without palpitation, cough, or sputum. He had a history of diabetes. Physical examination: T 37.0℃, P 80bpm, R 20bpm, BP 150 / 92mmHg, auscultation of the heart rhythm, coarse breath sounds in both lungs, and mild edema in both lower limbs. Coronary angiography is planned after admission. Please ask the doctor on duty for the patient's symptoms and emergency examination results.

[0094] Zhang San

[0095] Text annotation results:

[0096] [Bed number][Gender][Age][Hospitalization number][Date of admission][Patient type]

[0097]

diagnosis

[0098] [Chief complaint] [Current medical history] [Past medical history] [Physical examination (including vital signs)] [Diagnostic plan] [Content of attention]

[0099]

Doctor on duty

[0100] It should be noted that the indicators in the handover list include dynamic indicators and static indicators. Static indicators include the patient's gender, blood type, etc.; dynamic indicators include the patient's number of days in hospital, the patient's blood pressure, the patient's diagnosis results, etc., among which the patient's diagnosis results need to be changed in combination with the relevant indicators output by the patient this time. For example, if the blood sugar of a diabetic patient is significantly elevated, the blood gas analysis indicates acidosis, and ketone bodies appear in the urine routine, diabetic ketoacidosis is considered to have occurred. The medical record information this time matches the medical record template in the neural network model with the diagnosis of diabetes, blood gas analysis of acidosis, and positive urine ketone bodies. Therefore, the output diagnosis result changes from "diabetes" to "diabetic ketoacidosis". In addition, trend graphs of dynamic indicators (such as dynamic changes in blood sugar and blood pressure, etc.) can be output as needed.

[0101] The neural network model also predicts and outputs the patient's prognosis based on the patient's real-time indicators at the time of handover, strengthens reminders for patients at high risk of disease progression or complications, and points out which indicators need special attention and corresponding treatment measures.

[0102] In the implementation method using the neural network model, if after outputting the basic information of the first patient (see S140), the user believes that there are patients who have been missed and need attention, the intelligent handover method further includes:

[0103] S160: receiving basic information of a newly added second patient input by the user, and the attention tag of the second patient is yes, and executing S150.

[0104] Furthermore, in S150 , the first shift handover log of the first patient and the second patient is output.

[0105] After outputting the first handover log of the first patient and the second patient, if the user believes that the first handover log is incomplete, the user can supplement the content of the handover log. On this basis, the intelligent handover method of the present application also includes:

[0106] S170: Receive the second handover log of the first patient and / or the second patient.

[0107] S180: Merge the first shift handover log and the second shift handover log of the same patient and output them.

[0108] Based on the above-mentioned manual input of the second patient and the second handover log by the user, the intelligent handover method of the present application also includes receiving the reason for the second patient being paid attention to and the second handover log input by the user and inputting the training set of the neural network model for self-learning of the neural network model.

[0109] On the basis of the above, in a preferred embodiment, after obtaining the medical records of all patients from the HIS system (see S110), the intelligent handover system automatically determines whether the key indicator is obtained. If so, S120 is executed. Otherwise, a prompt message is output to prompt the user to supplement the indicator through the HIS system. If the indicator is supplemented later, S120 is continued to be executed. Otherwise (for example, the patient did not undergo the corresponding test, resulting in the missing indicator), the intelligent handover system outputs information that the indicator was not obtained.

[0110] In another preferred embodiment, the intelligent handover system also compares the indicators in the medical record information with the corresponding indicators in the medical record database, and automatically detects whether there are any abnormalities in the indicators (for example, the blood pressure is 1800 / 100 mmHg, and the systolic pressure is significantly deviated from the value of the systolic pressure in the medical record database). If there is an abnormality, a prompt message is output to remind the user to verify the result. If feedback information is received that the input data is correct, a key reminder of the indicator is output in the handover log to prompt the target object to pay special attention.

[0111] In another preferred embodiment, for a specific disease or a specific patient type, if the output handover log is wrong, redundant or missing, the user can manually revise it. For example, if the handover log of a patient with gastrointestinal bleeding lacks stool color, the stool color can be manually input.

[0112] Furthermore, after receiving the revised content from the user, the intelligent handover system inputs the content into the training set of the neural network model for the model to learn by itself.

[0113] Corresponding to the above embodiments and preferred solutions, the present invention also provides an embodiment of an intelligent shift handover device, such as Figure 4 As shown, it may specifically include a medical record information acquisition module 410 , a focus tag acquisition module 420 , and a shift log output module 430 .

[0114] The medical record information acquisition module 410 is used to acquire the medical record information of all patients from the hospital information system.

[0115] The attention tag acquisition module 420 is used to acquire the attention tag of the medical record information of the first patient.

[0116] The shift handover log output module 430 is used to output a first shift handover log of a first patient.

[0117] In one possible implementation, Figure 5 As shown, the attention label acquisition module 420 includes a patient type extraction module 4201 , a maximum matching degree acquisition module 4202 , a first label acquisition module 4203 and a second label acquisition module 4204 .

[0118] The patient type extraction module 4201 is used to extract the patient type of the first patient from the medical record information.

[0119] The maximum matching degree acquisition module 4202 is used to obtain the maximum matching degree between the medical record information and the first medical record template in the medical record database corresponding to the patient type.

[0120] The first tag acquisition module 4203 is used to acquire the attention tag of the second medical record template corresponding to the maximum matching degree.

[0121] The second tag acquisition module 4204 is used to use the attention tag of the second medical record template as the attention tag of the medical record information.

[0122] In one possible implementation, Figure 6 As shown, the shift handover log output module 430 includes a shift handover type determination module 4301 , a data extraction module 4302 and a first shift handover log output module 4303 .

[0123] The shift type determination module 4301 is used to determine the shift type according to the current time information.

[0124] The data extraction module 4302 is used to extract data corresponding to the indicators in the handover list corresponding to the handover type in the medical record template from the medical record information to form a first handover log.

[0125] The first shift handover log output module 4303 is used to output the first shift handover log.

[0126] It should be understood that the above Figure 4-6 The division of the various components of the intelligent handover device shown is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these components can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some components can also be implemented in the form of software calling through processing elements, and some components can be implemented in the form of hardware. For example, one of the above modules can be a separately established processing element, or it can be integrated in a chip of an electronic device. The implementation of other components is similar. In addition, all or part of these components can be integrated together, or they can be implemented independently. In the implementation process, each step of the above method or the above components can be completed by the hardware integrated logic circuit in the processor element or the instructions in the form of software.

[0127] For example, the above components may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more microprocessors (DSP), or one or more field programmable gate arrays (FPGA). For another example, these components may be integrated together to be implemented in the form of a system-on-a-chip (SOC).

[0128] Based on the above embodiments and their preferred embodiments, those skilled in the art can understand that, in actual operation, the present invention is applicable to a variety of implementations. The present invention uses the following carrier as a schematic illustration:

[0129] (1) An intelligent shift handover device, which may include:

[0130] One or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, which, when executed by the device, cause the device to perform the steps / functions of the aforementioned embodiments or equivalent implementations.

[0131] Figure 7 The figure is a schematic diagram of the structure of an embodiment of the intelligent handover device of the present invention. The electronic device may be a PC, a server, a smart terminal (a mobile phone, a tablet, a watch, etc.), a smart TV, a smart screen, etc. The specific form of the intelligent handover device is not limited in this embodiment.

[0132] Specific as Figure 7 As shown, the intelligent shift handover device 900 includes a processor 910, a memory 930 and a display unit 970. The processor 910 and the memory 930 can communicate with each other through an internal connection path to transmit control and / or data signals. The memory 930 is used to store a computer program, and the processor 910 is used to call and run the computer program from the memory 930. The processor 910 and the memory 930 can be combined into a processing device, or more commonly, they are independent components. The processor 910 is used to execute the program code stored in the memory 930 to implement the above functions. In specific implementation, the memory 930 can also be integrated in the processor 910, or independent of the processor 910. The display unit 970 can include a display screen.

[0133] In addition, in order to make the functions of the intelligent shift handover device 900 more complete, the device 900 may also include one or more of an input unit 960, an audio circuit 980, a camera 990 and a sensor 901, and the audio circuit may also include a speaker 982, a microphone 984, and the like.

[0134] Furthermore, the intelligent shift handover device 900 may also include a power supply 950 for providing electrical energy to various devices or circuits in the device 900 .

[0135] It should be understood that Figure 7 The intelligent shift handover device 900 shown can implement each process of the method provided in the aforementioned embodiment. The operation and / or function of each component in the device 900 can be respectively used to implement the corresponding process in the aforementioned method embodiment. For details, please refer to the description of the embodiments of the method, device, etc. in the previous text. To avoid repetition, the detailed description is appropriately omitted here.

[0136] It should be understood that Figure 7 The processor 910 in the smart shift handover device 900 shown may be a system on chip SOC, which may include a central processing unit (CPU) and may further include other types of processors, such as a graphics processing unit (GPU), etc., which will be described in detail below.

[0137] In summary, the various processors or processing units within the processor 910 can work together to implement the previous method flow, and the corresponding software programs of the various processors or processing units can be stored in the memory 930.

[0138] (2) A readable storage medium having a computer program or the above-mentioned device stored thereon, which, when executed, enables a computer to execute the steps / functions of the aforementioned embodiment or an equivalent implementation.

[0139] In several embodiments provided by the present invention, any function, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such an understanding, some technical solutions of the present invention are essentially or part of the technical solution that contributes to the prior art or part of the technical solution can be embodied in the form of the following software products.

[0140] (3) A computer program product (which may include the above-mentioned apparatus), which, when running on a terminal device, enables the terminal device to execute the intelligent shift handover method of the above-mentioned embodiment or an equivalent implementation manner.

[0141] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that all or part of the steps in the above implementation method can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the above computer program product may include but is not limited to APP; continuing from the previous text, the above device / terminal may be a computer device (such as a mobile phone, PC terminal, cloud platform, server, server cluster or network communication device such as media gateway, etc.). In addition, the hardware structure of the computer device may also specifically include: at least one processor, at least one communication interface, at least one memory and at least one communication bus; the processor, communication interface and memory can all communicate with each other through the communication bus. Among them, the processor may be a central processing unit CPU, DSP, microcontroller or digital signal processor, and may also include GPU, embedded neural network processor (Neural-network Process Units; hereinafter referred to as: NPU) and image signal processor (Image Signal Processing; hereinafter referred to as: ISP). The processor may also include a specific integrated circuit ASIC, or one or more integrated circuits configured to implement the embodiments of the present invention, etc. In addition, the processor may have the function of operating one or more software programs, and the software programs may be stored in a storage medium such as a memory; and the aforementioned memory / storage medium may include: non-volatile memory (non-volatile memory), such as a non-removable disk, U disk, mobile hard disk, optical disk, etc., as well as read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), etc.

[0142] In the embodiments of the present invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. A and B may be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c may be single or multiple.

[0143] Those skilled in the art will appreciate that the various modules, units, and method steps described in the embodiments disclosed in this specification can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0144] In addition, each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. In particular, for embodiments such as devices and equipment, since they are basically similar to method embodiments, the relevant parts can refer to the partial description of the method embodiments. The embodiments of the devices and equipment described above are merely schematic, wherein the modules, units, etc. described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed in multiple places, such as nodes of a system network. Specifically, some or all of the modules and units may be selected according to actual needs to achieve the purpose of the above-mentioned embodiment scheme. Those skilled in the art can understand and implement it without paying creative labor.

[0145] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings, but the above is only a preferred embodiment of the present invention. It should be noted that the technical features involved in the above embodiments and their preferred methods can be reasonably combined and matched into a variety of equivalent schemes by those skilled in the art without departing from or changing the design ideas and technical effects of the present invention; therefore, the present invention is not limited to the scope of implementation shown in the drawings, and all changes made in accordance with the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the specification and drawings, should be within the protection scope of the present invention.

Claims

1. An intelligent shift handover method, characterized in that: include: Obtain all patients' medical records from the hospital information system; For each first patient, obtaining a focus tag of the medical record information of the first patient; If the attention tag is yes, outputting the first shift log of the first patient; The attention tags for obtaining the medical record information of the first patient specifically include: extracting a patient type of the first patient from the medical record information; Obtaining a maximum degree of match between the medical record information and a first medical record template in a medical record database corresponding to the patient type; If the maximum matching degree is higher than a threshold, obtaining a focus tag of a second medical record template corresponding to the maximum matching degree; Using the attention tag of the second medical record template as the attention tag of the medical record information; Before obtaining the maximum matching degree, the method further includes: Get the target object; and, The medical record database is a medical record database corresponding to the patient type in a target database corresponding to the target object; Furthermore, outputting the first shift handover log of the first patient specifically includes: Determine the shift type based on the current time information; Extracting data corresponding to the indicators in the handover list corresponding to the handover type in the medical record template from the medical record information to form a first handover log; Output the first shift handover log.

2. The intelligent shift handover method according to claim 1, characterized in that: The intelligent handover method is implemented by a neural network model based on deep learning, wherein the medical record information of all patients is used as input information of the neural network model, and the first handover log of the first patient is used as output information of the neural network model.

3. The intelligent shift handover method according to claim 2, characterized in that: If the attention tag is yes, outputting the basic information of the first patient; In addition, the intelligent shift handover method also includes: Receive basic information of a newly added second patient, where the attention tag of the second patient is yes; and, A first shift handover log of the first patient and the second patient is output.

4. The intelligent shift handover method according to claim 3, characterized in that: Also includes: receiving a second handover log of the first patient and / or the second patient; Merge the first shift handover log and the second shift handover log of the same patient and output them.

5. The intelligent shift handover method according to claim 4, characterized in that: Also includes: receiving the reason why the second patient is being paid attention to and the second shift handover log; The reason why the second patient is being paid attention to and the second shift log are input into the training set of the neural network model.

6. An intelligent shift handover device, characterized in that: It includes a medical record information acquisition module, a focus tag acquisition module, and a shift log output module; The medical record information acquisition module is used to obtain the medical record information of all patients from the hospital information system; The attention tag acquisition module is used to acquire the attention tag of the medical record information of the first patient; The shift handover log output module is used to output the first shift handover log of the first patient; Wherein, the attention label acquisition module includes a patient type extraction module, a maximum matching degree acquisition module, a first label acquisition module and a second label acquisition module; The patient type extraction module is used to extract the patient type of the first patient from the medical record information; The maximum matching degree acquisition module is used to acquire the maximum matching degree between the medical record information and the first medical record template in the medical record database corresponding to the patient type; wherein the medical record database is a medical record database corresponding to the patient type in the target database corresponding to the obtained target object; The first tag acquisition module is used to acquire the attention tag of the second medical record template corresponding to the maximum matching degree; The second tag acquisition module is used to use the attention tag of the second medical record template as the attention tag of the medical record information; Furthermore, the shift handover log output module includes a shift handover type determination module, a data extraction module and a first shift handover log output module; The shift type determination module is used to determine the shift type according to the current time information; The data extraction module is used to extract data corresponding to the indicators in the handover list corresponding to the handover type in the medical record template from the medical record information to form a first handover log; The first shift handover log output module is used to output the first shift handover log.

7. An intelligent shift handover device, characterized in that: include: One or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, and when the instructions are executed by the intelligent shift handover device, the intelligent shift handover device executes the intelligent shift handover method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed on a computer, enables the computer to execute the intelligent shift handover method according to any one of claims 1 to 5.

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