Management method and device based on smart medical treatment, equipment and storage medium

Abstract

The invention provides a management method and device based on smart medical treatment, equipment and a storage medium. The method comprises the steps of obtaining illness state information of a patient to be operated; determining the disease importance degree of the to-be-operated patient based on the disease information of the to-be-operated patient, and matching a preset number of target nursing personnel for the to-be-operated patient according to the disease importance degree and the disease information of the to-be-operated patient; and for each to-be-operated patient, acquiring data of equipment and operating room environment, analyzing the data, and sending second completion information to prompt that the basic preparation work is prepared after the conditions are met, so as to help medical staff to arrange an operation process. According to the invention, through a layer-by-layer progressive mode, calculation and analysis are carried out from multiple angles of nursing personnel, equipment preparation angle and operating room environment angle, through the mode, appropriate target nursing personnel can be allocated, and the equipment accuracy and the operating room environment are ensured, so that the probability of smooth operation is improved.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to management methods, devices, equipment and storage media based on smart medical care. Background Art

[0002] Operating room nursing is a high-risk, high-tech, and core component of hospital care. Currently, hidden dangers in operating room nursing include environmental factors, equipment issues, and nursing staff professionalism. To ensure smooth surgical procedures and safe patient recovery, the risks and hazards of operating room nursing care, as well as their prevention and management, must be prioritized. Summary of the Invention

[0003] The purpose of the present invention is to provide a management method, device, equipment and storage medium based on smart medical care to improve the above problems.

[0004] In order to achieve the above objectives, the embodiments of the present application provide the following technical solutions: On the one hand, an embodiment of the present application provides a management method based on smart medical care, the method comprising: Obtaining medical information of a patient to be operated on; determining the severity of the patient's condition based on the medical information of the patient to be operated on, and matching a preset number of target nursing staff for the patient to be operated on according to the severity of the patient's condition and the medical information; For each patient awaiting surgery, the corresponding list of surgical equipment to be used and the image of the surgical equipment to be used uploaded by the target nursing staff are obtained, and the equipment image is compared and analyzed with the equipment list information. When the two are consistent, a first completion message is sent; in response to the first completion message, the environmental factor information in the operating room before the operation is obtained, and the environmental factor information includes noise information, temperature information and humidity information; the environmental score of the operating room is calculated based on the environmental factor information in the operating room before the operation, and when the environmental score is greater than the preset environmental score threshold, a second completion message is sent. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

[0005] In a second aspect, an embodiment of the present application provides a management device based on smart medical care, the device comprising: An acquisition module is used to obtain the condition information of the patient to be operated on; determine the severity of the condition of the patient to be operated on based on the condition information of the patient to be operated on, and match the patient to be operated on with a preset number of target nursing staff according to the severity of the condition of the patient to be operated on and the condition information; The calculation module is used to obtain the corresponding surgical equipment list information and the surgical equipment images uploaded by the target nursing staff for each patient to be operated on, compare and analyze the equipment images with the equipment list information, and send a first completion message when the two are consistent; in response to the first completion information, obtain the environmental factor information in the operating room before the operation, and the environmental factor information includes noise information, temperature information and humidity information; calculate the environmental score of the operating room based on the environmental factor information in the operating room before the operation, and send a second completion message when the environmental score is greater than a preset environmental score threshold. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

[0006] In a third aspect, embodiments of the present application provide a management device based on smart healthcare, comprising a memory and a processor. The memory is used to store a computer program; the processor is used to implement the steps of the above-mentioned management method based on smart healthcare when executing the computer program.

[0007] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned management method based on smart medical care are implemented.

[0008] The beneficial effects of the present invention are: The present invention first obtains the medical condition information of the patient to be operated on, and then determines whether the patient is a key patient to be operated on based on the obtained medical condition information, and then determines the target nursing staff for each patient to be operated on; after determining the target nursing staff, the surgical equipment to be used is also checked and verified to ensure the smooth progress of the operation. Finally, after the surgical equipment is checked, data is collected on the environment in the operating room, and the environmental score of the operating room is calculated based on the collected environmental data. When the environmental score is greater than the preset environmental score threshold, the second completion information is sent to indicate that the basic preparations have been completed; the present invention uses a step-by-step progressive approach to perform calculations and analyses from multiple angles, including the nursing staff perspective, the equipment preparation perspective, and the operating room environment perspective. In this way, a suitable target nursing staff can be matched, and the accuracy of the equipment and the appropriateness of the operating room environment can be ensured, thereby increasing the probability of a smooth operation and improving the success rate of the operation.

[0009] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 This is a flowchart of a management method based on smart medical care according to an embodiment of the present invention; Figure 2 Schematic diagram of the structure of the management device based on smart medical care described in an embodiment of the present invention; Figure 3 It is a schematic diagram of the structure of the management device based on smart medical care described in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0013] It should be noted that similar reference numerals or letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance. Example 1

[0014] like Figure 1 As shown, this embodiment provides a management method based on smart medical care, which includes step S1 and step S2.

[0015] Step S1, obtaining the medical condition information of the patient to be operated on; determining the severity of the patient's condition based on the medical condition information of the patient to be operated on, and matching the patient to be operated on with a preset number of target nurses according to the severity of the patient's condition and the medical condition information; In this step, the medical information of multiple patients undergoing surgery is obtained, wherein the medical information may include the patient's basic personal information, the main manifestations of the disease, the onset and course of the disease, previous examination information, family history, etc.; the preset digits can be customized; during surgery, the cooperation between doctors and nurses is also the key to the success of the operation. Therefore, this embodiment first matches the patients undergoing surgery with nursing staff, i.e., nurses, to increase the probability of successful surgery; In this step, the severity of the patient's condition is determined based on the patient's condition information, and the specific implementation steps of matching the patient with a preset number of target nursing staff according to the severity of the patient's condition and the condition information include step S11 and step S12; Step S11: performing cluster analysis on the medical condition information of all patients to be operated on to obtain multiple clustering results, and matching a corresponding Arabic numeral to each clustering result; at the same time, counting the number of medical condition information items contained in each clustering result, performing a difference calculation on the number of medical condition information items contained in any two clustering results, and determining whether the difference is less than a preset threshold; if the difference is less than the preset threshold, extracting a first proportion of medical condition information from each clustering result as a sample; otherwise, extracting a first quantity of medical condition information from each clustering result as a sample; In this step, after clustering all the medical information, if there are 5 clustering results, then these five clustering results can be matched with Arabic numerals 1-5 respectively. The Arabic numerals here can be understood as using numbers to replace categories, and 1-5 represent different categories respectively. At the same time, in this step, the purpose of performing difference calculation on the number of medical information is to analyze whether the number of data items contained in each clustering result is uniform. If it is less than a preset threshold, it means that the number of data items in these clustering results is relatively uniform, otherwise it is uneven. Therefore, under the premise of uniformity, a first proportion of medical information is extracted from each clustering result as a sample; under the premise of unevenness, a first number of medical information is extracted from each clustering result as a sample. This approach can improve the uniformity of samples in each category. Step S12: Label each sample, wherein the labeling information is the Arabic numerals corresponding to each sample. After the labeling is completed, the xgboost model is trained to obtain a disease classification model; based on the disease classification model, the severity of the patient's condition is determined, and according to the severity of the patient's condition and the disease information, a preset number of target nurses are matched for the patient.

[0016] In this step, labeling each sample can be understood as follows: through the previous clustering, each clustering result is matched with a corresponding Arabic numeral, so the Arabic numeral corresponding to the disease information in each clustering result is the Arabic numeral matched by the clustering result; At the same time, in this step, the severity of the patient's condition is determined based on the condition classification model, and the specific implementation steps for matching the patient with a preset number of target nurses according to the severity of the patient's condition and the condition information include steps S121 and S122; Step S121: Acquire medical information of a plurality of historical key surgical patients, input the medical information of the plurality of historical key surgical patients into the medical condition classification model, obtain an Arabic numeral corresponding to each historical key surgical patient, count the number of medical information items corresponding to each Arabic numeral, obtain an item value, and record the Arabic numeral corresponding to the largest item value as the target number; In this step, the medical condition information of multiple historical key surgery patients is the medical condition information of the past key surgery patients, wherein the doctor determines whether they are marked as key surgery patients; the medical condition information of multiple historical key surgery patients is input into the medical condition classification model, and the Arabic numerals corresponding to the medical condition information of each historical key surgery patient can be obtained, and then the Arabic numerals corresponding to each historical key surgery patient can be obtained; Step S122: record the clustering result whose Arabic numeral corresponding to the clustering result is the target numeral as the target clustering result, and record the medical information of the patient to be operated on contained in the target clustering result as the medical information of the key patient to be operated on; after the medical information of the patient to be operated on is recorded as the medical information of the key patient to be operated on, mark the corresponding patient to be operated on as the key patient to be operated on, and obtain a set of key nursing staff, wherein the set of key nursing staff includes multiple nursing staff, and each nursing staff has a preset number of years of nursing experience; match the key patient to be operated on with a preset number of target nursing staff based on the set of key nursing staff and the medical information of the key patient to be operated on; record the patient to be operated on who is not marked as the key patient to be operated on as the ordinary patient to be operated on, obtain the profile information of each nursing staff outside the set of key nursing staff for each ordinary patient to be operated on, and perform similarity calculation on the profile information of each nursing staff outside the set of key nursing staff with the medical information of the ordinary patient to be operated on, and match the ordinary patient to be operated on with a preset number of target nursing staff in descending order of similarity.

[0017] In this step, the above method can be used to simply and quickly screen out key patients waiting for surgery based on the condition information of multiple patients waiting for surgery, reducing manual work; once a patient is determined to be a key patient waiting for surgery, it is necessary to pay special attention to him or her. Therefore, in this embodiment, after marking the patient as a key patient waiting for surgery, a set of key nursing staff is obtained. This set is pre-set and stored, and one hospital corresponds to one set of key nursing staff. The preset number of years can be 5 years or more; At the same time, in this step, based on the set of key nursing staff and the condition information of the key patients to be operated on, specific implementation steps for matching the key patients to be operated on with a preset number of target nursing staff include step S1221; Step S1221: For each key patient awaiting surgery, obtain the profile information of each nurse in the key nursing staff set, the profile information includes the nursing content that each nurse is good at, calculate the similarity between the condition information of the key patient awaiting surgery and the profile information of each nurse, and obtain multiple first similarities, and collect the nursing staff whose first similarities are greater than the preset first similarity threshold to obtain a preliminary nursing staff set; analyze the number of nursing staff in the preliminary nursing staff set, and match the key patient awaiting surgery with a preset number of target nursing staff according to the analysis results.

[0018] In this step, the nursing content that one is good at may include, for example, previous nursing experience, nursing direction and other nursing work related content; in this step, the similarity analysis in step S1221 will be performed for each key patient to be operated on, and then the corresponding target nursing staff will be matched for each key patient to be operated on; and the similarity calculation can be performed using the following calculation formula, which is: , is the similarity between each key patient's condition information and each nurse's profile information, which is a logarithmic base and greater than 1; B is the number of repeated words between each nurse's profile information and each key patient's condition information; C is the total number of words in each nurse's profile information; in addition to this similarity calculation method, a common calculation method can also be used, which is not limited in this embodiment; At the same time, in this step, the number of nurses in the preliminary nurse set is analyzed, and the specific implementation steps of matching the key surgical patient with a preset number of target nurses according to the analysis result include step S12211, step S12212 and step S12213; Step S12211: Analyze the number of nursing staff in the preliminary nursing staff set, wherein, if the number of nursing staff in the preliminary nursing staff set is equal to the preset number of digits, all nursing staff in the preliminary nursing staff set are used as target nursing staff corresponding to the key patient to be operated on; if the number of nursing staff in the preliminary nursing staff set is less than the preset number of digits, nursing staff not included in the preliminary nursing staff set are selected from the key nursing staff set in descending order of the first similarity, and added to the preliminary nursing staff set until the number of nursing staff in the preliminary nursing staff set is equal to the preset number of digits; Step S12212: Analyze the number of nursing staff in the preliminary nursing staff set, wherein if the number of nursing staff in the preliminary nursing staff set is greater than a preset number, execute the first step: extract features from the profile information of each nursing staff in the preliminary nursing staff set, cluster based on the features to obtain multiple clusters, count the number of profile information items contained in each cluster, sort the obtained number in ascending order to obtain sorted data, determine the quartile difference and the third quartile in the sorted data respectively to obtain a first value and a second value, multiply the first value by the preset value to obtain a third value, and add the third value to the second value to obtain a fourth value; compare the number of profile information items contained in each cluster with the fourth value respectively, and when the number of profile information items contained in each cluster is greater than the fourth value, mark the nursing staff corresponding to this cluster as a candidate nursing staff; In this step, the preset value can be 1.5 or 2; Step S12213, determine the number of nurses in the remaining nursing staff set excluding the candidate nurses in the preliminary nursing staff set. If it is equal to the preset number of numbers, all nurses in the remaining nursing staff set will be used as target nurses corresponding to the key patients to be operated on. If it is less than the preset number of numbers, nurses will be screened from the candidate nurses to the remaining nursing staff set according to the preset rules until the number of nurses in the remaining nursing staff set is equal to the preset number of numbers. If it is greater than the preset number of numbers, the first step will be executed again for the remaining nursing staff set until the number of nurses in the remaining nursing staff set is less than or equal to the preset number of numbers.

[0019] In this step, if the number of candidates is greater than the preset number, step S12212 is executed again to screen out candidate caregivers, and naturally there will be a corresponding set of remaining caregivers. The screening is repeated, and the candidate caregivers screened out each time and the candidate caregivers screened out last time are both candidate caregivers. When the number of people in the remaining caregiver set is less than the preset number, caregivers are screened from the candidate caregivers to the remaining caregiver set according to the preset rules until the number of caregivers in the remaining caregiver set is equal to the preset number. Meanwhile, in this step, if it is less than, the specific implementation steps of screening nursing staff from candidate nursing staff to the remaining nursing staff set according to preset rules include step S122131; Step S122131. Perform mean calculation on the features corresponding to all nursing staff in the remaining nursing staff set to obtain the mean calculation result, perform similarity calculation on the features corresponding to the candidate nursing staff with the mean calculation result respectively to obtain multiple second similarities; select the corresponding candidate nursing staff in descending order of the second similarities and add them to the remaining nursing staff set.

[0020] Through the above steps, the medical condition information of each patient to be operated on can be analyzed, and then the key patients to be operated on can be objectively and quickly screened out; then, the key patients to be operated on can be matched with a set of key nursing staff, and then for each key patient to be operated on, a round of screening is first performed from the set of key nursing staff according to the similarity rule. After the first round of screening, a preliminary set of nursing staff is obtained. At this time, the number of nursing staff in the preliminary set of nursing staff will be analyzed. If the number of nursing staff after screening is greater than the preset number, a second round of screening will be performed. In the second round of screening, the number of nursing staff in the preliminary set of nursing staff will be screened out. Feature extraction is performed on the profile information of each nurse, and clustering is performed based on the features to obtain multiple clusters. Candidate nurses are screened out based on the multiple clusters. Finally, the target nurse corresponding to the key patient to be operated on is determined based on the candidate nurses and the preliminary nurse set. Through the above-mentioned hierarchical screening method, a list of nurses more suitable for the key patient to be operated on can be screened, thereby increasing the probability of successful surgery. In addition to nurses, the accuracy of surgical equipment and the environment of the operating room are still crucial to the success of the surgery. Therefore, in this embodiment, the surgical equipment and the environment of the operating room are also monitored and analyzed. Step S2: For each patient to be operated on, obtain the corresponding list of surgical equipment to be used and the image of surgical equipment to be used uploaded by the target nursing staff, compare and analyze the equipment image with the equipment list information, and send a first completion message when the two are consistent; in response to the first completion information, obtain the environmental factor information in the operating room before the operation, and the environmental factor information includes noise information, air circulation information, temperature information and humidity information; calculate the environmental score of the operating room based on the environmental factor information in the operating room before the operation, and send a second completion message when the environmental score is greater than the preset environmental score threshold. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

[0021] In this step, after the target nurse is matched, the preliminary preparations are completed. Then, the operating room-related data will be obtained. In this embodiment, the relevant data of the surgical equipment and the operating room environment are obtained. Obtaining corresponding surgical equipment list information and surgical equipment images uploaded by the target nurse, wherein the target nurse is any one of the preset number of target nurses; Comparing and analyzing the equipment image with the equipment list information, and when the two are consistent, sending the first completion information can be understood as: inputting the equipment image into a preset image recognition model, outputting the name of the corresponding equipment, and comparing and analyzing the output name with the name of the equipment included in the equipment list information. If all correspond, the first completion information can be sent, wherein the image recognition model can be obtained by training a convolutional neural network model using images labeled with equipment names; of course, another target nursing staff can also manually compare and analyze the names of the equipment included in the equipment image with the names of the equipment included in the equipment list information one by one. When all are consistent, the first completion information can be sent; this method can ensure that the equipment is properly prepared before the operation, avoiding the problem of increased surgical risks caused by finding that the wrong equipment or missing equipment is taken during the operation; In addition, after the equipment is prepared, environmental data will be obtained, and the specific implementation steps of calculating the environmental score of the operating room based on the environmental factor information in the operating room before the operation include step S21; Step S21: score the noise factor, temperature factor and humidity factor respectively and assign weights according to the noise information, temperature information and humidity information, and perform a weighted sum operation according to the scores and their corresponding weights to obtain a fifth value; at the same time, obtain the probability of environmental problems occurring in the operating room environment and the impact factors of problems in the operating room environment on the surgery; multiply the fifth value, probability and impact factor to obtain a sixth value, and subtract the sixth value from the preset value to obtain the environmental score of the operating room.

[0022] In this step, the user scores the noise factor, temperature factor, and humidity factor based on the collected noise, temperature, and humidity, and assigns weights. This step can be used to calculate the impact score of environmental factors. At the same time, in this step, environmental problems in the operating room environment can be understood as problems such as a sudden and significant increase or decrease in temperature / humidity / noise. A sudden and significant increase or decrease can be understood as an increase or decrease exceeding a preset threshold based on the current data. The probability of environmental problems in the operating room environment and the factors affecting surgery caused by these problems are both uploaded by the user. In addition to step S21, the specific implementation steps for calculating the environmental score of the operating room based on the environmental factor information in the operating room before the operation can also be to directly assign weights to the noise information, temperature information, and humidity information, and then perform weighted sum calculation on the noise, temperature, and humidity data with their corresponding weights, and use the obtained calculation result directly as the environmental score of the operating room; This embodiment first obtains the medical condition information of the patient to be operated on, and then determines whether the patient is a key patient to be operated on based on the obtained medical condition information, and then determines the target nursing staff for each patient to be operated on; after determining the target nursing staff, the surgical equipment to be used is also inspected and verified to ensure the smooth progress of the operation. Finally, after the surgical equipment is checked, data is collected on the environment in the operating room, and the environmental score of the operating room is calculated based on the collected environmental data. When the environmental score is greater than the preset environmental score threshold, the second completion information is sent to indicate that the basic preparations have been completed; this embodiment uses a step-by-step approach to perform calculations and analyses from multiple angles, including the perspective of nursing staff, the perspective of equipment preparation, and the perspective of the operating room environment. In this way, a suitable target nursing staff can be matched, and the accuracy of the equipment and the appropriateness of the operating room environment can be ensured, thereby increasing the probability of a smooth operation and improving the success rate of the operation. Example 2

[0023] like Figure 2 As shown, this embodiment provides a management device based on smart medical care, which includes an acquisition module 1 and a calculation module 2.

[0024] Acquisition module 1 is used to obtain the condition information of the patient to be operated on; determine the severity of the condition of the patient to be operated on based on the condition information of the patient to be operated on, and match the patient to be operated on with a preset number of target nursing staff according to the severity of the condition of the patient to be operated on and the condition information; Calculation module 2 is used to obtain the corresponding surgical equipment list information and the surgical equipment image uploaded by the target nursing staff for each patient to be operated on, compare and analyze the equipment image with the equipment list information, and send a first completion message when the two are consistent; in response to the first completion information, obtain the environmental factor information in the operating room before the operation, and the environmental factor information includes noise information, temperature information and humidity information; calculate the environmental score of the operating room based on the environmental factor information in the operating room before the operation, and send a second completion message when the environmental score is greater than the preset environmental score threshold. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

[0025] It should be noted that, regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here. Example 3

[0026] Corresponding to the above method embodiments, the embodiments of the present disclosure also provide a management device based on smart medical care. The management device based on smart medical care described below and the management method based on smart medical care described above can refer to each other.

[0027] Figure 3 FIG is a block diagram of a management device 300 based on smart medical care according to an exemplary embodiment. Figure 3 As shown, the management device 300 based on smart medical care may include: a processor 301, a memory 302. The management device 300 based on smart medical care may also include one or more of a multimedia component 303, an I / O interface 304, and a communication component 305.

[0028] The processor 301 is used to control the overall operation of the smart healthcare management device 300 to complete all or part of the steps in the smart healthcare management method described above. The memory 302 is used to store various types of data to support the operation of the smart healthcare management device 300. This data may include, for example, instructions for any application or method operating on the smart healthcare management device 300, as well as application-related data such as contact information, sent and received messages, images, audio, video, etc. The memory 302 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 303 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 302 or transmitted via the communication component 305. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 304 provides an interface between the processor 301 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 305 is used for wired or wireless communication between the smart medical management device 300 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more thereof, may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0029] In an exemplary embodiment, the smart healthcare-based management device 300 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the above-mentioned smart healthcare-based management method.

[0030] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When executed by a processor, the program instructions implement the steps of the aforementioned smart healthcare-based management method. For example, the computer-readable storage medium may be the aforementioned memory 302 including the program instructions. The program instructions may be executed by the processor 301 of the smart healthcare-based management device 300 to implement the aforementioned smart healthcare-based management method. Example 4

[0031] Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium. The readable storage medium described below and the management method based on smart medical care described above can refer to each other.

[0032] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the management method based on smart medical care in the above-mentioned method embodiment.

[0033] The readable storage medium may specifically be any readable storage medium that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0034] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A management method based on smart medical care, characterized in that: include: Obtaining medical information of patients awaiting surgery; Determining the severity of the patient's condition based on the patient's condition information, and matching a preset number of target nursing staff for the patient according to the severity of the patient's condition and the condition information; For each patient awaiting surgery, the corresponding list of surgical equipment to be used and the image of the surgical equipment to be used uploaded by the target nursing staff are obtained, and the equipment image is compared and analyzed with the equipment list information. When the two are consistent, a first completion message is sent; in response to the first completion information, the environmental factor information in the operating room before the operation is obtained, and the environmental factor information includes noise information, temperature information and humidity information; the environmental score of the operating room is calculated based on the environmental factor information in the operating room before the operation, and when the environmental score is greater than the preset environmental score threshold, a second completion message is sent. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

2. The management method based on smart medical care according to claim 1, characterized in that: Determining the severity of the patient's condition based on the patient's condition information, and matching a preset number of target nursing staff for the patient according to the severity of the patient's condition and the condition information, including: Performing cluster analysis on the medical condition information of all patients to be operated on to obtain a plurality of clustering results, and matching a corresponding Arabic numeral to each clustering result; at the same time, counting the number of pieces of medical condition information contained in each clustering result, performing a difference calculation on the number of pieces of medical condition information contained in any two clustering results, and determining whether the difference is less than a preset threshold; if the difference is less than the preset threshold, extracting a first proportion of medical condition information from each clustering result as a sample; otherwise, extracting a first quantity of medical condition information from each clustering result as a sample; Each sample is labeled, where the labeling information is the Arabic numeral corresponding to each sample. After the labeling is completed, the xgboost model is trained to obtain a condition classification model; based on the condition classification model, the severity of the patient's condition is determined, and according to the severity of the patient's condition and condition information, a preset number of target nurses are matched for the patient to be operated on.

3. The management method based on smart medical care according to claim 2, characterized in that: Determining the severity of the condition of the patient to be operated on based on the condition classification model, and matching a preset number of target nursing staff for the patient to be operated on according to the severity of the condition of the patient to be operated on and the condition information, including: Obtaining medical information of a plurality of historical key surgical patients, inputting the medical information of the plurality of historical key surgical patients into the medical condition classification model, obtaining an Arabic numeral corresponding to each historical key surgical patient, counting the number of medical information of the historical key surgical patients corresponding to each Arabic numeral, obtaining an item value, and recording the Arabic numeral corresponding to the largest item value as a target number; The clustering result whose Arabic numeral corresponding to the clustering result is the target number is recorded as the target clustering result, and the medical condition information of the patient to be operated on contained in the target clustering result is recorded as the medical condition information of the key patient to be operated on; after the medical condition information of the patient to be operated on is recorded as the medical condition information of the key patient to be operated on, the corresponding patient to be operated on is marked as the key patient to be operated on, and a set of key nursing staff is obtained, wherein the set of key nursing staff includes multiple nursing staff, and each nursing staff has a preset number of years of nursing experience; based on the set of key nursing staff and the medical condition information of the key patient to be operated on, a preset number of target nursing staff are matched for the key patient to be operated on; the patient to be operated on who is not marked as the key patient to be operated on is recorded as the ordinary patient to be operated on, and for each ordinary patient to be operated on, the profile information of each nursing staff outside the set of key nursing staff is obtained, and the similarity between the profile information of each nursing staff outside the set of key nursing staff and the medical condition information of the ordinary patient to be operated on is respectively calculated, and the preset number of target nursing staff are matched for the ordinary patient to be operated on in descending order of similarity.

4. The management method based on smart medical care according to claim 3, characterized in that: Matching a preset number of target nursing staff for the key patients to be operated on based on the set of key nursing staff and the condition information of the key patients to be operated on, including: For each key patient awaiting surgery, the profile information of each nurse in the key nursing staff set is obtained, the profile information includes the nursing content that each nurse is good at, the similarity between the condition information of the key patient awaiting surgery and the profile information of each nurse is calculated respectively, and multiple first similarities are obtained. The nursing staff corresponding to the first similarity greater than a preset first similarity threshold are grouped together to obtain a preliminary nursing staff set; the number of nursing staff in the preliminary nursing staff set is analyzed, and a preset number of target nursing staff are matched to the key patient awaiting surgery according to the analysis results.

5. The management method based on smart medical care according to claim 4, characterized in that: Analyzing the number of nurses in the preliminary nurse set, and matching a preset number of target nurses for the key patient to be operated on according to the analysis results, including: The number of nurses in the preliminary nurse set is analyzed, wherein, if the number of nurses in the preliminary nurse set is equal to a preset number of digits, all nurses in the preliminary nurse set are used as target nurses corresponding to the key patient to be operated on; if the number of nurses in the preliminary nurse set is less than the preset number of digits, nurses not included in the preliminary nurse set are selected from the key nurse set in descending order of the first similarity and added to the preliminary nurse set until the number of nurses in the preliminary nurse set is equal to the preset number of digits; The number of nursing staff in the preliminary nursing staff set is analyzed, wherein, if the number of nursing staff in the preliminary nursing staff set is greater than a preset number, the first step is executed: feature extraction is performed on the profile information of each nursing staff in the preliminary nursing staff set, and clustering is performed based on the features to obtain multiple clusters, the number of profile information items contained in each cluster is counted, the obtained number of items is sorted in ascending order to obtain sorted data, the quartile difference and the third quartile in the sorted data are determined respectively to obtain a first value and a second value, the first value is multiplied by the preset value to obtain a third value, and the third value is added to the second value to obtain a fourth value; the number of profile information items contained in each cluster is compared with the fourth value respectively, and when the number of profile information items contained in each cluster is greater than the fourth value, the nursing staff corresponding to this cluster is marked as a candidate nursing staff; Determine the number of nurses in the remaining nurse set excluding the candidate nurses in the preliminary nurse set. If it is equal to the preset number of numbers, all nurses in the remaining nurse set will be used as target nurses corresponding to the key patients to be operated on. If it is less than the preset number of numbers, nurses will be screened from the candidate nurses to the remaining nurse set according to the preset rules until the number of nurses in the remaining nurse set is equal to the preset number of numbers. If it is greater than the preset number of numbers, the first step will be executed again for the remaining nurse set until the number of nurses in the remaining nurse set is less than or equal to the preset number of numbers.

6. The management method based on smart medical care according to claim 5, characterized in that: If it is less than, then the nurses are screened from the candidate nurses according to the preset rules and added to the remaining nurses set, including: The features corresponding to all nursing staff in the remaining nursing staff set are averaged to obtain the average calculation result, and the features corresponding to the candidate nursing staff are respectively similarly calculated with the average calculation result to obtain multiple second similarities; in descending order of the second similarities, the corresponding candidate nursing staff are selected and added to the remaining nursing staff set.

7. The management method based on smart medical care according to claim 1, characterized in that: The operating room environmental score is calculated based on the environmental factors information in the operating room before surgery, including: Based on the noise information, air circulation information, temperature information and humidity information, the noise factor, air circulation factor, temperature factor and humidity factor are scored and weighted respectively, and a weighted sum operation is performed based on the scores and their corresponding weights to obtain a fifth value; at the same time, the probability of problems occurring in the operating room environment and the impact score of problems in the operating room environment on the surgery are obtained; the fifth value, probability and impact score are multiplied together to obtain a sixth value, and the preset value is subtracted from the sixth value to obtain the operating room environment score.

8. A management device based on smart medical care, characterized in that: include: An acquisition module is used to obtain the condition information of the patient to be operated on; Determining the severity of the patient's condition based on the patient's condition information, and matching a preset number of target nursing staff for the patient according to the severity of the patient's condition and the condition information; The calculation module is used to obtain the corresponding surgical equipment list information and the surgical equipment images uploaded by the target nursing staff for each patient to be operated on, compare and analyze the equipment images with the equipment list information, and send a first completion message when the two are consistent; in response to the first completion information, obtain the environmental factor information in the operating room before the operation, and the environmental factor information includes noise information, temperature information and humidity information; calculate the environmental score of the operating room based on the environmental factor information in the operating room before the operation, and send a second completion message when the environmental score is greater than a preset environmental score threshold. The second completion message is used to prompt that the basic preparations have been completed to help medical staff arrange the operation process.

9. A management device based on smart medical care, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the management method based on smart medical care as described in any one of claims 1 to 7 when executing the computer program.

10. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the management method based on smart medical care as claimed in any one of claims 1 to 7.

Images