Nurse shift change recording method and system

Abstract

The invention discloses a nurse handover recording method and system, and relates to the field of medical management, and the method comprises the steps: obtaining an original handover record of a target patient by a target handover worker; matching according to the current physiological features of the target patient to obtain a standard feature tag; the standard feature tag comprises a structural information feature item and a non-structural information feature item of a patient type corresponding to the target patient; obtaining a record completion degree according to a matching result of all the standard feature tags and the original handover record; if the record completion degree is not greater than the completion degree threshold value, generating first feedback information, returning to the step of obtaining the original handover records of the target handover personnel to the target patient until the record completion degree is greater than the completion degree threshold value, and obtaining a target handover record according to all the original handover records; therefore, the integrity verification of the original handover record provided by the target handover personnel is realized.

Description

Technical Field

[0001] The present application relates to the field of medical management, and in particular to a method and system for recording nurse shift handovers. Background Art

[0002] Nurse handover refers to the activity in which the handover nurse introduces and communicates the patient's condition, treatment, nursing care, etc. to the incoming nurse in verbal or written form when the nurse's work shift changes, so as to ensure that the patient receives continuous and timely treatment and care. Traditional handovers rely on verbal transmission and paper records. Time pressure, busy work, lack of nursing experience, etc. will affect the integrity of handover records.

[0003] With the rapid development of medical information technology, hospital information management systems and electronic medical record systems have been widely used in clinical nursing work. For example, a medical staff handover method, device and terminal equipment with application number CN201811042431.9 queries the patient data generated by the patient during the working time of the handover personnel through the electronic system, and then automatically generates a handover report. Although this method can efficiently and comprehensively obtain structured information such as the patient's test results, it is difficult for the electronic system to directly obtain the patient's subjective feelings and personalized demands in a timely, accurate and comprehensive manner. The lack of unstructured information in the handover record will lead to a high risk of missing important information in the handover record. Summary of the invention

[0004] The purpose of the present invention is to solve the technical problem of how to reduce the omission of important information in the process of nurse handover, and provide a nurse handover record method and system, which uses the patient's physiological characteristics to match the necessary feature items in the handover process, and performs integrity verification on the handover record provided by the handover personnel according to the matching results, so as to achieve the purpose of reducing the risk of missing important information in the handover process.

[0005] According to a first aspect of the present invention, the present invention claims protection for a nurse shift handover recording method, comprising: Obtain the original handover record of the target patient by the target handover personnel; Obtaining a standard feature label according to the current physiological feature matching of the target patient; the standard feature label includes structural information feature items and non-structural information feature items corresponding to the patient type of the target patient; Obtaining the record completion degree according to the matching results of all the standard feature tags and the original handover record; If the record completion degree is not greater than the completion degree threshold, a first feedback message is generated, and the process returns to the step of obtaining the original handover record of the target patient by the target handover personnel until the record completion degree is greater than the completion degree threshold, and the target handover record is obtained based on all the original handover records; the first feedback message is used to remind the corresponding target handover personnel to supplement the original handover record.

[0006] In one embodiment of the present application, in the step of obtaining a standard feature label according to the current physiological feature matching of the target patient, the following step is further included: Obtain candidate handover records and corresponding completeness evaluations based on historical handover records; Obtaining the feature similarity between the patient physiological feature corresponding to each of the candidate handover records and the current physiological feature of the target patient; Obtaining candidate feature items according to all the candidate handover records; Obtaining the necessity component of the candidate feature item existing in the corresponding candidate handover record according to the feature similarity and the completeness evaluation of each candidate handover record; Calculating the corresponding necessity degree according to all the necessity degree components of each of the candidate feature items; The candidate feature item whose necessity degree is greater than a necessity degree threshold is used as the standard feature item.

[0007] In an embodiment of the present application, the completeness evaluation includes high completeness and low completeness, and the necessity component of the candidate feature item also includes: ; Among them, N i，j Represents the candidate feature item c i In the candidate handover record j The necessity component, I represents the indicator function, S j Represents the candidate handover record r j The feature similarity, E j Represents the candidate handover record r j The completeness evaluation of .

[0008] In one embodiment of the present application, the completeness evaluation is obtained based on a comparison result between the number of medical events caused by abnormal handover in the next shift corresponding to the candidate handover record and a threshold value of the number of accidents.

[0009] In an embodiment of the present application, the step of obtaining a candidate handover record according to the historical handover record further includes: querying historical handover records according to the original handover record to obtain a reference handover record; the record similarity between the reference handover record and the original handover record is not less than a first similarity threshold; If the number of the reference handover records is equal to 0, second feedback information is generated, and the second feedback information is used to remind the target handover personnel that the handover behavior is abnormal; If the number of the reference handover records is greater than 0, a candidate handover record is selected from all the reference handover records, and the similarity between the patient physiological characteristics corresponding to the candidate handover record and the current physiological characteristics of the target patient is not less than a second similarity threshold; If the number of the candidate handover records is equal to 0, the second feedback information is generated.

[0010] In an embodiment of the present application, before the step of querying the historical handover record according to the original handover record, the method further includes: obtaining a rejection feature according to a current physiological feature of the target patient; The historical handover records having the exclusion feature are screened out from all the historical handover records.

[0011] In an embodiment of the present application, before the step of querying the historical handover record according to the original handover record, the method further includes: Screening out abnormal physiological characteristics from the current physiological characteristics of the target patient; Matching the historical handover record according to the abnormal physiological feature to obtain an abnormal handover record; Before the preset handover time, the historical handover record is updated according to the abnormal handover record, and the step of querying the updated historical handover record according to the original handover record is continued until a first target handover record is obtained, and the first target handover record is sent to a target successor; After the preset handover time, a second target handover record is obtained based on the first target handover record and the supplementary record of the target successor, the original handover record is updated based on the second target handover record, and all the historical handover records are continued to be queried based on the updated original handover record to obtain the second target handover record.

[0012] According to a second aspect of the present invention, the present invention claims protection for a nurse shift record system, comprising: A record acquisition module, the record acquisition module is used to obtain the original handover record of the target patient by the target handover personnel; A standard matching module, the standard matching module is used to obtain a standard feature label according to the current physiological feature matching of the target patient; wherein the standard feature label includes a structural information feature item and a non-structural information feature item of the patient type corresponding to the target patient; A completion degree calculation module, the completion degree calculation module is used to obtain the record completion degree according to the matching results of all the standard feature tags and the original handover record; A record processing module, the record processing module is used to compare the record completion degree and the completion degree threshold. If the record completion degree is not greater than the completion degree threshold, a first feedback message is generated and returned to the record acquisition module until the record completion degree is greater than the completion degree threshold, and a target handover record is obtained based on all the original handover records; the first feedback information is used to remind the corresponding target handover personnel to supplement the original handover record.

[0013] This application has the following beneficial effects: 1. The original handover record obtained in advance is an original detailed description of the individual characteristics of the target patient based on the professional knowledge and clinical experience of the target handover personnel. The corresponding handover feature items are matched according to the current physiological characteristics of the target patient, and the handover feature items are matched with the original handover records provided by the target handover personnel. The record completion of the original handover record is calculated according to the matching results. If the record completion is not greater than the completion threshold, the current original handover record is regarded as having important information missing, and the target handover personnel are reminded to supplement it until the record completion is greater than the completion threshold. This not only realizes the integrity verification of the original handover record provided by the target handover personnel, reduces the risk of missing important information in the handover record, but also retains the individualized feature description based on professional knowledge and clinical experience, reduces the phenomenon of special characteristics of the target patient being ignored, and further reduces the risk of missing important information in the handover record. .

[0014] 2. According to the degree of reference of the candidate handover record to the handover information of the target patient, the necessary degree of the candidate feature items existing in the candidate handover record is obtained. According to the historical handover records and historical handover evaluation results, the important information required for the handover of the target patient is personalized and accurately identified, which improves the adaptability of the handover information to the target patient and further reduces the risk of missing important information during nurse handover.

[0015] 3. The degree of necessity obtained from statistics of multiple candidate handover records is not only conducive to extracting common necessary handover feature items from high-completeness historical handover records, but also conducive to extracting necessary handover feature items omitted from low-completeness historical handover records based on the comparison results of low-completeness historical handover records and high-completeness historical handover records, thereby improving the matching completeness of standard feature labels and reducing the risk of missing important information.

[0016] 4. The completeness evaluation is obtained based on the number of medical events caused by abnormal handover in the next shift corresponding to the candidate handover record, so as to reduce the inaccurate completeness evaluation of historical handover records caused by human subjectivity.

[0017] 5. Candidate handover records are obtained by screening from historical handover records based on record similarity and feature similarity. On the one hand, the influence of handover records with little correlation with the target patient on the standard feature label is reduced, and the degree of adaptability of the standard feature label to the target patient is improved. On the other hand, the second feedback information can be used to capture the abnormal handover behavior of the target handover personnel and reduce the risk of missing information of the target patient caused by abnormal handover behavior. For example, when uploading the handover record, only a small number of patient feature descriptions are uploaded for integrity verification results to obtain the first feedback information containing feature items that do not meet the preset matching rules, so that the content of the first feedback information is used as a template to improve the handover record, ignoring the personalized characteristics of the target patient.

[0018] 6. The historical handover records are screened in advance by using the exclusion feature. The historical handover records with the exclusion feature will no longer participate in the matching of the standard feature labels of the target patient, so as to reduce the amount of calculation inside the computer.

[0019] 7. Before the preset handover time, all historical handover records are screened according to abnormal physiological characteristics, so as to ensure that the standard feature tags corresponding to the abnormal physiological characteristics can be matched before the preset handover time, while reducing the computational complexity of a single handover record verification task before the preset handover time and increasing the maximum number of concurrent requests of the computer. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0021] Figure 1 A flowchart of an implementation method of a nurse shift handover recording method involved in an embodiment of the present application; Figure 2 A flowchart for obtaining standard feature items involved in the embodiments of the present application; Figure 3 A flowchart of candidate handover record screening involved in an embodiment of the present application; Figure 4 A flowchart of another implementation of a nurse shift handover recording method involved in an embodiment of the present application; Figure 5 This is a structural diagram of a nurse shift handover recording system involved in an embodiment of the present application; Figure 6 This is a schematic diagram of the structure of an electronic device involved in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The present invention provides a method and system for recording nurse shift handover. In order to make the above-mentioned purposes, features and advantages of the present application more obvious and understandable, the technical scheme in the embodiment of the present application will be clearly and completely described in combination with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, not all embodiments. The components of the embodiment of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, with reference to the terms "one embodiment", "some embodiments", "implementation method", "embodiment", "illustrative embodiment", "example", "specific example" or "some examples", the following detailed description of the embodiment of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but only indicates that the specific features, structures or characteristics described in combination with the embodiment or example are included in at least one embodiment or example of the present invention. And the specific features, structures or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0023] It should be noted that similar reference numerals and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further defined and explained in the subsequent figures. At the same time, in the description of this application, the terms "first", "second" and other relational terms are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0024] According to the first aspect of the present invention, the present invention claims a method for recording nurse shift changes, referring to the attached Figure 1 As shown, including: S1: Obtain the original handover record of the target patient by the target handover personnel.

[0025] It should be noted that the target handover personnel include the medical staff who hand over the work status of the current shift, the condition of the target patient and other information to the next shift during the handover process. For example, the nurse of the current shift who is responsible for the target patient and the auxiliary nurse who assists the nurse of the current shift to complete the nursing task. There can be 1 or more target handover personnel. This application does not further limit the number of target handover personnel for the target patient. When there is more than one target handover personnel, the original handover record of each target handover personnel for the target patient is obtained separately.

[0026] It should be noted that the original handover record includes at least one of the target patient's basic information, condition changes, doctor's order execution information and precautions information, and of course it may not be limited to this. The basic information includes at least one of the patient's identity, gender, age and admission time, and of course it may not be limited to this. The identity includes an identifier for identifying the patient's unique identity information to verify the patient's information, such as the patient number, hospitalization number and bed number. The condition change includes at least one of vital signs and symptoms. Vital signs include heart rate, blood pressure, body temperature, blood oxygen saturation, etc. Symptoms include pain, bleeding, swelling, consciousness, drowsiness, coma, etc. The doctor's order execution information includes at least one of the completed doctor's order information, the doctor's order information to be executed by the next shift, and the doctor's order change information, and of course it may not be limited to this. The doctor's order information includes at least one of the main diagnosis, disease overview, treatment project information and nursing operation information. For example, the name of the medication, dosage and administration time, the operation method of sputum suction, the equipment used and the operation time, etc. The precautions information includes at least one of the special needs of the patient and family members, unexpected situations during treatment, and special medical instructions.

[0027] S2: Obtain standard feature labels based on the current physiological characteristics of the target patient. The standard feature labels include handover feature items of the patient type corresponding to the target patient, and the handover feature items include structural information feature items and non-structural information feature items, but they may not be limited thereto. The structural information feature items include feature items with clearly predefined data models and formats that can be obtained directly by querying electronic systems such as medical information management systems, such as biochemical test results, vital signs, etc. The non-structural information feature items include feature items that cannot be obtained directly by querying electronic systems such as medical information management systems and are not predefined, such as the patient's subjective feelings.

[0028] It should be noted that physiological characteristics include all treatment information stored in electronic systems such as the medical institution's information management system and / or electronic medical record system, such as basic information, vital signs, examination results, test results, etc.

[0029] It should be noted that the handover feature items of the patient type are obtained according to the handover specifications of the corresponding medical institution. The specific patient type and the corresponding handover feature items can be stored in the type feature database in a preset manner; when in use, the target patient is classified according to the current physiological characteristics of the target patient, and the type feature database is queried according to the corresponding patient type to obtain the corresponding standard feature label. It is also possible to set a preset standard feature label for the physiological characteristics of the historical patients visiting the medical institution, train a neural network model according to the physiological characteristics of the corresponding historical patients and the preset standard feature labels, optimize the neural network model according to the difference between the predicted standard feature label output by the neural network model and the preset standard feature label, and when in use, input the current physiological characteristics of the target patient into the trained neural network model to obtain the standard feature label.

[0030] S3: Obtaining the record completion degree according to the matching results of all the standard feature tags and the original handover record.

[0031] It should be noted that the matching result can be a classification result, such as a binary classification result (such as a successful match or a failed match), a multi-classification result (such as a high match, a medium match, and a low match), etc., or a regression result, such as a correlation, etc.

[0032] In this embodiment, step S3 also includes the following sub-steps: S31, respectively matching each of the standard feature tags with the original handover record. S32, filtering out the standard feature tags that meet the preset matching rules from all the standard feature tags; S33, calculating the proportion of the standard feature tags that meet the preset matching rules in all the standard feature tags to obtain the record completion degree.

[0033] In this embodiment, "whether the match is successful" is used as the matching result, and "the matching result is a standard feature tag with a successful match" is used as a preset matching rule as an example for detailed description. Step S31 can choose to retrieve each of the standard feature tags and corresponding synonyms in the original handover record. If the retrieval is successful, the matching result corresponding to the corresponding standard feature tag is set to a successful match. If the retrieval is unsuccessful, the matching result corresponding to the corresponding standard feature tag is set to a failed match. It is also possible to extract the keywords of the original handover record; convert all keywords into corresponding word vectors; convert all the standard feature tags into corresponding word vectors; respectively calculate the cosine similarity between the word vector of each keyword and the word vector of each standard feature tag; if there is a cosine similarity greater than the similarity threshold among all the cosine similarities corresponding to each standard feature tag, the matching result corresponding to the corresponding standard feature tag is set to a successful match. If all the cosine similarities corresponding to each standard feature tag are not greater than the similarity threshold, the matching result corresponding to the corresponding standard feature tag is set to a failed match. It is also possible to choose to pre-train the machine learning model, train the machine learning model by supervised learning, and obtain the matching result between the original handover record and each of the standard feature tags in the machine learning model.

[0034] S4: Compare the completeness of the record with the completeness threshold. If the record completion is greater than the completion threshold, generate a target handover record based on the original handover record, and send the target handover record to the target successor. If the record completion is not greater than the completion threshold, generate a first feedback message, and return to step S1 to execute until the record completion of the corresponding original handover record is greater than the completion threshold, and obtain the target handover record based on all the original handover records.

[0035] It should be noted that the completion threshold can be obtained by presetting.

[0036] It should be noted that the original handover record may be directly used as the first handover record, or the original handover record may be preprocessed to obtain the first handover record, where the preprocessing includes, for example, deduplication of contents of multiple original handover records.

[0037] It should be noted that the target successor includes the medical staff who takes over the nursing work for the target patient from the previous shift. For example, the next shift nurse responsible for the target patient and the auxiliary nurse who assists the next shift nurse to complete the nursing task. There can be one target successor or more than one. This application does not further limit the number of target successors for the target patient. When there is more than one target successor, the first handover record is sent to each of the target successors respectively.

[0038] In this embodiment, the first feedback information is used to remind the corresponding target handover personnel to supplement the original handover record. The first feedback information includes the standard feature tags that do not meet the preset matching rules. If the number of the target handover personnel is more than one, the first feedback information can be sent to each target handover personnel at the same time; the first feedback information can also be sent to a designated target handover personnel, such as a responsible nurse, etc.; the corresponding nursing executor can also be matched according to the standard feature tags that do not meet the preset matching rules, and the first feedback information can be sent to the nursing executor.

[0039] It should be noted that the original handover record obtained in advance is an original detailed description of the individual characteristics of the target patient based on the professional knowledge and clinical experience of the target handover personnel. The corresponding handover feature items are matched according to the current physiological characteristics of the target patient, and the handover feature items are matched with the original handover records provided by the target handover personnel. The record completion of the original handover record is calculated according to the matching results. If the record completion is not greater than the completion threshold, the current original handover record is regarded as having important information missing, and the target handover personnel are reminded to supplement it until the record completion is greater than the completion threshold. This not only realizes the integrity verification of the original handover record provided by the target handover personnel, reduces the risk of missing important information in the handover record, but also retains the individualized feature description based on professional knowledge and clinical experience, reduces the phenomenon of special characteristics of the target patient being ignored, and further reduces the risk of missing important information in the handover record.

[0040] In a possible implementation, refer to the attached Figure 2 As shown, step S2 also includes the following sub-steps: S21: Obtain candidate handover records and corresponding completeness evaluations based on historical handover records.

[0041] It should be noted that the candidate handover records are screened out from the historical handover records. The screening strategy may be no screening, or screening based on the similarity between the physiological characteristics of the patient corresponding to the historical handover records and the current physiological characteristics of the target patient, or other feasible implementation methods. The candidate handover records are denoted as R, R = {r1, r2, ..., r j ,…,r m}. Among them, r j represents the jth candidate handover record, and m represents the number of all candidate handover records.

[0042] It should be noted that the completeness evaluation can be obtained based on the evaluation results of the next shift nursing staff corresponding to the candidate handover record, or based on the evaluation results of the head nurse, etc., or in other feasible ways. The completeness can be a scoring result, such as a 10-point scoring result or a 100-point scoring result, or a grading result, such as a three-category grading result of a high completeness evaluation, a medium completeness evaluation, and a low completeness evaluation.

[0043] S22: Obtain the feature similarity between the patient physiological feature corresponding to each candidate handover record and the current physiological feature of the target patient.

[0044] It should be noted that the feature vectors of the current physiological characteristics of the target patient and the physiological characteristics of all the historical patients corresponding to the candidate handover records can be extracted respectively through the first neural network model. The cosine similarity between the feature vector of the current physiological characteristics of the target patient and the feature vector of the physiological characteristics of each historical patient corresponding to the candidate handover record is calculated respectively to obtain the feature similarity between the physiological characteristics of the historical patient corresponding to the candidate handover record and the current physiological characteristics of the target patient.

[0045] S23: Obtain candidate feature items according to all the candidate handover records.

[0046] It should be noted that the candidate feature items can be obtained by integrating all feature items in the candidate handover records. The candidate feature items are denoted as C, where C={c1, c2, ..., c i , …, c n}. Among them, c i represents the i-th candidate feature item, and n represents the number of all candidate feature items.

[0047] S24: Evaluate the necessity components of the candidate feature items in the corresponding candidate handover records according to the feature similarity and the completeness of each candidate handover record, and calculate the corresponding necessity degree according to all the necessity degree components of each candidate feature item.

[0048] It should be noted that the feature similarity and the completeness evaluation of each candidate handover record may be linearly weighted by setting a weight coefficient to obtain the necessity components of all the candidate feature items in the candidate handover record.

[0049] It should be noted that each necessity component corresponding to a candidate feature item may be linearly weighted by setting a weight coefficient to obtain the degree of necessity corresponding to the candidate feature item.

[0050] S25: taking the candidate feature item whose necessity degree is greater than the necessary threshold as the standard feature item. The specific value of the necessary threshold can be preset.

[0051] It should be noted that, for candidate handover records with the same completeness evaluation, the candidate handover record with a greater feature similarity has a greater reference to the handover information corresponding to the target patient, and the candidate handover record with a smaller feature similarity has a smaller reference to the handover information corresponding to the target patient. For candidate handover records with the same feature similarity, the candidate handover record with a greater completeness evaluation has a greater reference to the handover information corresponding to the target patient, and the candidate handover record with a smaller completeness evaluation has a smaller reference to the handover information corresponding to the target patient. The necessary degree of the candidate feature items existing in the candidate handover record is obtained based on the degree of reference of the candidate handover record to the handover information of the target patient, and the important information required for the handover of the target patient is personalized and accurately identified based on the historical handover records and historical handover evaluation results, thereby improving the adaptability of the handover information to the target patient and further reducing the risk of missing important information in the nurse handover.

[0052] In a feasible implementation, the completeness evaluation includes high completeness and low completeness. i Necessary degree of correspondence N i The calculation methods include: ; ; Wherein, m represents the number of candidate handover records, N i，j Indicates the i-th candidate feature item in the candidate handover record r j The necessity component of Sj represents the candidate handover record r j The feature similarity, E j Represents the candidate handover record r j The completeness evaluation of .

[0053] It should be noted that I represents an indicator function. When the "condition" is met, the value of I (condition) is 1, and when the "condition" is not met, the value of I (condition) is 0.

[0054] It should be noted that the candidate handover record shown in Table 1 below is used as an example for detailed description. When the candidate feature item belongs to the candidate handover record, the corresponding cell value is 1, otherwise the value is 0. For example, the corresponding values ​​of c7 and r2 in Table 1 are 1, indicating that the candidate feature item c7 belongs to the patient feature recorded in the candidate handover record r2, while the corresponding values ​​of c7 and r1 are 0, indicating that the candidate feature item c7 does not belong to the patient feature recorded in the candidate handover record r1.

[0055] Table 1 Statistics of candidate handover records

[0056] It should be noted that the necessity component N of the candidate feature item c7 in the candidate handover record r1 7，1 = 1*0.9=0.9, the necessity component N of the candidate feature item c7 in the candidate handover record r2 7，2 = 1*0.8=0.8, the necessity component N of candidate feature item c7 in candidate handover record r3 7，3 = 0*0.7=0. Thus, the value of the necessary degree N7 corresponding to the candidate feature item c7 is calculated to be 0.9+0.8+0=1.7. Similarly, the corresponding necessary degrees of c1-c7 can be calculated as shown in Table 2: Table 2 Example table of the necessary degree of candidate feature items

[0057] It should be noted that when the completeness evaluation of the candidate handover record is high completeness, it means that when evaluating the completeness of the candidate handover record, the effect of the feature items existing in the candidate handover record on the high completeness evaluation is greater than the effect of the feature items not existing in improving the completeness evaluation, that is, the degree of necessity of handover of the feature items existing in the candidate handover record with high completeness is greater than the degree of necessity of handover of the feature items not existing. When the completeness evaluation of the candidate handover record is low completeness, it means that when evaluating the completeness of the candidate handover record, the effect of the feature items not existing in the candidate handover record on improving the completeness evaluation is greater than the effect of the feature items existing in the candidate handover record on improving the completeness evaluation, that is, the candidate handover record with low completeness has feature items with a high degree of necessity of handover. The degree of necessity obtained from statistics of multiple candidate handover records is not only conducive to extracting common necessary handover feature items from high-completeness historical handover records, but also conducive to extracting necessary handover feature items omitted from low-completeness historical handover records based on the comparison results of low-completeness historical handover records and high-completeness historical handover records, such as candidate feature item c5 in Table 2, thereby improving the matching completeness of standard feature labels and reducing the risk of missing important information.

[0058] In a feasible implementation, the completeness evaluation is obtained based on the comparison result of the number of medical events caused by abnormal handover in the next shift corresponding to the candidate handover record and the threshold of the number of accidents. When the number of medical events that occurred to the historical patient due to abnormal handover in the next shift is greater than the threshold of the number of accidents, the completeness evaluation corresponding to the candidate handover record is the high completeness; when the number of medical events that occurred to the historical patient due to abnormal handover in the next shift is not greater than the threshold of the number of accidents, the completeness evaluation corresponding to the candidate handover record is the low completeness, so as to reduce the adverse effects of human subjective factors on the completeness evaluation of historical handover records.

[0059] It should be noted that the evaluation criteria for abnormal handover are pre-set according to the specifications of the medical institution. The specific value of the accident number threshold can be obtained by pre-setting.

[0060] In a possible implementation, refer to the attached Figure 3 As shown, step S21 also includes the following sub-steps: S210, obtaining rejection characteristics according to the current physiological characteristics of the target patient, obtaining all historical handover records, and filtering out historical handover records having the rejection characteristics from all the historical handover records.

[0061] It should be noted that the exclusion feature includes features that are inconsistent with the current physiological features of the target patient. For example, if the target patient is female, the corresponding exclusion feature includes features that are male. The historical handover records are screened in advance using the exclusion feature, and the historical handover records with the exclusion feature no longer participate in the matching of the standard feature tags of the target patient, so as to reduce the amount of calculation inside the computer.

[0062] S211, querying historical handover records according to the original handover record to obtain a reference handover record; the record similarity between the reference handover record and the original handover record is not less than a first similarity threshold. The specific value of the first similarity threshold can be obtained by presetting.

[0063] It should be noted that the feature vectors of the original handover record and all the historical handover records can be extracted respectively through the second neural network model. The cosine similarity between the feature vector of the original handover record and the feature vector of each of the historical handover records is calculated respectively to obtain the corresponding record similarity. The reference handover record is obtained based on the comparison result of all the record similarities with the first similarity threshold; the historical handover record whose record similarity is greater than the first similarity threshold is used as the reference handover record.

[0064] In this embodiment, if there is no historical handover record whose record similarity is greater than the first similarity threshold, a second feedback information is generated, and the second feedback information is used to remind the target handover personnel that the handover behavior is abnormal, and return to step 1; if the number of reference handover records is greater than 0, continue to execute step S212.

[0065] S212, obtaining reference physiological characteristics of historical patients corresponding to each reference handover record; calculating the feature similarity between the target patient and each reference physiological characteristic, and taking the reference handover record corresponding to the feature similarity greater than the second similarity threshold as the candidate handover record. The specific value of the second similarity threshold can be obtained by presetting.

[0066] It should be noted that the second neural network model can be used to extract the feature vectors of the current physiological characteristics of the target patient and the physiological characteristics of all historical patients corresponding to the reference handover records. The cosine similarity between the feature vector of the current physiological characteristics of the target patient and the feature vector of the physiological characteristics of each historical patient corresponding to the reference handover record is calculated to obtain the corresponding feature similarity. The candidate handover record is obtained based on the comparison result of all the feature similarities with the second similarity threshold; the reference handover record corresponding to the feature similarity greater than the second similarity threshold is used as the candidate handover record.

[0067] In this embodiment, if there is no reference handover record whose feature similarity is greater than the second similarity threshold, the second feedback information is generated and the process returns to step S1 for execution.

[0068] It should be noted that the candidate handover record is obtained by screening from the historical handover records according to the record similarity and the feature similarity. On the one hand, it reduces the impact of handover records with too little correlation with the target patient on the screening of standard feature labels, and improves the degree of adaptation of standard feature labels to the target patient. On the other hand, the second feedback information can be used to capture the abnormal handover record behavior of the target handover personnel, and reduce the risk of missing information of the target patient due to abnormal handover behavior. For example, when uploading the handover record, only upload too few patient feature descriptions for integrity verification results to obtain the first feedback information containing feature items that do not meet the preset matching rules, so as to use the first feedback information as a template to improve the handover record and ignore the personalized characteristics of the target patient.

[0069] In a possible implementation, refer to the attached Figure 4 As shown, step S21 also includes the following sub-steps: S210: Screening out abnormal physiological features from the current physiological features of the target patient. Matching the historical handover records with the abnormal physiological features to obtain abnormal handover records. The value of the physiological feature corresponding to the abnormal handover record on the abnormal physiological feature does not belong to the normal value range.

[0070] Before the preset handover time, the historical handover record is updated according to the abnormal handover record; from step S211, the updated historical handover record is queried according to the original handover record and the execution continues until the first target handover record is obtained. The record completion degree corresponding to the first target handover record is greater than the completion degree threshold.

[0071] After the preset handover time, obtain the target successor's supplementary record for the first target handover record, obtain the second target handover record based on the first target handover record and the target successor's supplementary record, use the second target handover record as the updated original handover record, and continue from step S211 to query all the historical handover records based on the updated original handover record until the target handover record is obtained.

[0072] It should be noted that at the same preset handover time, there will be multiple pairs of nurses handing over at the same time. At the same time, in order to ensure the continuity of patient care, the patient conditions in the handover record should be as close as possible to the patient conditions observed by the nurse taking over. Therefore, the time for nurses with the same preset handover time to upload and verify the integrity of the handover records is concentrated. Inevitably, the computer needs to verify the handover records of all target patients at the same time. Before the preset handover time, all historical handover records are preferentially screened according to abnormal physiological characteristics, so as to ensure that the standard feature labels corresponding to the abnormal physiological characteristics can be matched before the preset handover time, while reducing the amount of calculation for a single handover record verification task before the preset handover time, and increasing the maximum number of concurrent requests of the computer.

[0073] According to a second aspect of the present invention, the present invention claims protection for a nurse shift record system, referring to the attached Figure 5 As shown, including: A record acquisition module, the record acquisition module is used to obtain the original handover record of the target patient by the target handover personnel; A standard matching module, the standard matching module is used to obtain a standard feature label according to the current physiological feature matching of the target patient; wherein the standard feature label includes a structural information feature item and a non-structural information feature item of the patient type corresponding to the target patient; A completion degree calculation module, the completion degree calculation module is used to obtain the record completion degree according to the matching results of all the standard feature tags and the original handover record; A record processing module, the record processing module is used to compare the record completion degree and the completion degree threshold. If the record completion degree is not greater than the completion degree threshold, a first feedback message is generated and returned to the record acquisition module until the record completion degree is greater than the completion degree threshold, and a target handover record is obtained based on all the original handover records; the first feedback information is used to remind the corresponding target handover personnel to supplement the original handover record.

[0074] In a feasible implementation manner, the standard matching module further includes: A candidate record acquisition submodule, the candidate record acquisition submodule is used to obtain candidate handover records and corresponding completeness evaluations based on historical handover records; A feature similarity acquisition submodule, the feature similarity acquisition submodule is used to acquire the feature similarity between the patient physiological feature corresponding to each candidate handover record and the current physiological feature of the target patient; A feature necessity calculation submodule, the feature necessity calculation submodule is used to obtain candidate feature items based on all the candidate handover records; obtain the necessity components of the candidate feature items existing in the corresponding candidate handover records based on the feature similarity and the completeness evaluation of each candidate handover record; calculate the corresponding necessity degree based on all the necessity degree components of each candidate feature item; A feature screening submodule is used to use the candidate feature items whose necessity degree is greater than a necessity degree threshold as the standard feature items.

[0075] In a feasible implementation manner, the completeness evaluation includes high completeness and low completeness, and the necessity component of the candidate feature item also includes: ; Among them, N i，j Represents the candidate feature item c i In the candidate handover record j The necessity component, I represents the indicator function, S j Represents the candidate handover record r j The feature similarity, E j Represents the candidate handover record r j The completeness evaluation of .

[0076] In a feasible implementation, the completeness evaluation is obtained based on a comparison result between the number of medical events caused by abnormal handover in the next shift corresponding to the candidate handover record and a threshold number of accidents.

[0077] In a feasible implementation manner, the candidate record acquisition submodule further includes: a record similarity screening submodule, wherein the record similarity screening submodule is used to query the historical handover record according to the original handover record to obtain a reference handover record; the record similarity between the reference handover record and the original handover record is not less than a first similarity threshold; A first information feedback submodule, the first information feedback submodule is used to determine whether the number of the reference handover records is 0, if the number of the reference handover records is equal to 0, generate second feedback information, the second feedback information is used to remind the target handover personnel that the handover behavior is abnormal; if the number of the reference handover records is greater than 0, send all the reference handover records to the feature similarity screening submodule; The feature similarity screening module is used to screen candidate handover records from all the reference handover records, wherein the similarity between the patient physiological feature corresponding to the candidate handover record and the current physiological feature of the target patient is not less than a second similarity threshold; The second information feedback submodule is used to determine whether the number of the candidate handover records is 0, and if the number of the candidate handover records is equal to 0, generate the second feedback information.

[0078] In a feasible embodiment, the candidate record acquisition submodule also includes a rejection screening submodule, which is used to obtain rejection characteristics based on the current physiological characteristics of the target patient; and screen out historical handover records with the rejection characteristics from all the historical handover records.

[0079] In a feasible implementation, the candidate record acquisition submodule further includes an abnormal feature screening submodule, the abnormal feature screening submodule is used to screen out abnormal physiological features from the current physiological features of the target patient, and match the historical handover record according to the abnormal physiological features to obtain an abnormal handover record; Before the preset handover time, the abnormal feature screening submodule sends the abnormal handover record as the historical handover record to the record similarity screening submodule, and the record similarity screening submodule continues to query the updated historical handover record according to the original handover record until the first target handover record is obtained, and the first target handover record is sent to the target successor; After the preset handover time, the record processing module is also used to obtain a second target handover record based on the first target handover record and the supplementary record of the target successor. The record processing module sends the second target handover record to the record similarity screening submodule, and the record similarity screening submodule continues to query all the historical handover records based on the updated original handover record to obtain the second target handover record.

[0080] See attached Figure 6 As shown, an embodiment of the present application provides an electronic device, including: a processor and a memory, the processor and the memory are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanisms (not shown), the memory stores a computer program executable by the processor, and when the computing device is running, the processor executes the computer program to execute the system in any optional implementation of the above embodiments.

[0081] The embodiment of the present application provides a storage medium, and when the computer program is executed by the processor, the system in any optional implementation of the above embodiment is executed. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, disk or optical disk.

[0082] In the embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways. The system embodiments described above are merely schematic. For example, the division of the modules is only a logical function division, and can be implemented in another way. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some communication interface, system or unit, which can be electrical, mechanical or other forms.

[0083] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0085] Flowcharts are used herein to illustrate the steps of the method of the embodiments of the present disclosure. It should be understood that the preceding or following steps are not necessarily performed precisely in order. On the contrary, various steps may be evaluated in reverse order or simultaneously. At the same time, other operations may also be added to these processes.

[0086] Unless otherwise defined, all terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present disclosure belongs. It should also be understood that terms such as those defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or highly formal sense, unless explicitly defined as such herein.

[0087] The above is a detailed introduction to a nurse shift handover recording method and system. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only an embodiment of this application, which is only used to help understand a nurse shift handover recording method and system of this application, and is not used to limit the scope of protection of this application. At the same time, for those skilled in the art, this application can have various changes and variations. Any modifications and equivalent substitutions made within the spirit and principles of this application should be included in the scope of protection of this application.

Claims

1. A method for recording nurse shift handover, characterized in that: include: Obtain the original handover record of the target patient by the target handover personnel; Obtain standard feature labels based on the current physiological features of the target patient; The standard feature label includes structural information feature items and non-structural information feature items corresponding to the patient type of the target patient; Obtaining the record completion degree according to the matching results of all the standard feature tags and the original handover record; If the record completion degree is not greater than the completion degree threshold, a first feedback message is generated, and the process returns to the step of obtaining the original handover record of the target patient by the target handover personnel until the record completion degree is greater than the completion degree threshold, and the target handover record is obtained based on all the original handover records; the first feedback message is used to remind the corresponding target handover personnel to supplement the original handover record.

2. A nurse shift handover recording method according to claim 1, characterized in that: The step of obtaining a standard feature label according to the current physiological feature matching of the target patient also includes: Obtain candidate handover records and corresponding completeness evaluations based on historical handover records; Obtaining the feature similarity between the patient physiological feature corresponding to each of the candidate handover records and the current physiological feature of the target patient; Obtaining candidate feature items according to all the candidate handover records; Obtaining the necessity component of the candidate feature item existing in the corresponding candidate handover record according to the feature similarity and the completeness evaluation of each candidate handover record; Calculating the corresponding necessity degree according to all the necessity degree components of each of the candidate feature items; The candidate feature item whose necessity degree is greater than a necessity degree threshold is used as the standard feature item.

3. A nurse shift handover recording method according to claim 2, characterized in that: The completeness evaluation includes high completeness and low completeness, and the necessity component of the candidate feature item also includes: ； Among them, N i，j Represents the candidate feature item c i In the candidate handover record j The necessity component, I represents the indicator function, S j Represents the candidate handover record r j The feature similarity, E j Represents the candidate handover record r j The completeness evaluation of .

4. A nurse shift handover recording method according to claim 2, characterized in that: The completeness evaluation is obtained based on a comparison result between the number of medical events caused by abnormal handover in the next shift corresponding to the candidate handover record and a threshold value of the number of accidents.

5. A nurse shift handover recording method according to any one of claims 2 to 4, characterized in that: The step of obtaining candidate handover records according to historical handover records also includes: querying historical handover records according to the original handover record to obtain a reference handover record; the record similarity between the reference handover record and the original handover record is not less than a first similarity threshold; If the number of the reference handover records is equal to 0, second feedback information is generated, and the second feedback information is used to remind the target handover personnel that the handover behavior is abnormal; If the number of the reference handover records is greater than 0, a candidate handover record is selected from all the reference handover records, and the similarity between the patient physiological characteristics corresponding to the candidate handover record and the current physiological characteristics of the target patient is not less than a second similarity threshold; If the number of the candidate handover records is equal to 0, the second feedback information is generated.

6. A nurse shift handover recording method according to claim 5, characterized in that: Before the step of querying the historical handover record according to the original handover record, the method further includes: obtaining a rejection feature according to a current physiological feature of the target patient; The historical handover records having the exclusion feature are screened out from all the historical handover records.

7. A nurse shift handover recording method according to claim 5, characterized in that: Before the step of querying the historical handover record according to the original handover record, the method further includes: Screening out abnormal physiological characteristics from the current physiological characteristics of the target patient; Matching the historical handover record according to the abnormal physiological feature to obtain an abnormal handover record; Before the preset handover time, the historical handover record is updated according to the abnormal handover record, and the step of querying the updated historical handover record according to the original handover record is continued until a first target handover record is obtained, and the first target handover record is sent to a target successor; After the preset handover time, a second target handover record is obtained based on the first target handover record and the supplementary record of the target successor, the original handover record is updated based on the second target handover record, and all the historical handover records are continued to be queried based on the updated original handover record to obtain the second target handover record.

8. A nurse shift record system, characterized in that: include: A record acquisition module, the record acquisition module is used to obtain the original handover record of the target patient by the target handover personnel; A standard matching module, the standard matching module is used to obtain a standard feature label according to the current physiological feature matching of the target patient; wherein the standard feature label includes a structural information feature item and a non-structural information feature item of the patient type corresponding to the target patient; A completion degree calculation module, the completion degree calculation module is used to obtain the record completion degree according to the matching results of all the standard feature tags and the original handover record; A record processing module, the record processing module is used to compare the record completion degree and the completion degree threshold. If the record completion degree is not greater than the completion degree threshold, a first feedback message is generated and returned to the record acquisition module until the record completion degree is greater than the completion degree threshold, and a target handover record is obtained based on all the original handover records; the first feedback information is used to remind the corresponding target handover personnel to supplement the original handover record.

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