Management system and method for clinical nursing staff

Abstract

The present invention relates to the field of data processing technology, and in particular to a management system and method for clinical nursing staff. The system includes an acquisition module, a determination module, and a classification module. The acquisition module can obtain the various skills, professional background, and nursing scheduling of each clinical nursing staff, so that the deployment of clinical nursing staff is targeted; the determination module can accurately coordinate and quantify the actual needs of nursing staff and the symptoms of patients, so as to accurately match the preferred nursing staff for patients; the classification module can ensure the reasonable allocation of nursing staff, thereby completing the deployment management of clinical nursing staff. The system takes into account the skill requirements of hospitals and patients for clinical nursing staff, ensures the accuracy of the subsequent division of nursing staff work, and thus achieves accurate personnel management.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a management system and method for clinical nursing staff. Background Art

[0002] Clinical nurses play a vital role in medical services. The management of clinical nurses is to arrange appropriate clinical nurses for patients based on their professional level and skill requirements as well as the patients' personal information, medical history, treatment plan, etc., to ensure that patients receive accurate nursing services. Accurate classification of clinical nurses helps ensure that patients receive appropriate care.

[0003] However, each clinical nurse may have multiple skills and professional backgrounds. Currently, clinical nurses are classified only by their length of service, skill type, and skill level, without considering the different skill requirements of clinical nurses in different hospitals and the different needs of clinical nurses for different patients. This makes the classification process inflexible and incomplete, and may not effectively support the detailed classification and management of clinical nurses. Therefore, it is urgent to develop a management system for clinical nurses to solve the above problems. Summary of the invention

[0004] In order to solve the technical problem that clinical nursing staff are not properly matched with the needs of hospitals and patients, and clinical nursing staff cannot be effectively classified and managed in detail, the purpose of the present invention is to provide a management system and method for clinical nursing staff. The technical solution adopted is as follows:

[0005] In a first aspect, the present invention provides a management system for clinical nursing staff, the system comprising:

[0006] An acquisition module, used to obtain the certificate feature vectors and scheduling data of clinical nursing staff;

[0007] A determination module, for determining a comprehensive feature vector of a clinical nurse based on the certificate feature vector and the scheduling data, wherein the comprehensive feature vector includes job title, length of service, actual comprehensive feature value and relative level of certificate, wherein the actual comprehensive feature value is the product of the skill specialization and demand of the clinical nurse;

[0008] The classification module is used to classify and label clinical nursing staff based on the comprehensive feature vector, and the labels include nursing type and nursing ability level.

[0009] In some embodiments, the acquisition module includes:

[0010] The first acquisition unit is used to acquire the certificate data of different nursing types held by clinical nursing staff at the current moment;

[0011] The first determining unit is used to determine the certificate feature vector based on the certificate data, wherein the certificate data includes the certificate type, the relative level of the certificate and the duration of holding the certificate, and the certificate feature vector is expressed as ,in, , and They represent the relative levels of the certificates of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of the i-th clinical nurse, respectively, and i represents the serial number of the clinical nurse;

[0012] The second acquisition unit is used to acquire the scheduling data of clinical nursing staff in nursing work within three months before the current moment.

[0013] In some embodiments, the determining module includes:

[0014] The second determination unit is used to determine the degree of desirability of obtaining each certificate among all certificates held by the clinical staff;

[0015] A third determination unit is used to determine the actual demand for each certificate based on the demand for each certificate and the scheduling data;

[0016] A fourth determining unit, configured to determine the degree of demand for clinical nursing personnel based on the measured degree of demand and the actual degree of demand;

[0017] The fifth determination unit is used to determine the skill specialization of clinical nursing staff;

[0018] A sixth determining unit, used to determine an actual comprehensive characteristic value;

[0019] The construction unit is used to construct the comprehensive feature vector of clinical nurses. The comprehensive feature vector of the i-th clinical nurse is expressed as ,in, , and They represent the professional title, length of service and actual comprehensive characteristic value of the i-th clinical nurse respectively, , and They respectively represent the relative levels of the cardiac nursing certification, emergency nursing certification and operating room nursing certification of the i-th clinical nurse, and i represents the serial number of the clinical nurse.

[0020] In some embodiments, the desirability of obtaining each certificate among all certificates held by the clinical staff is determined according to the following formula:

[0021]

[0022] In the formula, Indicates The requirements for obtaining the certificates, represents the number of clinical nursing staff, Indicates holding The number of clinical nurses with the certificate Indicates holding All clinical nursing staff The mean of the relative grades of the certificates of the types of certificates, Indicates holding All clinical nursing staff The average length of time for holding the various certificates, Indicates the serial number of the certificate.

[0023] In some embodiments, the actual need for each certificate is determined based on the need for each certificate and the scheduling data according to the following formula:

[0024]

[0025] In the formula, Indicates The actual need for the certificate, Indicates The requirements for obtaining the certificates, Indicates holding The sum of the number of shifts for all clinical nursing staff with the same certificate, represents the sum of the number of shifts for all clinical nursing staff, Indicates the serial number of the certificate.

[0026] In some embodiments, the required degree of the clinical nursing staff is determined based on the measured required degree and the actual required degree according to the following formula:

[0027]

[0028] In the formula, Indicates The demand for clinical nursing staff, Indicates Clinical nurses The actual need for the certificate, Indicates Number of certifications held by clinical nurses, represents the sum of the number of shifts for all clinical nursing staff, Indicates The number of shifts per clinical nurse, Indicates the serial number of the clinical nurse.

[0029] In some embodiments, the skill level of the clinical nursing staff is determined according to the following formula:

[0030]

[0031] In the formula, Indicates The skill level of clinical nursing staff, Indicates The number of times the target symptom appears in all the symptom of all patients in all the nursing shifts of the clinical nurses, Indicates The number of illnesses of all patients corresponding to all shifts of clinical nurses in nursing work, Indicates The information entropy of all patients' symptoms corresponding to all shifts of clinical nurses in nursing work, , as well as Respectively represent The similarity between the set corresponding to the first symptom and the set corresponding to the second symptom, the similarity between the set corresponding to the first symptom and the set corresponding to the third symptom, and the similarity between the set corresponding to the second symptom and the set corresponding to the third symptom for each clinical nurse. represents an exponential function with a natural constant as base, Represents the serial number of the clinical nurse, wherein the target disease is the disease with the top three occurrences among all the diseases of all patients corresponding to all the nursing shifts of each clinical nurse, and the target disease includes the first disease, the second disease and the third disease. Among all the patients corresponding to all the nursing shifts of all clinical nurses, the set consisting of all patients suffering from the first disease is taken as the set corresponding to the first disease, the set consisting of all patients suffering from the second disease is taken as the set corresponding to the second disease, and the set consisting of all patients suffering from the third disease is taken as the set corresponding to the third disease.

[0032] In some embodiments, The similarity between the set corresponding to the first disease and the set corresponding to the second disease, the similarity between the set corresponding to the first disease and the set corresponding to the third disease, and the similarity between the set corresponding to the second disease and the set corresponding to the third disease corresponding to the clinical nursing staff are calculated by using the Jaccard similarity algorithm.

[0033] In some embodiments, the classification module includes:

[0034] The clustering unit is used to cluster the comprehensive feature vector by using a fuzzy C-means clustering algorithm to obtain a plurality of clusters, and to assign a label to each cluster.

[0035] In a second aspect, the present invention provides a management method for clinical nursing staff, the method comprising:

[0036] Obtain the certification feature vectors and scheduling data of clinical nursing staff;

[0037] Based on the certificate feature vector and the scheduling data, a comprehensive feature vector of the clinical nursing staff is determined, wherein the comprehensive feature vector includes the job title, length of service, actual comprehensive feature value and relative level of the certificate, wherein the actual comprehensive feature value is the product of the skill specialization and the demand degree of the clinical nursing staff;

[0038] Based on the comprehensive feature vector, clinical nursing staff are classified and labeled, and the labels include nursing type and nursing ability level.

[0039] The present invention has the following beneficial effects:

[0040] The present invention provides a management system and method for clinical nursing staff, the system includes an acquisition module for acquiring certificate feature vectors and scheduling data of clinical nursing staff, a determination module for determining the comprehensive feature vectors of clinical nursing staff based on the certificate feature vectors and scheduling data, and a classification module for classifying and labeling clinical nursing staff based on the comprehensive feature vectors, wherein the labels include nursing types and nursing ability levels. The acquisition module can obtain the various skills, professional backgrounds and scheduling of nursing work of each clinical nursing staff, so that the deployment of clinical nursing staff is targeted; since the comprehensive feature vector includes professional title, length of service and actual comprehensive feature value and certificate relative level, the actual comprehensive feature value is obtained according to the skill specialization and demand of clinical nursing staff, the demand can reflect the actual demand of clinical nursing staff certificates and the scheduling of nursing staff, and the skill specialization can reflect the specialization of nursing staff in nursing work for a certain disease, so the determination module can accurately coordinate and quantify the actual demand of nursing staff and the disease of patients, so as to accurately match the preferred nursing staff for patients; the classification module can ensure the reasonable allocation of nursing staff, thereby completing the deployment management of clinical nursing staff. The system takes into account the skill requirements of hospitals and patients for clinical nursing staff, ensures the accuracy of subsequent nursing staff work division, and thus achieves precise personnel management. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of the structure of a management system for clinical nursing staff provided by one embodiment of the present invention;

[0043] Figure 2 A method flow chart of a method for managing clinical nursing staff provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0046] In the first aspect, the present invention provides a management system for clinical nursing staff, see Figure 1 The system includes an acquisition module 101, a determination module 102 and a classification module 103.

[0047] The acquisition module 101 is used to acquire the certificate feature vector and scheduling data of clinical nursing staff.

[0048] Since each clinical nurse may have multiple skills and professional backgrounds, if only the length of service, skill type and skill level of the clinical nurses are mastered and used to classify the clinical nurses, without considering the different skill requirements of different hospitals for clinical nurses and the different requirements of different patients for clinical nurses, the subsequent classification process will be inflexible and incomplete. The acquisition module 101 can obtain the multiple skills, professional backgrounds and nursing scheduling of each clinical nurse, so that the deployment of clinical nurses is targeted.

[0049] In some embodiments, the acquisition module 101 includes: a first acquisition unit, which is used to obtain the certificate data of different nursing types held by clinical nursing staff at the current moment; a first determination unit, which is used to determine the certificate feature vector based on the certificate data, the certificate data includes the certificate type, the relative level of the certificate and the length of time of holding the certificate, and the certificate feature vector is expressed as ,in, , and They respectively represent the relative levels of the cardiac nursing certification, emergency nursing certification and operating room nursing certification of the i-th clinical nurse, and i represents the serial number of the clinical nurse; the second acquisition unit is used to obtain the scheduling data of the clinical nurse in nursing work within three months before the current moment.

[0050] In some embodiments, the certification levels of clinical nurses can be divided into four levels from low to high: 1, 2, 3 and 4. When the third clinical nurse holds a cardiology nursing certification and the level of the certificate is 2, the certificate feature vector can be expressed as , the relative level of its certificate The value of is 2 / 4.

[0051] In some embodiments, the certificate data may be certificate information of different nursing types held by each clinical nursing staff at the current moment, collected from a medical staff information database of any hospital.

[0052] Determination module 102 is used to determine the comprehensive feature vector of clinical nursing staff based on the certificate feature vector and scheduling data. The comprehensive feature vector includes professional title, length of service, actual comprehensive feature value and relative level of certificate, wherein the actual comprehensive feature value is the product of the skill expertise and demand of clinical nursing staff.

[0053] Because the hospital may have invested more resources and technology in a specific medical field, that is, it has advanced medical equipment and a medical team with rich experience and professional skills in this specific medical field, thus accumulating a high professional reputation and advantage in this field. For example, when a hospital may have particularly strong professional capabilities and facilities in the treatment of heart disease, the hospital will receive more patients with heart disease, that is, it will need more clinical nurses with certificates in heart disease nursing. The comprehensive feature vector includes professional title, length of service, actual comprehensive feature value and relative level of certificate. The actual comprehensive feature value is obtained based on the skill expertise and demand of clinical nurses. The demand can reflect the actual demand for clinical nurse certificates and the scheduling of nurses. The skill expertise can reflect the expertise of nurses in nursing work for a certain disease. Therefore, the determination module can accurately coordinate and quantify the actual demand for nurses and the disease conditions of patients, so as to accurately match the preferred nurses for patients.

[0054] In some embodiments, the determination module 102 includes:

[0055] The second determination unit is used to determine the degree of demand for obtaining each certificate among all certificates held by clinical personnel, so as to quantify the demand for obtaining nursing certificates in the hospital.

[0056] In some embodiments, the desirability of obtaining each certificate among all certificates held by the clinical staff is determined according to the following formula:

[0057]

[0058] In the formula, Indicates The degree of demand for the certificates reflects the demand for the certificates. The bigger the number, the more the certificate is needed by hospitals and patients. represents the number of clinical nursing staff, Indicates holding The number of clinical nurses with the certificate Indicates holding The ratio of the number of clinical nurses with the certificate to the number of clinical nurses, The larger the number, the more The higher the proportion of clinical nursing staff with this certificate, the more they can provide care for the corresponding patients. Indicates holding All clinical nursing staff The mean of the relative grades of the certificates of the types of certificates, It can reflect the holding of The average level of certification for all clinical nurses with this certification is The larger the number, the more The higher the average level of certification among all clinical nurses, Indicates holding All clinical nursing staff The average length of time for holding the various certificates, Reflects holding All clinical nursing staff The average length of time for holding the various certificates, The larger the number, the more All clinical nursing staff The longer you hold a certificate, the more likely you are to All clinical nursing staff with this certificate may have obtained it earlier and may have more nursing experience in this area. Indicates the serial number of the certificate. , and The product of the proportion of certificates, the overall certificate level and the overall certificate holding time determines the first Requirements for obtaining the certificates That is, the greater the proportion of certificate holders, the higher the overall certificate level, the longer the overall certification time, and the higher the demand for the certificate in the hospital, thereby quantifying the demand for nursing certificates.

[0059] The present invention collects the scheduling data of each clinical nurse in nursing work. When the number of patients with heart disease in a hospital increases within a period of time, clinical nurses with heart disease nursing certification will be scheduled more often for nursing work, while other clinical nurses will be assigned to other work, such as clerical work and record keeping, as well as education and guidance.

[0060] However, in reality, there are cases where people hold corresponding certificates but do other jobs, that is, a high-level certificate holder may be doing education and guidance work, while a low-level certificate holder may be doing nursing work. Therefore, it is necessary to adjust the degree of demand for the examination according to the actual work situation and determine the actual demand for each certificate.

[0061] The third determination unit is used to determine the actual need for each certificate based on the examination demand and scheduling data of each certificate to quantify the actual need for each certificate.

[0062] In some embodiments, the actual need for each certificate is determined based on the need for each certificate and the scheduling data according to the following formula:

[0063]

[0064] In the formula, Indicates The actual need for the certificate reflects the actual need for the certificate. Indicates The requirements for obtaining the certificates, Indicates holding The sum of the number of shifts for all clinical nurses with the same certificate can reflect the actual shift demand of all clinical nurses holding the certificate. The sum of the number of shifts for all clinical nursing staff can reflect the scheduling needs of all clinical nursing staff. Indicates holding The proportion of the sum of the scheduling times of all clinical nursing staff with the certificate to the sum of the scheduling times of all clinical nursing staff can reflect the actual scheduling demand of the certificate in the hospital. Indicates the serial number of the certificate, through For Requirements for obtaining the certificates Make adjustments to determine the actual need for each certificate, The larger the value, the higher the demand for the certificate in practice. The more credible, The bigger.

[0065] The fourth determining unit is used to determine the demand degree of clinical nursing staff based on the measured demand degree and the actual demand degree, so as to quantify the demand situation of each clinical nursing staff in the hospital.

[0066] In some embodiments, the required degree of the clinical nursing staff is determined based on the considered required degree and the actual required degree according to the following formula:

[0067]

[0068] In the formula, Indicates The demand for clinical nurses reflects the demand for clinical nurses in hospitals. Indicates Clinical nurses The actual need for this certificate reflects the Clinical nurses The actual need for the certificate Reflect the The actual need for all the certificates held by clinical nursing staff, Indicates Number of certifications held by clinical nurses, represents the sum of the number of shifts for all clinical nursing staff, Indicates The number of shifts per clinical nurse, Reflect the The proportion of the number of shifts of clinical nurses to the total number of shifts of all clinical nurses, Indicates the serial number of clinical nursing staff, through right Make adjustments to determine the need for clinical nursing staff , thereby quantifying the demand for each clinical nurse in the hospital.

[0069] When there are many patients with a certain disease, resulting in a shortage of clinical nurses with nursing certificates corresponding to the disease, some clinical nurses whose nursing certificates do not match the disease are often selected to perform nursing work. Therefore, the above analysis and deployment of nurses is only based on the number of shifts and certificates held, without considering the matching relationship between the actual disease of the patient and the skills of the clinical nurse.

[0070] The fifth determination unit is used to determine the degree of skill specialization of the clinical nursing staff, so as to quantify the clinical nursing staff's nursing ability for the disease, that is, the specialization of the skills.

[0071] Because individual energy is limited, clinical nurses often have in-depth expertise and experience in specific areas or conditions.

[0072] In some embodiments, the skill level of the clinical nursing staff is determined according to the following formula:

[0073]

[0074] In the formula, Indicates The skill specialization of clinical nurses can quantify their ability to care for diseases, that is, their specialization in skills. Indicates The number of times the target symptom appears in all the symptom of all patients in all the nursing shifts of the clinical nurses, It can reflect the number of times the clinical nurse has treated the target disease among all patients' diseases in all shifts in the nursing work. Indicates The number of illnesses of all patients corresponding to all shifts of clinical nurses in nursing work, Reflects the total number of illnesses of all patients treated by the clinical nurse in nursing work. It can reflect the number of times the clinical nurse treats the target disease among all the patients' diseases in all the shifts in the nursing work. The proportion of the number of symptoms of all patients corresponding to all shifts of clinical nurses in nursing work, The larger the value, the greater the proportion. Indicates The information entropy of all patients' symptoms corresponding to all shifts of clinical nurses in nursing work, The larger the The greater the uncertainty of the symptoms of all patients in all shifts of a clinical nurse, , as well as Respectively represent The similarity between the set corresponding to the first disease and the set corresponding to the second disease, the similarity between the set corresponding to the first disease and the set corresponding to the third disease, and the similarity between the set corresponding to the second disease and the set corresponding to the third disease corresponding to the clinical nurses can respectively measure the similarity of the sets consisting of all patients suffering from the first and second diseases, the first and third diseases, and the second and third diseases. It can reflect the average similarity of the three sets. The larger the value, the higher the overall average level of similarity among the three sets. Represents an exponential function with a natural constant as the base, using the exponential function right Perform negative correlation mapping and normalization processing, The larger the The smaller the uncertainty of the symptoms of all patients corresponding to all shifts of clinical nurses in nursing work, that is, the more appropriate the match between nurses and symptoms, Indicates the serial number of clinical nursing staff, through and right Adjust to get Skill specialization of clinical nursing staff .

[0075] When arranging clinical nurses for patients, the first choice is the clinical nurse who holds a high-level nursing certificate corresponding to the patient's condition. When there is a shortage of staff, clinical nurses with other levels of nursing certificates will be considered. Therefore, the more similar the sets of patients corresponding to the diseases that occur more frequently are, the more specialized the clinical nurses are in the disease.

[0076] It should be noted that the target symptoms are the top three symptoms that occur most frequently among all symptoms of all patients corresponding to all shifts of each clinical nurse in nursing work. The target symptoms include the first symptom, the second symptom and the third symptom. Among all patients corresponding to all shifts of all clinical nurses in nursing work, the set consisting of all patients suffering from the first symptom is taken as the set corresponding to the first symptom, the set consisting of all patients suffering from the second symptom is taken as the set corresponding to the second symptom, and the set consisting of all patients suffering from the third symptom is taken as the set corresponding to the third symptom.

[0077] In some embodiments, The similarity between the set corresponding to the first disease and the set corresponding to the second disease, the similarity between the set corresponding to the first disease and the set corresponding to the third disease, and the similarity between the set corresponding to the second disease and the set corresponding to the third disease for the clinical nursing staff can be calculated by the Jaccard similarity algorithm.

[0078] It should be noted that Jaccard similarity is an indicator used to measure the similarity between two sets, which can be applied to the calculation of similarity between diseases. The value range of Jaccard similarity is between 0 and 1. The closer the value is to 1, the higher the overlap between the two sets, that is, the higher the similarity. The Jaccard similarity algorithm can obtain the similarity of the sets corresponding to any two target diseases.

[0079] A nursing staff is usually responsible for taking care of multiple patients at the same time in each shift, and a patient can suffer from multiple diseases at the same time. In some embodiments, a disease vector consisting of all the diseases of all patients corresponding to each shift of each clinical nursing staff is constructed. In some embodiments, the disease vector of the i-th clinical nursing staff can be expressed as , for example, , , and They may be myocarditis, angina pectoris, angina pectoris and heart failure, respectively, indicating that the clinical nurse will nurse angina pectoris patients twice, myocarditis patients once, and heart failure patients once in the shift schedule. Determining the disease vector facilitates determining the target disease based on the disease vector.

[0080] In some embodiments, the specific method of determining information entropy is:

[0081] (1) Determine the The set of symptoms of all patients corresponding to all shifts of clinical nursing staff in nursing work.

[0082] (2) Count the number of times each identical symptom occurs in the symptom set.

[0083] (3) Calculate the ratio of the number of occurrences of each identical symptom to the number of data in the symptom set. This ratio can reflect the frequency of occurrence of each identical symptom.

[0084] (4) Calculate information entropy according to the following general calculation formula of information entropy:

[0085]

[0086] In the formula, Indicates The information entropy of all patients' symptoms corresponding to all shifts of clinical nurses in nursing work, Q represents the number of different types of symptoms, q represents the sequence number of the symptoms, represents the frequency of occurrence of the qth disease, Represents logarithmic operation, where the logarithm generally takes 2 as the base.

[0087] The sixth determination unit is used to determine the actual comprehensive characteristic value, so as to accurately coordinate and quantify the actual need for nursing staff and the patient's condition, so as to accurately match the patient with the preferred nursing staff.

[0088] In some embodiments, the actual comprehensive characteristic value is determined according to the following formula:

[0089]

[0090] In the formula, Indicates The actual comprehensive characteristic value of clinical nursing staff, Indicates The skill level of clinical nursing staff, Indicates The demand for clinical nursing staff, Indicates the serial number of clinical nursing staff. and Multiplying them together, we can get a more comprehensive reflection of the actual need for clinical nursing staff and the patient's condition, so as to accurately match the patient with the preferred nursing staff.

[0091] The construction unit is used to construct the comprehensive feature vector of clinical nurses. The comprehensive feature vector of the i-th clinical nurse is expressed as ,in, , and They represent the professional title, length of service and actual comprehensive characteristic value of the i-th clinical nurse respectively, , and They respectively represent the relative levels of the cardiac nursing certification, emergency nursing certification and operating room nursing certification of the i-th clinical nurse, and i represents the serial number of the clinical nurse.

[0092] In some embodiments, the title of the i-th clinical nurse It can be divided into five levels: chief nurse, deputy chief nurse, supervisor nurse, nurse and nurse.

[0093] The classification module 103 is used to classify and label clinical nursing staff based on the comprehensive feature vector, and the labels include nursing type and nursing ability level.

[0094] The classification module can ensure the rational allocation of nursing staff, thereby completing the deployment and management of clinical nursing staff.

[0095] In some embodiments, the classification module 103 includes:

[0096] The clustering unit is used to cluster the comprehensive feature vector through the fuzzy C-means clustering algorithm to obtain multiple clusters and assign a label to each cluster.

[0097] It should be noted that the fuzzy C-means clustering algorithm allows data points to belong to different clusters with a certain probability distribution according to their membership degree. Therefore, a data point can partially belong to one cluster and also partially belong to another or more clusters. That is, when a nursing staff is proficient in different aspects of nursing, the nursing staff will be divided into multiple clusters to ensure the reasonable allocation of personnel.

[0098] In some embodiments, the nursing type of each cluster, that is, the nursing type included in the label, is the certificate type with the most certificates in the cluster. The nursing type can reflect the nursing field that the clinical nurses in the cluster are suitable for assignment. The nursing ability level, that is, the nursing ability level included in the label, is the highest level in the certificate corresponding to the nursing type in the cluster. The nursing ability level can reflect the strength of the clinical nurses' nursing ability in the nursing field. The setting of the nursing ability level facilitates the deployment of clinical nurses for patients according to the severity of the patient's condition, thereby allocating clinical nurses with higher nursing ability levels to patients with severe conditions, thereby ensuring that the patient's nursing effect is optimal.

[0099] In some embodiments, the nursing type may include cardiac nursing, emergency nursing, and operating room nursing. The nursing type and nursing ability level are obtained by clustering the comprehensive feature vector. Since the comprehensive feature vector includes the certificate types of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of clinical nursing personnel, the certificate type corresponds to the nursing type, i.e., cardiac nursing, emergency nursing, and operating room nursing. After clustering the comprehensive feature vector, each cluster can obtain the corresponding nursing type, i.e., the nursing type included in the label. Since the comprehensive feature vector also includes the title, length of service, and the actual comprehensive feature value, each cluster can obtain the corresponding nursing ability level after clustering the comprehensive feature vector.

[0100] In some embodiments, when encountering a patient with a serious heart disease, appropriate clinical nursing staff are selected from the cluster corresponding to the label of the heart disease care to schedule shifts, thereby completing the deployment and management of clinical nursing staff.

[0101] In summary, the present invention provides a management system for clinical nursing staff, which takes into account the skill requirements of hospitals and patients for clinical nursing staff, ensures the accuracy of subsequent nursing staff work division, and thus realizes precise personnel management.

[0102] In a second aspect, the present invention provides a management method for clinical nursing staff, see Figure 2 , the method comprising:

[0103] Step 201, obtaining the certificate feature vector and scheduling data of clinical nursing staff.

[0104] Step 202, based on the certificate feature vector and the scheduling data, determine the comprehensive feature vector of the clinical nurses, the comprehensive feature vector includes the professional title, length of service and the actual comprehensive feature value and the relative level of the certificate, wherein the actual comprehensive feature value is the product of the clinical nurses' skill expertise and the degree of demand.

[0105] Step 203, based on the comprehensive feature vector, clinical nursing staff are classified and labeled, and the labels include nursing type and nursing ability level.

[0106] In summary, the present invention provides a management method for clinical nursing staff, which takes into account the skill requirements of hospitals and patients for clinical nursing staff, ensures the accuracy of subsequent division of nursing staff work, and thus achieves precise personnel management.

[0107] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0108] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A management system for clinical nursing staff, characterized in that, The system comprises: An acquisition module, used to obtain the certificate feature vectors and scheduling data of clinical nursing staff; A determination module, for determining a comprehensive feature vector of a clinical nurse based on the certificate feature vector and the scheduling data, wherein the comprehensive feature vector includes job title, length of service, actual comprehensive feature value and relative level of certificate, wherein the actual comprehensive feature value is the product of the skill specialization and demand of the clinical nurse; A classification module, used for classifying and labeling clinical nursing staff based on the comprehensive feature vector, wherein the labels include nursing type and nursing ability level; The acquisition module comprises: The first acquisition unit is used to acquire the certificate data of different nursing types held by clinical nursing staff at the current moment; The first determining unit is used to determine the certificate feature vector based on the certificate data, wherein the certificate data includes the certificate type, the relative level of the certificate and the duration of holding the certificate, and the certificate feature vector is expressed as ,in, , and They represent the relative levels of the certificates of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of the i-th clinical nurse, respectively, and i represents the serial number of the clinical nurse; The second acquisition unit is used to acquire the scheduling data of clinical nursing staff in nursing work within three months before the current moment; The determination module comprises: A second determination unit is used to determine the degree of desirability of obtaining each certificate among all certificates held by the clinical staff; A third determination unit is used to determine the actual demand for each certificate based on the demand for each certificate and the scheduling data; A fourth determining unit, configured to determine the degree of demand for clinical nursing personnel based on the measured degree of demand and the actual degree of demand; The fifth determination unit is used to determine the skill specialization of clinical nursing staff; A sixth determining unit, used to determine an actual comprehensive characteristic value; The construction unit is used to construct the comprehensive feature vector of clinical nurses. The comprehensive feature vector of the i-th clinical nurse is expressed as ,in, , and They represent the professional title, length of service and actual comprehensive characteristic value of the i-th clinical nurse respectively. , and They represent the relative levels of the certificates of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of the i-th clinical nurse, respectively, and i represents the serial number of the clinical nurse; According to the following formula, based on the measured demand and the actual demand, the demand for clinical nursing staff is determined: In the formula, Indicates The demand for clinical nursing staff, Indicates Clinical nurses The actual need for the certificate, Indicates Number of certifications held by clinical nurses, Represents the sum of the number of shifts for all clinical nursing staff, Indicates The number of shifts per clinical nurse, Indicates the serial number of clinical nursing staff; The skill specialization of clinical nursing staff is determined according to the following formula: In the formula, Indicates The skill level of clinical nursing staff, Indicates The number of times the target symptom appears in all the symptom of all patients in all the nursing shifts of the clinical nurses, Indicates The number of illnesses of all patients corresponding to all shifts of clinical nurses in nursing work, Indicates The information entropy of all patients' symptoms corresponding to all shifts of clinical nurses in nursing work, , as well as Respectively represent The similarity between the set corresponding to the first symptom and the set corresponding to the second symptom, the similarity between the set corresponding to the first symptom and the set corresponding to the third symptom, and the similarity between the set corresponding to the second symptom and the set corresponding to the third symptom for each clinical nurse. represents an exponential function with a natural constant as base, Represents the serial number of the clinical nurse, wherein the target disease is the disease with the top three occurrences among all the diseases of all patients corresponding to all the nursing shifts of each clinical nurse, and the target disease includes the first disease, the second disease and the third disease. Among all the patients corresponding to all the nursing shifts of all clinical nurses, the set consisting of all patients suffering from the first disease is taken as the set corresponding to the first disease, the set consisting of all patients suffering from the second disease is taken as the set corresponding to the second disease, and the set consisting of all patients suffering from the third disease is taken as the set corresponding to the third disease.

2. The management system for clinical nursing staff according to claim 1, characterized in that: The desirability of each certification held by clinical staff is determined according to the following formula: In the formula, Indicates The requirements for obtaining the certificates, represents the number of clinical nursing staff, Indicates holding The number of clinical nurses with the certificate Indicates holding All clinical nursing staff The mean of the relative grades of the certificates of the types of certificates, Indicates holding All clinical nursing staff The average length of time for holding the various certificates, Indicates the serial number of the certificate.

3. The management system for clinical nursing staff according to claim 1, characterized in that: The actual demand for each certificate is determined based on the demand for each certificate and the scheduling data according to the following formula: In the formula, Indicates The actual need for the certificate, Indicates The requirements for obtaining the certificates, Indicates holding The sum of the number of shifts for all clinical nursing staff with the same certificate, Represents the sum of the number of shifts for all clinical nursing staff, Indicates the serial number of the certificate.

4. The management system for clinical nursing staff according to claim 1, characterized in that: No. The similarity between the set corresponding to the first disease and the set corresponding to the second disease, the similarity between the set corresponding to the first disease and the set corresponding to the third disease, and the similarity between the set corresponding to the second disease and the set corresponding to the third disease corresponding to the clinical nursing staff are calculated by using the Jaccard similarity algorithm.

5. The management system for clinical nursing staff according to claim 1, characterized in that: The classification module comprises: The clustering unit is used to cluster the comprehensive feature vector by using a fuzzy C-means clustering algorithm to obtain a plurality of clusters, and to assign a label to each cluster.

6. A management method for clinical nursing staff, characterized in that, The method comprises: Obtain the certification feature vectors and scheduling data of clinical nursing staff; Based on the certificate feature vector and the scheduling data, a comprehensive feature vector of the clinical nursing staff is determined, wherein the comprehensive feature vector includes the job title, length of service, actual comprehensive feature value and relative level of the certificate, wherein the actual comprehensive feature value is the product of the skill specialization and the demand degree of the clinical nursing staff; Based on the comprehensive feature vector, clinical nursing staff are classified and labeled, and the labels include nursing type and nursing ability level; Obtain the certification feature vector and scheduling data of clinical nursing staff, including: Obtain data on the certificates of different nursing types held by clinical nursing staff at the current moment; Based on the certificate data, the certificate feature vector is determined. The certificate data includes the certificate type, the relative level of the certificate and the duration of the certificate. The certificate feature vector is expressed as ,in, , and They represent the relative levels of the certificates of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of the i-th clinical nurse, respectively, and i represents the serial number of the clinical nurse; Obtain the shift data of clinical nursing staff in nursing work within three months before the current moment; Determine a comprehensive characteristic vector of clinical nursing staff, including: Determine the desirability of each certification held by clinical staff; Determine the actual need for each certificate based on the demand and scheduling data for each certificate; Determining the degree of demand for clinical nursing personnel based on the measured degree of demand and the actual degree of demand; Determine the skill specialization of clinical nursing staff; Determine the actual comprehensive characteristic value; Construct the comprehensive feature vector of clinical nurses. The comprehensive feature vector of the i-th clinical nurse is expressed as ,in, , and They represent the professional title, length of service and actual comprehensive characteristic value of the i-th clinical nurse respectively, , and They represent the relative levels of the certificates of cardiac nursing certification, emergency nursing certification, and operating room nursing certification of the i-th clinical nurse, respectively, and i represents the serial number of the clinical nurse; According to the following formula, based on the measured demand and the actual demand, the demand for clinical nursing staff is determined: In the formula, Indicates The demand for clinical nursing staff, Indicates Clinical nurses The actual need for the certificate, Indicates Number of certifications held by clinical nurses, Represents the sum of the number of shifts for all clinical nursing staff, Indicates The number of shifts per clinical nurse, Indicates the serial number of clinical nursing staff; The skill specialization of clinical nursing staff is determined according to the following formula: In the formula, Indicates The skill level of clinical nursing staff, Indicates The number of times the target symptom appears in all the symptom of all patients in all the nursing shifts of the clinical nurses, Indicates The number of illnesses of all patients corresponding to all shifts of clinical nurses in nursing work, Indicates The information entropy of all patients' symptoms corresponding to all shifts of clinical nurses in nursing work, , as well as Respectively represent The similarity between the set corresponding to the first symptom and the set corresponding to the second symptom, the similarity between the set corresponding to the first symptom and the set corresponding to the third symptom, and the similarity between the set corresponding to the second symptom and the set corresponding to the third symptom for each clinical nurse. represents an exponential function with a natural constant as base, Represents the serial number of the clinical nurse, wherein the target disease is the disease with the top three occurrences among all the diseases of all patients corresponding to all the nursing shifts of each clinical nurse, and the target disease includes the first disease, the second disease and the third disease. Among all the patients corresponding to all the nursing shifts of all clinical nurses, the set consisting of all patients suffering from the first disease is taken as the set corresponding to the first disease, the set consisting of all patients suffering from the second disease is taken as the set corresponding to the second disease, and the set consisting of all patients suffering from the third disease is taken as the set corresponding to the third disease.

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