CN112908468A - Intelligent medical management system based on 5G network - Google Patents

Abstract

The invention discloses an intelligent medical management system based on a 5G network, and relates to the technical field of intelligent medical treatment; the infusion monitoring system comprises a server, a task allocation module, an infusion monitoring module, a storage module, a personnel assessment module and a display module; according to the invention, the task allocation module can reasonably select the corresponding nursing staff to carry out infusion operation according to the infusion value, so that the accuracy of venipuncture and puncture efficiency are improved, and the infusion monitoring module is used for monitoring venipuncture of the selected staff to ensure accurate infusion; meanwhile, in the venipuncture process, the physical sign data of a patient are collected in real time, the somatosensory value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, selected personnel are reminded to pacify the patient, and the pain of the patient is relieved; the venous puncture skill of the nursing staff can be checked according to the transfusion record; the management personnel can conveniently conduct targeted training on the nursing personnel, so that the service quality is improved.

Description

Intelligent medical management system based on 5G network

Technical Field

The invention relates to the technical field of intelligent medical treatment, in particular to an intelligent medical treatment management system based on a 5G network.

Background

The intelligent medical management system uses a relatively mature social hospital management mode to manage the medical service management from the check of the escorting personnel to the daily medical service management and the pharmacy management, and forms the whole process electronization;

the existing intelligent medical management system has some problems, the bed of each large hospital is tense, a large number of hallways are added, particularly, the medical department characterized by chronic diseases is full of people for a long time, and the infusion (venipuncture) in a ward is the most common medicine treatment mode, but the workload of medical staff is large, the accurate infusion cannot be ensured, and the error of medicine replacement of nurses is possible; the venipuncture can not guarantee one-time success due to factors such as poor filling of peripheral veins, tiny blood vessels of pediatric patients, lumen narrowing and even occlusion caused by damaged blood vessels of intima in cancer chemotherapy, poor blood vessel conditions of old and weak chronic patients and the like; the venipuncture is accompanied by mechanical injury pain, the pain of a patient is increased by repeated puncture, and the traditional venipuncture causes the adverse effects of fear, pain and the like on the patient; in view of this, we propose an intelligent medical management system based on 5G network.

Disclosure of Invention

Aiming at the defects in the prior art, the invention aims to provide an intelligent medical management system based on a 5G network. The invention can reasonably select the corresponding nursing staff to carry out transfusion operation according to the transfusion and distribution value; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and ensuring that the venipuncture is successful once as much as possible; the infusion monitoring module is used for monitoring venipuncture of the selected person; ensuring accurate transfusion; meanwhile, in the venipuncture process, collecting physical sign data of a patient in real time, calculating a somatosensory value of the patient to the venipuncture according to the change of the physical sign data of the patient, and reminding a selected person to pacify the patient if the somatosensory value Y is larger than a somatosensory threshold value; the pain of the patient is relieved, and the fear, pain and other bad emotions of the patient are relieved.

The purpose of the invention can be realized by the following technical scheme: an intelligent medical management system based on a 5G network comprises a registration login module, a task release module, a server, a task allocation module, an infusion monitoring module, a storage module, a personnel assessment module and a display module;

the task issuing module is used for issuing an infusion task by a doctor and accessing the task issuing module and receiving the infusion task by a nursing staff through a mobile phone terminal; the task allocation module is used for allocating corresponding selected personnel from nursing personnel receiving the infusion task to perform the infusion task; sending the infusion task information to the mobile phone terminal of the selected person;

the infusion monitoring module is used for monitoring venipuncture of the selected person to obtain an infusion record of the selected person; the personnel assessment module is used for acquiring and analyzing the infusion records of the nursing personnel and assessing the venipuncture skills of the nursing personnel; the specific analysis steps are as follows:

VV 1: collecting transfusion records of nursing personnel ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;

VV 2: obtaining a corresponding puncture duration, a corresponding venipuncture frequency and a curve graph of a somatosensory value Y along with time change in the venipuncture process in the infusion record;

marking the number of venipuncture times per infusion as Cp; when Cp is greater than the puncture time threshold, marking the vein puncture time as an influence puncture time, counting the times of influencing the puncture time and marking as an influence frequency YP; the puncture time threshold value takes a value of 1;

calculating the difference between the influence puncture times and the puncture time threshold to obtain a super value YT;

setting the coefficient of the order of the super as Hm, wherein m is 1, 2, … …, k; k is a positive integer; wherein H1 < H2 < … … < Hk; each super-order coefficient Hm corresponds to a preset super-order value range, and the method specifically comprises the following steps: the preset overvalue range corresponding to H1 is (0, H1 ]; the preset overvalue range corresponding to H2 is (H1, H2], … …, and the preset overvalue range corresponding to Hk is (Hk-1, Hk ]; wherein 0 < H1 < H2 < … … < Hk;

when YT belongs to (Hm-1, Hm), the corresponding coefficient of order exceeding is Hm;

obtaining an influence value M1 corresponding to the supersecondt value by using a formula M1 which is YT multiplied by Hm; summing the influence values corresponding to all the super-order values to obtain a super-order influence total value M2;

the puncture time lengths are summed and averaged to obtain an average puncture time length which is marked as WT;

comparing the somatosensory value Y with a somatosensory threshold; counting the time length of the somatosensory value Y which is greater than the somatosensory threshold value and marking the time length as the hypersensitive time length; summing the excess induction time lengths and taking the average value to obtain an average excess induction time length which is marked as GT;

VV 3: obtaining the assessment influence coefficient KH of the nursing staff by using a formula of KH (YT × b1+ M2 × b2+ WT × b3+ GT × b 4); wherein b1, b2, b3 and b4 are all proportionality coefficients;

VV 4: comparing the assessment influence coefficient KH with a coefficient threshold;

if the assessment influence coefficient KH is larger than or equal to the coefficient threshold value, the vein puncture skill assessment result of the nursing staff is unqualified; the nursing staff needs to perform venipuncture skill training again;

the staff assessment module is used for transmitting the assessment influence coefficient KH to the server, and the server is used for transmitting the assessment influence coefficient KH to the display module for real-time display by stamping a timestamp.

Further, the registration login module is used for a nursing staff to enter registration information for registration and transmit the registration information to the server for storage, wherein the registration information comprises a name, an age, an identification card number, time of entry and visual values of two eyes; the infusion task information comprises patient information, infusion medicine information and an infusion position; the patient information comprises the name, the identity card number and standard face image information of the patient; the infusion position is the position of a patient.

Further, the specific working steps of the task allocation module are as follows:

the method comprises the following steps: acquiring all infusion medicine information in an infusion task; the nursing staff receives the infusion medicines corresponding to the infusion task through the mobile phone terminal, and the nursing staff receiving the infusion medicines corresponding to the infusion task is marked as a primary selection staff;

step two: calculating the distance difference between the position of the primary selection person and the infusion position to obtain an infusion distance and marking the infusion distance as L1;

calculating the time difference between the time of entry of the primary selected person and the current time of the system to obtain the time length of entry of the primary selected person and marking the time length as T1;

step three: acquiring real-time video information of a primary selection person, and intercepting real-time face image information of the primary selection person from the real-time video information; judging whether the primary selected person wears glasses or not according to the real-time face image information, and if the primary selected person wears the glasses, enabling SD to be 1; if the primary selection personnel do not wear the glasses; making SD equal to 0;

acquiring registration information of the primary-selected person, and judging whether the primary-selected person is short-sighted or not; the method specifically comprises the following steps:

acquiring visual force values of two eyes of the primary selection person; if the vision values of both eyes are larger than 1, the primary election person is not short-sighted; otherwise, the person is selected for early sight;

if the primary selected person is short-sighted, making SC equal to 0, if the primary selected person is not short-sighted, making SC equal to 1;

step four: acquiring a rest value of the primary selection personnel one day before the current time of the system and marking the rest value as X1; setting the total times of infusion of the primary selection personnel as C1, and setting the age of the primary selection personnel as N1; the rest value of the previous day is expressed as the rest duration of the previous day;

step five: using formulas

Obtaining the distribution value SP of the primary selected person by SP [1/L1 × a1+ T1 × a2+ (SD + SC) × a3+ X1 × a4+ C1 × a5- | N1-30| × a6]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH represents the assessment influence coefficient of the primary selected person;

step six: and selecting the initially selected person with the largest infusion and distribution value as the selected person of the infusion task.

Further, the specific monitoring steps of the infusion monitoring module are as follows:

v1: the method comprises the steps that a selected person arrives at an infusion place after receiving collected and detected infusion task information through a mobile phone terminal, and shoots real-time face image information and medicine pictures of a patient through the mobile phone terminal and sends the real-time face image information and the medicine pictures to an infusion monitoring module, the infusion monitoring module matches the real-time face image information of the patient with corresponding standard face image information of the patient in an infusion task after receiving the real-time face image information and the medicine pictures of the patient sent by the selected person, and matches the medicine pictures with corresponding infusion medicine information in the infusion task; if both items match; generating a start working signal;

v2: when the infusion monitoring module receives a working starting signal, the infusion monitoring module carries out face recognition on the selected person, and after the face recognition is passed; the infusion monitoring module monitors venipuncture of the selected person; if the face recognition is not passed, generating an early warning signal;

v3: the selected person starts to carry out venipuncture on the patient, and in the venipuncture process, the physical sign data of the patient are collected in real time and marked as target physical sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; measuring the experience of the patient on venipuncture by using the change condition of the physical sign data; the physical sign data comprises body temperature, heart rate, blood pressure value, perspiration amount and the like;

marking the corresponding physical sign parameter values in the normal physical sign data as physical sign data normal values Z1i respectively; 1, ·, n; wherein i represents the ith physical sign parameter;

acquiring target sign data t time after venipuncture begins; marking the corresponding physical sign parameter values in the target physical sign data as physical sign data target values Z2i respectively; wherein Z1i corresponds to Z2i one-to-one;

each sign parameter has different weights, H1, H2, … …, Hj, H1 > H2 > … … > Hj, and H1+ H2+ … … + Hj is 1; wherein i and j correspond one to one;

the physical sensation value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, and the specific calculation formula is as follows:

wherein Y is the somatosensory value of the patient to venipuncture;

v4: comparing the somatosensory value Y with a somatosensory threshold;

if the somatosensory value Y is larger than the somatosensory threshold value, reminding the selected person to pay attention to the current unstable emotion of the patient, having a large response to venipuncture, and reminding the selected person to pacify the patient; until the somatosensory value Y is less than or equal to the somatosensory threshold value;

v5: calculating the time difference between the starting time of venipuncture and the ending time of venipuncture to obtain puncture duration, and marking the puncture duration as CT 1; the number of times of venipuncture in the venipuncture process is counted and marked as CT 2; collecting a curve graph of the variation of the somatosensory value Y along with time in the venipuncture process;

and the curve graphs of the puncture duration, the venipuncture times and the variation of the somatosensory value Y along with time in the venipuncture process are fused to form an infusion record of the selected person and the infusion record is transmitted to a server, and the server is used for stamping the infusion record and transmitting the timestamp to a storage module for storage.

The invention has the beneficial effects that:

1. the task allocation module is used for allocating corresponding selected personnel from nursing personnel who receive the infusion task to carry out the infusion task; marking the nursing staff who get the infusion medicine corresponding to the infusion task as the primary selection staff; calculating the distribution value of the primary selection personnel by combining the infusion distance, the working duration, whether to wear glasses, whether to be short-sighted, the rest value, the total infusion times and the age: selecting the primary selected person with the largest infusion and distribution value as the selected person of the infusion task; the corresponding nursing staff can be reasonably selected according to the infusion and distribution value to carry out infusion operation; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and ensuring that the venipuncture is successful once as much as possible;

2. the infusion monitoring module is used for monitoring venipuncture of a selected person; in the venipuncture process, the physical sign data of a patient are collected in real time, the somatosensory value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, and the specific calculation formula is as follows:

if the somatosensory value Y is larger than the somatosensory threshold value, reminding the selected person to pay attention to the current unstable emotion of the patient, having a large response to venipuncture, and reminding the selected person to pacify the patient; until the somatosensory value Y is less than or equal to the somatosensory threshold value; increase diseaseA human experience; the pain of the patient is relieved, and the fear, pain and other bad emotions of the patient are relieved;

3. the personnel assessment module is used for acquiring and analyzing the infusion records of the nursing personnel and assessing the venipuncture skill of the nursing personnel; if the vein puncture skill examination result is not qualified, the corresponding nursing staff needs to perform vein puncture skill training again; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and improving the service quality.

Drawings

In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.

FIG. 1 is a block diagram of the system of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, an intelligent medical management system based on a 5G network includes a registration login module, a task issue module, a server, a task allocation module, an infusion monitoring module, a storage module, a staff assessment module, and a display module;

the registration login module is used for the nursing staff to enter registration information for registration and transmit the registration information to the server for storage, wherein the registration information comprises name, age, identity card number, time of job entry and visual force values of two eyes;

the task issuing module is used for issuing an infusion task by a doctor and accessing the task issuing module and receiving the infusion task by a nursing staff through a mobile phone terminal; the infusion task information comprises patient information, infusion medicine information and an infusion position; the patient information comprises the name, the identity card number and the standard face image information of the patient; the transfusion position is the position of a patient;

the task allocation module is used for allocating corresponding selected personnel from the nursing personnel who receive the infusion task to carry out the infusion task; the specific working steps of the task allocation module are as follows:

the method comprises the following steps: acquiring all infusion medicine information in an infusion task; the nursing staff receives the infusion medicines corresponding to the infusion task through the mobile phone terminal, and the nursing staff receiving the infusion medicines corresponding to the infusion task is marked as a primary selection staff;

step two: calculating the distance difference between the position of the primary selection person and the infusion position to obtain an infusion distance and marking the infusion distance as L1;

calculating the time difference between the time of entry of the primary selected person and the current time of the system to obtain the time length of entry of the primary selected person and marking the time length as T1;

step three: acquiring real-time video information of a primary selection person, and intercepting real-time face image information of the primary selection person from the real-time video information; judging whether the primary selected person wears glasses or not according to the real-time face image information, and if the primary selected person wears the glasses, enabling SD to be 1; if the primary selection personnel do not wear the glasses; making SD equal to 0;

acquiring registration information of the primary-selected person, and judging whether the primary-selected person is short-sighted or not; the method specifically comprises the following steps:

acquiring visual force values of two eyes of the primary selection person; if the vision values of both eyes are larger than 1, the primary election person is not short-sighted; otherwise, the person is selected for early sight;

if the primary selected person is short-sighted, making SC equal to 0, if the primary selected person is not short-sighted, making SC equal to 1;

step four: acquiring a rest value of the primary selection personnel one day before the current time of the system and marking the rest value as X1; setting the total times of infusion of the primary selection personnel as C1, and setting the age of the primary selection personnel as N1; the rest value of the previous day is expressed as the rest duration of the previous day;

step five: using formulas

Obtaining the distribution value SP of the primary selected person by SP [1/L1 × a1+ T1 × a2+ (SD + SC) × a3+ X1 × a4+ C1 × a5- | N1-30| × a6]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH represents the assessment influence coefficient of the primary selected person; for example, a1 takes on a value of 0.11, a2 takes on a value of 0.19, a3 takes on a value of 0.45, a4 takes on a value of 0.35, a5 takes on a value of 0.28, and a6 takes on a value of 0.62;

in the formula, if the primary-selected person is not near sighted/wears glasses, it is shown that the visual object of the primary-selected person is clearer, the corresponding puncture vein searching is more accurate, the rest value of the primary-selected person in the previous day is larger, the spirit of the primary-selected person is fuller, the corresponding puncture vein searching is more accurate, and the efficiency is higher;

step six: selecting the primary selected person with the largest infusion and distribution value as the selected person of the infusion task; sending the infusion task information to the mobile phone terminal of the selected person;

the infusion monitoring module is used for monitoring venipuncture of selected personnel, and the specific monitoring steps are as follows:

v1: the method comprises the steps that a selected person arrives at an infusion place after receiving collected and detected infusion task information through a mobile phone terminal, and shoots real-time face image information and medicine pictures of a patient through the mobile phone terminal and sends the real-time face image information and the medicine pictures to an infusion monitoring module, the infusion monitoring module matches the real-time face image information of the patient with corresponding standard face image information of the patient in an infusion task after receiving the real-time face image information and the medicine pictures of the patient sent by the selected person, and matches the medicine pictures with corresponding infusion medicine information in the infusion task; if both items match; generating a working starting signal so as to ensure that a patient who carries out infusion (venipuncture) and corresponding medicines are correct, ensure accurate infusion and prevent errors;

v2: after the infusion monitoring module receives the working starting signal, the infusion monitoring module carries out face recognition on the selected person, and after the face recognition is passed; the infusion monitoring module monitors venipuncture of the selected person; if the face recognition is not passed, generating an early warning signal; thereby avoiding the irrelevant personnel from performing venipuncture at will and ensuring medical safety;

v3: the selected person starts to carry out venipuncture on the patient, and in the venipuncture process, the physical sign data of the patient are collected in real time and marked as target physical sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; measuring the experience of the patient on venipuncture by using the change condition of the physical sign data; the physical sign data comprises body temperature, heart rate, blood pressure value, perspiration amount and the like;

marking the corresponding physical sign parameter values in the normal physical sign data as physical sign data normal values Z1i respectively; 1, ·, n; wherein i represents the ith physical sign parameter;

acquiring target sign data t time after venipuncture begins; marking the corresponding physical sign parameter values in the target physical sign data as physical sign data target values Z2i respectively; wherein Z1i corresponds to Z2i one-to-one;

each sign parameter has different weights, H1, H2, … …, Hj, H1 > H2 > … … > Hj, and H1+ H2+ … … + Hj is 1; wherein i and j correspond one to one;

the physical sensation value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, and the specific calculation formula is as follows:

wherein Y is the somatosensory value of the patient to venipuncture; the larger Y is, the larger the response of the patient to the venipuncture is, and the more unstable the emotion is;

v4: comparing the somatosensory value Y with a somatosensory threshold;

if the somatosensory value Y is larger than the somatosensory threshold value, reminding the selected person to pay attention to the current unstable emotion of the patient, having a large response to venipuncture, and reminding the selected person to pacify the patient; until the somatosensory value Y is less than or equal to the somatosensory threshold value;

v5: calculating the time difference between the starting time of venipuncture and the ending time of venipuncture to obtain puncture duration, and marking the puncture duration as CT 1; the number of times of venipuncture in the venipuncture process is counted and marked as CT 2; collecting a curve graph of the variation of the somatosensory value Y along with time in the venipuncture process; the method comprises the steps of fusing a puncture duration, the number of times of venipuncture and a time-varying curve graph of a somatosensory value Y in the venipuncture process to form an infusion record of a selected person and transmitting the infusion record to a server, wherein the server is used for stamping a timestamp on the infusion record and transmitting the timestamp to a storage module for storage;

the personnel examination module is used for acquiring and analyzing the infusion records of the nursing personnel and examining the venipuncture skills of the nursing personnel; the specific analysis steps are as follows:

VV 1: collecting transfusion records of nursing personnel ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;

VV 2: obtaining a corresponding puncture duration, a corresponding venipuncture frequency and a curve graph of a somatosensory value Y along with time change in the venipuncture process in the infusion record;

marking the number of venipuncture times per infusion as Cp; when Cp is greater than the puncture time threshold, marking the vein puncture time as an influence puncture time, counting the times of influencing the puncture time and marking as an influence frequency YP; the puncture time threshold value takes 1;

calculating the difference between the influence puncture times and the puncture time threshold to obtain a super value YT;

setting the coefficient of the order of the super as Hm, wherein m is 1, 2, … …, k; k is a positive integer; wherein H1 < H2 < … … < Hk; each super-order coefficient Hm corresponds to a preset super-order value range, and the method specifically comprises the following steps: the preset overvalue range corresponding to H1 is (0, H1 ]; the preset overvalue range corresponding to H2 is (H1, H2], … …, and the preset overvalue range corresponding to Hk is (Hk-1, Hk ]; wherein 0 < H1 < H2 < … … < Hk;

when YT belongs to (Hm-1, Hm), the corresponding coefficient of order exceeding is Hm;

obtaining an influence value M1 corresponding to the supersecondt value by using a formula M1 which is YT multiplied by Hm; summing the influence values corresponding to all the super-order values to obtain a super-order influence total value M2;

the puncture time lengths are summed and averaged to obtain an average puncture time length which is marked as WT;

comparing the somatosensory value Y with a somatosensory threshold; counting the time length of the somatosensory value Y which is greater than the somatosensory threshold value and marking the time length as the hypersensitive time length; summing the excess induction time lengths and taking the average value to obtain an average excess induction time length which is marked as GT;

VV 3: obtaining the assessment influence coefficient KH of the nursing staff by using a formula of KH (YT × b1+ M2 × b2+ WT × b3+ GT × b 4); wherein b1, b2, b3 and b4 are all proportionality coefficients; for example, b1 takes the value of 0.15, b2 takes the value of 0.44, b3 takes the value of 0.35, and b4 takes the value of 0.39; the larger the examination influence coefficient KH is, the worse the vein puncture skill examination result of the nursing staff is;

VV 4: comparing the assessment influence coefficient KH with a coefficient threshold;

if the assessment influence coefficient KH is larger than or equal to the coefficient threshold value, the vein puncture skill assessment result of the nursing staff is unqualified; the nursing staff needs to perform venipuncture skill training again; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and ensuring that the venipuncture is successful once as much as possible; the pain of the patient is relieved, and the fear, pain and other bad emotions of the patient are relieved;

the personnel assessment module is used for transmitting the assessment influence coefficient KH to the server, and the server is used for transmitting the assessment influence coefficient KH to the display module for real-time display by stamping a timestamp; the display module is used for displaying the venous puncture skill examination result of the nursing staff, and the management staff and other nursing staff can check and see the examination result through the display module, so that the nursing staff can be objectively evaluated, the management staff can conveniently train the nursing staff in a targeted manner, and secondly, other nursing staff can check and improve the nursing staff according to the examination result, thereby promoting the common progress of all staff and improving the service quality.

The working principle of the invention is as follows:

when the intelligent medical management system based on the 5G network works, a task issuing module is used for issuing an infusion task by a doctor and accessing the task issuing module and receiving the infusion task by a nursing staff through a mobile phone terminal; the task allocation module is used for allocating corresponding selected personnel to perform infusion tasks from nursing personnel receiving the infusion tasks; marking the nursing staff who get the infusion medicine corresponding to the infusion task as the primary selection staff; calculating the distribution value of the primary selection personnel by combining the infusion distance, the working duration, whether to wear glasses, whether to be short-sighted, the rest value, the total infusion times and the age: selecting the primary selected person with the largest infusion and distribution value as the selected person of the infusion task; the corresponding nursing staff can be reasonably selected according to the infusion and distribution value to carry out infusion operation; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and ensuring that the venipuncture is successful once as much as possible;

the infusion monitoring module is used for monitoring venipuncture of a selected person, and before venipuncture, real-time face image information and medicine pictures of a patient are shot and information matching is carried out; thereby ensuring that the patient who carries out the transfusion (venipuncture) and the corresponding medicine are correct, ensuring the accurate transfusion and preventing the error; then, the face recognition is carried out on the selected person, so that the vein puncture of irrelevant persons is avoided, and the medical safety is ensured; in the venipuncture process, the physical sign data of a patient are collected in real time, the somatosensory value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, and the specific calculation formula is as follows:

if the somatosensory value Y is larger than the somatosensory threshold value, reminding the selected person to pay attention to the current unstable emotion of the patient, having a large response to venipuncture, and reminding the selected person to pacify the patient; until the somatosensory value Y is less than or equal to the somatosensory threshold value; the experience of the patient is improved; the pain of the patient is relieved, and the fear, pain and other bad emotions of the patient are relieved;

the personnel examination module is used for acquiring and analyzing the infusion records of the nursing personnel and examining the venipuncture skills of the nursing personnel; if the vein puncture skill examination result is not qualified, the corresponding nursing staff needs to perform vein puncture skill training again; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and improving the service quality.

The formula and the proportionality coefficient are both obtained by collecting a large amount of data to perform software simulation and performing parameter setting processing by corresponding experts, and the formula and the proportionality coefficient which are consistent with real results are obtained. The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims (4)

1. An intelligent medical management system based on a 5G network is characterized by comprising a registration login module, a task release module, a server, a task allocation module, an infusion monitoring module, a storage module, a personnel assessment module and a display module;

the task issuing module is used for issuing an infusion task by a doctor and accessing the task issuing module and receiving the infusion task by a nursing staff through a mobile phone terminal; the task allocation module is used for allocating corresponding selected personnel from nursing personnel receiving the infusion task to perform the infusion task; sending the infusion task information to the mobile phone terminal of the selected person;

the infusion monitoring module is used for monitoring venipuncture of the selected person to obtain an infusion record of the selected person; the personnel assessment module is used for acquiring and analyzing the infusion records of the nursing personnel and assessing the venipuncture skills of the nursing personnel; the specific analysis steps are as follows:

VV 1: collecting transfusion records of nursing personnel ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;

VV 2: obtaining a corresponding puncture duration, a corresponding venipuncture frequency and a curve graph of a somatosensory value Y along with time change in the venipuncture process in the infusion record;

marking the number of venipuncture times per infusion as Cp; when Cp is greater than the puncture time threshold, marking the vein puncture time as an influence puncture time, counting the times of influencing the puncture time and marking as an influence frequency YP; the puncture time threshold value takes a value of 1;

calculating the difference between the influence puncture times and the puncture time threshold to obtain a super value YT;

setting the coefficient of the order of the super as Hm, wherein m is 1, 2, … …, k; k is a positive integer; wherein H1 < H2 < … … < Hk; each super-order coefficient Hm corresponds to a preset super-order value range, and the method specifically comprises the following steps: the preset overvalue range corresponding to H1 is (0, H1 ]; the preset overvalue range corresponding to H2 is (H1, H2], … …, and the preset overvalue range corresponding to Hk is (Hk-1, Hk ]; wherein 0 < H1 < H2 < … … < Hk;

when YT belongs to (Hm-1, Hm), the corresponding coefficient of order exceeding is Hm;

obtaining an influence value M1 corresponding to the supersecondt value by using a formula M1 which is YT multiplied by Hm; summing the influence values corresponding to all the super-order values to obtain a super-order influence total value M2;

the puncture time lengths are summed and averaged to obtain an average puncture time length which is marked as WT;

comparing the somatosensory value Y with a somatosensory threshold; counting the time length of the somatosensory value Y which is greater than the somatosensory threshold value and marking the time length as the hypersensitive time length; summing the excess induction time lengths and taking the average value to obtain an average excess induction time length which is marked as GT;

VV 3: obtaining the assessment influence coefficient KH of the nursing staff by using a formula of KH (YT × b1+ M2 × b2+ WT × b3+ GT × b 4); wherein b1, b2, b3 and b4 are all proportionality coefficients;

VV 4: comparing the assessment influence coefficient KH with a coefficient threshold;

if the assessment influence coefficient KH is larger than or equal to the coefficient threshold value, the vein puncture skill assessment result of the nursing staff is unqualified; the nursing staff needs to perform venipuncture skill training again;

the staff assessment module is used for transmitting the assessment influence coefficient KH to the server, and the server is used for transmitting the assessment influence coefficient KH to the display module for real-time display by stamping a timestamp.

2. The intelligent medical management system based on 5G network of claim 1, wherein the registration login module is used for a caregiver to enter registration information for registration and transmit the registration information to the server for storage, the registration information includes name, age, identification number, time of entry and visual values of two eyes; the infusion task information comprises patient information, infusion medicine information and an infusion position; the patient information comprises the name, the identity card number and standard face image information of the patient; the infusion position is the position of a patient.

3. The intelligent medical management system based on 5G network as claimed in claim 1, wherein the task allocation module comprises the following specific steps:

the method comprises the following steps: acquiring all infusion medicine information in an infusion task; the nursing staff receives the infusion medicines corresponding to the infusion task through the mobile phone terminal, and the nursing staff receiving the infusion medicines corresponding to the infusion task is marked as a primary selection staff;

step two: calculating the distance difference between the position of the primary selection person and the infusion position to obtain an infusion distance and marking the infusion distance as L1;

calculating the time difference between the time of entry of the primary selected person and the current time of the system to obtain the time length of entry of the primary selected person and marking the time length as T1;

step three: acquiring real-time video information of a primary selection person, and intercepting real-time face image information of the primary selection person from the real-time video information; judging whether the primary selected person wears glasses or not according to the real-time face image information, and if the primary selected person wears the glasses, enabling SD to be 1; if the primary selection personnel do not wear the glasses; making SD equal to 0;

acquiring registration information of the primary-selected person, and judging whether the primary-selected person is short-sighted or not; the method specifically comprises the following steps:

acquiring visual force values of two eyes of the primary selection person; if the vision values of both eyes are larger than 1, the primary election person is not short-sighted; otherwise, the person is selected for early sight;

if the primary selected person is short-sighted, making SC equal to 0, if the primary selected person is not short-sighted, making SC equal to 1;

step four: acquiring a rest value of the primary selection personnel one day before the current time of the system and marking the rest value as X1; setting the total times of infusion of the primary selection personnel as C1, and setting the age of the primary selection personnel as N1; the rest value of the previous day is expressed as the rest duration of the previous day;

step five: using formulas

Obtaining the distribution value SP of the primary selected person by SP [1/L1 × a1+ T1 × a2+ (SD + SC) × a3+ X1 × a4+ C1 × a5- | N1-30| × a6]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH represents the assessment influence coefficient of the primary selected person;

step six: and selecting the initially selected person with the largest infusion and distribution value as the selected person of the infusion task.

4. The intelligent medical management system based on 5G network as claimed in claim 1, wherein the specific monitoring steps of the infusion monitoring module are as follows:

v1: the method comprises the steps that a selected person arrives at an infusion place after receiving collected and detected infusion task information through a mobile phone terminal, and shoots real-time face image information and medicine pictures of a patient through the mobile phone terminal and sends the real-time face image information and the medicine pictures to an infusion monitoring module, the infusion monitoring module matches the real-time face image information of the patient with corresponding standard face image information of the patient in an infusion task after receiving the real-time face image information and the medicine pictures of the patient sent by the selected person, and matches the medicine pictures with corresponding infusion medicine information in the infusion task; if both items match; generating a start working signal;

v2: when the infusion monitoring module receives a working starting signal, the infusion monitoring module carries out face recognition on the selected person, and after the face recognition is passed; the infusion monitoring module monitors venipuncture of the selected person; if the face recognition is not passed, generating an early warning signal;

v3: the selected person starts to carry out venipuncture on the patient, and in the venipuncture process, the physical sign data of the patient are collected in real time and marked as target physical sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; measuring the experience of the patient on venipuncture by using the change condition of the physical sign data; the physical sign data comprises body temperature, heart rate, blood pressure value, perspiration amount and the like;

marking the corresponding physical sign parameter values in the normal physical sign data as physical sign data normal values Z1i respectively; 1, ·, n; wherein i represents the ith physical sign parameter;

acquiring target sign data t time after venipuncture begins; marking the corresponding physical sign parameter values in the target physical sign data as physical sign data target values Z2i respectively; wherein Z1i corresponds to Z2i one-to-one;

each sign parameter has different weights, H1, H2, … …, Hj, H1 > H2 > … … > Hj, and H1+ H2+ … … + Hj is 1; wherein i and j correspond one to one;

the physical sensation value of the patient to the venipuncture is calculated according to the change of the physical sign data of the patient, and the specific calculation formula is as follows:

wherein Y is the somatosensory value of the patient to venipuncture;

v4: comparing the somatosensory value Y with a somatosensory threshold;

if the somatosensory value Y is larger than the somatosensory threshold value, reminding the selected person to pay attention to the current unstable emotion of the patient, having a large response to venipuncture, and reminding the selected person to pacify the patient; until the somatosensory value Y is less than or equal to the somatosensory threshold value;

v5: calculating the time difference between the starting time of venipuncture and the ending time of venipuncture to obtain puncture duration, and marking the puncture duration as CT 1; the number of times of venipuncture in the venipuncture process is counted and marked as CT 2; collecting a curve graph of the variation of the somatosensory value Y along with time in the venipuncture process;

and the curve graphs of the puncture duration, the venipuncture times and the variation of the somatosensory value Y along with time in the venipuncture process are fused to form an infusion record of the selected person and the infusion record is transmitted to a server, and the server is used for stamping the infusion record and transmitting the timestamp to a storage module for storage.

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