CN112908468B - Intelligent medical management system based on 5G network - Google Patents
Intelligent medical management system based on 5G network Download PDFInfo
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- 238000001802 infusion Methods 0.000 claims abstract description 128
- 230000000474 nursing effect Effects 0.000 claims abstract description 55
- 230000003238 somatosensory effect Effects 0.000 claims abstract description 53
- 238000012544 monitoring process Methods 0.000 claims abstract description 35
- 238000000034 method Methods 0.000 claims abstract description 25
- 239000003814 drug Substances 0.000 claims description 31
- 238000001990 intravenous administration Methods 0.000 claims description 15
- 208000001491 myopia Diseases 0.000 claims description 15
- 239000011521 glass Substances 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 11
- 206010020751 Hypersensitivity Diseases 0.000 claims description 9
- 230000004438 eyesight Effects 0.000 claims description 9
- 230000005540 biological transmission Effects 0.000 claims description 5
- 230000008451 emotion Effects 0.000 claims description 5
- 230000036772 blood pressure Effects 0.000 claims description 3
- 230000036760 body temperature Effects 0.000 claims description 3
- 229940079593 drug Drugs 0.000 claims description 3
- 206010027940 Mood altered Diseases 0.000 description 4
- 210000003462 vein Anatomy 0.000 description 4
- 210000004204 blood vessel Anatomy 0.000 description 3
- 230000006378 damage Effects 0.000 description 2
- 230000004379 myopia Effects 0.000 description 2
- 208000017667 Chronic Disease Diseases 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
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- 238000002512 chemotherapy Methods 0.000 description 1
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- 208000014674 injury Diseases 0.000 description 1
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- 230000036651 mood Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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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 distribution module can reasonably select corresponding nursing staff to perform infusion operation according to the infusion and distribution value, so that the accuracy and the puncture efficiency of venipuncture are improved, and the infusion monitoring module is used for monitoring the venipuncture of selected staff and ensuring accurate infusion; meanwhile, in the venipuncture process, the physical sign data of the patient are collected in real time, the somatosensory value of the patient on the venipuncture is calculated according to the change of the physical sign data of the patient, and the selected personnel are reminded to pacify the patient, so that the pain of the patient is relieved; the invention can check the venipuncture skills of nursing staff according to the transfusion record; the management personnel can be conveniently trained for the nursing personnel, so that the service quality is improved.
Description
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 manages daily medical service management from the check-in to the daily pharmacy management by using a relatively mature social hospital management mode, and forms the whole process electronization;
the existing intelligent medical management system has some problems, such as the shortage of beds in various hospitals and the large number of bed adding conditions in corridors, especially the internal medicine characterized by chronic diseases, is in full of people for a long time, and transfusion (venipuncture) in a ward is the most common medicine treatment mode, however, the workload of medical staff is large, the accurate transfusion cannot be ensured, and the medicine replacement of nurses may be wrong; the vein puncture cannot be ensured to be successful once due to factors such as poor filling of peripheral veins, tiny blood vessels of pediatric patients, damage of blood vessel intima in cancer chemotherapy period, narrowing and even occlusion of a lumen, poor condition of aged and weak chronic blood vessels and the like; the venipuncture is accompanied with mechanical injury pain, the pain of a patient is further increased by repeated puncture, and the traditional venipuncture causes fear, pain and other adverse effects to the patient; in view of this, we propose a 5G network-based intelligent medical management system.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide an intelligent medical management system based on a 5G network. The invention can reasonably select 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 enabling the venipuncture to be successful as much as possible; the infusion monitoring module is used for monitoring venipuncture of selected personnel; ensuring accurate transfusion; meanwhile, in the venipuncture process, the physical sign data of the patient are collected in real time, the body feeling value of the patient on the venipuncture is calculated according to the change of the physical sign data, and if the body feeling value Y is more than a body feeling threshold value, a selected person is reminded to pacify the patient; relieving pain of patients and relieving fear, pain and other bad moods of the patients.
The aim of the invention can be achieved 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 a nursing staff accessing the task issuing module through a mobile phone terminal and acquiring the infusion task; the task distribution module is used for distributing corresponding selected persons from nursing staff for picking up infusion tasks to carry out infusion tasks; the infusion task information is sent to a mobile phone terminal of the selected person;
the infusion monitoring module is used for monitoring venipuncture of selected personnel and obtaining infusion records of the selected personnel; the staff assessment module is used for acquiring and analyzing infusion records of nursing staff and assessing venipuncture skills of the nursing staff; the specific analysis steps are as follows:
VV1: collecting infusion records of nursing staff ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;
VV2: obtaining a graph of corresponding puncture time length, venipuncture times and change of a somatosensory value Y along with time in a venipuncture process in an infusion record;
marking the number of venipuncture times at each infusion as Cp; when Cp is larger than the puncture frequency threshold, marking the number of times of venipuncture as the number of times of influencing puncture, counting the number of times of influencing puncture and marking as the frequency of influence YP; the puncture frequency threshold value is 1;
performing difference value calculation on the puncture frequency and the puncture frequency threshold to obtain a super-frequency value YT;
setting the super coefficient as Hm, m=1, 2, … …, k; k is a positive integer; wherein H1 is more than H2 and less than … … and less than Hk; each super coefficient Hm corresponds to a preset super value range, and specifically: the preset super-value range corresponding to H1 is (0, H1), the preset super-value range corresponding to H2 is (H1, H2), the preset super-value range corresponding to … … and Hk is (Hk-1, hk), wherein 0 < H1 < H2 < … … < Hk;
when YT is E (Hm-1, hm), the corresponding super coefficient is Hm;
obtaining an influence value M1 corresponding to the super-order value by using a formula M1=YT×Hm; summing all the influence values corresponding to the super-order values to obtain a super-order influence total value M2;
summing the puncture time lengths and taking an average value to obtain an average puncture time length, and marking the average puncture time length as WT;
comparing the somatosensory value Y with a somatosensory threshold; counting the duration that the somatosensory value Y is greater than the somatosensory threshold and marking the duration as oversensitive duration; summing the hypersensitive duration, taking an average value to obtain an average hypersensitive duration, and marking the average hypersensitive duration as GT;
VV3: obtaining an assessment influence coefficient KH of a nursing staff by using a formula KH=YT×b1+M2×b2+WT×b3+GT×b4; wherein b1, b2, b3 and b4 are all proportionality coefficients;
VV4: comparing the assessment influence coefficient KH with a coefficient threshold;
if the assessment influence coefficient KH is more than or equal to the coefficient threshold, the assessment result of the intravenous puncture skill of the nursing staff is not qualified; the nursing staff needs to train the venipuncture skill again;
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 with a time stamp.
Further, the registration login module is used for a nursing staff to input registration information for registration and transmit the registration information to a server for storage, wherein the registration information comprises a name, an age, an identity card number, time of job entry and vision values of two eyes; the infusion task information comprises patient information, infusion medicine information and infusion positions; the patient information comprises the name, the identification card number and standard face image information of the patient; the infusion position is the position of the patient.
Further, the task allocation module comprises the following specific working steps:
step one: acquiring information of all infusion medicines in an infusion task; a nursing staff takes the transfusion medicine corresponding to the transfusion task through the mobile phone terminal and marks the nursing staff taking the transfusion medicine corresponding to the transfusion task as a primary selection staff;
step two: calculating the distance difference between the position of the primary selector and the infusion position to obtain an infusion distance and marking the infusion distance as L1;
performing time difference calculation on the time of the primary selection personnel and the current time of the system to obtain the time of the primary selection personnel, and marking the time as T1;
step three: collecting 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 selection personnel wear glasses according to the real-time face image information, and if the primary selection personnel wear the glasses, enabling SD to be 1; if the primary selection personnel do not wear glasses; let sd=0;
acquiring registration information of a primary selection person, and judging whether the primary selection person is short-sighted; the method comprises the following steps:
obtaining vision values of two eyes of a primary selection person; if the vision values of the two eyes are both larger than 1, the primary selection personnel are not myopic; otherwise, the primary selection personnel is short-sighted;
if the primary selection person is near-sighted, making SC=0, and if the primary selection person is not near-sighted, making SC=1;
step four: the rest value of the primary selection personnel on the day before the current time of the system is obtained and marked as X1; setting the total number of times of transfusion 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 time of the previous day;
step five: using the formula
Obtaining an infusion and distribution value SP of a primary selector by SP= [ 1/L1xa1+T1xa2+ (SD+SC) xa3+x1xa4+C1xa5- |N1-30|xa6 ]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH is expressed as an assessment influence coefficient of the primary selector;
step six: and selecting the primary person with the largest transmission and distribution value as the selected person of the transfusion task.
Further, the specific monitoring steps of the infusion monitoring module are as follows:
v1: the infusion monitoring module receives the real-time face image information of the patient and the medicine picture sent by the selected person, matches the real-time face image information of the patient with the corresponding standard face image information of the patient in the infusion task, and matches the medicine picture with the corresponding infusion medicine information in the infusion task; if both the two items are matched; generating a start-up signal;
v2: after receiving the working starting signal, the infusion monitoring module performs face recognition on the selected person, and after the face recognition is passed; the infusion monitoring module monitors venipuncture of selected personnel; if the face recognition does not pass, generating an early warning signal;
v3: the selected personnel start to carry out venipuncture on the patient, and in the process of venipuncture, the sign data of the patient are collected in real time and marked as target sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; the change condition of the physical sign data is used for measuring the experience of patients on venipuncture; the physical sign data comprise body temperature, heart rate, blood pressure value, perspiration and the like;
marking each corresponding sign parameter value in the normal sign data as a sign data normal value Z1i; i=1.. n; wherein i represents the ith sign parameter;
acquiring target sign data of t time after start of venipuncture; marking each corresponding sign parameter value in the target sign data as a sign data target value Z2i; wherein Z1i corresponds to Z2i one by one;
each of the sign parameters has different weights, H1, H2, … …, hj, H1 > H2 > … … > Hj, and h1+h2+ … … +hj=1; wherein i corresponds to j one by one;
according to the change of the patient sign data, the somatosensory value of the patient to the venipuncture is calculated, and the specific calculation formula is as follows:wherein Y is expressed as 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, reminding a selected person to pay attention to the current unstable emotion of the patient, and reminding the selected person to pacify the patient, wherein the intravenous puncture response is larger; until the somatosensory value Y is less than or equal to the somatosensory threshold;
v5: calculating the time difference between the start time and the end time of venipuncture to obtain the puncture time length and marking the puncture time length as CT1; counting the number of times of venipuncture in the venipuncture process, wherein the number of times of venipuncture is marked as CT2; collecting a graph of the change of the somatosensory value Y along with time in the venipuncture process;
and fusing the graph of the puncture duration, the venipuncture times and the motion sensing value Y which changes along with time in the venipuncture process to form an infusion record of the selected person, and transmitting the infusion record to a server, wherein the server is used for transmitting the infusion record with a time stamp to a storage module for storage.
The beneficial effects of the invention are as follows:
1. the task distribution module is used for distributing corresponding selected personnel from nursing personnel who get the infusion task to carry out the infusion task; marking a nursing staff for taking the transfusion medicine corresponding to the transfusion task as a primary selection staff; calculating the infusion interval, the time length of entering, whether to wear glasses, whether to myopia, the rest value, the total number of times of infusion and the age to obtain the infusion value of the primary selection personnel: the primary selection personnel with the largest transmission and distribution value is selected as the selection personnel of the transfusion task; the corresponding nursing staff can be reasonably selected 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 enabling the venipuncture to be successful as much as possible;
2. the infusion monitoring module is used for monitoring venipuncture of selected personnel; in the venipuncture process, the physical sign data of a patient are collected in real time, the somatosensory value of the patient on venipuncture is calculated according to the change of the physical sign data, and the specific calculation formula is as follows:if the somatosensory value Y is larger than the somatosensory threshold, reminding a selected person to pay attention to the current unstable emotion of the patient, and reminding the selected person to pacify the patient, wherein the intravenous puncture response is larger; until the somatosensory value Y is less than or equal to the somatosensory threshold; improving the experience of the patient; the pain of the patient is relieved, and the fear, pain and other bad moods of the patient are relieved;
3. the personnel checking module is used for acquiring and analyzing the infusion records of the nursing personnel and checking the venipuncture skills of the nursing personnel; if the intravenous puncture skill examination result is not qualified, the corresponding nursing staff needs to train the intravenous puncture skill again; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and improving the service quality.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
Fig. 1 is a system block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in FIG. 1, the intelligent medical management system based on the 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 registration login module is used for a nursing staff to input registration information for registration and transmit the registration information to the server for storage, wherein the registration information comprises a name, an age, an identity card number, time for entering and vision values of two eyes;
the task issuing module is used for issuing an infusion task by a doctor and a nursing staff accessing the task issuing module through the mobile phone terminal and acquiring the infusion task; the infusion task information comprises patient information, infusion medicine information and infusion positions; the patient information comprises the name, the identification card number and standard face image information of the patient; the transfusion position is the position of the patient;
the task distribution module is used for distributing corresponding selected personnel from nursing personnel who pick up the infusion task to carry out the infusion task; the task allocation module comprises the following specific working steps:
step one: acquiring information of all infusion medicines in an infusion task; a nursing staff takes the transfusion medicine corresponding to the transfusion task through the mobile phone terminal and marks the nursing staff taking the transfusion medicine corresponding to the transfusion task as a primary selection staff;
step two: calculating the distance difference between the position of the primary selector and the infusion position to obtain an infusion distance and marking the infusion distance as L1;
performing time difference calculation on the time of the primary selection personnel and the current time of the system to obtain the time of the primary selection personnel, and marking the time as T1;
step three: collecting 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 selection personnel wear glasses according to the real-time face image information, and if the primary selection personnel wear the glasses, enabling SD to be 1; if the primary selection personnel do not wear glasses; let sd=0;
acquiring registration information of a primary selection person, and judging whether the primary selection person is short-sighted; the method comprises the following steps:
obtaining vision values of two eyes of a primary selection person; if the vision values of the two eyes are both larger than 1, the primary selection personnel are not myopic; otherwise, the primary selection personnel is short-sighted;
if the primary selection person is near-sighted, making SC=0, and if the primary selection person is not near-sighted, making SC=1;
step four: the rest value of the primary selection personnel on the day before the current time of the system is obtained and marked as X1; setting the total number of times of transfusion 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 the formula
Obtaining an infusion and distribution value SP of a primary selector by SP= [ 1/L1xa1+T1xa2+ (SD+SC) xa3+x1xa4+C1xa5- |N1-30|xa6 ]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH is expressed as an assessment influence coefficient of the primary selector; for example, a1 takes on 0.11, a2 takes on 0.19, a3 takes on 0.45, a4 takes on 0.35, a5 takes on 0.28, a6 takes on 0.62;
in the formula, if the primary selection personnel are not near-sighted or wear glasses, the primary selection personnel are shown to see more clearly, the more accurate the puncture vein is correspondingly found, the larger the rest value of the primary selection personnel in the previous day is, the more full the spirit of the primary selection personnel is, the more accurate the puncture vein is correspondingly found, and the higher the efficiency is;
step six: the primary selection personnel with the largest transmission and distribution value is selected as the selection personnel of the transfusion task; the infusion task information is sent to a mobile phone terminal of the selected person;
the infusion monitoring module is used for monitoring venipuncture of selected personnel, and comprises the following specific monitoring steps:
v1: the infusion monitoring module receives the real-time face image information of the patient and the medicine picture sent by the selected person, matches the real-time face image information of the patient with the corresponding standard face image information of the patient in the infusion task, and matches the medicine picture with the corresponding infusion medicine information in the infusion task; if both the two items are matched; generating a start working signal so as to ensure that a patient who performs infusion (venipuncture) and a corresponding medicine are free of errors, 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 selected personnel; if the face recognition does not pass, generating an early warning signal; thereby avoiding the random intravenous puncture of irrelevant personnel and ensuring the medical safety;
v3: the selected personnel start to carry out venipuncture on the patient, and in the process of venipuncture, the sign data of the patient are collected in real time and marked as target sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; the change condition of the physical sign data is used for measuring the experience of patients on venipuncture; the physical sign data comprise body temperature, heart rate, blood pressure value, perspiration and the like;
marking each corresponding sign parameter value in the normal sign data as a sign data normal value Z1i; i=1.. n; wherein i represents the ith sign parameter;
acquiring target sign data of t time after start of venipuncture; marking each corresponding sign parameter value in the target sign data as a sign data target value Z2i; wherein Z1i corresponds to Z2i one by one;
each of the sign parameters has different weights, H1, H2, … …, hj, H1 > H2 > … … > Hj, and h1+h2+ … … +hj=1; wherein i corresponds to j one by one;
according to the change of the patient sign data, the somatosensory value of the patient to the venipuncture is calculated, and the specific calculation formula is as follows:wherein Y is expressed as the somatosensory value of the patient to venipuncture; the larger Y is, the more the patient's response to venipuncture is, the more the mood is unstable;
v4: comparing the somatosensory value Y with a somatosensory threshold;
if the somatosensory value Y is larger than the somatosensory threshold, reminding a selected person to pay attention to the current unstable emotion of the patient, and reminding the selected person to pacify the patient, wherein the intravenous puncture response is larger; until the somatosensory value Y is less than or equal to the somatosensory threshold;
v5: calculating the time difference between the start time and the end time of venipuncture to obtain the puncture time length and marking the puncture time length as CT1; counting the number of times of venipuncture in the venipuncture process, wherein the number of times of venipuncture is marked as CT2; collecting a graph of the change of the somatosensory value Y along with time in the venipuncture process; the puncture duration, the venipuncture times and the graph of the motion sensing value Y changing along with time in the venipuncture process are fused to form an infusion record of a selected person, the infusion record is transmitted to a server, and the server is used for transmitting the infusion record with a time stamp to a storage module for storage;
the personnel checking module is used for acquiring and analyzing the infusion records of the nursing personnel and checking the venipuncture skills of the nursing personnel; the specific analysis steps are as follows:
VV1: collecting infusion records of nursing staff ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;
VV2: obtaining a graph of corresponding puncture time length, venipuncture times and change of a somatosensory value Y along with time in a venipuncture process in an infusion record;
marking the number of venipuncture times at each infusion as Cp; when Cp is larger than the puncture frequency threshold, marking the number of times of venipuncture as the number of times of influencing puncture, counting the number of times of influencing puncture and marking as the frequency of influence YP; the puncture frequency threshold value is 1;
performing difference value calculation on the puncture frequency and the puncture frequency threshold to obtain a super-frequency value YT;
setting the super coefficient as Hm, m=1, 2, … …, k; k is a positive integer; wherein H1 is more than H2 and less than … … and less than Hk; each super coefficient Hm corresponds to a preset super value range, and specifically: the preset super-value range corresponding to H1 is (0, H1), the preset super-value range corresponding to H2 is (H1, H2), the preset super-value range corresponding to … … and Hk is (Hk-1, hk), wherein 0 < H1 < H2 < … … < Hk;
when YT is E (Hm-1, hm), the corresponding super coefficient is Hm;
obtaining an influence value M1 corresponding to the super-order value by using a formula M1=YT×Hm; summing all the influence values corresponding to the super-order values to obtain a super-order influence total value M2;
summing the puncture time lengths and taking an average value to obtain an average puncture time length, and marking the average puncture time length as WT;
comparing the somatosensory value Y with a somatosensory threshold; counting the duration that the somatosensory value Y is greater than the somatosensory threshold and marking the duration as oversensitive duration; summing the hypersensitive duration, taking an average value to obtain an average hypersensitive duration, and marking the average hypersensitive duration as GT;
VV3: obtaining an assessment influence coefficient KH of a nursing staff by using a formula KH=YT×b1+M2×b2+WT×b3+GT×b4; wherein b1, b2, b3 and b4 are all proportionality coefficients; for example, b1 takes on a value of 0.15, b2 takes on a value of 0.44, b3 takes on a value of 0.35, b4 takes on a value of 0.39; the greater the assessment influence coefficient KH is, the worse the intravenous puncture skill assessment result of the nursing staff is indicated;
VV4: comparing the assessment influence coefficient KH with a coefficient threshold;
if the assessment influence coefficient KH is more than or equal to the coefficient threshold, the assessment result of the intravenous puncture skill of the nursing staff is not qualified; the nursing staff needs to train the venipuncture skill again; thereby improving the accuracy and the puncture efficiency of venipuncture, ensuring accurate transfusion and enabling the venipuncture to be successful as much as possible; the pain of the patient is relieved, and the fear, pain and other bad moods 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 with a time stamp; the display module is used for displaying the intravenous puncture skill assessment result of the nursing staff, and the administrator and other nursing staff can check the assessment result through the display module, so that objective evaluation is carried out on the nursing staff, the administrator can conveniently carry out targeted training on the nursing staff, and secondly, the other nursing staff can check and improve themselves according to the assessment result, so that common progress of all staff is promoted, and the service quality is improved.
The working principle of the invention is as follows:
the intelligent medical management system based on the 5G network is characterized in that when in work, the task issuing module is used for issuing an infusion task by a doctor and a nursing staff accesses the task issuing module through a mobile phone terminal and obtains the infusion task; the task distribution module is used for distributing corresponding selected persons from nursing staff for picking up infusion tasks to carry out infusion tasks; marking a nursing staff for taking the transfusion medicine corresponding to the transfusion task as a primary selection staff; calculating the infusion interval, the time length of entering, whether to wear glasses, whether to myopia, the rest value, the total number of times of infusion and the age to obtain the infusion value of the primary selection personnel: the primary selection personnel with the largest transmission and distribution value is selected as the selection personnel of the transfusion task; the corresponding nursing staff can be reasonably selected 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 enabling the venipuncture to be successful as much as possible;
the infusion monitoring module is used for monitoring venipuncture of selected personnel, and before the venipuncture, the infusion monitoring module firstly shoots real-time face image information of a patient and a medicine picture and performs information matching; thereby ensuring that the patient who performs infusion (venipuncture) and the corresponding medicine have no errors, ensuring accurate infusion and preventing errors; then, face recognition is carried out on the selected person, so that the situation that unrelated persons randomly carry out venipuncture is avoided, and medical safety is ensured; in the venipuncture process, the physical sign data of the patient are collected in real time, and the somatosensory value of the patient on the venipuncture is calculated according to the change of the physical sign dataThe specific calculation formula is as follows:if the somatosensory value Y is larger than the somatosensory threshold, reminding a selected person to pay attention to the current unstable emotion of the patient, and reminding the selected person to pacify the patient, wherein the intravenous puncture response is larger; until the somatosensory value Y is less than or equal to the somatosensory threshold; improving the experience of the patient; the pain of the patient is relieved, and the fear, pain and other bad moods of the patient are relieved;
the personnel checking module is used for acquiring and analyzing the infusion records of the nursing personnel and checking the venipuncture skills of the nursing personnel; if the intravenous puncture skill examination result is not qualified, the corresponding nursing staff needs to train the intravenous puncture skill 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 obtained by acquiring a large amount of data to perform software simulation and corresponding experts to perform parameter setting processing. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form 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 understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (2)
1. The intelligent medical management system based on the 5G network is characterized by comprising a registration login module, a task release module, a server, a task distribution 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 a nursing staff accessing the task issuing module through a mobile phone terminal and acquiring the infusion task;
the task distribution module is used for distributing corresponding selected persons from nursing staff for picking up infusion tasks to carry out infusion tasks; the specific working steps are as follows:
step one: acquiring information of all infusion medicines in an infusion task; a nursing staff takes the transfusion medicine corresponding to the transfusion task through the mobile phone terminal and marks the nursing staff taking the transfusion medicine corresponding to the transfusion task as a primary selection staff;
step two: calculating the distance difference between the position of the primary selector and the infusion position to obtain an infusion distance and marking the infusion distance as L1; performing time difference calculation on the time of the primary selection personnel and the current time of the system to obtain the time of the primary selection personnel, and marking the time as T1;
step three: collecting 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 selection personnel wear glasses according to the real-time face image information, and if the primary selection personnel wear the glasses, enabling SD to be 1; if the primary selection personnel do not wear glasses; let sd=0;
acquiring registration information of a primary selection person, and judging whether the primary selection person is short-sighted; the method comprises the following steps:
obtaining vision values of two eyes of a primary selection person; if the vision values of the two eyes are both larger than 1, the primary selection personnel are not myopic; otherwise, the primary selection personnel is short-sighted;
if the primary selection person is near-sighted, making SC=0, and if the primary selection person is not near-sighted, making SC=1;
step four: the rest value of the primary selection personnel on the day before the current time of the system is obtained and marked as X1; setting the total number of times of transfusion 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 time of the previous day;
step five: obtaining an input and output value SP of the primary selection personnel by using a formula SP= [ 1/L1xa1+T1xa2+ (SD+SC) xa3+x1xa4+C1xa5- |N1-30|xa6 ]/KH, wherein a1, a2, a3, a4, a5 and a6 are all proportionality coefficients, and KH is expressed as an assessment influence coefficient of the primary selection personnel;
step six: the primary selection personnel with the largest transmission and distribution value is selected as the selection personnel of the transfusion task, and transfusion task information is sent to the mobile phone terminal of the selection personnel;
the infusion monitoring module is used for monitoring venipuncture of selected personnel and obtaining infusion records of the selected personnel; the specific monitoring steps are as follows:
v1: the selected personnel receives the information of the infusion task collected and detected through the mobile phone terminal, arrives at the infusion site, shoots real-time face image information and medicine pictures of the patient through the mobile phone terminal and sends the real-time face image information and medicine pictures to the infusion monitoring module; after receiving the real-time face image information and the medicine image of the patient sent by the selected person, the infusion monitoring module matches the real-time face image information of the patient with the corresponding standard face image information of the patient in the infusion task, and matches the medicine image with the corresponding infusion medicine information in the infusion task;
if both the two items are matched; generating a start-up signal;
v2: after receiving the working starting signal, the infusion monitoring module performs face recognition on the selected person, and after the face recognition is passed; the infusion monitoring module monitors venipuncture of selected personnel; if the face recognition does not pass, generating an early warning signal;
v3: the selected personnel start to carry out venipuncture on the patient, and in the process of venipuncture, the sign data of the patient are collected in real time and marked as target sign data; collecting sign data of a patient before venipuncture, and marking the sign data as normal sign data; the change condition of the physical sign data is used for measuring the experience of patients on venipuncture; the physical sign data comprises body temperature, heart rate, blood pressure value and perspiration;
marking each corresponding sign parameter value in the normal sign data as a sign data normal value Z1i; i=1.. n; wherein i represents the ith sign parameter;
acquiring target sign data of t time after start of venipuncture; marking each corresponding sign parameter value in the target sign data as a sign data target value Z2i; wherein Z1i corresponds to Z2i one by one;
each of the sign parameters has different weights, H1, H2, … …, hj, H1 > H2 > … … > Hj, and h1+h2+ … … +hj=1; wherein i corresponds to j one by one;
according to the change of the patient sign data, the somatosensory value of the patient to the venipuncture is calculated, and the specific calculation formula is as follows:the method comprises the steps of carrying out a first treatment on the surface of the Wherein Y is expressed as 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, reminding a selected person to pay attention to the current unstable emotion of the patient, and reminding the selected person to pacify the patient, wherein the intravenous puncture response is larger; until the somatosensory value Y is less than or equal to the somatosensory threshold;
v5: calculating the time difference between the start time and the end time of venipuncture to obtain the puncture time length and marking the puncture time length as CT1; counting the number of times of venipuncture in the venipuncture process, wherein the number of times of venipuncture is marked as CT2; collecting a graph of the change of the somatosensory value Y along with time in the venipuncture process;
the method comprises the steps that graphs of puncture duration, venipuncture times and motion sensing value Y changing along with time in the venipuncture process are fused to form infusion records of selected personnel, the infusion records are transmitted to a server, and the server is used for transmitting the infusion records with time stamps to a storage module for storage;
the staff assessment module is used for acquiring and analyzing infusion records of nursing staff and assessing venipuncture skills of the nursing staff; the specific analysis steps are as follows:
VV1: collecting infusion records of nursing staff ten days before the current time of the system; counting the total number of infusion records and marking as infusion frequency P1;
VV2: obtaining a graph of corresponding puncture time length, venipuncture times and change of a somatosensory value Y along with time in a venipuncture process in an infusion record;
marking the number of venipuncture times at each infusion as Cp; when Cp is larger than the puncture frequency threshold, marking the number of times of venipuncture as the number of times of influencing puncture, counting the number of times of influencing puncture and marking as the frequency of influence YP; the puncture frequency threshold value is 1;
performing difference value calculation on the puncture frequency and the puncture frequency threshold to obtain a super-frequency value YT;
setting the super coefficient as Hm, m=1, 2, … …, k; k is a positive integer; wherein H1 is more than H2 and less than … … and less than Hk; each super coefficient Hm corresponds to a preset super value range, and specifically: the preset super-value range corresponding to H1 is (0, H1), the preset super-value range corresponding to H2 is (H1, H2), the preset super-value range corresponding to … … and Hk is (Hk-1, hk), wherein 0 < H1 < H2 < … … < Hk;
when YT is E (Hm-1, hm), the corresponding super coefficient is Hm;
obtaining an influence value M1 corresponding to the super-order value by using a formula M1=YT×Hm; summing all the influence values corresponding to the super-order values to obtain a super-order influence total value M2;
summing the puncture time lengths and taking an average value to obtain an average puncture time length, and marking the average puncture time length as WT;
comparing the somatosensory value Y with a somatosensory threshold; counting the duration that the somatosensory value Y is greater than the somatosensory threshold and marking the duration as oversensitive duration; summing the hypersensitive duration, taking an average value to obtain an average hypersensitive duration, and marking the average hypersensitive duration as GT;
VV3: obtaining an assessment influence coefficient KH of a nursing staff by using a formula KH=YT×b1+M2×b2+WT×b3+GT×b4; wherein b1, b2, b3 and b4 are all proportionality coefficients;
VV4: comparing the assessment influence coefficient KH with a coefficient threshold;
if the assessment influence coefficient KH is more than or equal to the coefficient threshold, the assessment result of the intravenous puncture skill of the nursing staff is not qualified; the nursing staff needs to train the venipuncture skill again;
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 with a time stamp.
2. The 5G network-based intelligent medical management system of claim 1, wherein the registration login module is configured to enter registration information for registration by a caregiver and transmit the registration information to a server for storage, the registration information including a name, an age, an identification number, a time of job entry, and a vision value of both eyes; the infusion task information comprises patient information, infusion medicine information and infusion positions; the patient information comprises the name, the identification card number and standard face image information of the patient; the infusion position is the position of the patient.
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