CN117877664A - Intelligent nursing management system based on 5G Internet of things - Google Patents
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Abstract
The invention discloses an intelligent nursing management system based on a 5G Internet of things, which relates to the field of medical care and comprises a management center, wherein the management center is in communication connection with an information management module, a nursing monitoring module and a nursing early warning module; acquiring nursing information of a patient, processing the acquired nursing information, acquiring physiological data to be monitored and acquiring the physiological data; performing standard evaluation on the acquisition process of the physiological data to obtain corresponding physiological standard coefficients, analyzing the acquired physiological data to obtain corresponding physiological coefficients, and combining the obtained physiological standard coefficients and the physiological coefficients to obtain corresponding nursing indexes; judging whether the state of the patient is abnormal or not according to the obtained nursing index, generating corresponding early warning information if the state of the patient is abnormal, and matching the corresponding emergency nursing plan according to the obtained early warning information.
Description
Technical Field
The invention relates to the field of medical care, in particular to an intelligent care management system based on a 5G Internet of things.
Background
With the development of 5G communication technology, the high-bandwidth and low-delay characteristics of the technology provide a wider application space for internet of things (IoT).
Compared with the prior art, in the traditional nursing process, when the physiological data of a patient is monitored and managed, the physiological data of the patient is often measured in a mode of artificial memory, so that the method has great subjectivity, the problems of untimely measurement and the like caused by negligence of nursing staff are easy to occur, the labor intensity is high, and mistakes are easy to occur; in addition, the traditional method has limitations in terms of instantaneity, accuracy and efficiency, and is difficult to meet the current demands for efficient and accurate medical services, which are problems to be solved by us, and therefore, the intelligent nursing management system based on the 5G Internet of things is provided.
Disclosure of Invention
The invention aims to provide an intelligent nursing management system based on the 5G Internet of things.
The aim of the invention can be achieved by the following technical scheme: the intelligent nursing management system based on the 5G Internet of things comprises a management center, wherein the management center is in communication connection with an information management module, a nursing monitoring module and a nursing early warning module;
the information management module is used for acquiring nursing information of a patient, processing the acquired nursing information, acquiring physiological data to be monitored and acquiring the physiological data;
the nursing monitoring module is used for carrying out standard evaluation on the acquisition process of the physiological data to obtain corresponding physiological standard coefficients, analyzing the acquired physiological data to obtain corresponding physiological coefficients, and obtaining corresponding nursing indexes by combining the obtained physiological standard coefficients and the physiological coefficients;
the nursing early warning module is used for judging whether the state of the patient is abnormal according to the acquired nursing index, generating corresponding early warning information if the state of the patient is abnormal, and matching the corresponding emergency nursing plan according to the acquired early warning information.
Further, the process of the information management module obtaining the nursing information of the patient includes:
the information management module is internally provided with an information acquisition unit, an image acquisition unit and a database; acquiring medical history information of a patient through the image acquisition unit, wherein the medical history information comprises self-description of the patient at the time of the visit of a corresponding medical institution, the visit record of the patient at the time of the visit of the corresponding medical institution and the past medical history of the patient, the visit record comprises the visit time, the visit place, the diagnosis result, the treatment scheme and the like of the patient, and the past medical history comprises but is not limited to the medical history, the allergy history, the medication history and the family genetic history of the patient;
collecting emotion data of a corresponding patient by the image collecting unit, wherein the emotion data comprises but is not limited to facial expressions, sound tones and action postures of the patient;
collecting the acquired medical history information and emotion data, obtaining corresponding nursing information, and uploading the nursing information to a database for storage through a 5G network;
further, the process of the information management module processing the obtained nursing information, obtaining physiological data to be monitored according to the processing result and collecting the physiological data includes:
reading the past medical history in the obtained medical history information, determining vital sign data for monitoring the patient according to the past medical history of the patient, and recording the vital sign data as initial vital sign data;
further reading the obtained visit record, determining the disease type of the patient according to the visit record, and determining physiological data to be monitored for the patient by combining the obtained initialized vital sign data; for example, some conditions such as asthma or heart disease may suddenly worsen, and the respiration or heart rate of the patient should be closely monitored to prevent exacerbation, and for example, the patient is receiving certain treatments which may cause side effects, such as chemotherapy or certain antibiotics, and corresponding sign data such as blood routine or liver function should be monitored;
setting a data acquisition node and a monitoring period, and acquiring physiological data of a patient through the data acquisition node in the monitoring period to obtain corresponding physiological data, wherein the physiological data comprises but is not limited to heart rate, respiratory rate, body temperature and blood pressure; and recording the corresponding acquisition process to obtain a corresponding recording result, wherein the recording result comprises the time interval of each index data acquisition in the physiological data, the actual acquisition times and the measured value of the specific physiological data.
Further, the process of the nursing monitoring module for carrying out standard evaluation on the acquisition process of the physiological data and obtaining the corresponding physiological standard coefficient comprises the following steps:
reading the obtained recording result, obtaining the actual time interval when each index data in the physiological data of the corresponding patient is acquired, marking the longest acquisition time interval in the corresponding time interval, and marking the longest heart rate acquisition time interval, the longest body temperature acquisition time interval, the longest respiratory rate acquisition time interval and the longest blood pressure acquisition time interval as Txlmax, ttwmax, thxmax and Txymax respectively; calculating a corresponding first acquisition standard index according to the first acquisition standard index, and marking the first acquisition standard index as B1;
wherein,；
wherein; txl, ttw, thx, txy the set heart rate acquisition time interval, body temperature acquisition time interval, respiratory rate acquisition time interval and blood pressure acquisition time interval;
c1, C2, C3 and C4 respectively represent correction coefficients corresponding to the set heart rate acquisition time interval, body temperature acquisition time interval, respiratory frequency acquisition time interval and blood pressure acquisition time interval;
acquiring actual acquisition times of each index data in physiological data in a corresponding monitoring period, and marking the actual heart rate acquisition times, the actual body temperature acquisition times, the actual respiratory rate acquisition times and the actual blood pressure acquisition times as R1, R2, R3 and R4 respectively; and calculating a corresponding second acquisition standard index according to the first acquisition standard index, and marking the second acquisition standard index as B2, wherein a corresponding mathematical calculation formula is as follows:；
wherein Rxl, rtw, rhx, rxy respectively represents the heart rate minimum acquisition times, the body temperature minimum acquisition times, the respiratory frequency minimum acquisition times and the blood pressure minimum acquisition times which are set in the corresponding monitoring period; c5, c6, c7 and c8 respectively represent the weight coefficients corresponding to the heart rate minimum acquisition times, the body temperature minimum acquisition times, the respiratory frequency minimum acquisition times and the blood pressure minimum acquisition times;
obtaining corresponding physiological normative coefficients according to the obtained first acquisition standard index and the second acquisition standard index, and representing the physiological normative coefficients as SG, wherein,the method comprises the steps of carrying out a first treatment on the surface of the Wherein λ1 and λ2 respectively represent the weight coefficients of the first standard index and the second standard index;
further, the nursing monitoring module analyzes the collected physiological data, and the process of obtaining the corresponding physiological coefficient includes:
reading physiological data acquired in a corresponding monitoring period, numbering the acquired physiological data, and marking the physiological data as i, wherein i=1, 2, … …, n, n is more than 0 and n is an integer; the physiological data in the corresponding monitoring period can be expressed as heart rate XLi, respiratory rate HXi, body temperature TWi, and blood pressure XYi, respectively;
obtaining a corresponding heart rate index according to the obtained heart rate of the patient, and marking the heart rate index as xl;
wherein,；
wherein XLmax and XLmin respectively represent a preset highest heart rate value and a preset lowest heart rate value;
the corresponding respiratory index, blood pressure index and body temperature index are respectively obtained by adopting the same method; the obtained respiratory index, blood pressure index and body temperature index are respectively marked as hx, xy and tw; further, according to the obtained physiological coefficient, the obtained physiological coefficient is marked as SL;
wherein,；
wherein a1, a2, a3 and a4 respectively represent weight coefficients of heart rate index, respiratory index, blood pressure index and body temperature index, and b1, b2, b3 and b4 respectively represent slimming coefficients of heart rate index, respiratory index, blood pressure index and body temperature index, wherein the weight coefficients and the slimming coefficients are determined according to actual requirements;
further, the nursing early warning module obtains a corresponding nursing index according to the obtained physiological coefficient and the physiological standard coefficient, generates corresponding early warning information according to the obtained nursing index, and the process of matching the corresponding nursing plan with the nursing information of the patient comprises the following steps:
the obtained physiological coefficients and physiological normative coefficients are weighted and summed to obtain corresponding care indices, which are labeled HL, wherein,the method comprises the steps of carrying out a first treatment on the surface of the Wherein, beta 1 and beta 2 are respectively the weight values of physiological standard coefficients and physiological coefficients;
setting a nursing threshold range, and comparing the acquired nursing index with a corresponding nursing threshold range;
if the nursing index is within the range of the nursing threshold value, the existing nursing plan is reserved, and corresponding nursing staff is reminded to execute corresponding nursing operation according to the existing nursing plan;
if the nursing index is out of the range of the nursing threshold value, marking the corresponding patient as an early-warning patient, generating corresponding early-warning information and feeding the corresponding early-warning information back to the management center;
after receiving the early warning information, the management center acquires the physiological coefficient of the corresponding patient, compares the acquired physiological coefficient with a preset physiological threshold value, and determines the physiological early warning level of the corresponding patient according to the comparison result, wherein the physiological level comprises primary early warning and secondary early warning;
matching corresponding emergency care plans according to the physiological pre-warning levels of the patients and combining with the nursing information of the corresponding patients, carrying out corresponding pre-warning according to the obtained physiological pre-warning levels so as to remind corresponding nursing staff, and synchronously feeding back the existing care plans and the emergency care plans of the corresponding patients to the nursing staff so as to carry out emergency care on the corresponding patients; wherein the emergency care plan comprises a primary care plan and a secondary care plan, and the primary emergency care plan refers to a care plan for treating sudden diseases; secondary care refers to care regimens for chronic diseases;
the acquisition process of the preset physiological threshold value comprises the following steps:
according to the index threshold value corresponding to each index data in the big data, the emotion data of the corresponding patient is read, the current happiness degree of the corresponding patient is obtained according to the obtained emotion data, then the corresponding index threshold value is adjusted according to the happiness degree of the patient, and after the adjustment is completed, the corresponding physiological threshold value is obtained according to the weight coefficient and the correction coefficient and by combining the obtained index threshold value.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the physiological data of the patient is monitored, the heart rate index, the respiratory index, the body temperature index and the blood pressure index of the patient are obtained through analysis, and the physiological index of the patient is obtained through analysis, so that the judgment of the illness state of the patient is improved, and effective help is provided for making a corresponding nursing plan;
2. the invention is beneficial to reducing deviation and errors caused by human factors by carrying out standard evaluation on the process of collecting the physiological data of the patient, is beneficial to improving the nursing quality and efficiency of the patient, and improves the response speed of abnormal physiological data;
3. the index threshold value of each index data in the physiological data is properly adjusted according to the emotion data of the patient, so that the accuracy of judging the physiological data of the patient is improved, and the occurrence of misjudgment is reduced.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
As shown in fig. 1, the intelligent nursing management system based on the 5G internet of things comprises a management center, wherein the management center is in communication connection with an information management module, a nursing monitoring module and a nursing early warning module;
the information management module is used for acquiring nursing information of a patient, processing the acquired nursing information, acquiring physiological data to be monitored and acquiring the physiological data;
the nursing monitoring module is used for carrying out standard evaluation on the acquisition process of the physiological data to obtain corresponding physiological standard coefficients, analyzing the acquired physiological data to obtain corresponding physiological coefficients, and obtaining corresponding nursing indexes by combining the obtained physiological standard coefficients and the physiological coefficients;
the nursing early warning module is used for judging whether the state of the patient is abnormal according to the acquired nursing index, generating corresponding early warning information if the state of the patient is abnormal, and matching a corresponding emergency nursing plan according to the acquired early warning information;
it should be further noted that, in the implementation process, the process of obtaining the care information of the patient by the information management module includes:
the information management module is internally provided with an information acquisition unit, an image acquisition unit and a database; collecting medical history information of a patient through the information collecting unit, wherein the medical history information comprises self-description of the patient at the time of the visit of a corresponding medical institution, the visit record of the patient at the time of the visit of the corresponding medical institution and the past medical history of the patient, the visit record comprises the visit time, the visit place, the diagnosis result, the treatment scheme and the like of the patient, and the past medical history comprises but is not limited to the medical history, the allergy history, the medication history and the family genetic history of the patient;
collecting emotion data of a corresponding patient by the image collecting unit, wherein the emotion data comprises but is not limited to facial expressions, sound tones and action postures of the patient;
collecting the acquired medical history information and emotion data, obtaining corresponding nursing information, and uploading the nursing information to a database for storage through a 5G network;
it should be further noted that, in the specific implementation process, the information management module processes the obtained care information, and the process of obtaining the physiological data to be monitored and collecting according to the processing result includes:
reading the past medical history in the obtained medical history information, determining vital sign data for monitoring the patient according to the past medical history of the patient, and recording the vital sign data as initial vital sign data;
further reading the obtained visit record, determining the disease type of the patient according to the visit record, and determining physiological data to be monitored for the patient by combining the obtained initialized vital sign data; for example, some conditions such as asthma or heart disease may suddenly worsen, and the respiration or heart rate of the patient should be closely monitored to prevent exacerbation, and for example, the patient is receiving certain treatments which may cause side effects, such as chemotherapy or certain antibiotics, and corresponding sign data such as blood routine or liver function should be monitored;
setting a data acquisition node and a monitoring period, and acquiring physiological data of a patient through the data acquisition node in the monitoring period to obtain corresponding physiological data, wherein the physiological data comprises but is not limited to heart rate, respiratory rate, body temperature and blood pressure; and recording the corresponding acquisition process to obtain a corresponding recording result, wherein the recording result comprises the time interval of each index data acquisition in the physiological data, the actual acquisition times and the measured value of the specific physiological data.
It should be further noted that, in the specific implementation process, the process of the care monitoring module performing standard evaluation on the physiological data acquisition process to obtain the corresponding physiological standard coefficient includes:
reading the obtained recording result, obtaining the actual time interval when each index data in the physiological data of the corresponding patient is acquired, marking the longest acquisition time interval in the corresponding time interval, and marking the longest heart rate acquisition time interval, the longest body temperature acquisition time interval, the longest respiratory rate acquisition time interval and the longest blood pressure acquisition time interval as T respectively xlmax 、T twmax 、T hxmax T is as follows xymax The method comprises the steps of carrying out a first treatment on the surface of the Calculating a corresponding first acquisition standard index according to the first acquisition standard index, and marking the first acquisition standard index as B1;
wherein,；
wherein T is xl 、T tw 、T hx 、T xy Respectively representing a set heart rate acquisition time interval, a body temperature acquisition time interval, a respiratory rate acquisition time interval and a blood pressure acquisition time interval;
c1, c2, c3 and c4 respectively represent correction coefficients corresponding to the set heart rate acquisition time interval, body temperature acquisition time interval, respiratory frequency acquisition time interval and blood pressure acquisition time interval;
acquiring actual acquisition times of each index data in physiological data in a corresponding monitoring period, and marking the actual heart rate acquisition times, the actual body temperature acquisition times, the actual respiratory rate acquisition times and the actual blood pressure acquisition times as R1, R2, R3 and R4 respectively; and calculating a corresponding second acquisition standard index according to the first acquisition standard index, and marking the second acquisition standard index as B2, wherein a corresponding mathematical calculation formula is as follows:；
wherein R is xl 、R tw 、R hx 、R xy Respectively representing the heart rate minimum acquisition times, the body temperature minimum acquisition times, the respiratory frequency minimum acquisition times and the blood pressure minimum acquisition times which are set in the corresponding monitoring period; c5, c6, c7 and c8 respectively represent the weight coefficients corresponding to the heart rate minimum acquisition times, the body temperature minimum acquisition times, the respiratory frequency minimum acquisition times and the blood pressure minimum acquisition times;
obtaining corresponding physiological normative coefficients according to the obtained first acquisition standard index and the second acquisition standard index, and representing the physiological normative coefficients as SG, wherein,the method comprises the steps of carrying out a first treatment on the surface of the Wherein λ1 and λ2 respectively represent the weight coefficients of the first standard index and the second standard index;
further, according to the invention, whether the corresponding physiological data acquisition process accords with the standard is judged through the two directions of the acquisition time interval in the process of acquiring the physiological data of the patient and the acquisition times in the corresponding monitoring period, compared with the traditional manual memory by nursing staff, the recording deviation and error are effectively reduced, the negligence or other adverse events caused by subjectivity of the nursing staff are reduced, and meanwhile, the early warning speed of the abnormality of the physiological data of the patient is effectively improved;
it should be further noted that, in the implementation process, the process of analyzing the collected physiological data by the care monitoring module to obtain the corresponding physiological coefficient includes:
reading physiological data acquired in a corresponding monitoring period, numbering the acquired physiological data, and marking the physiological data as i, wherein i=1, 2, … …, n, n is more than 0 and n is an integer; the physiological data in the corresponding monitoring period can then be represented as heart rate XL, respectively i Respiratory rate HX i Body temperature TW i Blood pressure XY i ；
Obtaining a corresponding heart rate index according to the obtained heart rate of the patient, and marking the heart rate index as xl;
wherein,；
in XL max 、XL min Respectively representing a preset highest heart rate value and a preset lowest heart rate value;
the corresponding respiratory index, blood pressure index and body temperature index are respectively obtained by adopting the same method; the obtained respiratory index, blood pressure index and body temperature index are respectively marked as hx, xy and tw; further, according to the obtained physiological coefficient, the obtained physiological coefficient is marked as SL;
wherein,；
wherein a1, a2, a3 and a4 respectively represent weight coefficients of heart rate index, respiratory index, blood pressure index and body temperature index, and b1, b2, b3 and b4 respectively represent slimming coefficients of heart rate index, respiratory index, blood pressure index and body temperature index, wherein the weight coefficients and the slimming coefficients are determined according to actual requirements;
it should be further noted that, in the implementation process, the nursing early warning module obtains a corresponding nursing index according to the obtained physiological coefficient and the physiological standard coefficient, generates corresponding early warning information according to the obtained nursing index, and the process of matching the corresponding nursing plan with the nursing information of the patient includes:
the obtained physiological coefficients and physiological normative coefficients are weighted and summed to obtain corresponding care indices, which are labeled HL, wherein,the method comprises the steps of carrying out a first treatment on the surface of the Wherein, beta 1 and beta 2 are respectively the weight values of physiological standard coefficients and physiological coefficients;
setting a nursing threshold range, and comparing the acquired nursing index with a corresponding nursing threshold range;
if the nursing index is in the range of the nursing threshold value, indicating that the state of the patient is free of any abnormality, reserving the existing nursing plan, and reminding corresponding nursing staff to execute corresponding nursing operation according to the existing nursing plan;
if the nursing index is out of the range of the nursing threshold value, indicating that the state of the corresponding patient is abnormal, marking the corresponding patient as an early-warning patient, generating corresponding early-warning information and feeding the corresponding early-warning information back to the management center;
after receiving the early warning information, the management center acquires the physiological coefficient of the corresponding patient, compares the acquired physiological coefficient with a preset physiological threshold value, and determines the physiological early warning level of the corresponding patient according to the comparison result, wherein the physiological level comprises primary early warning and secondary early warning;
matching corresponding emergency care plans according to the physiological pre-warning levels of the patients and combining with the nursing information of the corresponding patients, carrying out corresponding pre-warning according to the obtained physiological pre-warning levels so as to remind corresponding nursing staff, and synchronously feeding back the existing care plans and the emergency care plans of the corresponding patients to the nursing staff so as to carry out emergency care on the corresponding patients; wherein the emergency care plan comprises a primary care plan and a secondary care plan, and the primary emergency care plan refers to a care plan for treating sudden diseases; secondary care refers to care regimens for chronic diseases;
it should be further noted that, in the implementation process, the process of obtaining the preset physiological threshold includes:
according to the index threshold value corresponding to each index data in the big data, the emotion data of the corresponding patient is read, the current happiness degree of the corresponding patient is obtained according to the obtained emotion data, then the corresponding index threshold value is adjusted according to the happiness degree of the patient, and after the adjustment is completed, the corresponding physiological threshold value is obtained according to the weight coefficient and the correction coefficient and by combining the obtained index threshold value.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. The intelligent nursing management system based on the 5G Internet of things comprises a management center, and is characterized in that the management center is in communication connection with an information management module, a nursing monitoring module and a nursing early warning module;
the information management module is used for acquiring nursing information of a patient, processing the acquired nursing information, acquiring physiological data to be monitored and acquiring the physiological data;
the nursing monitoring module is used for carrying out standard evaluation on the acquisition process of the physiological data to obtain corresponding physiological standard coefficients, analyzing the acquired physiological data to obtain corresponding physiological coefficients, and obtaining corresponding nursing indexes by combining the obtained physiological standard coefficients and the physiological coefficients;
the nursing early warning module is used for judging whether the state of the patient is abnormal according to the acquired nursing index, generating corresponding early warning information if the state of the patient is abnormal, and matching the corresponding emergency nursing plan according to the acquired early warning information.
2. The intelligent care management system based on the 5G internet of things of claim 1, wherein the process of the information management module obtaining the care information of the patient comprises:
the method comprises the steps of setting an information acquisition unit, an image acquisition unit and a database, and acquiring medical history information of a patient through the information acquisition unit, wherein the medical history information comprises a patient treatment record and a patient past medical history;
and acquiring emotion data of the corresponding patient through the image acquisition unit, summarizing the acquired medical history information and emotion data to obtain corresponding nursing information, and uploading the corresponding nursing information to a database through a 5G network for storage.
3. The intelligent care management system based on the 5G internet of things according to claim 2, wherein the process of processing the obtained care information to obtain the physiological data to be monitored comprises:
reading the obtained medical history information, determining vital sign data for monitoring the patient according to the medical history information of the patient, and recording the vital sign data as initial vital sign data;
reading the obtained visit record, determining the disease type of the patient according to the visit record, and determining the physiological data to be monitored of the patient by combining the obtained initial vital sign data.
4. The intelligent care management system based on the 5G internet of things of claim 3, wherein the process of collecting the obtained physiological data comprises:
setting a data acquisition node and a monitoring period, and acquiring physiological data of a patient through the data acquisition node in the monitoring period to obtain corresponding physiological data, and recording a corresponding acquisition process to obtain a corresponding recording result.
5. The intelligent nursing management system based on the 5G internet of things according to claim 4, wherein the care monitoring module performs a standard evaluation on the physiological data acquisition process, and the process of obtaining the corresponding physiological standard coefficient includes:
reading the obtained recording result, obtaining the actual time interval when each index data in the physiological data of the corresponding patient is acquired, and obtaining the corresponding first acquisition index by combining the set time interval when each index data in the physiological data is acquired;
acquiring actual acquisition times of each index data in the physiological data in the corresponding monitoring period, and acquiring a corresponding second acquisition index by combining the lowest acquisition times of each index data in the physiological data in the corresponding monitoring period;
and carrying out weighted summation on the obtained first acquisition index and the second acquisition index to obtain corresponding physiological normative coefficients.
6. The intelligent care management system based on the 5G internet of things according to claim 5, wherein the process of analyzing the collected physiological data by the information management module to obtain the corresponding physiological coefficient and obtaining the corresponding care index by combining the obtained physiological normative coefficient and the physiological coefficient comprises:
reading the acquired physiological data, obtaining heart rates of corresponding patients in each time period in a monitoring period, comparing the heart rates of each time period with a preset highest heart rate value and a preset lowest heart rate value, and obtaining corresponding heart rate indexes according to comparison results; the corresponding respiratory index, blood pressure index and body temperature index are respectively obtained by adopting the same method;
the obtained respiration index, blood pressure index, body temperature index and heart rate index are weighted and summed to obtain corresponding physiological coefficients;
and carrying out weighted summation on the obtained physiological coefficient and the physiological normative coefficient to obtain a corresponding nursing index.
7. The intelligent nursing management system based on the 5G internet of things according to claim 6, wherein the nursing early warning module judges whether the state of the patient is abnormal according to the obtained nursing index, and if so, the process of generating the corresponding early warning information includes:
setting a nursing threshold range, and comparing the acquired nursing index with a corresponding nursing threshold range; if the care index is within the care threshold range, the existing care plan is preserved; if the nursing index is out of the range of the nursing threshold value, marking the corresponding patient as an early-warning patient, generating corresponding early-warning information and feeding the corresponding early-warning information back to the management center.
8. The intelligent care management system based on the 5G internet of things of claim 7, wherein the process of matching the corresponding emergency care plan according to the obtained pre-warning information comprises:
when the management center receives the early warning information, the physiological coefficient of the corresponding patient is obtained, the obtained physiological coefficient is compared with a preset physiological threshold value, the physiological early warning level of the corresponding patient is determined according to the comparison result, the corresponding emergency care plan is matched according to the physiological early warning level of the patient and the nursing information of the corresponding patient, corresponding early warning is carried out according to the obtained physiological early warning level, so that corresponding nursing staff is reminded, and the existing nursing plan and the emergency care plan of the corresponding patient are synchronously fed back to the nursing staff.
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| CN202410282207.6A CN117877664B (en) | 2024-03-13 | 2024-03-13 | Intelligent nursing management system based on 5G Internet of things |
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