CN113921101A - Medical auxiliary system - Google Patents
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- 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
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- 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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Abstract
The invention relates to a medical assistance system comprising at least: the reminder is used for collecting and processing the state data information of the patient and carrying out reminding guidance according to a preset reminding instruction; the supervision system is configured to receive and store the state data information collected by the reminder and can set a prompt instruction based on the state data information, and the supervision system can correct at least part of the plan prompt instruction which does not meet the relevance and/or regularity between the past prompt instruction and the plan prompt instruction in the plan prompt instruction according to the state data information of the patient and in a mode of correlating the past prompt instruction and the plan prompt instruction corresponding to the state data information of the patient with each other and provides a correction result to a medical staff for confirmation so that the plan prompt instruction can be executed at least after the current checking and correcting operation is confirmed.
Description
Technical Field
The invention relates to the technical field of medical monitoring, in particular to a medical auxiliary system.
Background
CN111671651B discloses a medication reminding method based on mobile medical networking, which comprises a medical end and a plurality of user ends, wherein the medical end is in communication connection with the user ends, and the user ends are provided with a screen and a voice module, and the method is characterized by comprising the following steps: s1: the medical terminal collects the medicine taking frequency, the medicine quantity, the medicine taking attention information and the basic information of the patient; s2: the medical terminal regularly pushes medicine taking information to the user terminal, and the medicine taking information comprises medicine taking types, medicine taking quantities of various types and doctor prompt information in the medicine taking time period; s3: and the user side updates the medicine information and the medicine taking state held by the patient according to the received feedback information of the patient, and divides the patient into the medicine taking compliance degree according to the timeliness of the feedback information of the patient. The invention provides a medicine taking reminding method based on a mobile medical networking, which can remind a patient to take medicine according to medical advice, feed back the medicine to a doctor in time and match a proper medicine source for the patient.
Before special examination, testing and other works, doctors need to urge patients to prepare in advance, such as fasting, avoiding drinking during exercise or keeping warm; or the rehabilitation treatment of some patients needs to remind people of relevant matters at any time, such as delivery to medicine schedule, so as to inform the patients of what kind of medicines are taken at the right time and the corresponding dosage and relevant attention points. However, most of the currently adopted methods are that a nurse orally notifies a patient before personally going to a hospital bed, or a text label is made in advance for reminding related matters, which undoubtedly brings huge mental and physical burden to a nursing staff, and errors occur in the process due to the fact that the nursing staff difficultly avoids the daily complicated work, for example, the matters needing to be handed are notified to wrong objects due to different specific situations of each patient, or the sequence of the priority of the matters needing to be handed is mixed, so that the optimal notification time is delayed; secondly, it is common that one nurse needs to attend to many patients at the same time, so there is an inevitable problem of difficulty in hand turnover, especially when the number of nurse workers on duty is more rare during the night/early morning, and thus it is difficult for one nurse to want to notify several patients at the same time quickly in a short time; on the other hand, the effect of a simple oral or text reminding mode is also poor, especially for some old patients, the memory of the old patients is obviously declined along with the age, and if the old patients are not reminded at any time or are accompanied and supervised by a specially-assigned person, the old patients are inevitably forgotten about the matters to be waited or make wrong operation, so that the subsequent examination or treatment results are influenced. The various phenomena or problems described above may ultimately have even more serious consequences. Thus, there remains a need in the art for at least one or several aspects of improvement.
Furthermore, on the one hand, due to the differences in understanding to the person skilled in the art; on the other hand, since the applicant has studied a great deal of literature and patents when making the present invention, but the disclosure is not limited thereto and the details and contents thereof are not listed in detail, it is by no means the present invention has these prior art features, but the present invention has all the features of the prior art, and the applicant reserves the right to increase the related prior art in the background.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a medical auxiliary system, which aims to solve at least one or more technical problems in the prior art.
To achieve the above object, the present invention provides a medical assistance system, at least comprising: the reminder is used for collecting and processing the state data information of the patient and providing corresponding reminding/guiding for the patient according to a preset reminding instruction; the monitoring system is used for presetting a prompt instruction, receiving and storing the state data information collected by the reminder,
preferably, the supervision platform is at least capable of modifying at least part of contents in the plan prompt instruction and providing a modification result to the medical staff for confirmation when at least part of contents in the plan prompt instruction do not meet the relevance and/or regularity between the past prompt instruction and the plan prompt instruction according to the state data information of the patient and in a manner of associating the past prompt instruction and the plan prompt instruction corresponding to the state data information of the patient with each other, so that the plan prompt instruction can be executed at least after the current checking and modifying operation is confirmed.
Preferably, the reminder comprises: a control unit; the data transmission part is connected with the control part and is connected with the supervision platform through a network; the storage part is connected with the control part and is used for storing data information and program instructions; and an electronic medical record department at least capable of being used for displaying the state data information stored in the supervision platform.
Preferably, the reminder further comprises a detection part and an image shooting part which are connected with the control part, the detection part and the image shooting part can be cooperatively matched to collect a plurality of state information related to the patient, and the detection part comprises a plurality of sensors with different data transmission modes and different power generation modes.
Preferably, the supervision platform is at least capable of performing feedback reminding on the patient and/or the medical staff in advance according to the matching correlation result between the past prompting instruction and the plan prompting instruction and the related content in the plan prompting instruction, and automatically generating a new plan prompting instruction based on the correlation and/or regularity between the past prompting instruction and the plan prompting instruction, and providing the new plan prompting instruction to the medical staff for confirmation.
Preferably, the supervision platform is capable of automatically generating a plan prompt instruction corresponding to medical record data according to a mode of identifying content included in the medical record data at least when the medical record data related to the patient is formed, and providing the plan prompt instruction to the medical staff, so that the medical staff can modify and replace the content of any plan prompt instruction at least in a form of a lookup table.
Preferably, when the medical staff presets a plan prompt instruction and/or receives a feedback prompt of the system, the system can adjust the corresponding execution program so that the supervision platform can automatically generate and prompt a subsequent plan prompt instruction at least according to the instruction content currently input by the medical staff and the preset time period of the instruction content.
Preferably, the reminder comprises at least: a control section provided with a plurality of signal input terminals and output terminals; the data transmission part is connected with the control part and is connected with the monitoring system through a network; the storage part is connected with the control part and is used for storing data information and program instructions uploaded to the monitoring system and/or issued by the monitoring system; and the electronic medical record part is provided with a display unit and at least can be used for displaying the patient state information which is transmitted to the control part by the communication unit and is stored in the supervision system.
Preferably, the reminding device at least further comprises a detection unit and an image acquisition unit which are connected with the control part, and the detection unit and the image acquisition unit are used for being matched with each other in a coordinated mode to provide a plurality of state information related to the patient.
Preferably, based on the detection data of each environmental parameter of the space where the patient is located by the detection portion and the variation trend of each environmental parameter, the medical staff can adjust the running state of any equipment in advance according to the standard value/threshold value corresponding to each environmental parameter and the analysis and calculation result of the control portion to maintain the stability of each environmental parameter.
Preferably, the data transmission part comprises a communication unit and an authentication unit, the communication unit and the authentication unit are connected with the control part, wherein the communication unit can at least transmit the state data information of the patient to the electronic medical record part, and the authentication unit is used for acquiring data related to the identity information of the patient and providing the related data to the monitoring system for storage through a network.
Preferably, the supervision platform is capable of automatically generating and providing a corresponding unplanned prompting instruction to the patient and/or the medical staff when at least one item of detection data acquired by the detection part exceeds a standard range value, so that the unplanned prompting instruction is executed after being confirmed, wherein the unplanned prompting instruction is generated by the supervision platform in a manner that past prompting instructions and/or planned prompting instructions and the item of detection data are matched and associated with each other, and the generation time of the unplanned prompting instruction depends on the difference value between the detection data of the detection part and the standard threshold range.
Preferably, when the plurality of reminders send a plurality of requests containing abnormal signals and having prompt instructions to be sent to the supervision platform, the supervision platform regards the requests of the prompt instructions as pseudo-prompt requests and selects the requests which are regarded as pseudo-prompts and need secondary confirmation according to the past prompt instructions, wherein in a request set formed by the requests regarded as pseudo-prompts, the supervision platform can classify requesters of the relevant prompt instructions into special priority-like prompt objects according to the prompts with life risks in the past prompt instructions within preset time, and execute tertiary confirmation according to the positions of the special priority-like prompt objects. It is highly desirable to determine the patient most likely to require caregiver intervention by reducing the target data because the system of the present invention is not designed for special situations such as power interruptions or severe power fluctuations, and life-sustaining device outages such as oxygen supply pauses or ventilator outages that result from power interruptions can also result in large area alarms, where prioritization of numerous alarms is also a very important task. In this case, for example, a special priority-intended reminder object list is determined for the object by using a reminder of "there is a reminder of life threatening risk in a past reminder instruction", so that limited medical resources can be accurately allocated.
Preferably, based on the matching and associating result between the past prompting instruction and the plan prompting instruction, the supervision platform can at least provide a feedback prompt to the patient and/or the medical staff in advance according to the relevant content in the plan prompting instruction, and automatically generate at least one plan prompting instruction which accords with the relevance and/or regularity between the past prompting instruction and the plan prompting instruction, so that the plan prompting instruction is executed after being confirmed.
Preferably, when the monitoring platform receives a large number of prompt requests caused by data collected by various sensors within a preset time period, the monitoring platform sets the auxiliary system to an offline mode, and discards the data within the time period so as not to incorporate the data into patient state data information for activating the prompt instruction, wherein the monitoring platform stores the time period and building information corresponding to a power supply loop related to the prompt request in a combined manner, and archives the building information as feedback of power supply quality. For a power supply unit, the power supply quality of a specific transformer loop is difficult to measure accurately and objectively, because the loads involved in the loop are often many, and the voltage fluctuation of the loop cannot be reflected on the power supply and distribution end comprehensively, but appears on a user end. The situation where a large voltage fluctuation occurs in the field is like a human heart attack, i.e. only when it occurs, the cause can be looked for. Therefore, the large voltage fluctuation of the ward or the building in the residential department also needs 24-hour dynamic tracking like a dynamic electrocardiograph (Holtar machine) to determine which large load suddenly intervenes or breaks to cause the large voltage fluctuation, so as to directly eliminate the related risks at the user end of the hospital. Particularly, hospitals and their residences are often very complicated electricity utilization units, the combined use of new and old office buildings is a normal state, new and old equipment is also a normal state online at the same time, and many high-value electricity utilization equipment and precise instruments are involved, so that various potential problems cannot be verified one by one and eliminated one by one. Before the present invention was made, it was often only possible to passively wait for problems to occur and then eliminate them. Under the condition of wide deployment of intelligent hospitals, medical data summarization, particularly data mutual verification based on reasonable classification of the high-reliability medical sensor, can be used for quickly determining wards or buildings with frequent and large-amplitude voltage fluctuation on the site of electric equipment and hospitals with complex environments by using the time window with a large number of prompt requests without additionally arranging complex special equipment.
Preferably, when the supervision platform receives a large number of prompt requests caused by data collected by a sensor powered by a battery and a plurality of reminders sending the prompt requests are located in the same power supply loop, the supervision platform establishes a quasi-priority reminder object queue according to the number of times of reminding dangerous to life in a past prompt instruction, wherein the reminders are distinguished by the supervision platform in the quasi-priority reminder object queue according to the physical positions corresponding to the power supply loops, and sub-queues of the quasi-priority reminder object queue are respectively established in each power supply loop.
Preferably, when the supervision platform receives a large number of prompt requests caused by data collected by various sensors within a preset time period, the supervision platform switches the execution system to a non-working state, stores the time period and building information corresponding to a power supply loop related to the prompt requests in a combined manner, and archives the information as feedback of time and building power supply quality.
Drawings
FIG. 1 is a system architecture diagram of a preferred embodiment of the present invention;
fig. 2 is a schematic structural diagram of a preferred embodiment of the present invention.
List of reference numerals
10: a reminder; 20: a supervisory platform; 101: a control unit; 102: a data transmission unit; 103: an electronic medical record section; 104: an energy supply section; 105: a storage unit; 106: a detection unit; 107: an image pickup unit; 108: a warning module; 201: a platform database; 1021: a communication unit; 1022: an authentication unit; 1031: a display unit.
Detailed Description
The following detailed description is made with reference to the accompanying drawings.
The invention provides a medical assistance system, which can comprise one of the following components: at least one reminder 10 and a regulatory platform 20. Specifically, the administration platform 20 and the reminder 10 are connected to each other through a network connection.
According to a preferred embodiment, the reminder 10 can be disposed on or used in conjunction with a hospital bed, a nursing home, or a nursing home. Preferably, at least a portion of the related functions of the reminder 10 can be implemented by, for example, a smart play/display device, or the reminder 10 can be a smart monitoring bracelet. The monitoring platform 20 may be a computer device mounted on a nurse station or a portable mobile device such as a smart phone or a tablet computer, for example, an App application, a Web browser or a similar interface access program, so that the monitoring platform 20 can be used to realize driving control of the reminder 10 and monitoring and management of patients. In addition, a third party terminal device may be connected to the monitoring platform 20 and/or the reminder 10 via a network, so that the relevant user can obtain the status information related to the patient from multiple channels. Preferably, the third party terminal device may be a computer device provided at a nurse station or a mobile device such as a mobile phone, tablet computer or other portable multimedia device.
In accordance with a preferred embodiment, the administration platform 20 is configured to be at least operable to receive patient status information collected and uploaded by the reminder 10 and to control the reminder 10 based on external driving instructions to provide relevant care services to the patient and to administer supervisory management to the patient. Further, the monitoring platform 20 is configured with a platform database 201, which can be used to store medical record data related to the personal identification information, related medical history/medication history/allergy history, personal physiological contraindications and nursing matters (such as medication schedule, examination and laboratory schedule or operation schedule, etc.) of the patient, and the patient status information related to the patient collected and uploaded by the reminder 10.
According to a preferred embodiment, the caregiver can control the operation of the reminder 10 via the monitoring platform 20 based on the status information associated with the patient in conjunction with the physician's or nurse's treatment instructions to at least provide reminders to the patient for several items such as taking medications on time, fasting before testing, or taking a dietary break before surgery. Furthermore, the nursing staff can at least make arrangement and deployment of relevant matters in advance according to the actual state of the patient according to the patient state information, for example, the type, the administration frequency and the dosage of the subsequently administered medicines can be adjusted according to the administration condition of the patient; or schedule examination tests, surgery, etc. related to the patient within a suitable time period according to the current physical state of the patient, etc. Preferably, the status information related to the patient includes, but is not limited to, physiological parameters of the patient (such as blood pressure, heart rate, or body surface temperature, etc.), the activity status of the patient in the patient's bed and different spaces (such as the frequency of turning over in the patient's bed, the frequency of getting out of the bed, the main activity area and duration thereof in the space, or other actions related to the patient for reference), and the ambient environment status of the space (such as air quality, ambient humidity, or room brightness).
According to a preferred embodiment, the reminder 10 can include a control portion 101, a data transmission portion 102, an electronic medical record portion 103, an energy supply portion 104, and a storage portion 105. Specifically, the control portion 101 is electrically and/or communicatively coupled to the other units, and the control portion 101 is configured with a plurality of signal input terminals and output terminals for performing information transmission interaction with the other units.
According to a preferred embodiment, the storage unit 105 has a data storage function, and can be used to synchronously store the data uploaded to the platform database 201 and the data command issued by the monitoring platform 20, and can synchronize and update the data in the storage unit 105 and the platform database 201 through a network.
According to a preferred embodiment, the energy supply part 104 can be directly connected to the mains or can be formed by a combination of several rechargeable batteries, which are configured to provide the above-mentioned other functional units with the power required for operation.
According to a preferred embodiment, the data transmission part 102 may comprise a communication unit 1021 and an authentication unit 1022. Optionally, the communication module 102 is a wired or wireless communication protocol, such as Internet or Wifi network transmission protocol. The communication unit 1021 and the authentication unit 1022 are connected to the control unit 101, respectively. Further, the communication unit 1021 can be connected to the administration platform 20 through a network, and is configured to at least transmit the patient status information stored in the platform database 201 of the administration platform 20 to the electronic medical record 103. The authentication unit 1022 is configured to at least obtain data related to the identity information of the patient, and the related data can be transmitted to the administration platform 20 for storage through a network. Preferably, the authentication unit 1022 may be, for example, an RFID module.
According to a preferred embodiment, the electronic medical record part 103 at least includes a display unit 1031, i.e. a display screen, which can be at least used for displaying the patient status information transmitted by the communication unit 1021 to the control part 101 and stored in the platform database 201 of the monitoring platform 20, so that the doctor or the caregiver can judge the current body status of the patient and/or other status information related thereto according to the data information on the display unit 1031, and can further know the current status of the patient according to the information on the display unit 1031, such as examination/treatment items, treatment records and the like.
According to a preferred embodiment, the reminder 10 should further include at least a detection portion 106 and an image pickup portion 107. The detection part 106 and the image pickup part 107 are respectively connected with the control part 101 of the reminder 10 so as to control the operation of the detection part 106 and the image pickup part 107 and receive relevant detection data through the control part 101. The detecting portion 106 and the image capturing portion 107 are configured to cooperate to provide a doctor or a caregiver with a plurality of status information related to the patient, including but not limited to the aforementioned physiological parameters (e.g., blood pressure, heart rate, body surface temperature, etc.), the activity status of the patient on the patient's bed and in different spaces (e.g., turning frequency on the patient's bed, frequency of getting out of the bed, main activity areas and duration thereof in the space, or other visual behaviors related to the patient for reference), and the surrounding environment status of the space (e.g., air quality, ambient humidity, or indoor brightness).
According to a preferred embodiment, the detecting portion 106 includes several sensor modules, and it includes, but is not limited to, a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, a body temperature sensor or a pulse sensor capable of acquiring various physiological parameters of the patient, and/or a humidity sensor, an air quality sensor, a brightness sensor or an air pressure sensor for detecting the ambient environment state of the space where the patient is located, and/or a fingerprint sensor for confirming the identity information of the patient, and a positioning sensor, a weight/pressure sensor or an acceleration sensor for detecting the physical behavior of the patient.
According to a preferred embodiment, the image capturing part 107 may be, for example, one or a combination of a camera, a video camera or a still camera. Further, the image capturing unit 107 is configured to at least capture images/images of a patient lying on a hospital bed and/or moving in a certain range of space, so as to cooperate with various items of detection data of the detecting unit 106 to enable medical staff to know the state of the patient in time, and further, the control unit 101 analyzes and processes various items of detection data of the detecting unit 106 and image acquisition data of the image capturing unit 107, so as to monitor the patient in real time and predict possible accident risks. Preferably, for example, according to the real-time detection data of the detecting part 106, the system can remind the patient and/or the medical staff in a manner including, but not limited to, sound, light or text instructions at least when a certain physiological parameter of a certain patient is out of the standard range or is about to be out of the standard range.
According to a preferred embodiment, the reminder 10 can further include an alarm module 108, and the alarm module 108 is electrically connected or communicatively coupled to the control portion 101. Preferably, the alarm module 108 may be a speaker, a buzzer, or the like, which is configured to be at least capable of playing an audio signal preset by the doctor or the caregiver through an external terminal device or real-time voice information input by the doctor or the caregiver. Preferably, the patient-related actions/behaviors can be alerted or reminded by the alert module 108 and instructed or guided to perform actions including, but not limited to, taking medications, fasting, resting, exercising, and testing. Further, the warning module 108 can be used in cooperation with the image capturing unit 107, so that a doctor, a caregiver, or a family member of a patient who visits in the future can perform voice guidance on the patient, and the image capturing unit 107 can perform functions of monitoring and visiting the patient. In addition, the images/images related to the patient captured by the image capturing part 107 can be transmitted to the remote medical staff or the patient family members for watching through the network, so that the hospital can transparently disclose the supervision and management work of the patient, and the patient family members can know the physical state of the patient in time.
Preferably, for example, according to the detection data of the sensors for collecting physiological parameters of the patient, such as heart rate, blood pressure, blood oxygen, body temperature, or pulse, the medical staff can timely learn the current physical condition of the patient, and further, according to the variation values and variation trends of the physiological parameters in different time ranges, the standard values/threshold values corresponding to the physiological parameters and the analysis and calculation results of the control part 101 are combined to predict the possible risk accidents of the patient in advance, so that the medical staff can remind the patient of the related cautionary items in an acoustic/optical manner through the reminder 10 and instruct the patient to make corresponding adjustments and/or correspondingly adjust the related schemes of subsequent examination, treatment, and rehabilitation of the patient, and the like, so as to ensure the smooth development of the items of subsequent examination, testing, and/or rehabilitation.
According to a preferred embodiment, based on the detection data of the sensors for detecting the environmental parameters such as humidity, air, brightness or air pressure of the space in which the patient is located, the medical staff can timely learn the real-time environmental status of the current space (such as a ward, an examination laboratory, an operating room or an isolation room) of the patient, and further can learn the possible changes of the environmental status of the space in which the patient is located in advance according to the change values and the change trends of the environmental parameters in different time ranges by combining the standard values/threshold values corresponding to the environmental parameters and the analysis and calculation results of the control part 101, so that the medical staff can maintain the stability of the environmental parameters by adjusting the operating status of other equipment in advance, for example, the ventilation equipment and the ventilation equipment in the ward can be set in advance based on the detection values and the detection of the patient's environment's equipment, and the ventilation equipment can be set in advance according to the ventilation equipment, and the ventilation equipment, so that the ventilation equipment can be capable of the ventilation equipment can be used for detecting the ventilation equipment, and the ventilation equipment can be used for detecting the ventilation equipment, and the ventilation equipment can be used for detecting the ventilation equipment, and the medical staff can be used for detecting the medical equipment, and the ventilation equipment, the operation mode of the disinfection equipment or the cleaning equipment and other equipment is used for adjusting the operation state of the equipment in advance when the corresponding environmental parameters reach or are about to reach the standard values so as to ensure the good environmental state of the space where the patient is located, thereby providing a proper activity space for the patient and simultaneously helping the recovery of the patient in good environment.
According to a preferred embodiment, the medical staff can also timely acquire the action/behavior information of the patient according to the detection data of a plurality of sensors for detecting the physical behavior of the patient, and accordingly take corresponding reminding or adjusting measures. For example, according to the detection data of the positioning sensor, the daily action track of the patient and the residence time corresponding to different areas can be obtained, so that the medical staff can obtain the personal habits related to the action track, the cycle, the frequency and other data information, and the personal habits can be verified by combining the patient behavior information contained in the image/image collected by the image capturing part 107, because the action/behavior information of the patient and the personal emotion, the state of illness development and the subsequent rehabilitation treatment effect of the patient are closely related. Specifically, for example, according to the resident space, the corresponding stay time, and the visual body behavior or facial expression of the patient, the medical staff can generally know or determine the physiological or psychological state of the patient, for example, if a certain patient frequently goes to the toilet and the stay time is relatively long, the patient may have physiological or psychological discomfort, so that the medical staff can instruct or remind the patient and take countermeasures before a large risk accident occurs. In addition, if the patient turns over or gets out of bed frequently, the medical staff can generally know or judge that the patient may have physiological or psychological discomfort, and for some patients with language dysfunction or limited expression ability, the judgment through the body behaviors is more effective.
Furthermore, as a number of patients to be attended by one nurse is large, the work task is heavy, if the state of each patient is monitored at any time and the corresponding treatment management scheme is selectively prompted/guided or modified according to the state of the patient, the medical staff is likely to forget or confuse the corresponding indication reminding of the patient and/or modification and modification of the treatment management scheme due to the fact that other events are inserted midway, and the missing of the optimal time finally causes the monitoring and management of the patient to miss errors and even endanger the life of the patient; meanwhile, when the medical staff is busy, the medical staff cannot timely and effectively confirm whether the patients accurately receive the corresponding correct indication reminding messages and whether the indication reminding messages are strictly followed to complete corresponding events or behaviors and the like. Therefore, the prompt instruction can be automatically generated through the deep learning of the system so as to intelligently remind patients, and intelligently feed back the preset prompt instruction of medical staff.
According to a preferred embodiment, the deep learning of the system can be implemented as follows: the treatment management scheme and the instruction message to be communicated by the medical staff are different based on the individual condition of each patient. For example, in a short period, the types of medicines to be taken by each patient on the day or at least in a period of time, and the corresponding medicine taking frequency/period, the medicine taking amount and/or related cautions and the like are different; in a long term, the cycle/frequency of each patient for examination, review, or care and treatment, and the corresponding cautions, etc. are also different, so that the medical staff needs to preset a plurality of prompting messages/instructions in different time nodes and different specific indication contents for each patient in advance, and the corresponding reminding manners may also be different, so as to remind the patient or the patient himself of completing the related work in the indication contents in the preset reminding manner before or during at least a part of the time when the corresponding time nodes are met.
Further, because the number of patients is large and the work content required to be completed by the patients or completed by the medical staff is different, the medical staff may forget to preset the prompt instruction, and the patients may forget to perform the prompt or even perform the prompt by mistake, if the prompt is not actively reported and the medical staff does not review and verify the prompt, the risk remediation cannot be performed. Therefore, the system can perform self-learning based on certain sample data to achieve the purpose of intelligent reminding.
According to a preferred embodiment, the medical staff sets prompting instructions for a patient at different dates and different time nodes (such as morning time A, noon time B and evening time C of Monday and Wednesday … …), and the content of each prompting instruction may be different (such as fasting at least some time before time A, medicine B taken at time B, etc.), the specific reminding modes are different (for example, fasting can be reminded through the warning module 108 based on a voice message input by the medical staff in advance, while taking medicines can be reminded through a common sound/light mode, such as an alarm clock or an alarm light), if the medical staff forgets to set or mistakenly sets the related reminding instruction, the system can analyze and check the prompting instruction preset by the medical staff at least according to the historical disease information and the current disease information of the patient and various information contained in the corresponding executed and/or to-be-executed prompting instruction.
For example, the prompt instruction set by the medical staff for a certain patient includes: the medicine a needs to be taken in a certain period of time in the past, the medicine taking frequency is 3 times/day, and the time interval is 4h and 4 tablets/time; b is needed to be taken in a certain period of time, the taking frequency is 4 times/day, and the time intervals are 2 h-3 h and 2 tablets/time; the medicine b needs to be taken in the current certain time period, the dosage of the medicine b is changed into 1 tablet/time, and the dosage is changed into 0.5 tablet/time after a certain period, so the instruction contents in different time periods are different, forgetting or confusion phenomena are avoided, and the system can check and correct the content of the prompt instruction at least based on the time period preset by medical staff.
Further, the system can analyze the correctness of the prompt instruction preset by the medical staff according to the sample data of the prompt instruction in a certain time period, for example, according to the executed preset instruction X, the administration mode of the medicine a is known, in the prompt instruction Y to be executed later, at least one of the taking time, the corresponding frequency cycle or the dosage of the medicine a is different from the preset instruction X, the system may, on the one hand, sound/light alert the patient via the reminder 10 that there is an abnormality in the cue instruction Y prior to execution of the cue instruction Y, on the other hand, the abnormal information can be synchronously uploaded to the computer equipment of the nurse station or other portable multimedia equipment for mobile patrol for medical personnel to review and consult, so that at least one of the patient and the medical staff can timely know the correctness of the prompt instruction, and the preset instruction of the medical staff is intelligently fed back. Secondly, when the medical staff receives the abnormal information about the prompt instruction Y, the medical staff can confirm the correctness of the prompt instruction Y to be executed and modify and replace the information which does not accord with the indication content; on the other hand, the platform database 201 of the monitoring platform 20 stores a large number of prompt instructions, which are usually in the form of voice messages in some preferred embodiments, and the specific content of the voice message may also include information related to a patient, such as a name of a certain patient or a bed number corresponding to a certain patient, besides various matters to be dealt with by the medical staff, so that after the medical staff presets a certain prompt instruction Z, the system can analyze the correctness of the instruction content of the prompt instruction Z and automatically correct the instruction content in the way of voice recognition, based on the retrieval of the large number of prompt instructions in the platform database 201, and simultaneously feed back the results before and after correction to the medical staff. For example, the prompt instruction Z refers to "zhuang" or "bed number 003", and the system determines that the prompt instruction Z is wrong based on the analysis of the contents of the past prompt instructions of "zhuang" and/or "bed number 003", namely, the patient or bed number corresponding to the prompt instruction Z is wrong, and/or the relevant matters corresponding to the patient or bed number are wrong, based on the matching and correlation between the prompt instruction Z and the prompt instruction in the platform database 201, the system modifies and replaces at least part of the content in the prompt instruction Z and simultaneously feeds back the modified and replaced result to the medical staff for secondary confirmation, for example, the name or the bed number of the patient can be automatically replaced by the existing voice message or the text message according to the content after the voice recognition or the text recognition, or automatically replacing the voice/text instruction related to the specific attention with the existing voice/text message aiming at a certain patient.
According to a preferred embodiment, the system can set the prompt instruction in advance and/or remind the patient or the medical staff in advance based on the analysis and comparison of the historical disease information, the current disease information, the information contained in the corresponding executed and/or to-be-executed prompt instruction and the corresponding change trend of the patient. Specifically, the system obtains, based on the analysis of the specific content contained in the sample data of the prompt instruction within a certain time period, that the frequency/period of the patient taking the drug a within the certain time period increases and/or the dosage of the drug decreases, and the trend of the frequency/period increase or the trend of the dosage of the patient decreasing may have a certain rule (for example, an arithmetic progression, 2 times/day, 3 times/day, … …, N +1 times/day; 4 times/time, 3 times/time, … …, N-1 times/time), and further, the system can form a new prompt instruction according to a certain rule based on the correlation between the prompt instructions, for example, the frequency of the drug a being taken every week decreases once, and the dosage of the drug a corresponding to each time decreases by 0.5 piece, and the system can form a new prompt instruction according to the content that the frequency of the drug a is decreased once compared with the last period and the dosage of a single time is decreased by 0.5 piece at least And displaying the instruction, and simultaneously providing the prompt instruction to the medical staff for confirmation. Preferably, the certain period of time may be a period of time prescribed by a medical staff, for example one month; or the system is formed automatically based on the association or existence regularity of the specific contents contained in the prompt instruction, for example, the trend of the taking period, frequency and dosage of the medicine a in a certain period of time is reduced according to the equal difference and can be defined as a period of time, and when the trend of at least one of the changes does not accord with the previous rule, the next period of time can be defaulted as entering.
According to a preferred embodiment, after the medical staff presets a new prompt instruction, the system will analyze the specific content in the planned prompt instruction based on the retrieval of the past prompt instruction in the platform database 201, determine the relevance or regularity between the past prompt instruction and the planned prompt instruction through the deep learning of the system, when the relevance or regularity between the planned prompt instruction and the past prompt instruction does not satisfy the corresponding trend, for example, it is known that the medicine a is taken every other week according to the past prompt instruction, and the corresponding medicine amount is reduced by 0.5 tablet each time, when at least one of the period, the taking frequency or the taking dosage of the medicine in the planned prompt instruction is different from the trend shown in the past prompt instruction, the system will make a feedback prompt to the planned prompt instruction preset by the medical staff, reminding the correctness of the current preset prompt instruction and further correcting the error content; further, when there is an error between the content in the planned prompt instruction and the content in the past prompt instruction or the correlation between the planned prompt instruction and the past prompt instruction, it may be that the medical staff adjusts the configuration content related to a plurality of tasks such as checking, taking medicine, fasting, resting and/or exercising according to the physical state of the patient rather than setting a mistake, so that the medical staff can at least perform the automatic setting and reminding of the subsequent prompt instruction according to the new configuration mode by adjusting the setting of the corresponding execution program according to the specific arrangement content when the medical staff presets a new prompt instruction and/or receives the feedback reminding of the system, for example, after the medical staff sets the new instruction content, the medical staff can perform the automatic setting and reminding of the subsequent prompt instruction according to the current instruction content and a certain time period by setting the program, the automatic setting and reminding of the subsequent prompt instruction are not required to be carried out according to the past prompt instruction and the relevance between the past prompt instruction and the current prompt instruction is analyzed, so that the error probability of the multiple operation analysis of the system is reduced, and the accuracy of the automatic setting of the related prompt instruction by the system is further improved.
According to a preferred embodiment, since each medical staff needs to supervise and manage a large number of patients at the same time, it is troublesome to frequently set different prompting instructions for the actual situation of each patient, and even if the system automatically sets a new planned prompting instruction according to the past prompting instruction, the medical staff still needs to confirm for a plurality of times to execute the corresponding prompting instruction, however, preferably, in some preferred embodiments, the system can automatically configure the prompting instruction according to the following method: the medical record data of the patient comprises basic information, medical history/disease diagnosis information and corresponding treatment or management scheme, wherein the treatment or management scheme comprises a plurality of information related to physical examination, medicine taking, operation, daily rest/exercise/diet and the like of the patient, for example, according to the medical record data, the patient W is known to take medicine a in a manner of 3 times/day and 1 piece/time, the medicine taking time is 9: 00-22: 00, the medicine taking interval is at least 3h, and the medicine taking interval is 1 day every 5 days, therefore, when the medical record data of the patient is formed, the system can automatically set a plan prompt instruction expressed in a text and/or voice mode corresponding to the patient by identifying at least part of the content in the medical record data, and provide the automatically set plan prompt instruction to a medical care personnel for checking in a form such as a data table, thereby reducing the physiological and/or psychological burden caused by frequent operation of medical care personnel; meanwhile, medical staff in later period only need to modify the specific content of any plan prompt instruction based on the actual condition of the patient in a form of a lookup table, and new prompt instructions do not need to be set frequently, so that the risk caused by forgetting of the medical staff is reduced.
According to a preferred embodiment, when the system is enabled to automatically generate the plan prompt command by setting the corresponding execution program, the system can be enabled to more intelligently and effectively generate a new plan prompt command based on the following manner. Specifically, for example, each physiological parameter of the patient has a certain normal range value, when a certain physiological parameter is outside the normal range, the patient may need to take medicine immediately or perform relevant examination to solve the corresponding problem, and for some relatively complicated problems, the patient may have difficulty in self-judgment due to professional limitations, and therefore the patient needs to strictly follow the instruction of the medical staff and cannot make an unauthorized decision, however, some changes may be instantaneous, and the medical staff cannot predict all possible changes, so that before some sudden events occur, if there is no prompt instruction of the medical staff, the patient is difficult to make correct operation, and thus the physical and mental health of the patient bears a certain risk, but the medical staff cannot preset corresponding prompt instruction in advance for various foreseeable or unforeseeable events. Preferably, in addition to the medical staff setting the plan prompt command by itself and the system automatically generating the plan prompt command based on the content of the past prompt command and the content in the medical record data of the patient, for example, when the system knows that a certain physiological parameter of the patient is about to exceed the standard range value or exceeds the standard range value based on the detection data of the detection part 106, it can automatically generate the prompt command related to the change to overcome or eliminate the sudden change by retrieving, matching and associating the content related to the physiological parameter in the past prompt command and/or the unexecuted plan prompt command, and further, the prompt command out of the plan generated according to this way is respectively fed back to the patient and the medical staff for confirmation, and is executed at least after the medical staff confirms. Preferably, the timing of the generation of the unplanned reminder instruction depends on the magnitude of the difference between the detection data of the detection portion 106 and the standard threshold range, i.e. is generated when a certain difference is met, and the difference/difference can be set by the healthcare worker, since in general the healthcare worker is known about the specific numerical range of the controllable risk. Through this kind of mode, further alleviateed medical personnel and needed to predetermine the body and mind burden of multiple suggestion instruction in advance to also reduced because of medical personnel can't predict the accident in advance and do not set up corresponding suggestion instruction and then produce the emergence probability of careless risk accident that careless results in to the supervision and management of disease, simultaneously, medical personnel only need simply confirm or modify can, need not consume the plenty of time and set up the suggestion instruction, thereby improved medical personnel's efficiency of supervision and management.
According to a preferred embodiment, when the prompt command set by the medical staff responds/starts, the patient needs to reply to the corresponding prompt command to enable the medical staff to confirm that the medical staff receives the relevant message, and in order to further confirm whether the patient strictly follows the content of the command after receiving the prompt command to complete the corresponding matters, the patient needs to perform secondary confirmation, and the medical staff can verify whether the patient follows the content of the command to complete the corresponding task/action through the detection data of the detection part 106 and the image capturing part 107. Preferably, the behaviors of the patient such as each time of confirmation, feedback of the medical staff to the system reminding and the like can be regarded as the card punching record of the medical staff during the working period or the duty patrol period, the work performance of the medical staff can be evaluated by the card punching record and the execution conditions, the body states and the like of a plurality of patients supervised and managed by the medical staff, and meanwhile, the family members of the patients can visually know the supervision and management work of the hospital.
According to a preferred embodiment, a medical care provider can supervise and manage a plurality of patients through the administration platform 20. Specifically, after a patient is hospitalized, the identity information is input through the authentication unit 1022 of the reminder 10 by using the identity certificate (such as an identity card, admission permission, etc.) of the patient, the reminder 10 uploads the received identity information to the monitoring platform 20 through the network to confirm the identity of the patient, the monitoring platform 20 generates an electronic medical record list after confirming the identity of the patient and simultaneously stores the electronic medical record list in the platform database 201, and the reminder 10 can synchronously download the electronic medical record list through the network and store the electronic medical record list in the storage portion 105, so as to realize synchronous update of data, and further, the monitoring platform 20 can be connected with systems of other medical related entities through the network, so as to realize data transmission and/or information interaction between the monitoring platform 20 and the reminder 10.
According to a preferred embodiment, the reminder 10 is connected to the supervision platform 20 via a network, so that the corresponding steps executed by the supervision platform 20 can be transmitted to the reminder 10 via the network, and in some other preferred embodiments, the reminder 10 can download and store the corresponding executed steps to the data transmission part 102 in advance, so that the reminder can independently execute all the functions included in the reminder when the reminder is not connected to the supervision platform 20 via the network.
According to a preferred embodiment, in a specific ward, the sensors included in the detecting unit 106, i.e. no matter the sensors are a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, a body temperature sensor or a pulse sensor, etc. capable of acquiring physiological parameters of a patient, or a humidity sensor, an air quality sensor, a brightness sensor or an air pressure sensor, etc. for detecting the surrounding environment state of a space where the patient is located, or a fingerprint sensor for confirming the identity information of the patient, or a positioning sensor, a weight/pressure sensor or an acceleration sensor, etc. for detecting the body behavior of the patient, can be roughly divided into A, B, C and/or D-type sensors according to their corresponding power-obtaining forms and data transmission modes. For example, the class a sensor relies on a common primary battery to supply power and performs data transmission in a wireless manner; the B-type sensor is powered by a power supply or commercial power and performs data transmission in a wired mode; the C-type sensor is powered by a solar battery or a rechargeable battery and performs data transmission in a wireless mode; the D-type sensor depends on multiple power supplies and is provided with multiple data transmission channels.
Further, regardless of the data transmission mode or form of power supply used by the sensors, the sensors need to be directly or indirectly connected to the reminder 10 and the monitoring platform 20 in cooperation therewith. Thus, during a power supply failure, for example, when the voltage fluctuates to a large extent (the effective value of the supply voltage rapidly drops to 90% -10% of the nominal value, and the duration is 0.5-1.5 s at most), the detection behavior of several sensors or the data thereof will often have unpredictable results. For a ward where the system is deployed, a large number of feedback reminders and prompt instructions from the system are necessarily generated, and the feedback reminders and the prompt instructions have correct prompt information and also have error information or interference information. When the number of false messages is significantly greater than the number of correct prompts, the healthcare worker may be more inclined to ignore all reminders or even turn off the system, which is also a key reason why such devices or systems are difficult to use frequently after deployment. Since the quality of the power supplied by the power grid is not manageable by the hospital, solutions need to be found from the system itself to eliminate the situation that the number of "error messages" is significantly larger than that of correct prompt messages.
According to a preferred embodiment, in the system, although the data channels of the various sensors are connected to different data collection devices such as the reminder 10 of the present invention (and stored in their own storage unit 105), several reminders 10 deployed in different areas, floors and wards need to gather data to the same data collection server such as the administration platform 20 of the present invention. Since the alarm 10 is usually configured to be on-line for 24 hours, the required power is usually provided by the power grid voltage, and generally, the alarms 10 in the same ward are usually in the same power supply loop, and the alarms 10 on different floors are in different power supply loops from each other. When the power supply voltage of the whole inpatient building fluctuates, a large number of reminders 10 on each floor can give abnormal signals in the same time interval (for example, 50ms to 1s), and although the abnormal signals are different from each other, the supervision platform 20 of the present invention receives requests of the large number of reminders 10 for sending prompt commands in a centralized manner. When the supervision platform 20 of the present invention receives a large number of requests of the reminder 10 for sending the reminder command in a short time, the abnormal signals including the "request for reminder command" are first regarded as the pseudo reminder requests. To avoid false alarms but also to avoid false alarms, the management system 20 of the present invention may screen out "requests deemed to be false alarms" that require secondary screening based on possible patient life threatening alarms in the "past alarm instruction" (e.g., blood pressure, abnormal heart rate, etc. are believed to result in unexpected patient death).
Preferably, in the request set formed by the "request regarded as pseudo reminder", the supervising platform 20 classifies the requesters of the relevant prompt instructions as special priority-like reminder objects according to the positions of the special priority-like reminder objects in the "past prompt instructions" appearing in a predetermined time period, wherein the life-threatening reminders are classified into the special priority-like reminder objects. It is highly desirable to determine the patient most likely to require caregiver intervention by reducing the target data because the system of the present invention is not designed for special situations such as power interruptions or severe power fluctuations, and life-sustaining device outages such as oxygen supply pauses or ventilator outages that result from power interruptions can also result in large area alarms, where prioritization of numerous alarms is also a very important task. At this time, for example, by determining a special priority-intended reminder object list for the object by using the reminder 10 of "there is a reminder of life threatening risk in past reminder instruction", it is possible to accurately allocate limited medical resources.
Preferably, when the supervision platform 20 receives a large number of reminding requests caused by data collected by a multi-path power supply type-D sensor and under the condition that the reminders 10 sending the reminding requests are in the same power supply loop, the management system 20 establishes a priority-like reminding object queue according to the number of reminding times with life risks in past reminding instructions. Class D sensors are often used in particularly important devices, given higher priority by the supervisory platform 20 to send prompt instructions based on the characteristics of their multiple power supply and multiple data channels. A large number of reminders are generated in the same power supply loop (i.e. the same ward), which means that a power supply failure occurs at a high probability, and a large number of medical staff are required to intervene in an emergency, and these staff can determine the transfer or rescue order of patients according to the priority reminding object queue when entering the ward, wherein different reminding objects in the priority reminding object queue can be marked in different ways by using corresponding reminders 10, so that the medical staff can visually perceive the patients when attending in the emergency.
Preferably, when the monitoring platform 20 receives a large number of prompt requests caused by data collected by a battery-powered class a sensor and under the condition that the reminders 10 sending the prompt requests are in the same power supply loop, the monitoring platform 20 establishes a priority-like reminder object queue according to the number of times of reminding with life-threatening risks in the past prompt instruction, wherein the monitoring platform 20 distinguishes the reminders 10 in the priority-like reminder object queue according to the physical positions corresponding to the power supply loops and establishes sub-queues of the priority-like reminder object queue in each power supply loop respectively. The supervision platform 20 screens out a priority-intended reminding object queue containing the most sub-queues from a plurality of priority-intended reminding object queues according to the reminding requests of at least another type of sensors different from the class A sensors, in particular according to the reminders 10 to which the reminding requests from at least another type of sensors are directed, the routing information of the corresponding reminders 10 and the time correlation of the occurrence of a large number of reminding requests of at least another type of sensors and a large number of reminding requests of the class A sensors, wherein, the supervision platform 20 screens out the routers equipped with the reminder 10 sending the corresponding prompt request according to the routing information of the sub-queues of the queue of the to-be-prioritized reminder object containing the most sub-queues, and determining the building, floor or room with the most requests according to the related routing information, and determining the specific patient needing the intervention of the medical staff according to the priority-planned reminding object queue and the related sub-queue. Through the above mode of the invention, the equipment, line or power supply system barrier can be discovered with very little labor cost, and very limited medical staff can be distributed to the most urgent areas and patients in a very short time when a disaster such as a thunderstorm, typhoon or earthquake is faced. By means of the above solution, it is also possible to determine a power supply and distribution or consumer which may have short circuits, open circuits or even other serious problems without the need for special equipment.
In the invention, the number of false prompts caused by the sensors is the largest in view of the fact that the sensors are powered by a battery and wirelessly send data is the largest and the data is the most complicated, but the data of the sensors is the key link for improving the nursing quality, and the removal of the false prompts constitutes the technical key point of whether the system can be deployed for a long time and continuously improving the overall nursing quality of a hospital.
According to the prior art, when the supervision platform 20 receives a prompt request which is repeatedly caused by data collected by a class-A sensor which is powered by a battery and wirelessly transmits data, the medical staff or patients can manually evaluate the authenticity of the corresponding prompt request on the reminder 10. This freedom of manipulation of the authenticity assessment may also often be the desire of the patient to leave the supervision, or the medical staff temporarily overriding the excessive reminders and instead manually arranging the rescue work offline. In the case of a large amount of data intervention, a software system similar to the system of the present invention is difficult to truly deploy in a hospital, and the collected data cannot be sufficiently trusted by hospital management personnel. Among the data sent by a large number of class-a sensors, there are not only interference data (such as abnormal data generated due to power supply voltage fluctuation or sensor failure), but also normal collected data in the same time period (for example, the detected data reaches a corresponding critical value or the generation condition of a related prompt instruction, so a request is sent to the supervisory platform 20), so it is important to quickly eliminate the wrong data information from a large number of data sets, analyze the reason for generating each wrong data and the specific position of the data sending object corresponding to the wrong data, that is, the position of the reminder 10, and determine the authenticity/validity of the normal collected data, and configure different priority levels of the reminder 10 for the corresponding data sender or instruction requester corresponding to the normal collected data.
According to a preferred embodiment, when the monitoring platform 20 receives a large number of prompting requests caused by data collected by battery-powered class a sensors, the monitoring platform 20 determines the physical arrangement location of each reminder 10 according to the network routing information of each reminder 10 and the cabinet number (the cabinet number and the ward existence correspondence table) corresponding to the router, and in the case that the large number of prompting requests originate from a plurality of reminders 10 in the same power supply loop, the monitoring platform 20 receiving the requests performs analysis on data of at least one class B, class C or class D sensor powered by the power supply in the power supply loop, wherein the monitoring platform 20 compares the data abnormality occurrence time of the plurality of class B, class C or class D sensors in the same power supply loop with the data abnormality occurrence time of the plurality of class a sensors, the degree of occurrence of time coincidence was used as a screening condition for "false alarm". Preferably, the supervision platform 20 compares the occurrence time of the "loss" in the data abnormality of the class B, C or D sensor within the same power supply circuit with the occurrence time of the data abnormality of the class a sensor, and filters the data abnormality of the class a sensor coinciding with the occurrence time of the data loss of the class B sensor into a "pseudo cue list", wherein the "pseudo cue list" is used for extracting the item with the lowest time coincidence degree in the "pseudo cue list" by the supervision platform 20 in a manner of filtering according to the time coincidence degree with the occurrence time of the data abnormality of the class C and/or D sensor within the same power supply circuit, and the cue request of the corresponding reminder 10 is formed based on the item with the lowest time coincidence degree. Therefore, after the medical staff receives the related prompt, the medical staff can clearly and definitely provide the patient to be patrolled when entering the related ward, and the patient information including historical disease information, current disease information and information related to the past prompt instruction can be provided for the corresponding medical staff in advance in an appropriate mode. Through the design scheme of the invention, when a large number of potential reminding requests exist in the same ward (namely the same power supply loop), the supervision platform 20 instructs the medical staff to check only the patient corresponding to the reminder 10 corresponding to the item with the lowest time overlapping degree, and can also determine the safety of the whole ward by instructing to check individual patients on the premise of avoiding batch reminding, and reasonably remind the medical staff in a patient priority ranking mode while not remarkably increasing the workload.
Preferably, when a large number of prompt requests caused by data collected by the class a, class B, class C and class D sensors are received within a predetermined time window of the monitoring platform 20, the monitoring platform 20 sets the state of the patient monitoring prompting system to be system offline, and discards the data in the time window so as not to include the data in the patient state data information for activating the past prompt instruction, wherein the monitoring platform 20 stores the time window and building information corresponding to the power supply loop related to the prompt request in a combined manner, and archives the data as feedback of the power supply quality. After the patient monitoring reminder system state is set to system offline, the reminder 10 and/or the administration platform 20 will prompt the relevant caregiver to: the patient monitoring reminding system is already switched into a non-working state, and needs manual intervention for nursing work of related patients.
Preferably, when a predetermined time window of the supervision platform 20 receives a large number of prompt requests caused by data collected by at least three sensors of the types a, B, C and D, the supervision platform 20 switches the execution system to the "off" state, and stores the time window and building information corresponding to the power supply loop related to the prompt request in association, and archives the information as feedback of time and building power supply quality. For a power supply unit, the power supply quality of a specific transformer loop is difficult to measure accurately and objectively, because the loads involved in the loop are often many, and the voltage fluctuation of the loop cannot be reflected on the power supply and distribution end comprehensively, but appears on a user end. The situation where a large voltage fluctuation occurs in the field is like a human heart attack, i.e. only when it occurs, the cause can be looked for. Therefore, the large voltage fluctuation of the ward or the building in the residential department also needs 24-hour dynamic tracking like a dynamic electrocardiograph (Holtar machine) to determine which large load suddenly intervenes or breaks to cause the large voltage fluctuation, so as to directly eliminate the related risks at the user end of the hospital.
It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and figures are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents. The present description contains several inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", each indicating that the respective paragraph discloses a separate concept, the applicant reserves the right to submit divisional applications according to each inventive concept.
Claims (10)
1. A medical assistance system comprising at least:
a reminder (10) for collecting and processing the status data information of the patient and giving a reminding guide according to a preset reminding instruction,
a supervision platform (20) configured to receive and store status data information collected by the reminder (10) and to be able to set a prompt instruction based on the status data information,
it is characterized in that the preparation method is characterized in that,
the supervision platform (20) can correct at least part of the plan prompt instructions which do not meet the relevance and/or regularity between the past prompt instructions and the plan prompt instructions according to the state data information of the patient and in a mode of correlating the past prompt instructions and the plan prompt instructions corresponding to the state data information of the patient with each other, and provides correction results to the medical staff for confirmation, so that the plan prompt instructions can be executed at least after the current checking and correcting operations are confirmed.
2. The assistance system according to claim 1, characterized in that the reminder (10) comprises: a control unit (101);
a data transmission unit (102) connected to the control unit (101) and connected to the supervision platform (20) via a network;
a storage unit (105) connected to the control unit (101) and configured to store data information and program instructions;
and an electronic medical record (103) at least operable to display status data information stored in the administration platform (20).
3. The assistance system according to claim 2, wherein the reminder (10) further comprises a detection part (106) and an image capturing part (107) connected to the control part (101), the detection part (106) and the image capturing part (107) being capable of cooperating to collect a plurality of status information related to the patient,
wherein the content of the first and second substances,
the detection unit (106) includes a plurality of sensors having different data transmission modes and different power generation modes.
4. The support system of claim 2, wherein the data transmission unit (102) is composed of a communication unit (1021) connected to the control unit (101) and an authentication unit (1022), the communication unit (1021) is configured to transmit the status data information of the patient to the electronic medical record unit (103), and the authentication unit (1022) is configured to obtain data related to the identity information of the patient and upload the data to the monitoring platform (20) via the network for storage.
5. Assistance system according to claim 3, characterized in that the supervision platform (20) is able to automatically generate and provide corresponding unplanned reminder instructions to the patient and/or the healthcare worker when at least one item of detected data acquired by the detection section (106) is outside a standard range value, so that the unplanned reminder instructions are executed after being confirmed,
wherein the unplanned prompting instruction is generated by the supervision platform (20) in a manner that the past prompting instruction and/or the planned prompting instruction and the detection data are matched and associated with each other.
6. The assistance system according to claim 5, wherein the supervision platform (20) is capable of providing a patient and/or a medical staff with a pre-feedback reminder according to at least relevant content in a plan prompt instruction based on a matching correlation result between a past prompt instruction and a plan prompt instruction, and automatically generating at least one plan prompt instruction according to the correlation and/or regularity between the past prompt instruction and the plan prompt instruction, so that the plan prompt instruction is executed after being confirmed.
7. The assistance system according to claim 6, wherein when a plurality of reminders (10) send a plurality of requests containing abnormal signals and having prompt instructions to be sent to the supervision platform (20), the supervision platform (20) regards the requests of the prompt instructions as pseudo-prompt requests and selects the requests which need secondary confirmation and are regarded as pseudo-reminders according to the past prompt instructions,
in the request set formed by the requests regarded as the pseudo-reminders, the supervision platform (20) can collect the requesters of the related prompt instructions into special priority-like prompt objects aiming at the reminders with life risks in the past prompt instructions in preset time, and execute third confirmation according to the positions of the special priority-like prompt objects.
8. The assistance system according to claim 7, characterized in that, when the supervision platform (20) receives a large number of prompt requests originating from data collected by battery-powered sensors and the plurality of reminders (10) sending the prompt requests are within the same power supply loop, the supervision platform (20) establishes a queue of quasi-prioritized reminders objects according to the number of life-threatening reminders in past prompt instructions,
the monitoring platform (20) distinguishes the reminder (10) in the quasi-priority reminding object queue according to the physical position corresponding to the power supply loop, and establishes sub-queues of the quasi-priority reminding object queue in each power supply loop respectively.
9. The assistance system according to claim 8, wherein the monitoring platform (20) sets the assistance system to an offline mode when the monitoring platform (20) receives a plurality of prompt requests from the various sensors within a predetermined time period, and discards the data within the time period so as not to include the data in the patient status data information for activating the prompt instruction,
wherein, the supervision platform (20) jointly stores the time period and the building information corresponding to the power supply loop related to the prompt request, and archives the information as the feedback of the power supply quality.
10. The assistance system according to claim 9, characterized in that when said supervision platform (20) receives a plurality of prompt requests from the data collected by the various sensors within a predetermined time period, said supervision platform (20) switches the execution system to the non-operating state, and stores said time period and the building information corresponding to the power supply circuit related to said prompt request in association and archives them as feedback of the time and the building power supply quality.
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