Risk assessment prevention and control system for indwelling pipeline

Abstract

The invention provides a risk assessment prevention and control system for an indwelling pipeline. The risk assessment prevention and control system comprises an information acquisition terminal, a risk assessment terminal, a nursing plan terminal, a registration terminal and a control terminal, the information acquisition terminal is used for acquiring patient information and nurse information in a ward; the risk assessment terminal is used for performing risk assessment on the indwelling catheter according to the patient information and the nurse information to generate risk assessment information; the nursing plan terminal is used for generating corresponding nursing plan information according to the risk assessment information; the registration terminal is used for a nurse to perform nursing registration according to the corresponding nursing plan information to generate registration information; the control terminal is used for generating permission information according to the registration information, and the permission information is used for being transmitted to a medicine opening system in the ward so as to unlock the medicine opening system. The indwelling catheter has the effect of reducing the infection risk of the indwelling catheter of the patient.

Description

Technical Field

[0001] This invention relates to the technical field of risk assessment, and specifically to a risk assessment and control system for indwelling pipelines. Background Technology

[0002] Indwelling catheters, also known as indwelling needles, reduce patient pain and fear of injections caused by repeated punctures. They facilitate clinical medication administration, including emergency and critical care, and reduce nurses' workload. Indwelling catheters generally include indwelling needles, urethral catheters, and visceral catheters (gastrointestinal, liver, etc.). Risk assessment refers to the quantitative evaluation of the potential impact and loss on various aspects of people's lives, health, and property before a risk event occurs. In other words, risk assessment quantifies the degree of potential impact or loss from an event or phenomenon.

[0003] Numerous risk assessment and control systems and monitoring systems have been developed. Through extensive research and reference, we found existing technologies such as those disclosed in publications CN112133413A, CN111712196A, EP3598258A1, US20090018396A1, and JPWO2019159587A1. These systems generally include: a Hospital Information System (HIS), an indwelling catheter management system, a central processing unit, and a database server. The HIS includes modules for catheter risk assessment, catheter care, management personnel monitoring, adverse event reporting, and doctor-nurse-patient-catheter interaction. However, in hospital settings, cases of catheter dislodgement, patient removal, or failure of nurses to check in a timely manner frequently occur, increasing the risk of infection at the indwelling catheter site. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of the aforementioned risk assessment and control systems and monitoring systems by proposing a risk assessment and control system for indwelling pipelines.

[0005] The present invention adopts the following technical solution:

[0006] A risk assessment and control system for indwelling catheters includes an information acquisition terminal, a risk assessment terminal, a nursing plan terminal, a registration terminal, and a control terminal. The information acquisition terminal acquires patient and nurse information within the ward. The risk assessment terminal performs a risk assessment of the indwelling catheter based on the patient and nurse information, generating risk assessment information. The nursing plan terminal generates corresponding nursing plan information based on the risk assessment information. The registration terminal allows nurses to register nursing care according to the corresponding nursing plan information, generating registration information. The control terminal generates authorization information based on the registration information, which is transmitted to the medication dispensing system within the ward to unlock the medication dispensing system.

[0007] The information acquisition terminal includes an image information module and a sensor information module. The image information module is used to acquire patient image information and nurse image information. The sensor information module is used to acquire sensor information of the hospital bed and generate a patient's bed exit sensing index based on the sensor information.

[0008] The risk assessment terminal includes a risk assessment module and an information receiving module. The information receiving module is used to receive patient image information, nurse image information, and bed exit sensor index. The risk assessment module is used to generate a risk assessment index based on the patient image information, nurse image information, and bed exit sensor index, and to generate risk assessment information based on the risk assessment index.

[0009] The nursing plan terminal includes a nursing plan matching module and a nursing plan information generation module. The nursing plan matching module is used to match the corresponding nursing plan in a preset database based on risk assessment information. The nursing plan information generation module is used to generate corresponding nursing plan information based on the matched nursing plan.

[0010] The registration terminal includes an information reading module and a nursing registration module. The information reading module is used to read nursing plan information from the nursing plan information generation module, and the nursing registration module is used to enable the corresponding nurses to register nursing care according to the corresponding nursing plan information and generate registration information.

[0011] The control terminal includes an analysis module and a license information generation module. The analysis module is used to analyze the registration information and generate analysis results, and the license information is used to generate corresponding license information based on the analysis results.

[0012] Optionally, the risk assessment module includes a patient index calculation submodule, a nurse index calculation submodule, an exit parameter calculation submodule, a risk assessment index calculation submodule, and a risk assessment information generation submodule. The patient index calculation submodule is used to calculate the patient index based on patient image information. The nurse index calculation submodule is used to calculate the nurse index based on nurse image information. The exit parameter calculation submodule is used to calculate the corresponding patient's exit parameters based on the exit sensor index. The risk assessment index calculation submodule is used to calculate the risk assessment index based on the patient index, nurse index, and exit parameters. The risk assessment information generation submodule is used to generate corresponding risk assessment information based on the risk assessment index.

[0013] When the patient index calculation submodule performs the calculation, the following formula is satisfied:

[0014]

[0015] In this framework, B represents the patient index, C represents the patient cooperation level parameter, and S represents the patient physical condition parameter. K1 represents the weighting coefficient of the patient cooperation level parameter, and K2 represents the weighting coefficient of the patient physical condition parameter. Both K1 and K2 are set and adjusted by those skilled in the art based on actual circumstances. K1 ranges from 0 to 1 and is directly proportional to the importance of patient cooperation. If the patient is in a poor state of consciousness and unable to actively cooperate with the procedure, the weight of K1 should be increased to give cooperation a greater impact in risk assessment. Conversely, if the patient is conscious and actively cooperates, K1 can be relatively reduced. K2 ranges from 0 to 1 and is related to the degree of abnormality in the patient's vital signs. The more the vital signs such as body temperature, respiratory rate, and heart rate deviate from normal values, the worse the physical condition, and the weight of K2 should be increased to enhance the risk indication role of physical condition in the patient index. If the vital signs are basically normal, K2 can be appropriately reduced.

[0016]

[0017] Where Z represents the evaluation value of the patient's cooperation level from the attending physician in the ward, α represents the percentage coefficient of the evaluation value, and the longer the patient has been hospitalized, the higher the percentage coefficient of the evaluation value is set. The specific value shall be adjusted by those skilled in the art based on experience or actual situation; T iThe duration of the i-th segment of the patient image information where the patient is conscious is represented, preferably in minutes. I represents the total number of segments of images in the patient image information where the patient is conscious. Preferably, the image information module uses a lightweight image recognition model based on the YOLOv5 architecture to analyze the frequency of the patient's head movements, eye movement characteristics, and facial muscle tension to determine whether the patient is conscious or confused. Specifically, this includes changes in head movement frequency, eye movement characteristics, and facial muscle tension. The system processes continuous image frames in 5-second analysis cycles, analyzing and judging the state of consciousness in the following ways: First, the system tracks changes in the patient's head position. If the head shows multiple significant displacements in the horizontal or vertical direction within the analysis cycle, the patient is considered to have voluntary activity, indicating that they are conscious. If the head posture remains basically unchanged or only slightly trembles, the patient is judged to be in a static state, suggesting possible confusion. Secondly, the system identifies changes in the binocular regions. If the eyes are clearly open and accompanied by frequent changes in eye position in consecutive image frames, the patient is considered to be in the active gaze stage, indicating wakefulness. If the eyes are closed for a long time, or open but the eyeballs are not moving, the system judges it as a lack of gaze response, indicating weakened or blurred consciousness. Thirdly, the system monitors the contour changes of key facial areas (such as the cheeks and forehead) in consecutive frames to identify the degree of muscle activity. If the system detects slight and continuous dynamic changes in the facial muscle contours, it is considered as active muscle tone, indicating wakefulness. If the facial contours are stable, lack change, or show obvious tension, it indicates poor consciousness. After completing the extraction of the three types of features, the system will make a comprehensive judgment based on a preset weighting strategy. If the patient simultaneously possesses two or more of the three features—head movement, gaze response, and active muscle tone—within a cycle, they are judged to be conscious. Conversely, if the three features are insufficient or only one is present, the system automatically marks the patient as having blurred consciousness and provides the risk assessment module with the status label data for that image segment; f1(T i ) represents the filtering function; T j f2(T) represents the duration of the j-th segment of the patient's image information where the patient is in a state of confusion, and J represents the total number of segments of the patient's image information where the patient is in a state of confusion; j ) represents the adjustment function; β represents the adjustable correction coefficient;

[0018]

[0019] Where age represents the patient's age parameter, and weight represents the patient's weight parameter; A p This indicates the average clinical age of patients with the corresponding disease; W last This indicates the patient's average weight over the year prior to admission.

[0020] When the nurse index calculation submodule performs the calculation, the following formula is satisfied:

[0021]

[0022] Where H represents the nurse index, W represents the nurse's years of service, P represents the preset nurse's grade score, K3 represents the weighting coefficient of years of service, and K4 represents the weighting coefficient of the grade score.

[0023] When the bed undisturbed parameter calculation submodule performs the calculation, the following formula is satisfied:

[0024]

[0025] Where L represents the off-bed parameter, U m This represents the status value of the m-th pressure sensor under the patient's upper limb area in the hospital bed within a preset reference time period, i.e., the pressure sensor measurement value, in kPa, with a sampling frequency of 10Hz. Signal processing uses a sliding window mean filtering method to eliminate mattress elasticity interference; M represents the total number of pressure sensors under the patient's upper limb area in the hospital bed; D y V represents the status value of the y-th pressure sensor under the lower limb area of ​​the patient in the hospital bed within a preset reference time period, where Y represents the total number of pressure sensors under the lower limb area of ​​the patient in the hospital bed; n This represents the status value of the nth pressure sensor under the patient's torso and limb area in the hospital bed within a preset reference time period. N represents the total number of pressure sensors under the patient's torso and limb area in the hospital bed. μ1, μ2, and μ3 are proportionality coefficients, with values ​​ranging from 0 to 1, and are set by the administrator based on experience. μ1 < μ2 < μ3.

[0026] When the risk assessment index calculation submodule performs the calculation, the risk assessment index R satisfies the following formula:

[0027] R = B + H + L.

[0028] Optionally, the nursing plan matching module includes a comparison submodule and a selection submodule; the comparison submodule is used to compare the risk assessment index in the risk assessment information with a preset comparison threshold range to determine the nursing plan code corresponding to the comparison threshold range in which the patient's risk assessment index is located; the selection submodule is used to match the corresponding nursing plan in a preset database according to the nursing plan code corresponding to the comparison threshold range.

[0029] A risk assessment and control method for indwelling conduits, applied to a risk assessment and control system for indwelling conduits as described above, the risk assessment and control method comprising:

[0030] S1, obtain patient and nurse information in the ward;

[0031] S2, based on patient and nurse information, performs a risk assessment of indwelling catheters and generates risk assessment information;

[0032] S3, Generate corresponding nursing plan information based on risk assessment information;

[0033] S4 is used by nurses to register nursing care according to the corresponding nursing plan information and generate registration information.

[0034] S5, generate license information based on registration information;

[0035] S6 transmits the data to the medication dispensing system in the ward to unlock the medication dispensing system.

[0036] The beneficial effects achieved by this invention are:

[0037] 1. The setup of information acquisition terminals, risk assessment terminals, nursing plan terminals, registration terminals, and control terminals facilitates rapid and comprehensive information acquisition, risk assessment, selection of nursing plans, implementation of nursing plans, and improvement of the stability and safety of subsequent medication dispensing operations. It also accurately and efficiently reduces the risk of patient indwelling catheter dislodgement, thereby reducing the risk of infection at the patient's indwelling catheter site.

[0038] 2. The inclusion of image information module and sensor information module helps to increase the dimensionality of information, facilitates multi-angle calculation and generation of risk assessment information, thereby improving the accuracy of risk assessment;

[0039] 3. The nursing plan matching module and nursing plan information generation module are designed to help select the most suitable nursing plan for the patient based on risk assessment information, thereby further reducing the risk of patient indwelling catheter dislodgement and the risk of infection at the patient indwelling catheter site;

[0040] 4. The setup of the patient index calculation submodule, nurse index calculation submodule, bed exit parameter calculation submodule, risk assessment index calculation submodule, and risk assessment information generation submodule is conducive to working with the patient index algorithm, nurse index algorithm, bed exit parameter algorithm, and risk assessment index algorithm to further improve the accuracy of indwelling catheter dislodgement risk assessment, thereby making the selection of nursing plans more accurate, and thus greatly reducing the risk of patient indwelling catheter dislodgement and the risk of infection at the indwelling catheter site;

[0041] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the overall structure of the present invention;

[0043] Figure 2 This is a schematic diagram of the process flow for a risk assessment and control method for a lodged conduit in this invention;

[0044] Figure 3 This is a schematic diagram of the overall structure of the nursing plan terminal in this invention;

[0045] Figure 4 This is a schematic diagram of the judgment method of the indwelling pipeline monitoring module in this invention. Detailed Implementation

[0046] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0047] Example 1: This example provides a risk assessment and control system for indwelling conduits. Combined with... Figure 1 As shown, a risk assessment and control system for indwelling catheters includes an information acquisition terminal, a risk assessment terminal, a nursing plan terminal, a registration terminal, and a control terminal. The information acquisition terminal acquires patient and nurse information within the ward. The risk assessment terminal performs a risk assessment of the indwelling catheter based on the patient and nurse information, generating risk assessment information. The nursing plan terminal generates corresponding nursing plan information based on the risk assessment information. The registration terminal allows nurses to register nursing care according to the corresponding nursing plan information, generating registration information. The control terminal generates authorization information based on the registration information, which is transmitted to the medication dispensing system within the ward to unlock the medication dispensing system.

[0048] The information acquisition terminal includes an image information module and a sensor information module. The image information module is used to acquire patient image information and nurse image information. The sensor information module is used to acquire sensor information of the hospital bed and generate a patient's bed exit sensing index based on the sensor information.

[0049] The risk assessment terminal includes a risk assessment module and an information receiving module. The information receiving module is used to receive patient image information, nurse image information, and bed exit sensor index. The risk assessment module is used to generate a risk assessment index based on the patient image information, nurse image information, and bed exit sensor index, and to generate risk assessment information based on the risk assessment index.

[0050] The nursing plan terminal includes a nursing plan matching module and a nursing plan information generation module. The nursing plan matching module is used to match the corresponding nursing plan in a preset database based on risk assessment information. The nursing plan information generation module is used to generate corresponding nursing plan information based on the matched nursing plan.

[0051] The registration terminal includes an information reading module and a nursing registration module. The information reading module is used to read nursing plan information from the nursing plan information generation module, and the nursing registration module is used to enable the corresponding nurses to register nursing care according to the corresponding nursing plan information and generate registration information.

[0052] The control terminal includes an analysis module and a license information generation module. The analysis module is used to analyze the registration information and generate analysis results, and the license information is used to generate corresponding license information based on the analysis results.

[0053] It is important to note that after admitting a patient, a pre-observation period is predetermined. During this period, with the patient's consent, photographs and videos are taken to obtain image information. This observation period is set or adjusted by the doctor based on the patient's physical condition and serves as a reference timeframe.

[0054] Optionally, the risk assessment module includes a patient index calculation submodule, a nurse index calculation submodule, an exit parameter calculation submodule, a risk assessment index calculation submodule, and a risk assessment information generation submodule. The patient index calculation submodule is used to calculate the patient index based on patient image information. The nurse index calculation submodule is used to calculate the nurse index based on nurse image information. The exit parameter calculation submodule is used to calculate the corresponding patient's exit parameters based on the exit sensor index. The risk assessment index calculation submodule is used to calculate the risk assessment index based on the patient index, nurse index, and exit parameters. The risk assessment information generation submodule is used to generate corresponding risk assessment information based on the risk assessment index.

[0055] When the patient index calculation submodule performs the calculation, the following formula is satisfied:

[0056]

[0057] In this framework, B represents the patient index, C represents the patient cooperation level parameter, and S represents the patient physical condition parameter. K1 represents the weighting coefficient of the patient cooperation level parameter, and K2 represents the weighting coefficient of the patient physical condition parameter. Both K2 and K3 are set and adjusted by those skilled in the art based on actual circumstances. K1 ranges from 0 to 1 and is directly proportional to the importance of patient cooperation. If the patient is in a poor state of consciousness and unable to actively cooperate with the procedure, the weight of K1 should be increased to give cooperation a greater impact in risk assessment. Conversely, if the patient is conscious and actively cooperates, K1 can be relatively reduced. K2 ranges from 0 to 1 and is related to the degree of abnormality in the patient's vital signs. The more the vital signs such as body temperature, respiratory rate, and heart rate deviate from normal values, the worse the physical condition, and the weight of K2 should be increased to enhance the risk indication role of physical condition in the patient index. If the vital signs are basically normal, K2 can be appropriately reduced.

[0058]

[0059]

[0060] Where Z represents the evaluation value of the patient's cooperation level from the attending physician in the ward. The Z value is the cooperation level score given by the attending physician after assessing the patient's treatment compliance during hospitalization. The scoring rule is preferably a discrete integer value, ranging from 1 to 5, and is defined as follows: Z=1: The patient is completely uncooperative, exhibiting behaviors such as continuous refusal of treatment and violation of medical orders; Z=2: The patient's cooperation level is poor, often exhibiting delayed medication, partial refusal of examinations, etc.; Z=3: The patient's cooperation level is average, able to comply with most medical orders, with occasional delays or non-standard behaviors; Z=4: The patient's cooperation level is good, basically complying with medical orders, with only occasional minor non-cooperation; Z=5: The patient's cooperation level is excellent, actively cooperating with examinations, treatments, and rehabilitation suggestions. Those skilled in the art can also make corresponding settings based on the above rules. α represents the proportion coefficient of the evaluation value. The longer the patient has been hospitalized, the larger the proportion coefficient of the evaluation value should be set. The specific value can be adjusted by those skilled in the art based on experience or actual situation; T iThe duration of the i-th segment of the patient image information where the patient is conscious is represented, preferably in minutes. I represents the total number of segments of images in the patient image information where the patient is conscious. Preferably, the image information module uses a lightweight image recognition model based on the YOLOv5 architecture to analyze the frequency of the patient's head movements, eye movement characteristics, and facial muscle tension to determine whether the patient is conscious or confused. Specifically, this includes changes in head movement frequency, eye movement characteristics, and facial muscle tension. The system processes continuous image frames in 5-second analysis cycles, analyzing and judging the state of consciousness in the following ways: First, the system tracks changes in the patient's head position. If the head shows multiple significant displacements in the horizontal or vertical direction within the analysis cycle, the patient is considered to have voluntary activity, indicating that they are conscious. If the head posture remains basically unchanged or only slightly trembles, the patient is judged to be in a static state, suggesting possible confusion. Secondly, the system identifies changes in the binocular regions. If the eyes are clearly open and accompanied by frequent changes in eye position in consecutive image frames, the patient is considered to be in the active fixation stage, indicating wakefulness. If the eyes are closed for a long time, or open but the eyeballs are not moving, the system judges it as a lack of fixation response, indicating weakened or blurred consciousness. Thirdly, the system monitors the contour changes of key facial areas (such as the cheeks and forehead) in consecutive frames to identify the degree of muscle activity. If the system detects slight and continuous dynamic changes in the facial muscle contours, it is considered as active muscle tone, indicating wakefulness. If the facial contours are stable, lack change, or show obvious tension, it indicates poor consciousness. After completing the extraction of the three types of features, the system will make a comprehensive judgment based on a preset weighting strategy. If the patient simultaneously possesses two or more of the three features of head movement, fixation response, and active muscle tone within a cycle, the patient is judged to be conscious. Conversely, if the three features are insufficient or only one is present, the system automatically marks the patient as having blurred consciousness and provides the status label data of that image segment to the risk assessment module.

[0061] f1(T i ) represents the filtering function; T j f2(T) represents the duration of the j-th segment of the patient's image information where the patient is in a state of confusion, and J represents the total number of segments of the patient's image information where the patient is in a state of confusion; j ) represents the adjustment function; β represents the adjustable correction coefficient, which ranges from 0 to 1. The longer the patient's expected length of hospital stay, the larger the adjustable correction coefficient.

[0062]

[0063] Where age represents the patient's age parameter, i.e., physical age, and weight represents the patient's weight parameter, i.e., body weight; A p This indicates the average clinical age of patients with the corresponding disease; Wlast The average weight of the patient within one year prior to admission is indicated; in this embodiment, the unit of age is preferably years, and the unit of weight is preferably kg.

[0064] When the nurse index calculation submodule performs the calculation, the following formula is satisfied:

[0065]

[0066] Wherein, H represents the nurse index; W represents the nurse's years of service in years; P represents the preset nurse level score, which is used to quantify the nurse's ability level in the patient management process. The score is an integer value, ranging from 1 to 5. The preferred definitions of P value are as follows: P=1: indicates that the nurse is in the internship stage or a junior nurse, who can only complete basic nursing tasks and needs full guidance; P=2: indicates that the nurse has preliminary independent nursing ability, can complete routine nursing tasks, and needs intermittent supervision; P=3: indicates that the nurse is an intermediate nurse, who can independently handle common nursing events and has basic risk identification ability; P=4: indicates that the nurse is a senior nurse, who, in addition to having independent nursing ability, can also guide others and handle emergencies; P=5: indicates that the nurse is a senior nursing backbone, who has the ability to coordinate the entire process, teach, and handle complex problems. Those skilled in the art can also make corresponding settings according to the above rules. K3 represents the weighting coefficient for seniority; the more severe the patient's condition, the higher the weighting coefficient for seniority. K4 represents the weighting coefficient for grade rating; the more patients a nurse cares for, the higher the weighting coefficient for grade rating.

[0067] When the bed undisturbed parameter calculation submodule performs the calculation, the following formula is satisfied:

[0068]

[0069] Where L represents the off-bed parameter, U m This represents the status value of the m-th pressure sensor under the patient's upper limb area in the hospital bed within a preset reference time period; that is, the pressure sensor measurement value, in kPa, with a sampling frequency of 10Hz. Signal processing uses a sliding window mean filtering method to eliminate mattress elasticity interference; M represents the total number of pressure sensors under the patient's upper limb area in the hospital bed; D y V represents the status value of the y-th pressure sensor under the lower limb area of ​​the patient in the hospital bed within a preset reference time period, where Y represents the total number of pressure sensors under the lower limb area of ​​the patient in the hospital bed; nThis indicates the status value of the nth pressure sensor under the patient's torso and limb area in the hospital bed within a preset reference time period. N represents the total number of pressure sensors under the patient's torso and limb area in the hospital bed. μ1, μ2, and μ3 are all adjustable proportional coefficients, with values ​​ranging from 0 to 1, and are set by the administrator based on experience. μ1 < μ2 < μ3.

[0070] When the risk assessment index calculation submodule performs the calculation, the risk assessment index R satisfies the following formula:

[0071] R = B + H + L.

[0072] Optionally, the nursing plan matching module includes a comparison submodule and a selection submodule; the comparison submodule is used to compare the risk assessment index in the risk assessment information with a preset comparison threshold range to determine the nursing plan code corresponding to the comparison threshold range in which the patient's risk assessment index is located; the selection submodule is used to match the corresponding nursing plan in a preset database according to the nursing plan code corresponding to the comparison threshold range.

[0073] When the comparison submodule is working, the following equation is satisfied:

[0074]

[0075] Wherein, O(R) represents the nursing plan coding function, η1, η2, η3, η4, η5 and η6 represent adjustable comparison thresholds, and E1, E2, E3, E4, E5 and E6 represent nursing plan codes corresponding to their respective comparison threshold intervals; the nursing plan codes correspond one-to-one with the nursing plans in the database.

[0076] Optionally, the nursing plan corresponding to the nursing plan coding function O(R) = E1 is set to a viewing cycle of once every 2 hours; the nursing plan corresponding to the nursing plan coding function O(R) = E2 is set to a viewing cycle of once every 1.5 hours; the nursing plan corresponding to the nursing plan coding function O(R) = E3 is set to a viewing cycle of once every 1.25 hours; the nursing plan corresponding to the nursing plan coding function O(R) = E4 is set to a viewing cycle of once every 1 hour; the nursing plan corresponding to the nursing plan coding function O(R) = E5 is set to a viewing cycle of once every 0.5 hours; and the nursing plan corresponding to the nursing plan coding function O(R) = E6 is set to a viewing cycle of once every 0.25 hours.

[0077] A risk assessment and control method for indwelling conduits is applied to a risk assessment and control system for indwelling conduits as described above, combined with... Figure 2 As shown, the risk assessment and control methods include:

[0078] S1, obtain patient and nurse information in the ward;

[0079] S2, based on patient and nurse information, performs a risk assessment of indwelling catheters and generates risk assessment information;

[0080] S3, Generate corresponding nursing plan information based on risk assessment information;

[0081] S4 is used by nurses to register nursing care according to the corresponding nursing plan information and generate registration information.

[0082] S5, generate license information based on registration information;

[0083] S6 transmits the data to the medication dispensing system in the ward to unlock the medication dispensing system.

[0084] In summary, the setup of information acquisition terminals, risk assessment terminals, nursing plan terminals, registration terminals, and control terminals facilitates rapid and comprehensive information acquisition and analysis for risk assessment, nursing plan selection, and implementation, thereby improving the stability and safety of subsequent medication dispensing procedures and accurately and efficiently reducing the risk of indwelling catheter dislodgement. The inclusion of image and sensor information modules enhances the dimensionality of information, enabling multi-angle calculation and generation of risk assessment information. The nursing plan matching and nursing plan information generation modules facilitate the selection of the most suitable nursing plan for the patient based on risk assessment information. Furthermore, the inclusion of patient index calculation, nurse index calculation, bed exit parameter calculation, risk assessment index calculation, and risk assessment information generation submodules, in conjunction with patient index, nurse index, bed exit parameter, and risk assessment index algorithms, further improves the accuracy of indwelling catheter dislodgement risk assessment, leading to more accurate nursing plan selection and significantly reducing the risk of indwelling catheter dislodgement and infection at the catheter site.

[0085] Example 2; This example includes all the content of Example 1, and provides a risk assessment and control system for indwelling pipelines, combined with Figure 3 As shown, the selection submodule includes a special nursing time calculation unit and a selection unit. The selection unit is used to match the corresponding nursing plan in a preset database according to the nursing plan code corresponding to the comparison threshold interval. The special nursing time calculation unit is used to adjust the viewing cycle in the nursing plan corresponding to the nursing plan coding function O(R) = E6.

[0086] When the special care time calculation unit performs calculations, the following formula must be satisfied:

[0087] Q = A + f3(F) * log2|F|

[0088]

[0089] Where Q represents the special care time adjustment value, A represents the patient's question-and-answer score, and F represents the patient's physical examination score. Both A and F can be negative. The patient's question-and-answer score comes from a question-and-answer test conducted by the nurse during the patient's visit. The test consists of a preset number of questions, each with the same and adjustable score, set by the nurse or doctor based on actual circumstances or experience. Correct answers result in positive scores, while incorrect or unanswerable answers result in negative scores. The examination score comes from routine physical examinations performed by the nurse during the patient's visit. The number of routine examination items is adjusted according to the patient's specific condition, with each item having the same and adjustable score, also set by the nurse or doctor based on actual circumstances or experience. Patients whose physical condition matches the examination item receive positive scores, while those whose condition does not match receive negative scores. The number of routine examination items is greater than the number of test questions. f3(F) represents the sign selection function.

[0090] For example, the test has 4 questions, each worth ±1 point. If a patient in the ward answers 3 questions correctly and 1 incorrectly, they receive 2 points, so A = 2. The routine examination has 16 items, each worth ±1 point. If a patient in the ward meets 12 of the requirements and does not meet 4, they receive 8 points, so F = 8. Therefore, Q = 5, and the unit of Q is set to minutes. That is, the nursing plan update corresponding to the nursing plan coding function O(R) = E6 is: the viewing cycle is set to once every 20 minutes.

[0091] In summary, the setting of a special nursing time calculation unit facilitates the updating of the nursing plan corresponding to the nursing plan coding function O(R) = E6, enabling patients of the corresponding level to receive better and more reasonable care.

[0092] Example 3: This example includes all the content of Example 2, and provides a risk assessment and control system for indwelling conduits, combined with... Figure 4 As shown, the information acquisition terminal also includes an indwelling tube monitoring module. The indwelling tube monitoring module is used to monitor the externally inserted tube and generate monitoring image information; based on the monitoring image information, it determines whether there is a risk of the indwelling tube dislodging; if a risk exists, it generates an alarm message.

[0093] When the indwelling tube monitoring module determines whether there is a risk of the indwelling tube detaching, it includes the following steps:

[0094] A1 performs image processing on the monitoring image information, identifies the displacement of the indwelling pipe, and generates displacement information;

[0095] A2, makes a judgment based on the shift information and the preset shift threshold;

[0096] A3. If the shift information is greater than the shift threshold, it is determined that there is a risk of detachment, and an alarm message is generated.

[0097] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A risk assessment and control system for indwelling pipelines, characterized in that, It includes an information acquisition terminal, a risk assessment terminal, a nursing plan terminal, a registration terminal, and a control terminal; the information acquisition terminal is used to acquire patient information and nurse information in the ward; the risk assessment terminal is used to perform risk assessment of indwelling tubes based on patient information and nurse information, and generate risk assessment information; The nursing plan terminal is used to generate corresponding nursing plan information based on risk assessment information; The registration terminal is used by nurses to register nursing care according to the corresponding nursing plan information and generate registration information. The control terminal is used to generate permission information based on the registration information, and the permission information is used to transmit to the medication dispensing system in the ward to unlock the medication dispensing system; The information acquisition terminal includes an image information module and a sensor information module. The image information module is used to acquire patient image information and nurse image information. The sensor information module is used to acquire sensor information of the hospital bed and generate a patient's bed exit sensing index based on the sensor information. The risk assessment terminal includes a risk assessment module and an information receiving module. The information receiving module is used to receive patient image information, nurse image information, and bed exit sensor index. The risk assessment module is used to generate a risk assessment index based on the patient image information, nurse image information, and bed exit sensor index, and to generate risk assessment information based on the risk assessment index. The nursing plan terminal includes a nursing plan matching module and a nursing plan information generation module. The nursing plan matching module is used to match the corresponding nursing plan in a preset database based on risk assessment information. The nursing plan information generation module is used to generate corresponding nursing plan information based on the matched nursing plan. The registration terminal includes an information reading module and a nursing registration module. The information reading module is used to read nursing plan information from the nursing plan information generation module, and the nursing registration module is used to enable the corresponding nurses to register nursing care according to the corresponding nursing plan information and generate registration information. The control terminal includes an analysis module and a license information generation module. The analysis module is used to analyze the registration information and generate analysis results, and the license information is used to generate corresponding license information based on the analysis results.

2. The risk assessment and control system for indwelling pipelines as described in claim 1, characterized in that, The risk assessment module includes a patient index calculation submodule, a nurse index calculation submodule, an exit parameter calculation submodule, a risk assessment index calculation submodule, and a risk assessment information generation submodule. The patient index calculation submodule is used to calculate the patient index based on patient image information. The nurse index calculation submodule is used to calculate the nurse index based on nurse image information. The exit parameter calculation submodule is used to calculate the corresponding patient's exit parameters based on the exit sensor index. The risk assessment index calculation submodule is used to calculate the risk assessment index based on the patient index, nurse index, and exit parameters. The risk assessment information generation submodule is used to generate corresponding risk assessment information based on the risk assessment index. When the patient index calculation submodule performs the calculation, the following formula is satisfied: Wherein, B represents the patient index, C represents the patient cooperation parameter, and S represents the patient physical condition parameter; K1 represents the weighting coefficient of the patient cooperation parameter, K2 represents the weighting coefficient of the patient physical condition parameter, and K2 and K3 are set and adjusted by those skilled in the art according to the actual situation. Where Z represents the evaluation value of the patient's cooperation level from the attending physician in the ward, α represents the percentage coefficient of the evaluation value, which is adjusted by those skilled in the art based on experience or actual situation; T i f1(T) represents the duration of the i-th segment of the patient image information where the patient is conscious; I represents the total number of segments of the patient image information where the patient is conscious, f1(T) i ) represents the filtering function; T j f2(T) represents the duration of the j-th segment of the patient's image information where the patient is in a state of confusion, and J represents the total number of segments of the patient's image information where the patient is in a state of confusion; j ) represents the adjustment function; β represents the adjustable correction coefficient; Where age represents the patient's age parameter, i.e., physical age, and weight represents the patient's weight parameter, i.e., body weight; A p This indicates the average clinical age of patients with the corresponding disease; W last This indicates the patient's average weight over the year prior to admission. When the nurse index calculation submodule performs the calculation, the following formula is satisfied: Where H represents the nurse index, W represents the nurse's years of service, P represents the preset nurse's grade score, K3 represents the weighting coefficient of years of service, and K4 represents the weighting coefficient of the grade score. When the bed undisturbed parameter calculation submodule performs the calculation, the following formula is satisfied: Where L represents the off-bed parameter, U m This represents the status value of the m-th pressure sensor under the upper limb area of ​​the patient in the bed within a preset reference time period, where M represents the total number of pressure sensors under the upper limb area of ​​the patient in the bed; D y V represents the status value of the y-th pressure sensor under the lower limb area of ​​the patient in the hospital bed within a preset reference time period, where Y represents the total number of pressure sensors under the lower limb area of ​​the patient in the hospital bed; n This represents the status value of the nth pressure sensor under the patient's trunk and limb area in the hospital bed within a preset reference time period, where N represents the total number of pressure sensors under the patient's trunk and limb area in the hospital bed; μ1, μ2, and μ3 are all adjustable proportional coefficients, where μ1 < μ2 < μ3; When the risk assessment index calculation submodule performs the calculation, the risk assessment index R satisfies the following formula: R = B + H + L.

3. The risk assessment and control system for indwelling pipelines as described in claim 2, characterized in that, The nursing plan matching module includes a comparison submodule and a selection submodule. The comparison submodule is used to compare the risk assessment index in the risk assessment information with a preset comparison threshold range to determine the nursing plan code corresponding to the comparison threshold range in which the patient's risk assessment index is located. The selection submodule is used to match the corresponding nursing plan in a preset database according to the nursing plan code corresponding to the comparison threshold range.

4. A risk assessment and control method for indwelling conduits, applied to a risk assessment and control system for indwelling conduits as described in claim 3, characterized in that, The risk assessment and prevention methods include: S1, obtain patient and nurse information in the ward; S2, based on patient and nurse information, performs a risk assessment of indwelling catheters and generates risk assessment information; S3, Generate corresponding nursing plan information based on risk assessment information; S4 is used by nurses to register nursing care according to the corresponding nursing plan information and generate registration information. S5, generate license information based on registration information; S6 transmits the data to the medication dispensing system in the ward to unlock the medication dispensing system.

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