Intelligent nursing safety management skin management reckoning disc

Abstract

The invention discloses an intelligent nursing safety management skin management reckoning disc which comprises a chart module of a multilayer concentric circle structure, a calculation model and intelligent analysis algorithm module, a touch operation interface, a data recording and exporting module and an implementation module. The reckoning disc adopts a chart module of a multi-layer concentric circle structure, through different colors and layered display of skin stages, clinical manifestation, nursing measures and prevention strategies, nursing personnel can obtain information visually and conveniently, a skin health score calculation model, a treatment scheme recommendation algorithm, a nursing effect prediction model and a risk early warning algorithm are integrated in the system, and the system is convenient to use. The skin condition of the patient is accurately evaluated based on multiple skin health indexes, and the nursing suggestions are updated in real time, so that the nursing efficiency is improved, and the misjudgment risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of medical care and skin management, and in particular to an intelligent care safety management skin management abacus. Background Art

[0002] In the field of medical care, skin management is an important part of daily care for patients. Its safety and effectiveness are directly related to the patient's recovery process and quality of life. With the continuous advancement of medical technology and the increasing diversity of patient needs, how to scientifically and efficiently manage skin problems has become an important issue that needs to be solved in nursing work.

[0003] Traditional skin management methods mainly rely on the personal experience and manual operation of nursing staff. This method is highly subjective, often resulting in inaccurate evaluation results and is easily affected by nursing staff's judgment bias. At the same time, manual operation is inefficient, and the entire evaluation and management process is cumbersome and time-consuming, which is more prone to operational errors or omissions when facing a large number of patients. In addition, since nursing methods are difficult to standardize, it is easy to cause data inconsistency and lack of traceability, which ultimately affects the quality and effectiveness of nursing.

[0004] The skin condition of each patient varies significantly due to various factors such as age, medical condition, and lifestyle habits. Traditional skin management methods are often unable to provide personalized care designs for different patients. Due to the lack of scientific quantitative standards and analysis models, nursing staff can only formulate skin care plans based on limited experience, which is not conducive to improving the quality of care.

[0005] Based on this, an intelligent care safety management skin management abacus is needed. Summary of the invention

[0006] To achieve the above object, the present invention provides the following solution: an intelligent nursing safety management skin management abacus, comprising:

[0007] Multi-layer concentric circle structure chart module, calculation model and intelligent analysis algorithm module, touch operation interface, data recording and export module and implementation module;

[0008] The multi-layer concentric circle structure chart module is expanded layer by layer from the center to the outside, and each layer is evenly divided into multiple areas and distinguished by different colors, so as to intuitively present the pressure injury information of each stage; each layer of the chart respectively displays the stage identification, clinical manifestations, description of injury characteristics, nursing measures and prevention strategies;

[0009] The multi-layer concentric circle structure chart module includes:

[0010] The first level: used to indicate the stages of pressure injuries, using numbers to identify the injury status at different stages to help nursing staff quickly identify the extent of the injury;

[0011] The second layer: used to display the clinical manifestations of pressure injuries at different stages and to visually determine the type of injury;

[0012] The third level: a written description of the clinical manifestations of each stage of injury in the second level, providing detailed symptom characteristics information;

[0013] Level 4: Describe in text the nursing measures suitable for injuries of different stages;

[0014] Level 5: Demonstrate the prevention strategies for each stage and describe the preventive measures for the formulation of prevention plans;

[0015] The computational model and intelligent analysis algorithm module includes a skin condition assessment model, a treatment plan recommendation algorithm, a nursing effect prediction model, and a safety risk management algorithm, which are constructed based on a large amount of clinical data and expert experience, and conduct in-depth analysis of the input patient information;

[0016] To achieve: accurately assess the patient's skin condition, recommend personalized treatment plans, predict care effects, and warn of potential safety risks;

[0017] The touch operation interface is equipped with an intuitive touch screen, supports click, slide and voice interaction, completes information query and nursing advice acquisition through simple operation, and provides data export and printing;

[0018] The data recording and exporting module is used to store the patient's assessment report, nursing records and analysis results so that nursing staff can view and share nursing information later;

[0019] The implementation module includes:

[0020] Skin condition assessment: after the nurse inputs the patient's basic information and skin symptoms, the abacus will automatically generate an assessment report;

[0021] Recommend treatment plans and provide personalized care and treatment plans based on the results of skin condition assessment;

[0022] Nursing effect prediction: through nursing records and feedback information, the abacus predicts the patient's recovery process and provides adjustment suggestions;

[0023] Safety risk management, real-time monitoring of changes in skin conditions, and automatic warnings if abnormalities occur.

[0024] Further preferably, the multi-layer concentric circle structure chart module displays skin health conditions, damage characteristics, care measures and prevention strategies at different stages in a standardized manner, wherein:

[0025] The first circle shows the different stages of skin damage, using different colors to indicate the status of each stage: 0 represents normal skin, displayed in white; 1 represents mild damage, displayed in pink; 2 represents moderate damage, displayed in red; 3 represents full-thickness skin damage, displayed in yellow; 4 represents severe damage, displayed in black;

[0026] The second circle shows the characteristics and manifestations of skin damage at different stages, including: Stage 0 is normal skin structure, showing that the epidermis, dermis and subcutaneous tissue are intact; Stage 1 is epidermal damage, manifested as non-fading erythema; Stage 2 is dermal damage, which may have blisters of varying sizes, shallow ulcers and exudate; Stage 3 is full-thickness skin damage, with visible fat layer and slough, but no exposed bones, tendons or muscles; Stage 4 damage reaches bones and tendons, and in severe cases, exposed bones and muscles can be seen, accompanied by insidious and tunnel-like damage characteristics;

[0027] The third circle contains pictures of pressure injuries corresponding to each stage of injury;

[0028] The content of the fourth circle shows the nursing measures and operational suggestions for different injury stages. The susceptible population in stage 0 is patients who cannot move on their own, have decreased consciousness, are incontinent, are bedridden or in wheelchairs for a long time, and the elderly with poor nutritional status; stage 1 recommends routine care, including keeping the skin clean and dry, turning over regularly, using air mattresses and other measures; stage 2 recommends consulting the skin management nursing team and adjusting the nursing plan in a targeted manner; stage 3 recommends consulting the skin management nursing team and standardizing the treatment; stage 4 requires the skin management team to work with the multidisciplinary team MDT of orthopedics and nutrition to prevent systemic infection.

[0029] Further preferably, the skin condition assessment model is based on a multivariate regression analysis method of skin health score, and the skin health score S is calculated by comprehensively considering factors such as the humidity, temperature, elasticity, injury area and blood flow of the patient's skin. The specific formula is as follows:

[0030] S=α1X1+α2X2+α3X3+α4X4+α5X5+β

[0031] Among them: S represents the skin health score, which quantifies the current overall health status of the patient's skin;

[0032] Variables X1 to X5 represent five indicators that have a greater impact on skin health, namely skin moisture, temperature, elasticity, damaged area, and blood flow:

[0033] Humidity X1 reflects the hydration of the skin, temperature X2 indicates the metabolic activity on the surface and inside of the skin, elasticity X3 evaluates the skin's recovery ability, damage area X4 measures the severity of skin damage, and blood flow X5 reflects the nutrition and oxygen supply of the skin;

[0034] The regression coefficients α1 to α5 and the bias term β are obtained by fitting based on clinical data and are used to determine the relative impact of each indicator on the skin health score; to eliminate the differences between the units of different indicators, each input variable X i will be standardized before calculation, and the standardization formula is:

[0035]

[0036] where, X i i is the value after standardization, μX i is the mean value, σX i is the standard deviation. The skin health score S will be used as an input parameter for subsequent treatment recommendations and prediction of nursing effects to ensure continuous data invocation between different modules.

[0037] Further preferably, the treatment plan recommendation algorithm generates a treatment intensity T based on the patient's skin health score S and the injury stage D, which is used to optimize the selection of the treatment plan. The formula is:

[0038]

[0039] where: The treatment intensity T is a continuous value, ranging from 0 to 1 exponential value. The higher the value, the higher the treatment intensity requirement, and it is recommended to adopt a more aggressive treatment method;

[0040] The skin health score S is provided by the skin condition assessment model, which reflects the patient's current skin health level. The stage D is determined according to the degree of injury and is set as an integer from 1 to 5. The parameters λ and μ in the formula are adjusted through clinical data to optimize the relative impact of the score and the stage on the treatment intensity. Through the Sigmoid activation function ensure that the calculated result T is always within the range of 0 to 1;

[0041] Then, according to the obtained treatment intensity T, the following treatment methods are intelligently selected:

[0042] When T > 0.8: Recommend surgical debridement to deal with severe injuries; when 0.5 < T ≤ 0.8: Recommend antibiotics or anti-inflammatory drugs; when T ≤ 0.5: Suggest physical therapy to adapt to the injury conditions of different patients.

[0043] Further preferably, the nursing effect prediction model is based on the recursive neural network (RNN) architecture, and dynamically predicts the patient's recovery process E(t) through historical nursing data and the skin health score S. The specific formula is:

[0044] E(t) = σ(W·E(t - 1) + U·S + V·F + b)

[0045] Among them, the predicted value of the nursing effect E(t) represents the rehabilitation progress at time t, which is used to evaluate the nursing effect of the patient and quantify the patient's rehabilitation progress. By using the time series characteristics of the recurrent neural network, the predicted value E(t - 1) at the previous moment is combined with the current skin health score S and the nursing frequency F to achieve continuous prediction.

[0046] The weight matrices W, U, V and the bias term b are obtained through backpropagation training to ensure that the model adapts to the individual differences of patients. The activation function σ uses ReLU to make the output value change smoothly. The loss function is calculated using the mean square error MSE, and the formula is:

[0047]

[0048] The loss function is used to minimize the prediction error and optimize the model parameters.

[0049] Further preferably, the safety risk management algorithm calculates the comprehensive risk score R based on the change trends of the skin health score S and the predicted value of the nursing effect E(t) to evaluate the risk in the nursing process in real time. The formula is

[0050] The risk score R measures the nursing risk through the relative change amount of the skin health score and the nursing effect. Among them, S represents the current skin health score, and E(t) is the current predicted value of the nursing effect. Both are compared with S 基准 and E 基准 in the ideal state. The reference value is set through the data of healthy individuals or standard nursing samples to provide a comparison benchmark.

[0051] Risk trigger conditions: When R > 40%, the system automatically triggers a high - risk warning to prompt the nursing staff to closely monitor. When 20% < R ≤ 40% and it exceeds 20% three times in a row, a medium - risk warning is triggered, and it is recommended to adjust the nursing frequency or plan. The risk warning in the nursing process is provided through the risk score R calculated in real time.

[0052] Further preferably, the click selection of the touch operation interface is used to locate and view the information of different skin stages among the layers of the multi - layer concentric circle structure; the sliding switch supports navigation between different layers to display the skin stage, clinical manifestations and the content of the nursing plan; the voice input allows the nursing staff to describe the patient's skin condition through voice input, and the system automatically generates a preliminary evaluation result and displays it on the interface in real time.

[0053] Further preferably, the data recording and exporting module has data analysis and standardized report generation functions, which is used for nursing staff to systematically manage and store patient care data, and clearly show the changes in patient care effects over time by generating skin health score trend graphs and rehabilitation progress curve graphs; and generate standardized care reports, including skin health score reports, personalized care recommendations, care effect predictions and risk warning records.

[0054] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0055] 1. The intelligent nursing safety management skin management abacus of the present invention can accurately evaluate the patient's skin condition by integrating calculation models and intelligent analysis algorithms. It can generate objective and quantitative skin health scores based on multiple skin health indicators such as humidity, temperature, elasticity, damage area and blood flow. Compared with the traditional method that relies on the experience and judgment of nursing staff, the evaluation method of the abacus is more scientific and effectively reduces the subjectivity and error rate in the nursing process.

[0056] Second, the safety risk management algorithm built into the abacus of the present invention can monitor the changing trend of the patient's skin condition in real time, automatically calculate the comprehensive risk score, and issue a warning signal when the risk reaches the set threshold. Nursing staff can adjust nursing measures in time according to the warning, thereby reducing potential risks caused by delayed nursing or improper operation;

[0057] 3. The abacus of the present invention adopts a portable and intuitive and easy-to-use operating interface, which is convenient for nursing staff to carry and use. At the same time, its built-in calculation model and intelligent analysis algorithm can automatically complete tedious calculation and analysis work, reducing the workload of nursing staff. In addition, through the data export and printing function, nursing staff can easily save and share information such as evaluation results, treatment plans and nursing records, thereby improving the efficiency and quality of nursing work;

[0058] 4. The abacus of the present invention provides a scientific and accurate skin management plan, and helps patients restore skin health faster by recommending personalized treatment plans; the skin condition assessment model of the abacus can generate appropriate treatment suggestions based on the patient's real-time condition, including appropriate nursing measures, drug therapy or physical therapy, etc.; nursing staff can choose the optimal nursing strategy based on the plan recommended by the abacus. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 It is a schematic diagram of the structure of the present invention;

[0061] Figure 2 This is a photograph of the damaged skin layer of the present invention in phase 1;

[0062] Figure 3 This is a photo of the damaged skin layer of the present invention in phase 2;

[0063] Figure 4 This is a photo of the damaged skin layer in phase 3 of the present invention;

[0064] Figure 5 This is a photograph of the damaged skin layer in phase 4 of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] Example

[0068] like Figure 1 As shown, in this embodiment, an intelligent nursing safety management skin management abacus includes:

[0069] The multi-layer concentric circle structure chart module is expanded layer by layer from the center to the outside. Each layer is evenly divided into multiple areas and distinguished by different colors, which is convenient for intuitively presenting the pressure injury information of each stage; each layer of the chart displays the stage identification, clinical manifestations, injury characteristics description, nursing measures and prevention strategies respectively;

[0070] The multi-layer concentric circle structure chart module includes:

[0071] The first level: used to indicate the stages of pressure injuries, using numbers to identify the injury status at different stages to help nursing staff quickly identify the extent of the injury;

[0072] The second layer: used to display the clinical manifestations of pressure injuries at different stages and to visually determine the type of injury;

[0073] The third level: a written description of the clinical manifestations of each stage of injury in the second level, providing detailed symptom characteristics information;

[0074] Level 4: Describe in text the nursing measures suitable for injuries of different stages;

[0075] Level 5: Demonstrate the prevention strategies for each stage and describe the preventive measures for the formulation of prevention plans;

[0076] The multi-layered concentric circle structure chart module displays skin health conditions, damage characteristics, care measures and prevention strategies at different stages in a standardized manner, including:

[0077] The first circle shows the different stages of skin damage, using different colors to indicate the status of each stage: 0 represents normal skin, displayed in white; 1 represents mild damage, displayed in pink; 2 represents moderate damage, displayed in red; 3 represents full-thickness skin damage, displayed in yellow; 4 represents severe damage, displayed in black;

[0078] The second circle shows the characteristics and manifestations of skin damage at different stages, including: Stage 0 is normal skin structure, showing that the epidermis, dermis and subcutaneous tissue are intact; Stage 1 is epidermal damage, manifested as non-fading erythema; Stage 2 is dermal damage, which may have blisters of varying sizes, shallow ulcers and exudate; Stage 3 is full-thickness skin damage, with visible fat layer and slough, but no exposed bones, tendons or muscles; Stage 4 damage reaches bones and tendons, and in severe cases, exposed bones and muscles can be seen, accompanied by insidious and tunnel-like damage characteristics;

[0079] The third circle contains pictures of pressure injuries corresponding to each stage of injury, as shown in the attached Figure 2 —Attachment Figure 5 ;

[0080] The content of the fourth circle shows the nursing measures and operational suggestions for different injury stages. The susceptible population in stage 0 is patients who cannot move on their own, have decreased consciousness, are incontinent, are bedridden or in wheelchairs for a long time, and the elderly with poor nutritional status; stage 1 recommends routine care, including keeping the skin clean and dry, turning over regularly, using air mattresses and other measures; stage 2 recommends consulting the skin management nursing team and adjusting the nursing plan in a targeted manner; stage 3 recommends consulting the skin management nursing team and standardizing the treatment; stage 4 requires the skin management team to work with the multidisciplinary team MDT of orthopedics and nutrition to prevent systemic infection.

[0081] The specific implementation contents are as follows:

[0082] 1. Initialization settings:

[0083] When using the Smart Nursing Safety Management Skin Management Abacus for the first time, the nursing staff needs to perform initial settings so that the system can be effectively integrated with the hospital information system and obtain the required patient data. The specific steps include:

[0084] Input basic information: Nurses input basic information such as hospital name, department information, nurse name, position, etc. through the touch screen interface to ensure that the device records the operator's identity and environment;

[0085] Connect to hospital information system: Tuiaopan obtains the patient's basic information and medical history information by connecting to the hospital information system, including the patient's name, age, gender, admission date, medical history, current skin condition and other key information. By directly accessing patient data, it reduces the tedious manual input operations of nursing staff and ensures the accuracy and real-time nature of the data.

[0086] Data security and privacy protection: During the data acquisition process, the system uses identity authentication to protect patient privacy and data security, ensuring that the equipment meets the standards of medical information security;

[0087] Through the initialization setting steps, the abacus can better adapt to the hospital information environment and provide sufficient data support for subsequent skin assessment, care and risk management, ensuring the convenience and reliability of nursing staff in actual operations.

[0088] 2. Evaluation model design:

[0089] The calculation formula of the skin health score S is as follows: S = α1X1+α2X2+α3X3+α4X4+α5X5+β. The score range calculated by the model can help caregivers quickly judge the patient's skin condition. The higher the value, the better the skin health condition. The lower the value, the higher the risk of skin damage and the need for more active nursing intervention.

[0090] The five indicators selected by the skin condition assessment model reveal the key characteristics of skin health status from different perspectives:

[0091] Humidity X1: Skin humidity is an important parameter for measuring skin hydration. Keeping the skin properly moist can prevent dryness, cracks and stratum corneum shedding, thereby reducing the risk of bacterial infection. Excessive humidity may cause the skin to be moist and susceptible to infection. Changes in humidity have a direct impact on the barrier function of the skin, so an appropriate weight is given in the model.

[0092] Temperature X2: Temperature reflects the metabolic activity and blood circulation of the skin. Too high a temperature is often associated with inflammation, infection, or increased local metabolic activity, while too low a temperature may indicate insufficient blood flow or hypoxia in the skin tissue. Monitoring temperature changes can help determine whether the skin is at risk of infection or has poor blood supply.

[0093] Elasticity X3: Skin elasticity is an important indicator of skin recovery ability. The better the skin elasticity, the stronger the skin tissue's ability to recover and can quickly return to its original state after being compressed. Poor elasticity indicates that the skin may be in an aging state or has been damaged due to long-term compression. Skin with low elasticity is more likely to develop bedsores or pressure injuries.

[0094] Damage area x4: The damage area directly reflects the severity of skin damage; the larger the area, the wider the damage to the skin, and the more attention needs to be paid to care; the increase in the damage area often means that the skin's ability to resist external bacteria or irritation decreases, and care and treatment interventions need to be accelerated;

[0095] Blood flow X5: Blood flow directly affects the skin's ability to repair itself. When the blood flow is sufficient, the skin can obtain enough nutrients and oxygen, which helps tissue regeneration and repair. Low blood flow may cause skin hypoxia and reduced tissue repair ability. Skin with insufficient blood flow is prone to tissue necrosis and requires close attention and care.

[0096] Then, in order to ensure the accuracy and consistency of the skin health score S across patients, each input data needs to be standardized before entering the model. The standardization formula is as follows:

[0097]

[0098] Through standardization, the differences between variables of different units are eliminated, ensuring that each indicator is reasonably compared in the model. The standardized data more directly reflects the relative contribution of different indicators to skin health, thereby enhancing the adaptability and prediction accuracy of the model.

[0099] Example: Suppose the skin condition assessment data of a patient is:

[0100] Humidity: 60%, temperature: 33℃, elasticity: 80%, injury area: 5cm2, blood flow: 3ml / min;

[0101] If the regression coefficients and bias terms in the model are α1 = 0.2, α2 = 0.15, α3 = 0.25, α4 = 0.1, and α5 = 0.3, then the skin health score S of the patient is calculated as:

[0102] S=(0.2×60)+(0.15×33)+(0.25×80)+(0.1×5)+(0.3×3)+0.5=38.85;

[0103] The scoring result is displayed on the interface and an evaluation report is automatically generated, including the patient's skin type, lesion severity, and etiology analysis. Then, based on different scores, the system will conduct a risk assessment of the skin condition. A low score prompts nursing staff to strengthen the patient's skin care, such as increasing the frequency of turning over, using an air mattress, and strengthening nutritional support; a high score indicates that the skin is in good condition and the intensity of nursing intervention can be appropriately reduced.

[0104] 3. Recommended treatment plan:

[0105] After completing the skin health assessment, Tui Suan Pan recommends personalized care plans based on the treatment intensity TTT generated by the score. The system's treatment plan recommendation algorithm generates treatment intensity based on the patient's skin health score S and damage stage D. The specific formula is as follows:

[0106]

[0107] Among them: treatment intensity T represents the intensity of the demand for nursing intervention, ranging from 0 to 1. The higher the value, the more serious the patient's skin damage and the higher the demand for treatment;

[0108] Damage stage D is used to indicate the severity of skin damage and is divided into grades 1 to 5;

[0109] Example: Skin health score S = 38.85, damage stage D = 3, parameters λ = 0.05, μ = 0.3, then

[0110]

[0111] Based on the obtained treatment intensity T = 0.739, the system recommends that the caregiver use antibiotics or anti-inflammatory drugs. If the calculated result T>0.8, a more aggressive treatment method will be recommended;

[0112] 4. Nursing effect prediction and safety risk management

[0113] The abacus regularly predicts the patient's recovery progress during nursing care and monitors risks in real time to ensure the safety of the nursing process;

[0114] Nursing effect prediction: Rehabilitation prediction is performed through the recursive neural network RNN ​​model, the formula is as follows: E(t) = σ(W·E(t-1)+U·S+V·F+b), where:

[0115] E(t): predicted value of nursing effect at time t, indicating the degree of recovery;

[0116] The nursing frequency F indicates the frequency of nursing operations and helps reflect the continuity of nursing;

[0117] Example: E(t-1) = 0.6, S = 38.85, nursing frequency F = 0.7, weight W = 0.2, U = 0.15, V = 0.1, bias b = 0.1, then

[0118] E(t)=tanh(0.2×0.6+0.15×38.85+0.1×0.7+0.1)≈0.999, and its recovery prediction value is close to 1, indicating that the patient's recovery progress is good.

[0119] Safety risk management: Real-time monitoring of the changing trends of the skin health score S and the predicted value of the nursing effect E(t), and calculation of the comprehensive risk score R to assess the potential risks in the nursing process. The formula is as follows:

[0120]

[0121] Example: If the reference value Sreference = 50, E(t)reference = 1, and the current value S = 38.85, E(t) = 0.999, then:

[0122]

[0123] If R>40%, the system will trigger a high-risk warning. If R is lower than 40% and exceeds 20% for three consecutive times, a medium-risk warning will be triggered, reminding nursing staff to pay more attention and adjust nursing strategies. Nursing staff can take timely measures according to the warning signals to ensure the safety and health of patients.

[0124] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An intelligent nursing safety management skin management abacus, characterized in that: include: Multi-layer concentric circle structure chart module, calculation model and intelligent analysis algorithm module, touch operation interface, data recording and export module and implementation module; The multi-layer concentric circle structure chart module is expanded layer by layer from the center to the outside, and each layer is evenly divided into multiple areas and distinguished by different colors, so as to intuitively present the pressure injury information of each stage; Each layer of the chart displays staging identification, clinical manifestations, description of injury characteristics, nursing measures, and prevention strategies; The multi-layer concentric circle structure chart module includes: The first level: used to indicate the stages of pressure injuries, using numbers to identify the injury status at different stages to help nursing staff quickly identify the extent of the injury; The second layer: used to display the clinical manifestations of pressure injuries at different stages and to visually determine the type of injury; The third level: a written description of the clinical manifestations of each stage of injury in the second level, providing detailed symptom characteristics information; Level 4: Describe in text the nursing measures suitable for injuries of different stages; Level 5: Demonstrate the prevention strategies for each stage and describe the preventive measures for the formulation of prevention plans; The computational model and intelligent analysis algorithm module includes a skin condition assessment model, a treatment plan recommendation algorithm, a nursing effect prediction model, and a safety risk management algorithm, which are constructed based on a large amount of clinical data and expert experience, and conduct in-depth analysis of the input patient information; To achieve: accurately assess the patient's skin condition, recommend personalized treatment plans, predict care effects, and warn of potential safety risks; The touch operation interface is equipped with an intuitive touch screen, supports click, slide and voice interaction, completes information query and nursing advice acquisition through simple operation, and provides data export and printing; The data recording and exporting module is used to store the patient's assessment report, nursing records and analysis results so that nursing staff can view and share nursing information later; The implementation module includes: Skin condition assessment: after the nurse inputs the patient's basic information and skin symptoms, the abacus will automatically generate an assessment report; Recommend treatment plans and provide personalized care and treatment plans based on the results of skin condition assessment; Nursing effect prediction: through nursing records and feedback information, the abacus predicts the patient's recovery process and provides adjustment suggestions; Safety risk management, real-time monitoring of changes in skin conditions, and automatic warnings if abnormalities occur.

2. According to claim 1, the intelligent nursing safety management skin management abacus is characterized in that: The multi-layer concentric circle structure chart module displays skin health conditions, damage characteristics, care measures and prevention strategies at different stages in a standardized manner, wherein: The first circle shows the different stages of skin damage, using different colors to indicate the status of each stage: 0 represents normal skin, displayed in white; 1 represents mild damage, displayed in pink; 2 represents moderate damage, displayed in red; 3 represents full-thickness skin damage, displayed in yellow; 4 represents severe damage, displayed in black; The content of the second circle shows the characteristics and manifestations of skin injuries at different stages, including: stage 0 represents normal skin structure, showing intact epidermis, dermis, and subcutaneous tissue; stage 1 indicates epidermal layer injury, manifested as non-blanchable erythema; stage 2 is dermal layer injury, which may present blisters of varying sizes, superficial ulcers, and exudate; stage 3 is full-thickness skin injury, with visible adipose layer and slough, but no exposure of bone, tendon, or muscle; stage 4 injury reaches bone and tendon, and in severe cases, bone and muscle are exposed, accompanied by undermining and tunneling injury characteristics; The content of the third circle contains pictures of pressure injuries corresponding to each stage of injury; The content of the fourth circle shows nursing measures and operation suggestions for different injury stages. The high-risk population for stage 0 includes patients who cannot move independently, have decreased consciousness, incontinence, are bedridden or in a wheelchair for a long time, and the elderly with poor nutritional status; for stage 1, routine nursing is recommended, including measures such as keeping the skin clean and dry, turning over regularly, and using an air mattress; for stage 2, it is recommended to consult the skin management nursing team and adjust the nursing plan accordingly; for stage 3, it is recommended to invite the skin management nursing team for consultation and standardized treatment; for stage 4, it requires the skin management team to jointly prevent systemic infection with a multi-disciplinary team (MDT) including orthopedics and nutrition departments.

3. According to claim 1, the intelligent nursing safety management skin management abacus is characterized in that: The skin condition assessment model is based on a multivariate regression analysis method of skin health scores. By comprehensively considering factors such as skin humidity, temperature, elasticity, injury area, and blood flow of the patient, the skin health score S is calculated. The specific formula is as follows: S = α1X1 + α2X2 + α3X3 + α4X4 + α5X5 + β Where: S represents the skin health score, quantifying the current overall health status of the patient's skin; Variables X1 to X5 represent five indicators that have a greater impact on skin health status, namely skin humidity, temperature, elasticity, injury area, and blood flow: Humidity X1 reflects the hydration of the skin, temperature X2 represents the metabolic activities on and inside the skin surface, elasticity X3 evaluates the skin's recovery ability, injury area X4 measures the severity of skin damage, and blood flow X5 reflects the nutritional and oxygen supply status of the skin; The regression coefficients α1 to α5 and the bias term β were obtained based on the clinical data fitting and were used to determine the relative impact of each indicator on the skin health score. To eliminate the differences between different indicator units, each input variable X i Normalization will be performed before calculation. The normalization formula is: Among them, X′ i is the standardized value, μX i is the average value, σX i is the standard deviation. The skin health score S will be used as an input parameter for subsequent treatment recommendations and nursing effect predictions to ensure continuous data calls between different modules.

4. According to claim 1, the intelligent nursing safety management skin management abacus is characterized in that: The treatment plan recommendation algorithm generates the treatment intensity T based on the patient's skin health score S and injury stage D, which is used to optimize the selection of treatment plans. The formula is: Where: The treatment intensity T is a continuous value, ranging from 0 to 1 exponential value. The higher the value, the higher the treatment intensity requirement, and it is recommended to adopt a more aggressive treatment method; The skin health score S is provided by the skin condition assessment model, reflecting the patient's current skin health level. The stage D is determined according to the degree of damage and is set to an integer from 1 to 5. The parameters λ and μ in the formula are adjusted through clinical data to optimize the relative impact of the score and stage on the treatment intensity. The Sigmoid activation function Ensure that the calculated result T is always in the range of 0 to 1; Then, according to the obtained treatment intensity T, the following treatment methods are intelligently selected: When T > 0.8: Surgical debridement is recommended to deal with severe injuries; when 0.5 < T ≤ 0.8: Antibiotics or anti-inflammatory drugs are recommended; when T ≤ 0.5: Physical therapy is recommended to adapt to the injury conditions of different patients.

5. According to claim 1, the intelligent nursing safety management skin management abacus is characterized in that: The nursing effect prediction model is based on the Recurrent Neural Network (RNN) architecture. By using historical nursing data and the skin health score S, it dynamically predicts the patient's recovery process E(t). The specific formula is: E(t) = σ(W·E(t - 1) + U·S + V·F + b) Among them: The predicted value of the nursing effect E(t) represents the rehabilitation progress at time t, which is used to evaluate the nursing effect of the patient and quantify the patient's rehabilitation progress; and through the time series characteristics of the recurrent neural network, the predicted value E(t-1) at the previous moment is combined with the current skin health score S and nursing frequency F to achieve continuous prediction. The weight matrices W, U, V and the bias term b are obtained through backpropagation training to ensure that the model adapts to the individual differences of patients. The activation function σ uses ReLU to make the output value change smoothly. The loss function is calculated using the mean square error MSE, and the formula is: The loss function is used to minimize the prediction error and optimize the model parameters.

6. The intelligent nursing safety management skin management abacus according to claim 1, characterized in that: The safety risk management algorithm calculates the comprehensive risk score R based on the change trends of the skin health score S and the predicted value of the nursing effect E(t) to evaluate the risk during the nursing process in real time. The formula is The risk score R measures the nursing risk by the relative change of the skin health score and the nursing effect, where S represents the current skin health score and E(t) is the current nursing effect prediction value. The two are compared with S under the ideal state. 基准 and E 基准 For comparison, benchmark values ​​are set using healthy individual data or standard care samples to provide a benchmark for comparison; Risk trigger condition: When R > 40%, the system automatically triggers a high-risk warning to prompt the nursing staff to closely monitor. When 20% < R ≤ 40% and it exceeds 20% three times in a row, a medium-risk warning is triggered, and it is recommended to adjust the nursing frequency or plan. The risk warning during the nursing process is provided through the real-time calculated risk score R.

7. According to claim 1, the intelligent nursing safety management skin management abacus is characterized in that: The click selection of the touch operation interface is used to locate and view the information of different skin stages among the circles of the multi-layer concentric circle structure; the sliding switch supports navigation between different circles to display the skin stage, clinical manifestations and the content of the nursing plan. Voice input allows the nursing staff to describe the patient's skin condition through voice input, and the system automatically generates a preliminary evaluation result and displays it on the interface in real time.

8. The intelligent nursing safety management skin management abacus according to claim 1, characterized in that: The data recording and export module has the functions of data analysis and standardized report generation, which is used for the nursing staff to systematically manage and store the patient's nursing data. By generating a trend chart of the skin health score and a curve chart of the rehabilitation progress, it clearly shows the change of the patient's nursing effect over time; and generates a standardized nursing report, including a skin health score report, personalized nursing suggestions, nursing effect prediction and risk warning records.

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