Personalized nursing scheme management system and method for oral nursing of intubation patient

Abstract

The invention discloses a personalized nursing scheme management system and method for oral nursing of an intubation patient, and relates to the technical field of nursing scheme management.The immunity condition and antibiotic resistance are constructed into a first data set, the oral condition is constructed into a second data set, and the first data set and the second data set are input into a condition fusion model; the condition fusion model outputs the current physical condition of the patient, judges whether the number threshold needs to be dynamically adjusted or not according to the current physical condition, and obtains the adjusted number threshold through an adjustment algorithm when judging that the number threshold needs to be dynamically adjusted; and generating a personalized nursing scheme according to a comparison result of the number of bacteria and the adjusted number threshold value. When the management system monitors the number of Klebsiella pneumoniae in the oral cavity of an intubation patient in real time, abnormality analysis is performed on the patient, and a number threshold value is dynamically adjusted based on an abnormality analysis result, so that intervention timeliness is guaranteed, and a personalized nursing scheme is generated for the patient.

Description

Technical Field

[0001] The present invention relates to the technical field of nursing program management, and in particular to a personalized nursing program management system and method for oral care of intubated patients. Background Art

[0002] Oral care for intubated patients is a vital part of critical care, especially for patients using mechanical ventilation. Such patients usually need intubation to assist breathing due to their serious condition, but intubation will bring a series of oral health problems. If not promptly and effectively cared for, it may lead to serious complications or even endanger life. The oral care program management system can help the medical team effectively monitor and manage the oral health of patients.

[0003] Klebsiella pneumoniae is one of the bacteria that is prone to appear in the mouth of intubated patients. The existing method for detecting Klebsiella pneumoniae is: through microfluidic technology (introducing oral secretions (such as saliva) into tiny channels, and combining multiple detection technologies to analyze the number of Klebsiella pneumoniae), the obtained number of Klebsiella pneumoniae is then compared with a preset number threshold to determine whether intervention is needed. However, when the intubated patient himself has abnormalities, a fixed number threshold is still used for comparison, which may lead to failure to intervene in time and thus delay treatment.

[0004] Based on this, the present invention proposes a personalized nursing plan management system and method for oral care of intubated patients. While monitoring the number of Klebsiella pneumoniae in the oral cavity of intubated patients in real time, abnormal analysis is performed on the patients, and the number threshold is dynamically adjusted based on the abnormal analysis results, thereby ensuring the timeliness of intervention and generating a personalized nursing plan for the patients. Summary of the invention

[0005] The purpose of the present invention is to provide a personalized care plan management system and method for oral care of intubated patients to address the deficiencies in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a personalized nursing plan management method for oral care of intubated patients, the management method comprising the following steps:

[0007] The management system uses microfluidics technology to regularly obtain oral secretions from patients and analyze the number of bacteria in their mouths;

[0008] The patient's current immunity status and antibiotic resistance are obtained through the API interface of the medical platform, and the immunity status and antibiotic resistance are constructed as a first data set. A plurality of frames of patient's oral cavity images are obtained through a camera device arranged at the patient's oral cavity. After pre-processing the plurality of frames of patient's oral cavity images, the patient's oral cavity condition is analyzed, and the oral cavity condition is constructed as a second data set.

[0009] The first data set and the second data set are input into the condition fusion model as input, and the condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted according to the current physical condition;

[0010] When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and a personalized care plan is generated based on the comparison result between the bacterial quantity and the adjusted quantity threshold, and the personalized care plan is sent to relevant medical personnel.

[0011] In a preferred embodiment, the management system constructs the immunity status and antibiotic resistance as a first data set, comprising the following steps:

[0012] The management system obtains authorization to access the medical platform API, and sends a request to the medical platform through the API interface according to the documentation of the medical platform API to obtain the patient's immunity status and antibiotic resistance data;

[0013] An immunity index is calculated based on the immunity data, and a drug resistance index is calculated based on the drug resistance data. The immunity index and the drug resistance index are constructed into a first data set.

[0014] In a preferred embodiment, analyzing the patient's oral condition and constructing the oral condition as a second data set comprises the following steps:

[0015] By analyzing the color information of the oral image, the color features are extracted by analyzing the color histogram or HSV color space to identify the ulcer or wound area;

[0016] Ulcers and wounds are collectively referred to as abnormal areas. When an ulcer or wound is identified in the patient's mouth, the patient's oral image is divided into several 1×1 grids. After recording the number of grids occupied by each abnormal area, the oral abnormality index is obtained by comprehensive calculation. The expression is:

[0017] In the formula, K t is the oral abnormality index, m is the number of abnormal areas, Y i is the number of grids occupied by the ith abnormal area, and the oral abnormality index is used to establish a second data set.

[0018] In a preferred embodiment, the first data set and the second data set are input into a condition fusion model as inputs, the condition fusion model outputs the patient's current physical condition, and determines whether the quantity threshold needs to be dynamically adjusted based on the current physical condition, including the following steps:

[0019] The first data set includes the immunity index and drug resistance index, and the second data set includes the oral abnormality index;

[0020] The immunity index, drug resistance index and oral abnormality index are input into the condition fusion model, and the condition fusion model outputs the patient's condition coefficient, which is expressed as:

[0021] In the formula, I e I is the immunity index, r is the drug resistance index, K t is the oral abnormality index, status is the status coefficient, ∈1, ∈2, ∈3 are the adjustment coefficients of the drug resistance index, immunity index and oral abnormality index, respectively, and ∈1, ∈2, ∈3 are all greater than 0;

[0022] The obtained condition coefficient is compared with the preset coefficient threshold. If the condition coefficient is less than or equal to the coefficient threshold, the patient's overall physical condition is analyzed to be good, and it is judged that there is no need to dynamically adjust the quantity threshold. If the condition coefficient is greater than the coefficient threshold, the patient's overall physical condition is analyzed to be poor, and it is judged that the quantity threshold needs to be dynamically adjusted.

[0023] In a preferred embodiment, when it is determined that the quantity threshold needs to be dynamically adjusted, obtaining the adjusted quantity threshold through an adjustment algorithm includes the following steps:

[0024] When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm. The algorithm expression is: In the formula, quantity new is the dynamically adjusted quantity threshold, quantity old is the quantity threshold before dynamic adjustment, and status is the status coefficient.

[0025] In a preferred embodiment, generating a personalized care plan based on the comparison result of the bacterial count and the adjusted count threshold comprises the following steps:

[0026] After obtaining the dynamically adjusted quantity threshold, the dynamically adjusted quantity threshold is updated to the personalized quantity threshold, and the bacterial quantity is compared with the personalized quantity threshold. If the bacterial quantity is less than or equal to the personalized quantity threshold, the conventional care plan is maintained. If the bacterial quantity is greater than the personalized quantity threshold, an emergency intervention care plan is generated.

[0027] In a preferred embodiment, the calculation expression of the immunity index is:

[0028] In the formula, I e is the immunity index, WBC is the patient's white blood cell count, WBC min ~WBC maxis the normal reference range of white blood cells, Lymph is the lymphocyte count of the patient, Lymph min ~Lymph max is the normal reference range of lymphocytes, IgG is immunoglobulin G count, IgG min IgG max Normal reference range for immunoglobulin G;

[0029] The calculation expression of the drug resistance index is: In the formula, I r is the drug resistance index, n is the number of antibiotics used to treat Klebsiella pneumoniae infection, R i represents the patient's resistance to the i-th antibiotic, w i represents the weight of the ith antibiotic.

[0030] The personalized nursing plan management system for oral care of intubated patients includes a bacteria monitoring module, a data set building module, a condition analysis module, a dynamic adjustment module, and a plan generation module:

[0031] Bacteria monitoring module: After obtaining oral secretions of patients at regular intervals based on microfluidics technology, the number of bacteria in the patient's mouth is analyzed and sent to the solution generation module;

[0032] Dataset construction module: obtain the patient's current immunity status and antibiotic resistance through the API interface of the medical platform, construct the immunity status and antibiotic resistance into a first data set, obtain multiple frames of patient oral images through a camera device set at the patient's oral cavity, analyze the patient's oral condition after preprocessing the multiple frames of patient oral images, and construct the oral condition into a second data set. The first data set and the second data set are sent to the condition analysis module;

[0033] Condition analysis module: takes the first data set and the second data set as inputs and inputs them into the condition fusion model. The condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted based on the current physical condition. The judgment result is sent to the dynamic adjustment module.

[0034] Dynamic adjustment module: when it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and the adjusted quantity threshold is sent to the solution generation module;

[0035] Plan generation module: Generates personalized care plans based on the comparison results between the number of bacteria and the adjusted number threshold, and sends the personalized care plans to relevant medical personnel.

[0036] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0037] The present invention constructs the immunity status and antibiotic resistance as a first data set, analyzes the patient's oral condition, and constructs the oral condition as a second data set. The first data set and the second data set are input into a condition fusion model as inputs. The condition fusion model outputs the patient's current physical condition, and determines whether it is necessary to dynamically adjust the quantity threshold according to the current physical condition. When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through an adjustment algorithm, and a personalized nursing plan is generated based on the comparison result between the number of bacteria and the adjusted quantity threshold. While the management system monitors the number of Klebsiella pneumoniae in the oral cavity of the intubated patient in real time, it performs abnormal analysis on the patient, and dynamically adjusts the quantity threshold based on the abnormal analysis results, thereby ensuring the timeliness of intervention and generating a personalized nursing plan for the patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application 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 recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0041] Example 1: Please refer to Figure 1 As shown, the personalized nursing plan management method for oral care of intubated patients described in this embodiment includes the following steps:

[0042] After the management system obtains the patient's oral secretions at regular intervals based on microfluidic technology, it analyzes the number of bacteria in the patient's mouth. The management system obtains the patient's current immunity status and antibiotic resistance through the API interface of the medical platform, and constructs the immunity status and antibiotic resistance into a first data set. A camera device set at the patient's mouth obtains multiple frames of patient oral images, and after pre-processing the multiple frames of patient oral images, the patient's oral condition is analyzed, and the oral condition is constructed as a second data set. The first data set and the second data set are used as input and input into the condition fusion model. The condition fusion model outputs the patient's current physical condition and determines whether it is necessary to dynamically adjust the quantity threshold based on the current physical condition. When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and a personalized care plan is generated based on the comparison result between the bacterial quantity and the adjusted quantity threshold, and the personalized care plan is sent to relevant medical personnel.

[0043] This application constructs the immunity status and antibiotic resistance as a first data set, analyzes the patient's oral condition, and constructs the oral condition as a second data set. The first data set and the second data set are input into the condition fusion model. The condition fusion model outputs the patient's current physical condition and determines whether it is necessary to dynamically adjust the quantity threshold based on the current physical condition. When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and a personalized care plan is generated based on the comparison result between the bacterial quantity and the adjusted quantity threshold. While the management system monitors the number of Klebsiella pneumoniae in the oral cavity of the intubated patient in real time, it performs abnormal analysis on the patient and dynamically adjusts the quantity threshold based on the abnormal analysis results, thereby ensuring the timeliness of intervention and generating a personalized care plan for the patient.

[0044] Example 2: The management system obtains oral secretions of patients at regular intervals based on microfluidic technology and analyzes the number of bacteria in the oral cavity of the patients, including the following steps:

[0045] The system obtains oral secretion samples, usually saliva, from the patient at regular intervals using a micro-collection device (such as a micro-collector mounted on a cannula or oral care device).

[0046] The collected oral secretions are automatically transported to the detection channel of the microfluidic chip through a micropump or capillary to ensure sample integrity and real-time performance.

[0047] The fluid dynamics within the microfluidic channel are used to separate specific bacteria such as Klebsiella pneumoniae to ensure the accuracy of subsequent analysis. Specific markers or probes (such as fluorescently labeled antibodies, DNA probes) are used to bind to the bacteria and identify specific bacteria (such as Klebsiella pneumoniae).

[0048] By combining the fluorescent probe with the bacterial specific antigen, a fluorescent signal is generated to facilitate subsequent detection. The signal intensity of the fluorescent marker is detected by an optical sensor. The strength of the fluorescent signal is proportional to the number of bacteria. The processor on the microfluidic chip or the connected computing device calculates the specific number of Klebsiella pneumoniae or other bacteria in the sample based on the signal intensity, the volume of the sample and the known standard curve. This step belongs to the prior art and will not be elaborated in this application.

[0049] The management system obtains the patient's current immunity status and antibiotic resistance through the API interface of the medical platform, and constructs the immunity status and antibiotic resistance into a first data set, including the following steps:

[0050] Ensure that the management system is authorized to access the medical platform API. Authentication (such as OAuth or API key authentication) may be required to ensure the security and compliance of data access. According to the documentation of the medical platform API, determine the specific interface and request format for obtaining patient immunity status and antibiotic resistance information, including the required patient ID, access rights and related parameters.

[0051] Send a request to the medical platform through the API interface to obtain the immunity status and antibiotic resistance data of the specified patient. This usually involves calling different API endpoints to obtain immunity and resistance data respectively.

[0052] An immunity index is calculated based on the immunity data, and a drug resistance index is calculated based on the drug resistance data, and the immunity index and the drug resistance index are constructed into a first data set;

[0053] The calculation expression of immunity index is:

[0054] In the formula, I e is the immunity index, WBC is the patient's white blood cell count, WBC min ~WBC max is the normal reference range of white blood cells, Lymph is the lymphocyte count of the patient, Lymph min ~Lymph max is the normal reference range of lymphocytes, IgG is immunoglobulin G count, IgG min IgG max This is the normal reference range for immunoglobulin G. The larger the value of the immunity index is, the stronger the patient's immunity is.

[0055] The calculation expression of drug resistance index is:

[0056] In the formula, I r is the drug resistance index, n is the number of antibiotics used to treat Klebsiella pneumoniae infection, Ri represents the patient's resistance to the i-th antibiotic, w i represents the weight of the i-th antibiotic;

[0057] The patient's resistance level to the i-th antibiotic is usually recorded in the medical platform and can be directly obtained.

[0058] For example, a patient has the following susceptibility test results:

[0059] Table 1 Results of drug sensitivity test

[0060] antibiotic Degree of resistance Weight Ceftazidime 0 0.3 Imipenem 1 04 Levofloxacin 0.5 0.2 Piperacillin-tazobactam 1 0.1

[0061] After calculation, the patient resistance index I r =0.6, indicating that the Klebsiella pneumoniae strain has a high drug resistance and infection treatment may be challenging, that is, the larger the drug resistance index, the more difficult it is to treat Klebsiella pneumoniae.

[0062] Acquiring multiple frames of patient oral cavity images by a camera device arranged at the patient's oral cavity, preprocessing the multiple frames of patient oral cavity images, analyzing the patient's oral cavity conditions, and constructing the oral cavity conditions into a second data set, including the following steps:

[0063] A high-resolution camera is installed in the patient's mouth to continuously capture multiple frames of oral images. The camera needs to be able to adapt to low-light environments and capture clear oral mucosa, teeth, tongue and other parts.

[0064] In order to observe the subtle changes of oral mucosa (such as ulcers, wounds, etc.) more clearly, histogram equalization is used to enhance the local contrast of the image.

[0065] By analyzing the color information of oral images, the color distribution of the oral mucosa area is extracted. For example, ulcers or wounds may appear as abnormal colors such as red and white. Color features are extracted by analyzing the color histogram or HSV color space.

[0066] Ulcers and wounds are collectively referred to as abnormal areas. When an ulcer or wound is identified in the patient's mouth, the patient's oral image is divided into several 1×1 grids. After recording the number of grids occupied by each abnormal area, the oral abnormality index is obtained by comprehensive calculation. The expression is:

[0067] In the formula, K t is the oral abnormality index, m is the number of abnormal areas, Y i is the number of grids occupied by the ith abnormal area. The larger the value of the oral abnormality index is, the more ulcers or wounds there are in the patient's mouth, or the larger the area of ​​the ulcers or wounds in the patient's mouth is. The oral abnormality index is used to establish a second data set.

[0068] The first data set and the second data set are input into the condition fusion model as inputs. The condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted according to the current physical condition, including the following steps:

[0069] The first data set includes the immunity index and drug resistance index, and the second data set includes the oral abnormality index;

[0070] The immunity index, drug resistance index and oral abnormality index are input into the condition fusion model, and the condition fusion model outputs the patient's condition coefficient, which is expressed as:

[0071] In the formula, I e I is the immunity index, r is the drug resistance index, K t is the oral abnormality index, status is the status coefficient, ∈1, ∈2, ∈3 are the adjustment coefficients of the drug resistance index, immunity index and oral abnormality index respectively, and ∈1, ∈2, ∈3 are all greater than 0.

[0072] The larger the condition coefficient is, the worse the patient's overall physical condition is, and the more dynamic adjustment of the quantity threshold is needed. The obtained condition coefficient is compared with the preset coefficient threshold. If the condition coefficient is less than or equal to the coefficient threshold, the patient's overall physical condition is analyzed to be good, and it is judged that there is no need to dynamically adjust the quantity threshold. If the condition coefficient is greater than the coefficient threshold, the patient's overall physical condition is analyzed to be poor, and it is judged that there is a need to dynamically adjust the quantity threshold to improve the monitoring of Klebsiella pneumoniae.

[0073] When it is determined that the quantity threshold needs to be dynamically adjusted, obtaining the adjusted quantity threshold through an adjustment algorithm includes the following steps:

[0074] When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm. The algorithm expression is: In the formula, quantity new is the dynamically adjusted quantity threshold, quantity old is the quantity threshold before dynamic adjustment, and status is the status coefficient.

[0075] A personalized care plan is generated based on the comparison result of the bacterial count and the adjusted count threshold, and the personalized care plan is sent to relevant medical personnel, including the following steps:

[0076] After obtaining the dynamically adjusted quantity threshold, the dynamically adjusted quantity threshold is updated to the personalized quantity threshold, and the bacterial quantity is compared with the personalized quantity threshold. If the bacterial quantity is less than or equal to the personalized quantity threshold, the conventional care plan is maintained. If the bacterial quantity is greater than the personalized quantity threshold, an emergency intervention care plan is generated.

[0077] The emergency intervention care plan includes the following:

[0078] If the patient has developed antibiotic resistance, the bacterial load may rebound rapidly after antibiotic treatment, and fixed thresholds may not be able to capture this change in time. Strengthen oral care: Increase the frequency of oral care, such as using antibacterial mouthwash, strengthening oral cleaning, and using medical oral care gel.

[0079] Antibiotic treatment plan: According to the patient's antibiotic resistance index, adjust the type and dosage of antibiotics used, and consider using more potent antibiotics or multidrug combination therapy.

[0080] Wound care: If ulcers or wounds are detected in the patient's mouth, additional care measures will be taken for the wounds, such as the use of antibacterial patches, oral mucosal repair agents, etc.

[0081] Immune support: If the immune index is low, it may be necessary to consider providing the patient with immune-boosting medications or nutritional support.

[0082] Through the API interface of the hospital or medical institution's information management platform, the care plan is automatically pushed to the account or system of relevant medical personnel.

[0083] System generates draft plan: The system automatically generates a nursing plan based on the test results for review by relevant doctors and nursing staff.

[0084] Doctor review: The attending physician or relevant medical team can review and modify the automatically generated care plan to ensure that the plan is suitable for the patient's actual situation.

[0085] Nursing staff confirmation: After receiving the plan, the nursing staff confirms its feasibility and begins to implement it.

[0086] Message notification: Send notifications to medical staff through internal communication platforms (such as SMS, email, instant messaging software, etc.) to remind them that there are new care plans that need to be implemented.

[0087] Nursing record update: The generated nursing plan is automatically entered into the patient's electronic medical record (EMR) to ensure that all nursing records are kept complete.

[0088] Embodiment 3: The personalized nursing plan management system for oral care of intubated patients described in this embodiment includes a bacteria monitoring module, a data set building module, a status analysis module, a dynamic adjustment module, and a plan generation module:

[0089] Bacteria monitoring module: After obtaining oral secretions of patients at regular intervals based on microfluidics technology, the number of bacteria in the patient's mouth is analyzed and sent to the solution generation module;

[0090] Dataset construction module: obtain the patient's current immunity status and antibiotic resistance through the API interface of the medical platform, construct the immunity status and antibiotic resistance into a first data set, obtain multiple frames of patient oral images through a camera device set at the patient's oral cavity, analyze the patient's oral condition after preprocessing the multiple frames of patient oral images, and construct the oral condition into a second data set. The first data set and the second data set are sent to the condition analysis module;

[0091] Condition analysis module: takes the first data set and the second data set as inputs and inputs them into the condition fusion model. The condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted based on the current physical condition. The judgment result is sent to the dynamic adjustment module.

[0092] Dynamic adjustment module: when it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and the adjusted quantity threshold is sent to the solution generation module;

[0093] Plan generation module: Generates personalized care plans based on the comparison results between the number of bacteria and the adjusted number threshold, and sends the personalized care plans to relevant medical personnel.

[0094] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0095] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0096] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0097] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0098] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A personalized nursing program management method for oral care of intubated patients, characterized by: The management method comprises the following steps: The management system uses microfluidics technology to regularly obtain oral secretions from patients and analyze the number of bacteria in their mouths; The patient's current immunity status and antibiotic resistance are obtained through the API interface of the medical platform, and the immunity status and antibiotic resistance are constructed as a first data set. A plurality of frames of patient's oral cavity images are obtained through a camera device arranged at the patient's oral cavity. After pre-processing the plurality of frames of patient's oral cavity images, the patient's oral cavity condition is analyzed, and the oral cavity condition is constructed as a second data set. The first data set and the second data set are input into the condition fusion model as input, and the condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted according to the current physical condition; When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and a personalized care plan is generated based on the comparison result between the bacterial quantity and the adjusted quantity threshold, and the personalized care plan is sent to relevant medical personnel.

2. The personalized nursing program management method for oral care of intubated patients according to claim 1 is characterized by: The management system constructs the immunity status and antibiotic resistance as the first data set, including the following steps: The management system obtains authorization to access the medical platform API, and sends a request to the medical platform through the API interface according to the documentation of the medical platform API to obtain the patient's immunity status and antibiotic resistance data; An immunity index is calculated based on the immunity data, and a drug resistance index is calculated based on the drug resistance data. The immunity index and the drug resistance index are constructed into a first data set.

3. The personalized nursing plan management method for oral care of intubated patients according to claim 2, characterized in that: Analyzing the oral condition of the patient and constructing the oral condition as a second data set includes the following steps: By analyzing the color information of the oral image, the color features are extracted by analyzing the color histogram or HSV color space to identify the ulcer or wound area; Ulcers and wounds are collectively referred to as abnormal areas. When an ulcer or wound is identified in the patient's mouth, the patient's oral image is divided into several 1×1 grids. After recording the number of grids occupied by each abnormal area, the oral abnormality index is obtained by comprehensive calculation. The expression is: In the formula, K t is the oral abnormality index, m is the number of abnormal areas, Y i is the number of grids occupied by the ith abnormal area, and the oral abnormality index is used to establish a second data set.

4. The personalized nursing program management method for oral care of intubated patients according to claim 3 is characterized by: The first data set and the second data set are input into the condition fusion model as inputs. The condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted according to the current physical condition, including the following steps: The first data set includes the immunity index and drug resistance index, and the second data set includes the oral abnormality index; The immunity index, drug resistance index and oral abnormality index are input into the condition fusion model, and the condition fusion model outputs the patient's condition coefficient, which is expressed as: In the formula, I e I is the immunity index, r is the drug resistance index, K t is the oral abnormality index, status is the status coefficient, ∈1, ∈2, ∈3 are the adjustment coefficients of the drug resistance index, immunity index and oral abnormality index, respectively, and ∈1, ∈2, ∈3 are all greater than 0; The obtained condition coefficient is compared with the preset coefficient threshold. If the condition coefficient is less than or equal to the coefficient threshold, the patient's overall physical condition is analyzed to be good, and it is judged that there is no need to dynamically adjust the quantity threshold. If the condition coefficient is greater than the coefficient threshold, the patient's overall physical condition is analyzed to be poor, and it is judged that the quantity threshold needs to be dynamically adjusted.

5. The personalized nursing program management method for oral care of intubated patients according to claim 4 is characterized by: When it is determined that the quantity threshold needs to be dynamically adjusted, obtaining the adjusted quantity threshold through an adjustment algorithm includes the following steps: When it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm. The algorithm expression is: In the formula, quantity new is the dynamically adjusted quantity threshold, quantity old is the quantity threshold before dynamic adjustment, and status is the status coefficient.

6. The personalized nursing program management method for oral care of intubated patients according to claim 5, characterized in that: Generate a personalized care plan based on the comparison result of the bacterial count and the adjusted count threshold, including the following steps: After obtaining the dynamically adjusted quantity threshold, the dynamically adjusted quantity threshold is updated to the personalized quantity threshold, and the bacterial quantity is compared with the personalized quantity threshold. If the bacterial quantity is less than or equal to the personalized quantity threshold, the conventional care plan is maintained. If the bacterial quantity is greater than the personalized quantity threshold, an emergency intervention care plan is generated.

7. The personalized nursing program management method for oral care of intubated patients according to claim 2, characterized in that: The calculation expression of the immunity index is: In the formula, I e is the immunity index, WBC is the patient's white blood cell count, WBC min ~WBC max is the normal reference range of white blood cells, Lymph is the lymphocyte count of the patient, Lymph min ~Lymph max is the normal reference range of lymphocytes, IgG is immunoglobulin G count, IgG min IgG max Normal reference range for immunoglobulin G; The calculation expression of the drug resistance index is: In the formula, I r is the drug resistance index, n is the number of antibiotics used to treat Klebsiella pneumoniae infection, R i represents the patient's resistance to the i-th antibiotic, w i represents the weight of the i-th antibiotic.

8. A personalized nursing plan management system for oral care of intubated patients, used to implement the management method according to any one of claims 1 to 7, characterized in that: Including bacteria monitoring module, data set construction module, situation analysis module, dynamic adjustment module, solution generation module: Bacteria monitoring module: After obtaining oral secretions of patients at regular intervals based on microfluidics technology, the number of bacteria in the patient's mouth is analyzed and sent to the solution generation module; Dataset construction module: obtain the patient's current immunity status and antibiotic resistance through the API interface of the medical platform, construct the immunity status and antibiotic resistance into a first data set, obtain multiple frames of patient oral images through a camera device set at the patient's oral cavity, analyze the patient's oral condition after preprocessing the multiple frames of patient oral images, and construct the oral condition into a second data set. The first data set and the second data set are sent to the condition analysis module; Condition analysis module: takes the first data set and the second data set as inputs and inputs them into the condition fusion model. The condition fusion model outputs the patient's current physical condition and determines whether the quantity threshold needs to be dynamically adjusted based on the current physical condition. The judgment result is sent to the dynamic adjustment module. Dynamic adjustment module: when it is determined that the quantity threshold needs to be dynamically adjusted, the adjusted quantity threshold is obtained through the adjustment algorithm, and the adjusted quantity threshold is sent to the solution generation module; Plan generation module: Generates personalized care plans based on the comparison results between the number of bacteria and the adjusted number threshold, and sends the personalized care plans to relevant medical personnel.

Images