Anorectal postoperative intelligent follow-up management method and system based on mobile terminal

Abstract

The invention discloses an anorectal postoperative intelligent follow-up visit management method and system based on a mobile terminal, and relates to the technical field of communication data. Comprising the steps that a dynamic follow-up survey matrix is constructed according to clinical indexes and preset weights of patients before and after an operation, and the follow-up survey matrix aims at determining the interval duration of all follow-up stages; the mobile terminal establishes a timeliness doctor-patient communication channel through the follow-up survey matrix, and the mobile terminal generates a personalized rehabilitation guidance scheme based on follow-up data. According to the method, the dynamic follow-up survey matrix is constructed, the comprehensive risk value is calculated according to the quantitative assignment of the clinical indexes and the weighting of the preset weight, and the follow-up interval is iteratively optimized in combination with the real-time recovery data, so that the precision of the follow-up period is realized, the dynamic adjustment reduces unnecessary follow-up disturbance to low-risk patients, and the follow-up efficiency is improved. Tracking frequency is enhanced for middle-high risk patients, and the defect that a traditional fixed follow-up visit mode is cut at a time is thoroughly overcome.

Description

Technical Field

[0001] The present invention relates to the field of communication data technology, and in particular to a mobile terminal-based intelligent follow-up management method and system for anorectal surgery. Background Art

[0002] The intelligent follow-up management method is a systematic process based on mobile terminal technology that integrates data collection, analysis and artificial intelligence algorithms to achieve remote health monitoring, rehabilitation guidance and risk warning for patients after anorectal surgery.

[0003] After searching, the Chinese invention patent application with publication number "CN117253628A" proposed "an intelligent follow-up method, device, computer equipment and storage medium", which extracts health indicators from the patient's health file; configures grouping rules according to the health indicators, divides all patients into different follow-up groups, and configures corresponding follow-up plans for the follow-up groups; assembles the patient information and corresponding follow-up plan of each patient to generate a scheduled follow-up task; executes the scheduled follow-up task and sends the follow-up plan to the patient; analyzes the follow-up response of the patient based on the follow-up plan feedback to obtain the patient's current health indicator; determines whether the current health indicator triggers the warning rule; when the warning rule is triggered, sends the warning information to the corresponding patient.

[0004] The Chinese invention patent application with publication number "CN115512818A" proposes "an intelligent follow-up management system based on a medical system". By registering the patient's personal information at the outpatient terminal, a patient archive is established, and a personal patient follow-up unit is established for the patient to update the patient's condition information in real time. During the patient's treatment process, the customer service follow-up unit is used to communicate with the patient, inquire about relevant information during the patient's treatment process, and record the content of the follow-up communication. The recorded information is fed back to the outpatient terminal to facilitate the hospital to follow up the patient's recovery status in real time. When following up on the patient, online communication between the patient and the doctor is realized through the outpatient terminal, allowing the doctor to inquire about the patient's status online and give guidance. While providing high-quality follow-up services, it can provide rehabilitation guidance to patients and improve treatment effects.

[0005] However, during use, the above-mentioned disclosed methods and similar methods do not fully consider the differentiated impact of individual pathological characteristics of patients after anorectal surgery (such as the degree of surgical trauma, wound recovery status, underlying disease history, defecation irritation risk, and patient constitution) on follow-up needs. They mostly adopt a fixed-cycle follow-up model and have not established a dynamic risk stratification mechanism based on quantitative evaluation of clinical indicators. They cannot iteratively adjust the follow-up interval according to the patient's real-time recovery data (such as pain score, wound exudation, and stool shape), and their applicability is poor. Summary of the Invention

[0006] The purpose of the present invention is to provide a mobile terminal-based intelligent follow-up management method and system for anorectal surgery to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] First, a mobile terminal-based intelligent follow-up management method for anorectal surgery is proposed, including:

[0009] Based on the clinical indicators and preset weights of patients before and after surgery, a dynamic follow-up survey matrix is ​​constructed. The follow-up survey matrix is ​​designed to determine the interval length of each follow-up stage;

[0010] Mobile terminals establish timely doctor-patient communication channels through follow-up survey matrices.

[0011] The mobile terminal generates personalized rehabilitation guidance plans based on follow-up data;

[0012] Implement dynamic rehabilitation intervention and effect evaluation based on personalized rehabilitation guidance plan;

[0013] The construction methods of dynamic follow-up survey matrix include:

[0014] Converting clinical indicators into quantitative values ​​based on quantitative rules, where the quantitative rules are used to convert clinical indicators into quantitative values ​​and are coordinated with the preset weights;

[0015] Determine the patient's comprehensive risk value based on preset weights and quantitative values;

[0016] Divide risk levels based on comprehensive risk scores and determine access intervals based on risk levels;

[0017] Collect patients' real-time postoperative recovery data, iteratively optimize preset weights, recalculate comprehensive risk values, and dynamically adjust follow-up intervals.

[0018] As a further preferred embodiment of the present invention, the clinical indicators include: type of surgery, wound size, immediate postoperative bleeding, visual analogue scale for pain, patient age and history of underlying diseases, and preoperative bowel function;

[0019] The preset weights are established based on the participation of hospital clinical experts in multiple rounds of online questionnaire consultation and opinion integration. The collection of clinical indicators is completed by establishing a data connection between the mobile terminal and the hospital information system or electronic medical record system.

[0020] As a further preferred embodiment of the present technical solution, the quantification rules include: quantitatively assigning values ​​to the type of surgery based on the degree of surgical trauma and the difficulty of postoperative recovery, quantitatively assigning values ​​to the size of the wound based on the wound area, quantitatively assigning values ​​to the immediate postoperative bleeding situation based on the severity of bleeding, quantitatively assigning values ​​to the time of the first postoperative bowel movement and the shape of the bowel movement based on the degree of delay in the defecation time and the risk of irritation to the wound based on the shape, quantitatively assigning values ​​to the preoperative bowel movement function based on the degree of functional abnormality, quantitatively assigning values ​​to the patient's age based on the postoperative recovery rate corresponding to the age group, quantitatively assigning values ​​to the history of underlying diseases based on the type, number and control status of the underlying diseases, and quantitatively assigning values ​​to the visual analog score of pain based on the VAS score in the prior art.

[0021] As a further preferred embodiment of the present technical solution, the calculation of the comprehensive risk value is achieved by weighted summing the quantitative values ​​of each clinical indicator with the corresponding preset weights. The comprehensive risk level is divided into three levels: low risk, medium risk, and high risk. The division threshold is determined by the clinical follow-up data statistics of patients after anorectal surgery and the consensus opinions of anorectal surgery experts.

[0022] As a further preferred embodiment of the present technical solution, the mobile terminal is divided into a medical end and a patient end, and the doctor-patient communication channel is used for the medical end to push personalized follow-up task reminders based on the current comprehensive risk level and real-time recovery status to the patient end.

[0023] As a further preferred embodiment of the present technical solution, the method for establishing the time-effective doctor-patient communication channel includes:

[0024] Establish a personalized follow-up task template library based on risk level to formulate different follow-up task sets;

[0025] Automatically trigger personalized follow-up task push based on the follow-up cycle, which is used to match and generate follow-up tasks corresponding to the current patient risk level and recovery status from the task template library, and send them to the patient in the form of message push, pop-up reminder or calendar to-do;

[0026] A real-time feedback and intervention mechanism is established on the medical side, where the data uploaded by the patient side triggers the preset classification threshold to automatically generate high-risk warning information, and push it to the follow-up doctor through the medical mobile terminal. The doctor will send text, voice or video feedback to the patient side as soon as possible, and adjust the drug prescription, guide the patient's lifestyle or ask the patient to return for a follow-up visit if necessary.

[0027] As a further optimization of this technical solution, the personalized rehabilitation guidance program integrates real-time follow-up data from the patient side, information from the hospital side, and individual characteristics of the patient, and converts them into executable rehabilitation action recommendations. The specific content of the rehabilitation action recommendations varies according to the comprehensive risk level.

[0028] As a further preferred embodiment of the present technical solution, the content of the dynamic rehabilitation intervention includes:

[0029] Through follow-up tasks, the interventions in the personalized rehabilitation guidance plan are converted into quantitative assessment task indicators and included in the patient's daily follow-up task list. The medical staff can check the patient's task completion status in real time through the doctor-patient communication channel;

[0030] Obtain the follow-up data of the patients and the score ratio of the preset goals, and analyze the effect of dynamic rehabilitation intervention based on the score ratio;

[0031] Adjust the guidance plan based on the results of the effectiveness evaluation.

[0032] Secondly, in order to improve the above technical solution, a mobile terminal-based intelligent follow-up management system for anorectal surgery is also proposed, which uses the above-mentioned mobile terminal-based intelligent follow-up management method for anorectal surgery and includes:

[0033] Patient-side module, medical-side module, data processing module and knowledge base module;

[0034] The patient-side module is used for receiving and displaying follow-up tasks, uploading rehabilitation data, viewing rehabilitation guidance, and interacting with follow-up feedback;

[0035] The medical and nursing module is used to undertake patient data monitoring, early warning processing, rehabilitation guidance editing and efficacy evaluation functions;

[0036] The data processing module is used for integrating data from multiple sources, calculating risks, generating personalized plans, and evaluating efficacy;

[0037] The knowledge base module is used to store and provide standardized follow-up task templates, expert experience and rehabilitation guidance content.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This mobile-based intelligent follow-up management method and system for anorectal surgery builds a dynamic follow-up survey matrix, relies on quantitative assignment of clinical indicators and preset weights to calculate comprehensive risk values, and combines real-time recovery data to iteratively optimize follow-up intervals. This allows for precise and dynamic adjustment of follow-up cycles, reducing unnecessary follow-up interruptions for low-risk patients and increasing follow-up frequency for medium- and high-risk patients, completely overcoming the drawbacks of the traditional fixed follow-up model.

[0040] In addition, by establishing a timely doctor-patient communication channel, on the one hand, personalized follow-up tasks are automatically pushed based on risk levels, and patients are reminded to complete tasks such as data upload and symptom feedback in the form of messages, pop-ups, or calendar to-dos, thereby improving patient participation and compliance. On the other hand, a real-time early warning and intervention mechanism is built. When the data uploaded by the patient, such as postoperative bleeding and increased pain, triggers the preset threshold, the system quickly pushes a high-risk warning to the medical staff. The doctor can immediately guide the patient to take hemostatic measures, adjust medications, or arrange for an early follow-up visit through text, voice, or video, effectively reducing the risk of postoperative complications.

[0041] At the same time, personalized rehabilitation guidance plans generated based on multi-source data integrate information such as the patient's surgical type, wound size, underlying medical history, and real-time recovery status. For example, for patients with larger wounds or preoperative bowel dysfunction, the system will provide targeted rehabilitation action recommendations rather than one-size-fits-all guidance, significantly improving the adaptability and effectiveness of rehabilitation plans.

[0042] Through a dynamic rehabilitation intervention and effect evaluation mechanism, rehabilitation guidance is transformed into quantitative assessment tasks and included in the patient's daily checklist. Medical staff can view the task completion status in real time, analyze the intervention effect by combining follow-up data with the score ratio of preset targets, and remind doctors to adjust the guidance method or strengthen supervision, forming a closed-loop management and continuously improving the rehabilitation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a step method diagram of the present invention;

[0044] Figure 2 is a flowchart of the steps of the method for constructing a follow-up survey matrix of the present invention;

[0045] Figure 3 This is a diagram of the system module composition disclosed in the present invention. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0047] Before understanding the technical solution proposed in the present invention, it should be clear that the application scenario of this technical solution is the follow-up management scenario of patients after discharge after anorectal surgery, covering the patient's recovery period from 1 day to 6 months after surgery, and involving the collaborative interaction of the hospital's anorectal surgery department, patients and their families, and mobile terminal applications (APP / mini programs).

[0048] like Figure 1 As shown, the present invention provides a technical solution: an intelligent follow-up management method for anorectal surgery based on a mobile terminal, mainly an application management method of a mobile terminal, which includes: steps S100 to S400.

[0049] Step S100: Construct a dynamic follow-up survey matrix based on the patient's clinical indicators and preset weights before and after the operation. The follow-up survey matrix is ​​intended to determine the interval length of each follow-up stage.

[0050] It should be noted that the clinical indicators in step S100 include:

[0051] Type of surgery (eg, hemorrhoidectomy, anal fistula seton, and perianal abscess incision and drainage);

[0052] Wound size (measured in area);

[0053] Immediate postoperative bleeding (categorized as no bleeding, minor bleeding, moderate bleeding, and major bleeding);

[0054] Visual analogue scale for pain (VAS score in existing technology, 0-10 points);

[0055] The patient's age and history of underlying medical conditions (such as diabetes, hypertension, and immunosuppression);

[0056] Preoperative bowel function (such as constipation, diarrhea, and fecal incontinence) and the time of first bowel movement and stool form (such as hard stool, soft stool, and loose stool) after surgery;

[0057] It is worth noting that these clinical indicators need to be extracted through the existing patient electronic medical record system (EMR) or surgical records, and quantified according to preset weights to form structured data input into the follow-up survey matrix.

[0058] It should be noted that the preset weights in this technical solution are 0.2 for surgical type, 0.15 for wound size, 0.15 for bleeding, 0.15 for pain score, 0.15 for underlying disease history, and 0.2 for bowel function. These clinical indicators are obtained by associating data between mobile terminals and hospital information systems (HIS) or electronic medical record systems (EMR). The values ​​of the preset weights are determined by hospital clinical experts after participating in multiple rounds of online questionnaire consultations and integrating opinions.

[0059] As a preferred embodiment, refer to Figure 2It can be seen that due to the significant individual differences in the postoperative recovery rates of different patients (for example, the wound healing speed of young patients is usually faster than that of elderly patients, and the bleeding risk of patients without a history of underlying diseases is lower than that of patients with a history of diabetes), fixed weights are difficult to match the dynamic changes in the patient's recovery status in real time. Therefore, this implementation plan collects real-time data such as the wound healing status (such as the percentage of wound reduction), defecation pain score and bleeding frequency of patients every week after surgery, and iteratively optimizes the initial preset weights. For example, when the wound reduction percentage of a patient two weeks after surgery is lower than the expected value (such as less than 30%), the model will automatically increase the weight of the wound size indicator (for example, from 0. The weight of the pain score indicator is adjusted from 0.15 to 0.2), and the weight of the pain score indicator is reduced (for example, from 0.15 to 0.1). When the patient's first bowel movement after surgery is hard stool with a small amount of bleeding, the weight of the defecation function indicator is temporarily increased (for example, from 0.2 to 0.25) to strengthen the follow-up attention to the patient's defecation-related complications. This dynamic adjustment mechanism makes the follow-up survey matrix more in line with the patient's actual recovery progress, avoids the problem of follow-up intervals being too long or too short due to fixed weights, and further improves the accuracy of the follow-up interval duration. Therefore, the method for constructing the follow-up survey matrix includes: steps S101 to S104.

[0060] Step S101: converting clinical indicators into quantitative values ​​based on quantitative rules.

[0061] It is worth noting that the quantification rules announced in step S101 specifically cover the following:

[0062] 1. The type of surgery is quantified and assigned a value based on the degree of surgical trauma and the difficulty of postoperative recovery: hemorrhoidectomy (e.g., stapled hemorrhoidectomy) is assigned a value of 1, anal fistula hanging thread surgery is assigned a value of 2, and perianal abscess incision and drainage (especially complex abscesses) is assigned a value of 3;

[0063] 2. Wound size is quantified based on wound area, with a value of 1 for wound area <4 cm², 2 for wound area 4 cm² ≤ <10 cm², and 3 for wound area ≥10 cm² (larger wounds require longer tissue repair time and have higher risks of infection, bleeding, and delayed healing).

[0064] 3. Immediate postoperative bleeding was assigned a score based on the severity of bleeding: no bleeding (0 points), minor bleeding (spotting blood after defecation, bleeding volume <5 ml; 1 point), moderate bleeding (ejaculation after defecation or bleeding from dressings, 5 ml ≤ bleeding volume <20 ml; 2 points), and major bleeding (bleeding volume ≥20 ml or requiring emergency hemostasis; 3 points).

[0065] 4. The time of the first postoperative bowel movement and the shape of the stool were used to quantify the risk of wound irritation based on the degree of delay and shape of the bowel movement: a value of 1 was assigned to the first bowel movement within 24 hours after surgery, 2 to 48 hours, and 3 to the first bowel movement after 48 hours (the later the bowel movement, the more water the stool absorbs and the harder it becomes, which increases the friction and pressure on the wound and is more likely to cause bleeding, pain, or tearing). Stool shape was based on the Bristol stool classification: soft stool (types 4-5, banana-shaped or soft, easy to pass) was assigned a value of 1, hard stool (types 1-2, granular or lumpy, difficult to pass) was assigned a value of 2, and loose stool (types 6-7, paste-like or watery, difficult to form) was assigned a value of 3 (hard stools easily scratch the newly formed granulation tissue on the wound, while loose stools continuously soak the wound, reducing local resistance and increasing the risk of infection).

[0066] 5. Preoperative defecation function is assigned a value based on the degree of functional abnormality: no constipation, diarrhea, or fecal incontinence is assigned a value of 0, simple constipation (<3 bowel movements per week) is assigned a value of 2, simple diarrhea (>3 bowel movements per day) is assigned a value of 1, and fecal incontinence (inability to control bowel movements) is assigned a value of 3.

[0067] 6. Patient age is quantified based on the corresponding postoperative recovery rate for each age group: 1 for 18-44 years (young adults), 2 for 45-64 years (middle-aged adults), and 3 for 65 years and older (elderly patients). (Elderly patients have decreased tissue repair capacity and prolonged wound healing time, so the follow-up interval should be shortened accordingly.)

[0068] 7. The history of underlying diseases is quantitatively assigned a value based on the type, number, and control of the underlying diseases: no history of underlying diseases is assigned a value of 0, a history of one underlying disease with stable control (such as hypertension with blood pressure controlled below 140 / 90 mmHg, or non-insulin-dependent diabetes with glycosylated hemoglobin <7%) is assigned a value of 1, and a history of two or more underlying diseases (such as diabetes with hypertension, or immunodeficiency with chronic kidney disease) or a history of severe uncontrolled underlying diseases (such as insulin-dependent diabetes with large blood sugar fluctuations, or severe hypertension not meeting the control standard) is assigned a value of 2 (a history of underlying diseases increases the risk of complications such as postoperative infection, bleeding, and delayed wound healing, necessitating increased follow-up frequency and attention).

[0069] 8. The visual analogue scale (VAS) for pain is based on the existing VAS scale, which uses a linear scale of 0-10 to quantify the patient's subjective pain perception immediately after surgery and during the follow-up period. A score of 0 indicates no pain at all, 1-3 indicates mild pain (pain is tolerable and does not affect sleep or daily activities), 4-6 indicates moderate pain (requiring oral nonsteroidal anti-inflammatory drugs such as ibuprofen for relief, with mild interference with sleep and activities), and 7-10 indicates severe pain (requiring opioid injections and preventing normal sleep and simple activities).

[0070] Step S102: Determine the patient's comprehensive risk value based on the preset weights and quantitative values.

[0071] It should be noted that the calculation of the comprehensive risk value in step S102 is specifically achieved by performing weighted summation on the quantified value of each clinical indicator and the corresponding preset weight.

[0072] Specifically, the formula is: comprehensive risk value = (quantified value of surgical type × 0.2) + (quantified value of wound size × 0.15) + (quantified value of immediate postoperative bleeding × 0.15) + (visual analogue score for pain × 0.15) + (quantified value of history of underlying disease × 0.15) + (quantified value of bowel function × 0.2).

[0073] It should be noted that the quantitative value of defecation function is the sum of the quantitative values ​​of preoperative defecation function (such as no constipation is assigned a value of 0, simple constipation is assigned a value of 2), the time of first defecation after surgery (such as within 24 hours is assigned a value of 1, more than 48 hours is assigned a value of 3) and the shape of stool (such as soft stool is assigned a value of 1, hard stool is assigned a value of 2).

[0074] Step S103: Divide the risk levels based on the comprehensive risk scores, and determine the access interval period according to the risk levels.

[0075] It should be noted that in step S103, the comprehensive risk level is divided into three levels: low risk, medium risk, and high risk. The division threshold is determined based on the clinical follow-up data statistics of 5,000 patients after anorectal surgery and the consensus opinions of 10 anorectal surgery experts.

[0076] Specifically, a comprehensive risk value of ≤5 is considered a low-risk level, corresponding to a low risk of postoperative recovery, with the wound healing rate expected to be consistent with the normal physiological process, and the probability of complications (such as infection, delayed bleeding, and wound laceration) less than 5%;

[0077] 5 points < Comprehensive risk value ≤ 8 points indicates medium risk, indicating that the patient has 1-2 high-risk factors (such as elderly patients with mild diabetes, wound diameter 3-5 cm with minor postoperative bleeding). The recovery process may lag slightly behind expectations, and the probability of complications is 5%-15%;

[0078] A comprehensive risk score of >8 is considered a high-risk level, indicating that the patient has two or more high-risk factors (such as a patient over 65 years old undergoing complex perianal abscess incision and drainage, a wound area >10 cm² with moderate postoperative bleeding, and fecal incontinence before surgery), slow postoperative recovery, and a risk of complications >15%.

[0079] Based on the above risk levels, the initial follow-up intervals are set as follows:

[0080] For low-risk patients, the first follow-up interval is 14 days, followed by follow-up every 2 weeks until 6 weeks after surgery (wounds are basically healed);

[0081] For patients at intermediate risk, the first follow-up interval is 7 days, followed by follow-up every 10 days until 8 weeks after surgery;

[0082] The first follow-up interval for high-risk patients was 3 days, and then every 5 days until 10 weeks after surgery.

[0083] It is worth noting that the follow-up interval here is the initial benchmark value and serves only as the starting point for follow-up management. Subsequently, the interval duration will be iteratively optimized through the dynamic adjustment mechanism of step S104, combined with the patient's real-time recovery data every week (such as the percentage of wound reduction, defecation pain score, and number of bleeding times), to avoid insufficient or excessive follow-up due to fixed intervals.

[0084] Step S104: Collect the patient's real-time postoperative recovery data, iteratively optimize the preset weights, recalculate the comprehensive risk value, and dynamically adjust the follow-up interval.

[0085] It should be noted that step S104 aims to correct the fixed deviation of the initial preset weight through the real-time recovery data feedback obtained from each follow-up visit of the patient after surgery, so that the comprehensive risk value is more in line with the current recovery status, and then dynamically adjust the follow-up interval to match the patient's actual needs.

[0086] It is worth noting that real-time recovery data is obtained through two-way interaction between mobile terminals, patients, and medical staff. In addition, it should be noted that the rules for dynamically adjusting the follow-up interval length include:

[0087] Wound healing dimension: If the wound reduction percentage is less than 80% of the expected target (e.g., 20% expected for high-risk patients, but actual <16%), the weight of the wound size indicator is increased by 0.05 (e.g., from 0.15 to 0.2), and the weight of the pain score indicator is reduced by 0.05 (e.g., from 0.15 to 0.1), strengthening attention to delayed wound healing. The wound reduction percentage is calculated by obtaining the area data from two adjacent follow-up visits and calculating it by (initial wound area - current wound area) / initial wound area × 100%. For example, if a patient's initial wound area is 10 cm² and the wound area is 7 cm² at the one-week follow-up visit after surgery, the wound reduction percentage is 30%, which is in line with the expected target. If the wound area is still 9 cm², the reduction percentage is 10%, which is significantly lower than expected. It should be noted that the wound area is obtained by implanting a Net deep learning model in the existing technology into the mobile terminal.

[0088] In addition to wound healing, real-time recovery data also includes dynamic adjustment rules for bowel function, pain scores, and bleeding conditions:

[0089] Defecation function dimension: If the patient has two consecutive hard bowel movements (Bristol type 1-2) or blood dripping after defecation (small amount of bleeding) during the follow-up period, indicating an increased risk of wound irritation due to defecation, the weight of the defecation function indicator will be increased from 0.2 to 0.25, and the weight of the underlying disease history indicator will be reduced by 0.05 (e.g., from 0.15 to 0.1) to strengthen attention to defecation-related complications; if the subsequent bowel movements return to soft stools (Bristol type 4-5) without bleeding, the weight of the defecation function will be gradually adjusted back to the initial value.

[0090] Pain score dimension: If the patient's VAS score is still ≥6 points (moderate pain) one week after surgery or increases by ≥2 points compared with the previous week, it indicates that the wound may be infected or healing poorly. In this case, the weight of the pain score indicator is increased from 0.15 to 0.2, and the weight of the surgery type indicator is reduced by 0.05 (e.g., from 0.2 to 0.15), and the follow-up frequency of pain-related issues is increased. If the VAS score drops to ≤3 points (mild pain) and remains stable, the weight of the pain score is reduced accordingly.

[0091] Bleeding status dimension: If the patient experiences moderate or more bleeding during the follow-up period (such as post-defecation bleeding, dressing bleeding exceeding 20 ml) or bleeding frequency ≥ 2 times / week, indicating that the bleeding risk is not effectively controlled, the weight of the bleeding status indicator will be increased from 0.15 to 0.2, and the weight of the age indicator will be reduced by 0.05 (such as from 0.15 to 0.1) to strengthen the monitoring of bleeding risk; if there is no bleeding for 2 consecutive weeks, the initial weight will be adjusted back to the original weight.

[0092] It is worth noting that after each weight adjustment, the comprehensive risk value must be recalculated according to the formula in step S102, and the patient risk level must be updated according to the risk level classification standard in step S103. For example, when an initially high-risk patient (comprehensive risk value of 9 points) is followed up one week after surgery, the wound reduction percentage is only 10% (far below the expected 30%), then the wound size weight is increased from 0.15 to 0.2, the recalculated comprehensive risk value is increased to 10 points, and the follow-up interval is shortened from every 5 days to every 3 days. If the patient's subsequent wound reduction percentage increases to 40% (in line with expectations), the wound size weight is adjusted back to 0.15, the comprehensive risk value is reduced to 8.5 points, and the follow-up interval is extended to every 5 days.

[0093] It should also be added that the iterative optimization preset weights of step S104 are set to be performed after each follow-up visit after the patient's surgery. Real-time data needs to be collected and weight optimization and comprehensive risk calculations need to be performed. This iterative optimization of preset weights ensures that the follow-up interval is always consistent with the patient's current recovery status. For patients with initial low risk but slow recovery, the follow-up interval can be shortened in time to detect problems such as delayed wound healing at an early stage. For patients with initial high risk but smooth recovery, the follow-up interval can be gradually extended to reduce unnecessary medical interventions and improve patient compliance.

[0094] Step S200: The mobile terminal establishes a timely doctor-patient communication channel through a follow-up survey matrix.

[0095] It should be noted that in step S200, the mobile terminal is divided into a medical end and a patient end, and the medical-patient communication channel is used for the medical end (mobile terminal of the hospital object) to push personalized follow-up task reminders based on the current comprehensive risk level and real-time recovery status to the patient end (mobile terminal of the patient object) (such as uploading digital images of the wound, recording the shape and frequency of bowel movements, filling in the pain visual analog score, submitting basic disease history indicator monitoring data, etc.). In addition, the timeliness in step S200 specifically refers to the follow-up interval dynamically adjusted according to step S104, and the mobile terminal automatically pushes personalized follow-up tasks matching the current recovery stage (such as uploading digital images of the wound, recording the shape and frequency of bowel movements, and filling in the pain VAS score) to the patient end at the preset time point of each follow-up cycle (such as 8 am on the third day after surgery for high-risk patients, 6 pm on the seventh day after surgery for medium-risk patients, and 12 noon on the fourteenth day after surgery for low-risk patients), ensuring that the task triggering is synchronized with the focus of the patient's recovery process.

[0096] As a preferred implementation scheme, in the existing anorectal postoperative follow-up management process, the use of fixed time intervals for follow-up will not be able to effectively match the actual rehabilitation needs of different patients due to significant individual differences in patients' postoperative recovery speed and complication risks. This may lead to some high-risk patients experiencing delayed wound healing, bleeding or defecation disorders during the follow-up interval, which may not be discovered and intervened in time. On the other hand, for low-risk patients with smooth recovery, frequent follow-up not only increases the consumption of medical resources, but also adds unnecessary burdens to patients. Therefore, it is necessary to establish a timely doctor-patient communication channel. By dynamically associating follow-up tasks with patients' risk levels and real-time rehabilitation data, automatic adjustment of follow-up time points and follow-up content can be achieved, thereby ensuring the timeliness and pertinence of the communication process.

[0097] Specifically, the method for establishing a time-sensitive doctor-patient communication channel includes: steps S201 to S203.

[0098] Step S201: Establish a personalized follow-up task template library based on risk level.

[0099] It should be noted that in step S201, the construction of the personalized follow-up task template library is based on the different characteristics of low-risk, medium-risk and high-risk patients divided in step S103, combined with the main monitoring dimensions of postoperative recovery (wound healing, bowel function, bleeding situation and pain score), and different follow-up task sets are formulated respectively.

[0100] Specifically, the follow-up tasks for low-risk patients focus on routine rehabilitation monitoring, such as uploading wound images, recording bowel movements, and filling in VAS pain scores. In addition to the tasks for low-risk patients, the follow-up tasks for medium-risk patients also include monitoring of underlying disease history indicators (such as uploading blood sugar and blood pressure) and detailed records of bowel movement frequency and accompanying symptoms (such as blood in the stool). For high-risk patients, the frequency of follow-up and the granularity of tasks are further strengthened on the basis of the above tasks. For example, daily uploading of digital images of the wound, real-time filling in of VAS scores, recording of each bowel movement and the degree of accompanying bleeding, and an additional instant feedback module on the doctor's side are required to ensure that intervention can be made in the first time when abnormalities occur.

[0101] As a preferred solution, the construction of the task template library is not fixed, but is updated in real time through the hospital information system (HIS) and expert experience library to cover different surgical types and different complication risk scenarios, ensuring the scientificity and comprehensiveness of follow-up tasks.

[0102] Step S202: Automatically trigger personalized follow-up task push based on the follow-up cycle.

[0103] It should be noted that in step S202, the mobile terminal automatically matches and generates a follow-up task corresponding to the current patient risk level and recovery status from the task template library of step S201 at the follow-up time point by calling the follow-up interval duration dynamically adjusted in step S104, and sends it to the patient end in the form of message push, pop-up reminder or calendar to-do.

[0104] Specifically, for low-risk patients, a follow-up task reminder will be pushed at 12 noon on the 14th day after surgery, which requires uploading wound images, filling in VAS scores and bowel movement records. For medium-risk patients, the task will be pushed at 6 pm on the 7th day after surgery. In addition to images and scores, basic disease history data such as blood pressure and blood sugar must also be uploaded; for high-risk patients, the task will be pushed at 8 am on the 3rd day after surgery, and the next task push will be triggered again within 72 hours after the task is completed.

[0105] As a preferred solution, in order to improve patient compliance, the task push message contains a progress bar and completion rewards (such as "80% completed, keep going"), and allows patients to choose the reminder method (SMS, in-app reminder or voice broadcast). At the same time, the medical staff can view the patient's task completion status in real time. If it is not completed within 24 hours, the medical staff will intervene manually.

[0106] Step S203: Establish a real-time feedback and intervention mechanism for medical staff.

[0107] It should be noted that in step S203, the medical side connects with the patient side through task completion and real-time data upload to achieve dynamic monitoring and feedback. When the data uploaded by the patient triggers the preset classification threshold (such as VAS score ≥ 7, wound reduction percentage <10%, two consecutive bowel movements with bleeding), high-risk warning information will be automatically generated and pushed to the follow-up doctor through the medical side mobile terminal. The doctor will send text, voice or video feedback to the patient side as soon as possible, and adjust the drug prescription, guide the patient's lifestyle or ask the patient to return for a follow-up visit in advance if necessary.

[0108] Specifically, for example, if a high-risk patient reports a VAS score of 8 during follow-up on the 5th day after surgery, and the uploaded wound image shows obvious redness and swelling, the patient is judged to be at high risk of infection, and a "red alert" is automatically pushed to the medical end. After receiving the information through the medical end, the doctor guides the patient to take oral antibiotics through video consultation and requires a follow-up visit the next day.

[0109] Step S300: The mobile terminal generates a personalized rehabilitation guidance plan based on the follow-up data.

[0110] It should be noted that step S300 aims to combine the real-time follow-up data of the patient (wound healing, defecation function, pain score, and control of underlying disease history) with the hospital side and individual characteristics of the patient (such as age, type of surgery, and lifestyle habits), and convert them into rehabilitation action recommendations for implementation, so as to solve the common problems of "lack of nursing knowledge" and "unclear rehabilitation direction" in patients after anorectal surgery, promote wound healing and reduce the risk of complications through precise intervention, and at the same time improve the patient's sense of participation in the rehabilitation process.

[0111] Specifically, for low-risk patients (such as those who recover smoothly after surgery and have no history of underlying diseases), if the follow-up data show that the wound reduction is in line with expectations (such as 30% reduction one week after surgery) but the stool is slightly dry (Bristol type 3), the personalized rehabilitation guidance plan focuses on strengthening routine care: including "wound care" (sitz bath with warm water for 15 minutes every day to keep the wound clean), "defecation optimization" (drink 200ml of warm salt water every morning and eat more vegetables rich in dietary fiber such as celery and leek), and "activity suggestions" (avoid sitting for more than 1 hour, and get up and walk around every 30 minutes). If the patient reports that "the water temperature is difficult to control during the sitz bath", "water temperature guidance" will be supplemented (the water temperature is recommended to be 38-40℃, and it is best to use your elbow to test the temperature to ensure it is not hot).

[0112] For medium-risk patients (such as those with mild diabetes and a wound diameter of 3-5 cm), if follow-up data show poor blood sugar control (fasting blood sugar 7.6 mmol / L) and the wound is red and swollen (VAS score 4 points), the personalized rehabilitation guidance plan needs to take into account the history of underlying diseases and wound recovery. In addition to the guidance content for low-risk patients mentioned above, "blood sugar management" (monitor blood sugar 4 times a day, avoid eating high-sugar foods such as watermelon and milk tea, and take hypoglycemic drugs as prescribed by the doctor) and "wound anti-inflammatory" (topical application of mupirocin ointment, 2 times a day, disinfection before application) are added. If the patient reports that he "forgot to monitor blood sugar", the medical staff will add a "blood sugar monitoring reminder" through follow-up tasks (such as a pop-up window at 7 am every day to remind "it's time to measure fasting blood sugar").

[0113] For high-risk patients (e.g., those with complex perianal abscesses after surgery and wound area >10 cm²), if follow-up data show slow wound shrinkage (15% reduction 2 weeks after surgery) and exudate (VAS score 6), the guidance plan needs to strengthen high-frequency interventions, including "wound care upgrade" (two 20-minute sitz baths with 1:5000 potassium permanganate solution daily, followed by gentle drying of the wound with sterile gauze), "pain management" (taking diclofenac sodium sustained-release tablets as prescribed by the doctor, one tablet every 12 hours, and avoid taking on an empty stomach), and "real-time feedback requirements" (uploading photos of wound exudate daily).

[0114] As a preferred option, the personalized rehabilitation guidance program adopts a multimodal presentation method: for young patients (such as those aged 25-40), the operation steps are demonstrated in the form of short videos (such as the video "The Correct Way to Do a Sitz Bath on the Wound", which is 1 minute long and includes details such as preparing warm water, adding potassium permanganate, and sitz bath posture); for elderly patients (such as those aged 60 and above), the program is presented in the form of pictures and texts + voice explanations (such as the picture and text of the "Dietary Fiber Food List", accompanied by the voice "Eat apples with the skin and cook buckwheat noodles softer for easier digestion"); in addition, the medical staff will adjust the focus of the guidance program based on the patient's feedback (such as "Have you done a sitz bath every day this week?" The patient selects "yes") - if the implementation effect is good (such as the reduction of wound redness and swelling), the frequency of similar guidance will be reduced; if the implementation effect is not good (such as hard stools are still present), the level of detail of the guidance will be increased (such as "You can try cooking oatmeal into porridge and adding a spoonful of honey to increase dietary fiber and promote bowel movements").

[0115] It should also be added that the personalized rehabilitation guidance program and the follow-up task of step S200 form a closed-loop linkage: by incorporating the actions in the guidance program (such as "daily sitz bath") into the follow-up tasks (such as "please upload a photo of the wound after today's sitz bath"), and evaluating the patient's execution effect through task completion (such as "You completed 5 sitz baths this week, reaching 83% of the goal, keep it up"), if the patient does not complete the action (such as not taking a sitz bath for 3 consecutive days), the follow-up task will remind the patient "You have not taken a sitz bath for 3 days, the wound recovery needs to be kept clean, please complete it as soon as possible", and push a short article on "The Importance of Sitz Baths" (such as "Sitz baths can promote blood circulation in the wound, reduce the risk of infection, and help the wound heal").

[0116] Step S400: Implement dynamic rehabilitation intervention and effect evaluation according to the personalized rehabilitation guidance plan.

[0117] It should be noted that step S400 aims to form a closed-loop management of "program generation-execution-feedback-optimization" by real-time tracking and effect evaluation of the implementation of the personalized rehabilitation guidance program, thereby ensuring the pertinence and effectiveness of the rehabilitation guidance.

[0118] Specifically, the content of dynamic rehabilitation intervention includes:

[0119] First, execution tracking: Through the follow-up task of step S200, the intervention actions in the personalized rehabilitation guidance plan (such as warm water sitz bath for 15 minutes / time on the wound, daily dietary fiber intake ≥25g, blood glucose monitoring once / day) are converted into quantifiable and assessable task indicators, and included in the patient's daily follow-up task list (such as "Please record the types and weight of dietary fiber food intake today" and "Please upload the wound photo after today's sitz bath"). The medical staff can check the patient's task completion status in real time through the doctor-patient communication channel, including the completion rate (such as "Completed 6 sitz baths this week, with a completion rate of 75%) and the execution quality (such as "The wound photo is clear" and "The blood glucose data is continuous without omissions").

[0120] Second, effect evaluation: compared with the preset goals of the guidance program (such as wound reduction ≥30% one week after surgery, Bristol type 4-5 stool shape, VAS score ≤3 points, fasting blood glucose ≤7.0mmol / L), and the multi-dimensional comprehensive scoring method in the existing technology was used to calculate the effect (full score 100 points), and the difference between the results and the patient's follow-up data (wound reduction percentage, Bristol stool shape score, VAS pain score, fasting blood glucose value) was used to determine the effectiveness of the guidance program. It should be added that the difference calculation ratio within the follow-up data is 40% for wound healing, 30% for bowel function, 20% for pain control, and 10% for basic disease history management. The total score of the patient's follow-up data is the sum of the differences multiplied by the proportions.

[0121] Third, program optimization: Adjust the guidance plan based on the effectiveness evaluation results. For patients with a "good effect (over 80 points)," repeated instructions will be reduced (e.g., the "wound sitz bath" reminder will be changed from once daily to once every two days), and advanced suggestions will be added (e.g., "Perform kegel exercises for 10 minutes daily to promote anal function recovery"). For patients with a "fair effect (60 to 80 points)," implementation difficulties will be analyzed (e.g., "No time to prepare dietary fiber"), and the approach will be adjusted (e.g., "Recommended dietary fiber powder for quick and easy consumption") or short videos with "quick recipes" (e.g., celery juice or oatmeal porridge) will be provided). For patients with a "poor effect (less than 60 points)," proactive doctor intervention will be initiated (e.g., video consultation to understand the reason for reducing sitz baths due to pain, suggesting the addition of compound phellodendron chinense solution to relieve pain, or psychological counseling to emphasize that "pain is a normal process and sitz baths can reduce inflammation").

[0122] As a preferred solution, the effect evaluation result is linked to the risk level in step S100: if the score is ≥80 points for two consecutive times and there are no complications, the risk level will be reduced by one level (such as medium risk to low risk), and the follow-up interval will be extended (such as 7 days to 14 days); if the score is <60 points for two consecutive times or new complications (such as wound infection) occur, the risk level will be increased by one level (such as low risk to medium risk), and follow-up will be strengthened (such as increasing daily wound image upload).

[0123] It should also be added that step S400 forms a closed loop with the previous steps: S100 risk assessment determines the initial level, S200 pushes the follow-up task, S300 generates the guidance plan, S400 tracks the effect and feeds back to S100 to adjust the risk level, thereby optimizing the S200 task and S300 plan.

[0124] refer to Figure 3 It can be seen that the present application also proposes an intelligent follow-up management system for anorectal surgery based on a mobile terminal, which uses an intelligent follow-up management method for anorectal surgery based on a mobile terminal in the above content and includes:

[0125] Patient-side module, medical-side module, data processing module and knowledge base module.

[0126] It is worth noting that in this technical solution, the patient-side module is the core entrance for patients to participate in follow-up management, and undertakes the functions of "task reception, data upload, guidance review, and feedback interaction".

[0127] Specifically, the patient-side module includes the following functions:

[0128] Task display: To-do / completed tasks are displayed in a window, with the task type (e.g., "wound care," "blood sugar monitoring"), deadline (e.g., "complete by 2024-05-10 23:59"), and progress bar (e.g., "70% completed, 1 item left"). Click a task to view detailed requirements (e.g., "upload a photo of the wound after sitz bath, clearly showing the wound boundary").

[0129] Data upload: It provides three methods: "photo upload" (wound images, medication receipts), "manual input" (pain score, bowel movement frequency), and "device synchronization" (blood sugar and blood pressure monitors are automatically uploaded via Bluetooth connection). It supports real-time preview (such as "wound photo clarity") and retransmission functions.

[0130] Guidance Tips: Categorized by "Daily Care," "Dietary Recommendations," and "Exercise Guidance," it displays graphics (e.g., "Dietary Fiber Food List"), short videos (e.g., "The Correct Sitz Bath Method"), and audio explanations (e.g., "Kegel Exercise Tutorial"). It also supports "Collecting" and "Sharing" (e.g., sharing with family members).

[0131] Feedback input: proactively inquire about the patient's performance (e.g., "Did you encounter any difficulty taking a sitz bath this week?"), provide quick feedback options such as "increased pain" and "abnormal bowel movements," and allow the patient to enter text or voice descriptions of the problem (e.g., "The wound hurts a little when I take a sitz bath").

[0132] As a preferred option, a "recovery diary" function can be added to the patient's end during actual use. This automatically integrates daily task completion status (such as "completed one sitz bath and one blood glucose monitoring"), symptom records (such as "two soft bowel movements today, no bleeding"), and the effectiveness of the guidance plan (such as "wound redness and swelling reduced"), generating visual line graphs (such as "pain score trend" and "wound reduction percentage trend"), allowing patients to monitor their "recovery progress" at any time and enhance their confidence in recovery. For example, one patient discovered through the "recovery diary" that "after three consecutive days of sitz baths, the pain score dropped from 6 to 4 points," which made them more proactive in continuing to take sitz baths.

[0133] It should be added that in this technical solution, the medical and nursing module is a management tool for follow-up doctors, and undertakes the functions of "data monitoring, early warning processing, guidance adjustment, and effect evaluation".

[0134] Specifically, the functions of the medical module include:

[0135] Patient management: Display a list of patients by "risk level" (low / medium / high) and "follow-up status" (to be completed / completed / overdue), annotate key information (such as "Zhang San, medium risk, 7 days after surgery, task completion rate 80%)"; click on a patient to view detailed files (operative records, underlying medical history, follow-up history data);

[0136] Early warning prompts: Warning levels are marked with "red (high risk), yellow (medium risk), and green (low risk)", displaying the patient information that triggered the warning (such as "Li Si, high risk, VAS score 8 points, wound surface redness and swelling"), the trigger threshold (such as "VAS ≥ 7 points") and the system suggestion (such as "video consultation immediately"). Doctors can click the "process" button and choose "send text feedback", "initiate video consultation" or "issue electronic prescription" (such as "oral antibiotics recommended");

[0137] Guidance plan editor: Doctors can customize rehabilitation guidance content, adding "hospital-specific nursing methods" (such as "our hospital's Chinese medicine sitz bath formula: 30g of Phellodendron amurense, 20g of Sophora flavescens, decocted in water for sitz bath"), and "personalized adjustments" (such as adding "recommended dietary fiber powder for oral administration" for patients who "don't have time to prepare dietary fiber foods"), and push these to patients in real time;

[0138] Effect evaluation: Multi-dimensional evaluation results are displayed in the form of charts, such as "the compliance rate of patients with different risk levels" (85% for low risk, 60% for medium risk, and 40% for high risk), "common implementation difficulties" (such as "no time for sitz baths" accounting for 35%, "no understanding of dietary fiber foods" accounting for 25%), and "guidance program optimization effect" (such as "after adjusting the dietary fiber supplement method, the compliance rate increased from 50% to 70%"), to help doctors quickly identify the root cause of "poor results".

[0139] As a preferred solution, in actual use, the medical module can also add "batch operation" functions (such as "pushing 'blood sugar monitoring reminders' to all medium-risk patients") and "template reuse" functions (such as "copying the 'low-risk guidance plan after mixed hemorrhoid surgery' to new patients") to reduce duplication of work. For example, if a doctor receives 10 "high-risk warnings" through the "Warning Center", he can batch select "initiate video consultations", and the system will automatically prioritize the "most urgent" (such as VAS ≥ 9 points) patients.

[0140] It should be noted that in this technical solution, the data processing module undertakes the functions of "data integration, risk calculation, solution generation, and effect evaluation".

[0141] Specifically, the functions of the data processing module in this technical solution include:

[0142] Data integration: Connecting to the hospital information system (HIS), electronic medical record system (EMR), patient-side and medical-side data, cleaning (such as removing duplicate data and correcting incorrect formats), structuring (such as converting "wound redness and swelling" into "wound inflammation index: moderate"), and storing it in the patient's personal health record;

[0143] Risk assessment model: Using a combined "logistic regression + random forest" algorithm, the model inputs individual patient characteristics (age, surgery type, underlying medical history), postoperative data (wound size, bleeding), and follow-up data (pain score, bowel function), outputs a risk level (low / medium / high), and dynamically adjusts the risk level (if two consecutive positive results are achieved, the risk level is reduced by one level);

[0144] Intelligent generation of guidance plans: Based on "risk level + individual characteristics + follow-up data," matching guidance content is retrieved from the existing hospital knowledge base module (e.g., "medium risk + diabetes + wound redness and swelling" results in "blood sugar management + wound anti-inflammatory + dietary fiber guidance"). By setting rules (e.g., "if the patient reports 'no time to prepare dietary fiber,' then recommend dietary fiber powder"), the content is optimized to generate personalized guidance plans.

[0145] Effect evaluation engine: According to the "multi-dimensional comprehensive scoring method" of method step S400, the patient effect score (full score 100 points) is calculated, an evaluation report is generated (such as "Wang Wu, medium risk, 14 days after surgery, comprehensive score 75 points, average effect"), and it is synchronized to the medical and nursing end module.

[0146] As a preferred solution, the data processing module in this technical solution can add the existing "federated learning" technology in actual use, that is, without leaking patient privacy, it can integrate follow-up data from multiple hospitals, optimize the risk assessment model and guidance plan generation engine (for example, through 5,000 patient data from 10 hospitals, adjust the threshold of "wound reduction percentage" from "<10%" to "<15%", thereby improving the accuracy of early warning).

[0147] It should be noted that the knowledge base module is integrated between the hospital information system (HIS) and the electronic medical record system.

[0148] Specifically, the knowledge base module in this technical solution includes the following contents:

[0149] Task template library: Categorized by "risk level," "surgery type," and "follow-up period," it stores standardized follow-up tasks (e.g., "low-risk patients after mixed hemorrhoid surgery, 14-day postoperative tasks: upload wound images, fill in VAS scores, record bowel movements") and supports "custom templates" (e.g., if a hospital adds the "anal fistula surgery" surgery type, it can add a "high-risk task template after anal fistula surgery").

[0150] Expert Experience Database: This database collects the clinical experience of anorectal specialists (e.g., "Early Identification of Wound Infection: Redness, Swelling, Exudate, and Increased Pain" and "Defecation Care for Diabetic Patients: Avoid High-Sugar Foods and Increase Dietary Fiber"), presented in the form of "Case + Suggestions" (e.g., "Case: A patient experienced wound redness and swelling 5 days after surgery, and improved after receiving antibiotics and a Chinese medicine sitz bath; Suggestion: In similar cases, prioritize video consultation");

[0151] Rehabilitation Guidance Library: Categorized by "symptoms" (pain, difficulty in defecation, wound exudation) and "scenarios" (diet, exercise, nursing), it stores multimodal guidance content such as pictures, texts, short videos, and voice (e.g., "Pain Relief" includes a video on "How to Use VAS Scoring," pictures and text on "Compound Phellodendron Liquid Application Tutorial," and voice on "Pain Management Tips"), and is updated regularly (e.g., adjusting the "Recommended Dietary Fiber Amount" every quarter according to the corresponding nursing guidelines).

[0152] As an optimal solution, when this technical solution is actually running, the knowledge base module can also add support for the "expert contribution" function. For example, an anorectal doctor adds personal experience through the medical and nursing module (such as "I use purslane sitz bath to treat red and swollen wounds, the effect is very good, and I recommend adding it to the guidance library"), which is included in the expert experience library after review by the hospital to achieve "knowledge co-creation". That is, an expert adds a "purslane sitz bath recipe" (50g purslane, 30g dandelion, decocted in water for sitz bath). After expert review, the rehabilitation guidance library adds a new "Chinese medicine sitz bath" category, and the patient side can view this content.

[0153] It is worth noting that the actual operation process of each module in this technical solution is as follows: First, the patient uploads postoperative data (such as wound size and underlying disease history). After the data processing module integrates the data, the risk assessment model outputs the initial risk level. The initial risk level is synchronized to the patient side (displaying "Your risk level is medium risk") and the medical side (labeled "medium-risk patient"). Subsequently, the data processing module retrieves the corresponding task template from the knowledge base module based on the risk level, generates personalized follow-up tasks, and pushes the information through the patient-side module (such as "medium-risk patients, push tasks 7 days after surgery"). After that, the patient uploads follow-up data (such as wound images and pain scores). After the data processing module integrates the data, if the preset warning threshold (such as VAS ≥ 7 points) is triggered, the warning center will push an alert to the medical side; the doctor will send feedback (such as video guidance) through the medical side; and the patient side will receive the feedback and execute it. Then, the data processing module retrieves guidance content from the knowledge base module based on the follow-up data, generates a personalized guidance plan, and displays it through the patient-side module; after the patient implements the feedback and provides the effect (such as "pain is reduced after sitz bath"), the data processing module evaluates the effect and adjusts the guidance plan accordingly (such as reducing the frequency of sitz bath reminders), and synchronizes it to the patient and medical ends.

[0154] It should be noted that during this process, the data processing module dynamically adjusts the risk level based on the effect evaluation results (if the effect is good for two consecutive times, the medium risk will be changed to low risk), and the adjusted risk level is synchronized to the patient side (displaying "Your risk level has been reduced to low risk") and the medical side (the follow-up interval is adjusted at the same time).

[0155] Specifically, the system linkage process for a patient (post-operative mixed hemorrhoid surgery, with a history of diabetes, and an initial medium-risk level) is as follows:

[0156] On the third day after surgery, the patient uploaded the wound image (showing redness and swelling), blood sugar value (7.8 mmol / L), and VAS score (5 points). After the data processing module integrated the data, the risk assessment model maintained the medium-risk judgment and retrieved the "medium-risk + diabetes" task template from the knowledge base module. The patient then pushed the "7-day task after surgery" (requiring uploading of wound images, blood sugar value, VAS score and bowel movement records). On the seventh day after surgery, the patient completed the follow-up task and uploaded the data (wound redness and swelling were reduced, blood sugar was 7.2 mmol / L, VAS score was 4 points, and bowel movements were 2 times). The data processing module evaluated the effect (comprehensive score was 70 points, and the effect was judged to be general). The "Dietary Fiber Powder Recommendation" guidance content was retrieved from the knowledge base module. The patient displayed the "Dietary Fiber Powder Preparation Method" video. The patient reported that "due to time reasons, dietary fiber powder was used directly, and the effect was good". On the 14th day after surgery, the patient uploaded the data (wound area was reduced by 20%, blood sugar was 7.0 mmol / L, VAS score of 3, and 3 bowel movements), the data processing module evaluated the effect (comprehensive score of 80 points, which was judged to be good), and accordingly reduced the risk level to low risk. The follow-up interval was extended from 7 days to 14 days. The patient side displayed "Your risk level has been reduced to low risk, and the follow-up interval has been adjusted to 14 days", and the medical staff updated the status to "low-risk patient" and reduced the frequency of task push accordingly.

[0157] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is limited by the accompanying embodiments and their equivalents.

Claims

1. A mobile terminal-based intelligent follow-up management method for anorectal surgery, characterized in that: include: Based on the clinical indicators and preset weights of patients before and after surgery, a dynamic follow-up survey matrix is ​​constructed. The follow-up survey matrix is ​​designed to determine the interval length of each follow-up stage; Mobile terminals establish timely doctor-patient communication channels through follow-up survey matrices. The mobile terminal generates personalized rehabilitation guidance plans based on follow-up data; Implement dynamic rehabilitation intervention and effect evaluation based on personalized rehabilitation guidance plan; The construction methods of dynamic follow-up survey matrix include: Converting clinical indicators into quantitative values ​​based on quantitative rules, where the quantitative rules are used to convert clinical indicators into quantitative values ​​and are coordinated with the preset weights; Determine the patient's comprehensive risk value based on preset weights and quantitative values; Divide risk levels based on comprehensive risk scores and determine access intervals based on risk levels; Collect patients' real-time postoperative recovery data, iteratively optimize preset weights, recalculate comprehensive risk values, and dynamically adjust follow-up intervals; The comprehensive risk value is calculated by weighted summing the quantified values ​​of each clinical indicator with the corresponding preset weights. The comprehensive risk level is divided into three levels: low risk, medium risk, and high risk. The classification threshold is determined by clinical follow-up data statistics of patients after anorectal surgery and the consensus opinions of anorectal surgery experts; The mobile terminal is divided into a medical terminal and a patient terminal. The medical terminal is used to push personalized follow-up task reminders based on the current comprehensive risk level and real-time recovery status to the patient terminal. The methods for establishing the time-effective doctor-patient communication channel include: Establish a personalized follow-up task template library based on risk level to formulate different follow-up task sets; Automatically trigger personalized follow-up task push based on the follow-up cycle, which is used to match and generate follow-up tasks corresponding to the current patient risk level and recovery status from the task template library, and send them to the patient in the form of message push, pop-up reminder or calendar to-do; A real-time feedback and intervention mechanism is established on the medical side, where the data uploaded by the patient side triggers the preset classification threshold to automatically generate high-risk warning information, and push it to the follow-up doctor through the medical mobile terminal. The doctor immediately sends text, voice or video feedback to the patient side, and adjusts the drug prescription, guides the patient's lifestyle or requires the patient to return for a follow-up visit in advance based on the warning information.

2. The intelligent follow-up management method for anorectal surgery based on a mobile terminal according to claim 1, characterized in that: The clinical indicators include: surgical type, wound size, immediate postoperative bleeding, pain visual analogue scale, patient age, underlying disease history, and preoperative bowel function; The preset weights are established based on the participation of hospital clinical experts in multiple rounds of online questionnaire consultation and opinion integration. The collection of clinical indicators is completed by establishing a data connection between the mobile terminal and the hospital information system or electronic medical record system.

3. The intelligent follow-up management method for anorectal surgery based on a mobile terminal according to claim 2, characterized in that: The quantification rules include: the type of surgery is quantitatively assigned based on the degree of surgical trauma and the difficulty of postoperative recovery, the size of the wound is quantitatively assigned based on the wound area, the immediate postoperative bleeding situation is assigned in sequence based on the severity of bleeding, the time of the first bowel movement after surgery and the shape of the bowel movement are quantitatively assigned based on the degree of delay in the defecation time and the risk of irritation to the wound by the shape, the preoperative bowel function is assigned based on the degree of functional abnormality, the patient's age is quantitatively assigned based on the postoperative recovery rate corresponding to the age group, the basic disease history is quantitatively assigned based on the type, number and control status of the basic disease, and the pain visual analog score is assigned based on the VAS score in the existing technology.

4. The intelligent follow-up management method for anorectal surgery based on a mobile terminal according to claim 1, characterized in that: The personalized rehabilitation guidance plan integrates real-time follow-up data from the patient side, information from the hospital side, and individual characteristics of the patient, and converts them into executable rehabilitation action recommendations. The specific content of the rehabilitation action recommendations varies depending on the comprehensive risk level.

5. The intelligent follow-up management method for anorectal surgery based on a mobile terminal according to claim 1, characterized in that: The content of the dynamic rehabilitation intervention includes: Through follow-up tasks, the interventions in the personalized rehabilitation guidance plan are converted into quantitative assessment task indicators and included in the patient's daily follow-up task list. The medical staff can check the patient's task completion status in real time through the doctor-patient communication channel; Obtain the follow-up data of the patients and the score ratio of the preset goals, and analyze the effect of dynamic rehabilitation intervention based on the score ratio; Adjust the guidance plan based on the results of the effectiveness evaluation.

6. A mobile terminal-based intelligent follow-up management system for anorectal surgery, using the mobile terminal-based intelligent follow-up management method for anorectal surgery according to any one of claims 1 to 5, characterized in that: include: Patient-side module, medical-side module, data processing module and knowledge base module; The patient-side module is used for receiving and displaying follow-up tasks, uploading rehabilitation data, viewing rehabilitation guidance, and interacting with follow-up feedback; The medical and nursing module is used to undertake patient data monitoring, early warning processing, rehabilitation guidance editing and efficacy evaluation functions; The data processing module is used to integrate data from multiple sources, calculate risks, generate personalized plans, and evaluate efficacy; The knowledge base module is used to store and provide standardized follow-up task templates, expert experience and rehabilitation guidance content.

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