AI reminding method for gastroenterology department enteroscope patient to take laxative

Abstract

The invention relates to the technical field of medical health and artificial intelligence, and discloses an AI reminding method for a gastroenterology department enteroscope patient to take a laxative, comprising the following steps: S1, guiding the patient to enter an AI interaction interface through a two-dimensional code or an applet entry; s2, generating a personalized medication scheme according to the basic information and the real-time data input by the patient; s3, ensuring that the patient completes an intestinal tract preparation process through a staged guidance and real-time reminding function; s4, performing abnormal reaction identification according to real-time feedback data input by the patient, and adjusting subsequent operation suggestions; and S5, screening potential drug interaction through the integrated drug database, and providing a safe drug use prompt. Personalized data such as age, weight, basic diseases, daily medication and daily work and rest of a patient are collected through the personal information input module, the medication scheme generation module calls a preset algorithm to calculate the optimal medication dosage, medication time nodes are determined, and diet suggestions are generated.

Description

Technical Field

[0001] This invention relates to the fields of medical health and artificial intelligence technology, specifically to an AI-powered reminder method for patients undergoing gastroenterology colonoscopy to take laxatives. Background Technology

[0002] In modern clinical medicine, particularly in the field of gastroenterology, colonoscopy plays an indispensable role as a core diagnostic and screening technique for the early detection, diagnosis, and treatment monitoring of various diseases, including colorectal polyps, inflammatory bowel disease, and colorectal cancer. The diagnostic accuracy of colonoscopy largely depends on the quality of bowel preparation before the procedure. A thorough and clean bowel environment is essential for endoscopists to clearly and comprehensively observe the entire colonic mucosa, thereby identifying minute lesions. Inadequate bowel preparation not only leads to missed diagnoses and increased medical risks but can also prolong the examination time, exacerbate patient discomfort, and even require rescheduled examinations. This undoubtedly increases the patient's financial burden and psychological stress, and wastes limited medical resources. Therefore, ensuring that patients complete high-quality bowel preparation is a crucial step in improving the level of colonoscopy diagnosis and treatment.

[0003] Currently, medical staff provide verbal education to patients during outpatient or inpatient visits, supplemented by a pre-printed instruction manual. The manual details the name of the laxative used, the method of administration, the timing of administration, dietary requirements for several days prior to the examination, and possible normal reactions.

[0004] However, the traditional approach treats bowel preparation as a uniform, linear process applicable to everyone, neglecting the complexity of individual patients and the dynamic changes that occur during the preparation process. Patients vary significantly in age, weight, underlying diseases (such as diabetes, renal insufficiency, and a history of constipation), daily medication use, and lifestyle, all of which directly affect the metabolism, efficacy, and safety of laxatives. Standardized instructions cannot provide differentiated, optimal dosages, administration times, or hydration strategies for elderly patients with diabetes and healthy young men, potentially leading to over- or under-preparation in some patients, and even increasing the risk of adverse events.

[0005] Furthermore, paper instructions present a complex task involving dozens of hours and multiple steps (such as dietary control, divided doses, adequate water intake, and monitoring bowel movements) to patients all at once in static text form. This can easily cause cognitive overload, leading to misunderstandings, forgetting, or errors in execution regarding key time points, dosages, or operational details. This method of information delivery inherently lacks process management capabilities, failing to break down complex procedures into easily executable single instructions triggered at specific times, thus significantly increasing patient compliance issues. Moreover, this model completely lacks an effective dynamic feedback and intervention loop. Bowel preparation is a physiological response process during which various unforeseen circumstances may occur, such as severe nausea, vomiting, abdominal pain after medication, or delayed bowel movements failing to reach the standard of clear, watery stools. When these dynamic changes occur, static instructions cannot provide any real-time guidance, often leaving patients anxious, making their own judgments, or passively interrupting the process, resulting in preparation failure. Furthermore, healthcare personnel cannot obtain information about the patient's preparation outside the hospital, nor can they intervene to adjust the plan at critical moments. Summary of the Invention

[0006] (a) Technical problems to be solved

[0007] To address the shortcomings of existing technologies, this invention provides an AI-powered reminder method for patients undergoing gastroenterology colonoscopy to take laxatives, thus solving the problem of "low reminder efficiency in existing technologies" mentioned above.

[0008] (II) Technical Solution

[0009] To achieve the above objectives, the present invention provides the following technical solution: an AI-powered reminder method for patients undergoing colonoscopy in gastroenterology to take laxatives, comprising the following steps:

[0010] S1: Guide patients to the AI ​​interactive interface via QR code or mini-program entry;

[0011] S2: Generate personalized medication plans based on basic information and real-time data input by patients;

[0012] S3: Ensures patients complete the bowel preparation process through phased guidance and real-time reminders;

[0013] S4: Identify abnormal reactions based on real-time feedback data input by the patient and adjust subsequent operation suggestions accordingly;

[0014] S5: Screen for potential drug interactions and provide safe medication tips through an integrated drug database;

[0015] S6: Use animated demonstrations and picture illustrations to enhance patient understanding and cooperation.

[0016] Preferably, the basic information includes the patient's age, weight, underlying diseases, daily medication, and lifestyle characteristics, and the real-time data includes the patient's physical reaction after taking the medication, bowel movements, and water intake records.

[0017] Preferably, the QR code or mini-program supports multiple language options to meet the usage needs of patients in different countries.

[0018] Preferably, the steps in S2 include:

[0019] S201: Collect the patient's basic information and calculate the optimal medication dosage using a preset algorithm;

[0020] S202: Determine the timing of medication based on the patient's daily routine;

[0021] S203: Generate dietary control recommendations for the days leading up to the examination based on the patient's dietary habits.

[0022] Preferably, the specific steps in S3 include:

[0023] S301: Divide the entire bowel preparation process into multiple stages, with independent operation instructions set for each stage;

[0024] S302: Guide patients to complete the tasks of the current stage through timed push reminders;

[0025] S303: After each stage is completed, the operation command for the next stage is automatically triggered.

[0026] Preferably, the specific steps in S3 include:

[0027] S301: Divide the entire bowel preparation process into multiple stages, with independent operation instructions set for each stage;

[0028] S302: Guide patients to complete the tasks of the current stage through timed push reminders;

[0029] S303: After each stage is completed, the operation command for the next stage is automatically triggered.

[0030] Preferably, the specific steps in S5 include:

[0031] S501: Invoke the integrated drug database to match potential interactions between patients’ daily medications and laxatives;

[0032] S502: If a potential interaction is found, alert the patient and advise them to consult a doctor;

[0033] S503: For patients with contraindications, directly inform them that the current laxative regimen is not suitable.

[0034] Preferably, the specific implementation of S6 includes:

[0035] S601: Design an animated demonstration of the working principle of the gut to visually show the gut cleansing process;

[0036] S602: Provide images of bowel cleansing results that meet the requirements to help patients assess their own readiness;

[0037] S603: Explain complex operating procedures using a combination of concise text and icons.

[0038] Preferably, the interactive interface of the QR code or mini-program adopts a modular design, including a personal information input module, a medication plan generation module, and a real-time feedback module, and stores the patient's historical data in the cloud so that medical staff can view and analyze the patient's preparation progress outside the hospital.

[0039] (III) Beneficial Effects

[0040] This invention provides an AI-based reminder method for patients undergoing colonoscopy in gastroenterology to take laxatives. It features the following:

[0041] Beneficial effects:

[0042] (1) This invention collects personalized data such as patient age, weight, underlying diseases, daily medications, and lifestyle habits through a personal information entry module. The medication plan generation module then calls a preset algorithm to calculate the optimal medication dosage, determine the medication timing, and generate dietary recommendations. Compared to traditional standardized paper instructions that ignore individual differences, this invention can provide differentiated medication dosages, timing, and hydration strategies for different patients, avoiding over- or under-preparation, reducing the risk of adverse events, and ensuring the quality of bowel preparation.

[0043] (2) This invention divides the complex bowel preparation process into multiple stages, each with independent operating instructions. Timed reminders guide patients through the steps, replacing the cognitive overload caused by the static, one-time presentation of static text in traditional paper instructions. Simultaneously, the combination of animated demonstrations, illustrative images, and text-icon explanations enhances patients' understanding of key points and operational details, reducing misunderstandings, forgetting, or errors, effectively lowering compliance barriers, and ensuring patients complete the preparation process step-by-step.

[0044] (3) This invention receives data such as the patient's physical reaction and bowel movements after medication through a real-time feedback module. The abnormal reaction identification mechanism can promptly identify abnormalities and push adjustment suggestions. The drug database can screen for drug interactions and issue warnings. Compared with the traditional model, which lacks dynamic feedback and intervention and medical staff cannot grasp the situation of outpatient preparation, this method realizes dynamic monitoring of the bowel preparation process. When patients experience abnormalities, they can receive real-time guidance. Medical staff can also understand the patient's progress through cloud-stored data and intervene to adjust the plan at critical moments, reducing the risk of preparation failure and ensuring patient safety. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0046] Figure 2 This is a schematic diagram of the process for generating a personalized medication plan in step S2 of the present invention;

[0047] Figure 3 This is a schematic diagram of the S3 phased guidance and real-time reminder process of the present invention;

[0048] Figure 4 This is a schematic diagram of the abnormal reaction identification and adjustment process of the present invention (S4).

[0049] Figure 5 This is a schematic diagram of the drug interaction screening process S5 of the present invention;

[0050] Figure 6 This is a schematic diagram illustrating the animation and image description process of the present invention, S6. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Please see Figure 1 - Figure 6 This invention provides an AI-powered reminder method for patients undergoing colonoscopy in gastroenterology to take laxatives, comprising the following steps:

[0053] S1: Patients first access the AI ​​interactive interface by scanning a QR code or opening a mini-program. The interface employs a modular system design, including a personal information input module, a medication plan generation module, and a real-time feedback module. The personal information input module collects basic information such as the patient's age, weight, underlying diseases (e.g., diabetes, renal insufficiency, constipation history), daily medication history, and lifestyle characteristics. The medication plan generation module calculates the optimal medication dosage using a preset algorithm and determines the medication timing based on the patient's lifestyle characteristics. The real-time feedback module receives real-time data input by the patient, such as post-medication physical reactions, bowel movements, and fluid intake records.

[0054] S2: After the patient completes basic information entry, the personal information entry module transmits the collected data to the medication plan generation module. The medication plan generation module then uses an internal preset algorithm for analysis and processing. First, it calculates the optimal medication dosage based on the patient's weight and underlying medical conditions. Second, it determines the medication timing based on the patient's lifestyle characteristics, such as work hours and sleep patterns. Finally, it generates dietary control recommendations for the days leading up to the examination based on the patient's eating habits. For example, for patients with a history of constipation, the system will recommend increasing dietary fiber intake and reducing the intake of fatty foods two days before the examination. These operations are all completed step-by-step through the sub-functions of the medication plan generation module, ensuring that the generated medication plan is both scientific and targeted.

[0055] S3: After generating a personalized medication plan, the system enters a phased guidance and real-time reminder stage. The entire bowel preparation process is divided into multiple stages, each with independent operation instructions. Stage 1 corresponds to the dietary adjustment tasks for the three days prior to the check, requiring the patient to avoid high-fiber and dark-colored foods; Stage 2 corresponds to the medication administration tasks for the day before the check, requiring the patient to take laxatives at the set times; Stage 3 corresponds to the fasting and bowel cleansing tasks for the day of the check, requiring the patient to take the last laxative within the specified time and remain in a fasting state. The system guides the patient to complete the tasks of the current stage through a timed push reminder function. For example, during the execution of the Stage 2 operation instructions, the system will send a reminder notification to the patient 30 minutes before each medication dose. After each stage is completed, the system automatically triggers the operation instructions for the next stage, thereby ensuring that the patient can complete the complex bowel preparation process step by step.

[0056] S4: To ensure patient safety and adherence, the system also includes an abnormal reaction detection mechanism. When patients input real-time feedback data such as nausea, vomiting, abdominal pain, or dehydration symptoms through the real-time feedback module, the system will call a preset rule base to determine if an abnormal reaction exists. If an abnormal reaction is detected, the system will immediately push adjustment suggestions to the patient. For example, for patients experiencing severe nausea and vomiting, the system will suggest reducing the single dose or extending the dosing interval; for patients experiencing dehydration symptoms, the system will prompt them to replenish fluids and closely monitor their physical condition.

[0057] S5: In addition, the system integrates a drug database to screen for potential drug interactions. When a potential interaction exists between a patient's daily medication and a laxative, the system will issue a warning and advise the patient to consult a doctor. For patients with contraindications, the system will directly indicate that the current laxative regimen is not suitable and recommend alternatives.

[0058] S6: Features animated demonstrations and image illustrations to help patients intuitively understand the importance of bowel preparation by dynamically showcasing the bowel cleansing process. It also includes textual and icon-based explanations of operation steps, using a combination of concise text and icons to explain complex procedures. For example, when explaining how to correctly take laxatives, the system will use textual descriptions along with appropriate icons to clearly display the required timing, dosage, and fluid intake.

[0059] To further optimize the user experience, this invention also supports cloud storage and smart device data upload functions. Patient historical data is stored in the cloud, allowing medical staff to view and analyze the patient's preparation progress outside the hospital through the backend. Simultaneously, the system supports patients automatically uploading real-time data, such as heart rate, body temperature, and fluid intake, via devices like smart bracelets. This data not only helps medical staff monitor the patient's preparation status in real time but also provides a reference for subsequent diagnosis and treatment.

[0060] In actual operation, the personal information entry module is responsible for collecting the patient's basic information and transmitting it to the medication plan generation module; the medication plan generation module generates a personalized medication plan based on the received data and assigns tasks to each stage through phased guidance and real-time reminder functions; the real-time feedback module is responsible for receiving the patient's real-time data and feeding it back to the abnormal reaction identification mechanism and drug interaction screening function to ensure that the patient receives comprehensive support and guidance throughout the entire bowel preparation process.

[0061] As can be seen from the above specific implementation methods, this invention achieves full-process management of the patient's bowel preparation process through modular design and intelligent functions. From basic information entry to personalized medication plan generation, and then to phased guidance and real-time reminders, it ensures that patients can smoothly complete the complex bowel preparation process. At the same time, the abnormal reaction identification mechanism and drug interaction screening function effectively reduce the risks caused by adverse reactions or combined medications, ensuring patient safety. The animation demonstration and picture explanation functions further enhance patient understanding and cooperation, improving the overall preparation effect.

[0062] To enable those skilled in the art to fully understand and implement this invention, the following supplementary explanation of the specific implementation principle and operation process of this invention is provided in conjunction with a specific application scenario.

[0063] After scanning a QR code or opening a mini-program to access the AI ​​interactive interface, patients first complete the basic information entry in the personal information input module. Specifically, patients need to input data such as age, weight, underlying diseases (e.g., diabetes, renal insufficiency, constipation history), daily medication use, and lifestyle characteristics. For example, a 65-year-old patient with diabetes and a history of constipation who takes hypoglycemic drugs and goes to bed late will have this information entered into the system. The personal information input module transmits the collected data to the medication plan generation module, which uses an internal preset algorithm for analysis. This algorithm calculates the optimal medication dosage based on the patient's weight and underlying disease status, while also considering the patient's lifestyle characteristics to determine the timing of medication administration. For example, for this elderly patient, the system will adjust the laxative dosage based on their weight and diabetes status and recommend taking the medication two hours after dinner to avoid blood sugar fluctuations. In addition, considering their constipation history, the system will also generate dietary control recommendations, requiring the patient to increase dietary fiber intake and reduce the intake of fatty foods two days before the examination. The above operations are completed one by one through the sub-functions in the medication plan generation module, ensuring that the generated medication plan is both scientific and targeted.

[0064] After the personalized medication plan is generated, the system enters a phased guidance and real-time reminder stage. The entire bowel preparation process is divided into multiple stages, each with independent operational instructions. For example, in stage one, the system instructs the patient to avoid high-fiber and dark-colored foods for three days prior to the examination. At this time, the system sends a reminder notification to the patient at a fixed time each day, such as prompting the patient to choose low-fiber foods before breakfast, along with a picture of a recommended menu. In stage two, the system instructs the patient to take laxatives at set times. For example, for the elderly patient mentioned above, the system sends a reminder notification minutes before medication and dynamically demonstrates how to correctly take the laxatives using animation, including the timing, dosage, and fluid intake requirements. In stage three, the system instructs the patient to take the last laxative on the day of the examination and maintain an empty stomach. At this point, the system guides the patient through the current stage's tasks using timed reminders and automatically triggers the next stage's instructions upon completion of each stage, ensuring the patient can complete the complex bowel preparation process step by step.

[0065] To ensure patient safety and adherence, the system incorporates an adverse reaction detection mechanism. When patients input their physical reaction data through the real-time feedback module, the system invokes a pre-defined rule base to determine if any adverse reactions exist. For example, if a patient experiences severe nausea and vomiting after taking medication, the system immediately analyzes the feedback data and provides adjustment suggestions, such as reducing the single dose or extending the dosing interval. Furthermore, the system integrates a drug database to screen for potential drug interactions. For instance, for the elderly patient mentioned above, the system matches potential interactions between their daily hypoglycemic medication and laxative, issuing a warning prompting the patient to consult a doctor. If the patient has contraindications, the system directly indicates that the current laxative regimen is unsuitable and recommends alternatives. This adverse reaction detection mechanism and drug interaction screening function effectively reduce the risks associated with adverse reactions or combined medication use, ensuring patient safety.

[0066] To enhance patient understanding and cooperation, the system offers animated demonstrations and illustrative images, dynamically showcasing the bowel preparation process to help patients intuitively understand its importance. For example, animations simulate the mechanism of laxatives in the intestines, demonstrating how they promote bowel movements to remove residue. The system also includes textual and icon-based explanations of the procedures, using a combination of concise text and icons to explain complex steps. For instance, when explaining how to correctly take laxatives, the system uses textual descriptions accompanied by appropriate icons to clearly show the required timing, dosage, and fluid intake. This multi-faceted information delivery significantly improves patient understanding and cooperation.

[0067] To further optimize the user experience, the system supports cloud storage and data upload from smart devices. For example, patients' historical data is stored in the cloud, allowing healthcare professionals to view and analyze their preparation progress outside the hospital. Simultaneously, the system supports patients automatically uploading real-time data, such as heart rate, body temperature, and fluid intake, via devices like smart bracelets. For instance, when a patient wears a smart bracelet, the system automatically records their fluid intake and uploads it to the cloud. This data not only helps healthcare professionals monitor patients' preparation in real time but also provides a reference for subsequent diagnosis and treatment. Furthermore, the system dynamically adjusts medication regimens based on data uploaded from smart devices. For example, if a patient's heart rate rises abnormally, the system will send a warning notification and suggest suspending medication.

[0068] In actual operation, the personal information input module collects basic patient information and transmits it to the medication plan generation module. The medication plan generation module generates personalized medication plans based on the received data and assigns tasks to each stage through phased guidance and real-time reminders. The real-time feedback module receives real-time patient data and feeds it back to the abnormal reaction identification mechanism and drug interaction screening function. For example, when a patient inputs bowel movement data, the real-time feedback module transmits the data to the abnormal reaction identification mechanism, and the system determines whether subsequent operational suggestions need adjustment based on a preset rule base. This modular design enables the system to operate efficiently, ensuring that patients receive comprehensive support and guidance throughout the entire bowel preparation process.

[0069] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An AI-powered reminder method for patients undergoing colonoscopy in gastroenterology to take laxatives, characterized in that, Includes the following steps: S1: Guide patients to the AI ​​interactive interface via QR code or mini-program entry; S2: Generate personalized medication plans based on basic information and real-time data input by patients; S3: Ensures patients complete the bowel preparation process through phased guidance and real-time reminders; S4: Identify abnormal reactions based on real-time feedback data input by the patient and adjust subsequent operation suggestions accordingly; S5: Screen for potential drug interactions and provide safe medication tips through an integrated drug database; S6: Use animated demonstrations and picture illustrations to enhance patient understanding and cooperation.

2. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives, as described in claim 1, is characterized in that: The basic information includes the patient's age, weight, underlying diseases, daily medication, and lifestyle characteristics. The real-time data includes the patient's physical reaction after taking medication, bowel movements, and water intake records.

3. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives, as described in claim 1, is characterized in that: The QR code or mini-program supports multiple language options to meet the usage needs of patients in different countries.

4. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives, as described in claim 1, is characterized in that: The steps in S2 include: S201: Collect the patient's basic information and calculate the optimal medication dosage using a preset algorithm; S202: Determine the timing of medication based on the patient's daily routine; S203: Generate dietary control recommendations for the days leading up to the examination based on the patient's dietary habits.

5. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives according to claim 1, characterized in that: The specific steps in S3 include: S301: Divide the entire bowel preparation process into multiple stages, with independent operation instructions set for each stage; S302: Guide patients to complete the tasks of the current stage through timed push reminders; S303: After each stage is completed, the operation command for the next stage is automatically triggered.

6. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives according to claim 1, characterized in that: The specific steps in S4 include: S401: Receives real-time feedback data input by the patient, including symptoms of nausea, vomiting, abdominal pain, and dehydration; S402: Determine if there is an abnormal response by using a preset rule base; S403: If an abnormal reaction occurs, an adjustment suggestion will be sent to the patient.

7. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives according to claim 1, characterized in that: The specific steps in S5 include: S501: Invoke the integrated drug database to match potential interactions between patients’ daily medications and laxatives; S502: If a potential interaction is found, alert the patient and advise them to consult a doctor; S503: For patients with contraindications, directly inform them that the current laxative regimen is not suitable.

8. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives according to claim 1, characterized in that: The specific implementation methods of S6 include: S601: Design an animated demonstration of the working principle of the gut to visually show the gut cleansing process; S602: Provide images of bowel cleansing results that meet the requirements to help patients assess their own readiness; S603: Explain complex operating procedures using a combination of concise text and icons.

9. The AI-based reminder method for patients undergoing gastroenterology colonoscopy to take laxatives according to claim 1, characterized in that: The interactive interface of the QR code or mini-program adopts a modular design, including a personal information input module, a medication plan generation module, and a real-time feedback module. It also stores the patient's historical data in the cloud so that medical staff can view and analyze the patient's preparation progress outside the hospital.

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