Intelligent hospital outpatient registration and registration information management system
By analyzing patients' symptoms and age groups' habitual consultation times through an intelligent management system, special patients can be identified and prioritized. This solves the problems of resource waste and excessively long waiting times in traditional registration methods, achieving efficient use of medical resources and improving the patient's medical experience.
Patent Information
- Application Number
- CN202410811837.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-21
- Publication Date
- 2026-02-24
AI Technical Summary
Traditional hospital outpatient registration and check-in methods cannot effectively handle the differences in the severity and complexity of patients' conditions in different consultation rooms, resulting in uneven consultation times, affecting doctors' efficiency and patients' waiting time. Furthermore, they cannot quickly identify and prioritize patients with urgent or serious conditions, which may lead to a waste of medical resources and increased costs.
The hospital adopts an intelligent outpatient registration and check-in information management system. By analyzing patients' disease types and age groups and their habitual consultation duration, the system identifies patient identity types and flexibly sorts and calls patients according to different types, ensuring priority treatment for special patients and rational allocation of medical resources.
It has improved the efficiency of medical resource utilization, reduced patient waiting time, ensured timely medical treatment for emergency and special patients, and enhanced the overall efficiency of medical services and patient satisfaction.
Smart Images
Figure CN121565403A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of outpatient registration and check-in management technology, and relates to an intelligent hospital outpatient registration and check-in information management system. Background Technology
[0002] Hospital outpatient registration and check-in are two crucial steps in the patient's medical process. Patients gain eligibility for treatment through outpatient registration. After registration, patients need to follow the instructions to the corresponding floor's treatment area for check-in. After check-in, patients can wait in the waiting area and follow the prompts on the display screen or voice system for their treatment. Hospital outpatient registration and check-in directly determine the smooth and efficient operation of the hospital's outpatient department; therefore, intelligent management of hospital outpatient registration and check-in information is of great significance.
[0003] Traditional outpatient registration methods typically use a fixed number of registrations based on different consultation rooms. This method does not take into account the differences in the severity and complexity of patients' conditions in each consultation room, which may lead to deviations in actual consultation time. This may result in long remaining consultation time or excessively long consultation time. When consultation time is too long, it can affect the doctor's work efficiency, cause patients to wait for longer, reduce patient satisfaction, and lead to a waste of medical resources.
[0004] Traditional departmental check-in and queuing systems typically follow a first-come, first-served basis. This system ignores the actual needs of special circumstances. Traditional queuing methods cannot quickly identify and prioritize patients with urgent or serious conditions, which can lead to these patients not receiving timely treatment. If special patients miss the optimal treatment window due to excessive waiting times, the hospital may need to invest more medical resources in subsequent treatment and care, increasing medical costs and lacking flexibility. Summary of the Invention
[0005] In view of this, in order to solve the problems mentioned in the background technology, an intelligent hospital outpatient registration and check-in information management system is proposed.
[0006] The objective of this invention can be achieved through the following technical solution: an intelligent hospital outpatient registration and check-in information management system, comprising: a patient registration module, used to extract the medical information of patients who have already obtained a number at the current time, specifically including the type of illness and the patient's age, and then retrieve the hospital's historical medical records and analyze the habitual medical time for each age group corresponding to each type of illness, thereby determining whether to allow the patient to obtain a number, and if so, issuing a number and recording it as the current patient, and obtaining the registration type, specifically including initial consultation number and follow-up consultation number.
[0007] The department check-in confirmation module is used to check in when the current patient arrives at the department entrance.
[0008] The patient identity classification module is used to identify the current patient's identity type based on the current patient's medical information and check-in information. The identity type is normal patient and special patient, where special patients specifically include elderly patients, patients who missed their appointment, and patients returning for follow-up visits.
[0009] The normal patient sorting module is used to sort patients who are identified as normal patients according to their arrival time.
[0010] The special patient sorting module is used to further identify patients as special cases, and to perform different priority analyses for different categories of special patients. This analysis then sorts the special patients according to their priority and their medical treatment.
[0011] The follow-up patient adjustment module is used to extract the initial consultation room corresponding to the initial consultation record of the follow-up patient, and then determine whether there is any remaining consultation time in the corresponding consultation room. If so, the follow-up patient is arranged to the corresponding consultation room, and special consultation order is adjusted for special patients in the consultation room.
[0012] The appointment sorting display module is used to display the normal appointment sorting and special appointment sorting separately on the display screen.
[0013] The queuing method analysis module is used to extract the number of normal patients and special patients from the display screen, and then analyze the patient distribution and the queuing method based on the patient distribution.
[0014] A data repository is used to store patients' historical missed appointment records and hospital's historical consultation records.
[0015] In a preferred embodiment of the present invention, the analysis of the habitual consultation time for each disease type corresponding to each age group is specifically as follows: retrieve the hospital's historical consultation records and obtain the patient's disease type and patient age corresponding to each historical consultation record, then compare the historical consultation records, and classify the historical consultation records corresponding to the same disease type to obtain a number of historical consultation records corresponding to each disease type.
[0016] By comparing the historical medical records corresponding to each disease type, the historical medical records corresponding to the same age are categorized to obtain the historical medical records for each disease type and each age.
[0017] Extract the historical consultation duration corresponding to each disease type and age group from the historical consultation records. Then, compare the historical consultation durations of each disease type and age group, categorize the same historical consultation durations to obtain the number of historical consultation records corresponding to each consultation duration, and then compare the number of historical consultation records corresponding to each consultation duration. Select the consultation duration corresponding to the largest number of historical consultation records as the habitual consultation duration for that disease type and age group.
[0018] In a preferred embodiment of the present invention, the step of determining whether a patient is allowed to obtain a number is as follows: based on the current patient's disease type, determine the department that needs to be registered and record it as the target department, and record patients who have obtained numbers in the target department but have not yet visited the doctor as patients waiting to be seen.
[0019] Extract the age-appropriate consultation duration for each disease type in the target department, and match the age of patients waiting to be seen in the target department to obtain the age-appropriate consultation duration for each patient waiting to be seen in the target department.
[0020] After extraction and sorting, the patient appointment order displayed on the screen is used to obtain the consultation room corresponding to each patient. The consultation rooms corresponding to each patient are then classified according to the same consultation room to obtain the patients corresponding to each consultation room.
[0021] The expected total consultation time for each consultation room is obtained by summing up the habitual consultation times of patients waiting for consultation in each consultation room.
[0022] The closing time is obtained based on the outpatient opening hours. The difference between the closing time and the current time is used to calculate the remaining consultation time for each clinic. Then, the difference between the remaining consultation time for each clinic and the total expected consultation time for each clinic is used to calculate the available time for each clinic.
[0023] The available time in each clinic was compared, and the maximum available time was selected as the monitoring time.
[0024] The monitoring duration is compared with the preset valid consultation duration. When the monitoring duration is greater than or equal to the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is allowed to take the number. When the monitoring duration is less than the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is not allowed to take the number.
[0025] In a preferred embodiment of the present invention, the step of identifying the current patient's identity type is as follows: extract the patient's age based on the current patient's medical information, and then compare the current patient's age with a preset age threshold. If the current patient's age is greater than or equal to the age threshold, the current patient is determined to be an elderly patient; if the current patient's age is less than the age threshold, the current patient is determined not to be an elderly patient.
[0026] Extract the registration type of the current patient. If the registration type of the current patient is a follow-up visit, then determine that the current patient is a follow-up visit patient.
[0027] Based on the current patient's reported information, the frequency of the current patient's check-in within the current working day is extracted. If the patient's check-in frequency is more than once, it is further determined whether the patient went for a medical visit after the last check-in. If the patient did not go for a medical visit, the patient is determined to be a missed appointment patient.
[0028] If the current patient does not fall into any of the categories of elderly patient, missed appointment, or follow-up patient, the current patient is judged to be a normal patient.
[0029] In a preferred embodiment of the present invention, the analysis of different priority situations specifically includes the analysis of the priority index for missed appointments, the priority index for the elderly, and the priority index for follow-up visits. If the current patient is a patient who missed their appointment, the specific steps of the analysis of the priority index for missed appointments are as follows: extract the calling time and the current time of the patient who missed their appointment, and then calculate the difference between the current time and the calling time to obtain the missed appointment duration of the patient who missed their appointment.
[0030] Extract the historical missed appointment records of patients who missed their appointments, then count the number of such records to obtain the patient's historical missed appointment frequency, and calculate the average of the missed appointment durations for each historical missed appointment record to obtain the patient's habitual missed appointment duration.
[0031] Substitute the missed appointment time T, the historical missed appointment frequency X0, and the habitual missed appointment time T0 of the patient into the formula. Obtain the current patient's priority index λ for missed appointments. 过号 , where t0 represents the hospital's operating hours, α1 and α2 represent the weights corresponding to the time spent missing appointments and the time spent missing appointments due to habit, respectively, and e represents the natural constant.
[0032] In a preferred embodiment of the present invention, the step of performing the elderly priority index analysis is as follows: Substitute the patient's age N into the formula. Obtain the current patient's priority index for elderly patients (λ) 高龄 , where N0 represents the pre-set age threshold.
[0033] In a preferred embodiment of the present invention, the step of performing the follow-up visit priority index analysis is as follows: Substitute the interval JT between the follow-up visit and the previous visit into the analysis formula. Obtain the current patient's priority index for follow-up visits λ 复诊 , where JT0 represents the pre-set reference follow-up visit duration.
[0034] In a preferred embodiment of the present invention, the step of analyzing patient priority is as follows: The current patient's missed appointment priority index λ is... 过号 Priority Index for the Elderly (λ) 高龄 and the priority index for follow-up visits λ 复诊 Substituting into the formula λ=β1*λ 过号 +β2*λ 高龄 +β3*λ 复诊 The priority λ for special patients is obtained, where β1, β2, and β3 represent the weights of the priority index for missed appointments, the priority index for the elderly, and the priority index for follow-up visits, respectively, and β1+β2+β3=1.
[0035] In a preferred embodiment of the present invention, the determination of whether there is remaining consultation time in the corresponding consultation room is as follows: the consultation room where the follow-up patient first visited is recorded as the target consultation room, the available time corresponding to the target consultation room is extracted, and then the available time corresponding to the target consultation room is compared with the preset effective consultation time. When the available time is greater than or equal to the preset effective remaining consultation time, it is determined that there is remaining consultation time. When the available time is less than the preset effective remaining consultation time, it is determined that there is no remaining consultation time.
[0036] In a preferred embodiment of the present invention, the analysis of the queuing method is as follows: the ratio of the number of patients seeking normal medical treatment to the number of patients seeking special medical treatment is calculated to obtain the patient distribution ratio at the current moment.
[0037] The patient distribution index is calculated by rounding up to obtain the monitored patient distribution index, and then the calling method is determined based on the monitored patient distribution index.
[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention analyzes the habitual consultation time of each disease type corresponding to each age group and then identifies the consultation time required by the patient at that time, and then determines whether the patient is allowed to register. This analysis method can more accurately predict the patient's consultation time, avoid the waste of resources or the patient's long waiting time caused by a fixed number of registrations, ensure the maximum utilization of medical resources, reduce unnecessary waiting time, and flexibly adjust the registration and consultation strategy according to the patient's actual needs and consultation situation to ensure the timeliness and effectiveness of medical services.
[0039] (2) This invention further identifies registered patients and divides them into normal patients and special patients. Different calling methods are used for different types of patients, and intermittent calling is carried out. This analysis method enables special patients to be given priority, reducing their waiting time and improving their medical experience. At the same time, by identifying special patients and giving them priority, the hospital can ensure that these patients who need more attention and time receive timely service, thereby improving the overall efficiency of medical services. Attached Figure Description
[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0041] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention. Detailed Implementation
[0042] 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.
[0043] Please see Figure 1 As shown, this invention provides an intelligent hospital outpatient registration and check-in information management system. The system includes a patient registration module, a department check-in confirmation module, a patient identity classification module, a normal patient sorting module, a special patient sorting module, a follow-up patient adjustment module, a check-in ranking display module, a call number analysis module, and a data storage module. The patient registration module is connected to the department check-in confirmation module, which is connected to the patient identity classification module. The patient identity classification module is connected to both the normal patient sorting module and the special patient sorting module. The special patient sorting module is connected to the follow-up patient adjustment module. Both the normal patient sorting module and the follow-up patient adjustment module are connected to the check-in ranking display module. The check-in ranking display module is connected to the call number analysis module. The data storage module is connected to both the patient registration module and the special patient sorting module.
[0044] The patient registration module is used to extract the consultation information of patients who have already obtained a number at the current time, specifically including the type of illness and the patient's age. It then retrieves the hospital's historical consultation records and analyzes the habitual consultation time for each age group corresponding to each type of illness. Based on this, it determines whether to allow the patient waiting to obtain a number to take a number. If allowed, a number is issued and recorded as the current patient, and the registration type is obtained. The registration type specifically includes initial consultation number and follow-up consultation number.
[0045] For example, the types of illnesses include skin diseases and stomach diseases, with different types of illnesses corresponding to different departments. Skin diseases correspond to the dermatology department, and stomach diseases correspond to the gastroenterology department.
[0046] Preferably, the hospital's historical medical records are retrieved to obtain the patient's disease type and age corresponding to each historical medical record. Then, the historical medical records are compared, and the historical medical records corresponding to the same disease type are categorized to obtain a number of historical medical records corresponding to each disease type.
[0047] By comparing the historical medical records corresponding to each disease type, the historical medical records corresponding to the same age are categorized to obtain the historical medical records for each disease type and each age.
[0048] Extract the historical consultation duration corresponding to each disease type and age group from the historical consultation records. Then, compare the historical consultation durations of each disease type and age group, categorize the same historical consultation durations to obtain the number of historical consultation records corresponding to each consultation duration, and then compare the number of historical consultation records corresponding to each consultation duration. Select the consultation duration corresponding to the largest number of historical consultation records as the habitual consultation duration for that disease type and age group.
[0049] It should be noted that the consultation duration corresponding to the largest number of historical consultation records is selected as the habitual consultation duration for this disease type and age group because the largest number indicates that the consultation duration is frequently observed for the corresponding disease type, which, under certain circumstances, reflects the complexity and difficulty of consultation for this disease type.
[0050] More preferably, the department that needs to be registered for is determined based on the type of illness of the current patient and recorded as the target department, and patients who have obtained a number for the target department but have not yet visited the doctor are recorded as patients waiting for treatment.
[0051] Extract the age-appropriate consultation duration for each disease type in the target department, and match the age of patients waiting to be seen in the target department to obtain the age-appropriate consultation duration for each patient waiting to be seen in the target department.
[0052] After extraction and sorting, the patient appointment order displayed on the screen is used to obtain the consultation room corresponding to each patient. The consultation rooms corresponding to each patient are then classified according to the same consultation room to obtain the patients corresponding to each consultation room.
[0053] The expected total consultation time for each consultation room is obtained by summing up the habitual consultation times of patients waiting for consultation in each consultation room.
[0054] The closing time is obtained based on the outpatient opening hours. The difference between the closing time and the current time is used to calculate the remaining consultation time for each clinic. Then, the difference between the remaining consultation time for each clinic and the total expected consultation time for each clinic is used to calculate the available time for each clinic.
[0055] The available time in each clinic was compared, and the maximum available time was selected as the monitoring time.
[0056] It should be explained that the maximum available time is selected as the monitoring time because the patient can be scheduled for registration as long as there is available time in any consultation room of the department where the patient is currently registering.
[0057] The monitoring duration is compared with the preset valid consultation duration. When the monitoring duration is greater than or equal to the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is allowed to take the number. When the monitoring duration is less than the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is not allowed to take the number.
[0058] It should be noted that this invention analyzes the habitual consultation time of different age groups for different types of diseases to identify the required consultation time for patients at that time, and then determines whether to allow the patient to register. This analysis method can more accurately predict the patient's consultation time, avoid the waste of resources or long waiting times caused by a fixed number of registrations, ensure the maximum utilization of medical resources, reduce unnecessary waiting time, and flexibly adjust registration and consultation strategies according to the patient's actual needs and consultation situation to ensure the timeliness and effectiveness of medical services.
[0059] For example, the preset effective consultation time is 10 minutes.
[0060] It should be noted that the reason for setting an effective consultation time is to avoid the time being too short to meet the basic consultation needs, so as to reduce overtime.
[0061] The department check-in confirmation module is used to check in when the current patient arrives at the department entrance.
[0062] It should be noted that the reason for checking in and confirming at the entrance of each department before sorting is to avoid some patients not arriving at the department in time after getting their number, resulting in missed appointments.
[0063] The patient identity classification module is used to identify the current patient's identity type based on the current patient's medical information and check-in information. The identity type is normal patient and special patient, where special patients specifically include elderly patients, patients who missed their appointment, and patients returning for follow-up visits.
[0064] It should be noted that the reasons for selecting elderly patients, patients who missed their appointments, and patients returning for follow-up visits as special cases are as follows: 1. Elderly patients often have multiple chronic diseases that interact with each other, complicating their health conditions. They may face psychological problems such as loneliness and anxiety, requiring more psychological support and care from medical staff; 2. Patients who missed their appointments may have missed their scheduled time for various reasons. They usually hope to receive medical treatment as soon as possible to save time and prevent their condition from worsening. Missing their appointments may cause them anxiety and unease; 3. Patients returning for follow-up visits may experience psychological problems such as frustration and anxiety due to long-term illness.
[0065] Preferably, the patient's age is extracted based on the current patient's medical information, and then the current patient's age is compared with a preset age threshold. If the current patient's age is greater than or equal to the age threshold, the current patient is determined to be an elderly patient; if the current patient's age is less than the age threshold, the current patient is determined not to be an elderly patient.
[0066] For example, the age threshold is 80 years old.
[0067] Extract the registration type of the current patient. If the registration type of the current patient is a follow-up visit, then determine that the current patient is a follow-up visit patient.
[0068] Based on the current patient's reported information, the frequency of the current patient's check-in within the current working day is extracted. If the patient's check-in frequency is more than once, it is further determined whether the patient went for a medical visit after the last check-in. If the patient did not go for a medical visit, the patient is determined to be a missed appointment patient.
[0069] It should be noted that if the number of check-ins is more than once, and no medical visit was performed after the last check-in, it indicates that the patient missed their appointment after the last check-in.
[0070] If the current patient does not fall into any of the categories of elderly patient, missed appointment, or follow-up patient, the current patient is judged to be a normal patient.
[0071] The normal patient sorting module is used to sort patients who are identified as normal according to their arrival time.
[0072] The special patient sorting module is used to further identify special patients, and to perform different priority analyses for different categories of special patients, thereby analyzing the priority of special patients' visits and sorting them according to the order of their priority.
[0073] Preferably, when the current patient is a patient who missed their number among special patients, the patient's call time and current time are extracted, and then the difference between the current time and the call time is calculated to obtain the missed time of the patient.
[0074] It should be noted that the calling time refers to the time when the doctor calls the number after the patient who missed their turn last reported for duty.
[0075] Extract the historical missed appointment records of patients who missed their appointments, then count the number of such records to obtain the patient's historical missed appointment frequency, and calculate the average of the missed appointment durations for each historical missed appointment record to obtain the patient's habitual missed appointment duration.
[0076] Substitute the missed appointment time T, the historical missed appointment frequency X0, and the habitual missed appointment time T0 of the patient into the formula. Obtain the current patient's priority index λ for missed appointments. 过号 , where t0 represents the hospital's operating hours, α1 and α2 represent the weights corresponding to the time spent missing appointments and the time spent missing appointments due to habit, respectively, and e represents the natural constant.
[0077] It should be added that α1 + α2 = 1.
[0078] For example, α1 = 0.6 and α2 = 0.4.
[0079] It should be noted that the reasons for selecting the duration of missed appointments, the frequency of missed appointments in the past, and the duration of missed appointments in the past as factors influencing the priority index of missed appointments for current patients are as follows: by reducing the priority of missed appointments for patients with longer durations of missed appointments, the frequency of missed appointments in the past, and the duration of missed appointments in the past, we can guide patients to pay more attention to the accuracy of their appointment time and reduce unnecessary missed appointments. This helps to improve the overall order and efficiency of medical services and create a better medical environment for patients.
[0080] Preferably, if the current patient is an elderly patient among special patients, the patient's age N is substituted into the formula. Obtain the current patient's priority index for elderly patients (λ) 高龄 , where N0 represents the pre-set age threshold.
[0081] Preferably, if the current patient is a follow-up patient among special patients, the interval JT between the follow-up visit and the last visit is substituted into the analysis formula. Obtain the current patient's priority index for follow-up visits λ 复诊 , where JT0 represents the pre-set reference follow-up visit duration.
[0082] For example, the recommended follow-up visit duration is 3 days.
[0083] More preferably, the current patient's priority index λ is used to prioritize past appointments. 过号 Priority Index for the Elderly (λ) 高龄 and the priority index for follow-up visits λ 复诊 Substituting into the formula λ=β1*λ 过号 +β2*λ 高龄 +β3*λ 复诊 The priority λ for special patients is obtained, where β1, β2, and β3 represent the weights of the priority index for missed appointments, the priority index for the elderly, and the priority index for follow-up visits, respectively, and β1+β2+β3=1.
[0084] For example, β1 = 0.2, β2 = 0.6, and β3 = 0.2.
[0085] It should be noted that the current patient may be one or more of the following special patients: elderly patients, repeat patients, or patients who missed their appointment. Therefore, it is necessary to comprehensively analyze the priority of special patients.
[0086] The follow-up patient adjustment module is used to extract the initial consultation room corresponding to the initial consultation record of the follow-up patient, and then determine whether there is any remaining consultation time in the corresponding consultation room. If so, the follow-up patient is arranged to the corresponding consultation room, and special consultation order is adjusted for special patients in the consultation room.
[0087] It should be added that if there is no remaining consultation time in the corresponding clinic, the returning patient will be treated as a special patient and prioritized and ranked accordingly.
[0088] Preferably, the consultation room where the follow-up patient first visited is recorded as the target consultation room. The available time corresponding to the target consultation room is extracted, and then the available time corresponding to the target consultation room is compared with the pre-set effective consultation time. When the available time is greater than or equal to the pre-set effective remaining consultation time, it is determined that there is remaining consultation time. When the available time is less than the pre-set effective remaining consultation time, it is determined that there is no remaining consultation time.
[0089] It should be noted that the reason for arranging follow-up patients in the initial consultation room is to ensure the consistency and continuity of the correction and improve the efficiency of the consultation.
[0090] The appointment sorting display module is used to display the normal appointment sorting and the special appointment sorting separately on the display screen.
[0091] The queuing method analysis module is used to extract the number of normal patients and special patients from the display screen, and then analyze the patient distribution and the queuing method based on the patient distribution.
[0092] Preferably, the patient distribution ratio at the current moment is calculated by comparing the number of patients seeking normal medical care with the number of patients seeking special medical care.
[0093] The patient distribution index is calculated by rounding up to obtain the monitored patient distribution index, and then the calling method is determined based on the monitored patient distribution index.
[0094] For example, if the current patient distribution ratio is 2:1, the calling method is 2 initial consultation numbers and 1 special number.
[0095] It should be noted that this invention further identifies registered patients, categorizing them into normal and special patients. Different call-up methods are then used for different patient types, employing an intermittent calling system. This approach prioritizes special patients, reducing their waiting time and improving their overall experience. Furthermore, by identifying and prioritizing special patients, hospitals can ensure that those requiring more attention and time receive timely service, thereby enhancing the overall efficiency of healthcare services.
[0096] The data repository is used to store patients' historical missed appointment records and hospital historical consultation records.
[0097] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.
Claims
1. An intelligent hospital outpatient registration and check-in information management system, characterized in that, include: The patient registration module is used to extract the consultation information of patients who have already obtained a number at the current time, including the type of illness and the patient's age. Then, it retrieves the hospital's historical consultation records and analyzes the habitual consultation time for each age group corresponding to each type of illness. Based on this, it determines whether to allow the patient to obtain a number. If allowed, a number is issued and recorded as the current patient, and the registration type is obtained. The registration type specifically includes initial consultation number and follow-up consultation number. The department check-in confirmation module is used to check in when the current patient arrives at the department entrance; The patient identity classification module is used to identify the current patient's identity type based on the current patient's medical information and check-in information. The identity type is normal patient and special patient, where special patients specifically include elderly patients, patients who missed their appointment, and patients returning for a follow-up visit. The normal patient sorting module is used to sort patients who are identified as normal patients according to their check-in time. The special patient sorting module is used to further identify patients as special patients, and to perform different priority analyses for different categories of special patients. It then analyzes the priority of special patients' medical treatment and sorts them according to the order of priority. The follow-up patient adjustment module is used to extract the initial consultation room corresponding to the initial consultation record of the follow-up patient, and then determine whether there is any remaining consultation time in the corresponding consultation room. If so, the follow-up patient is arranged to the corresponding consultation room, and special consultation order is adjusted for special patients in the consultation room. The patient appointment sorting display module is used to display the normal patient appointment sorting and the special patient appointment sorting separately on the display screen; The queuing method analysis module is used to extract the number of normal patients and special patients from the display screen, and then analyze the patient distribution and the queuing method based on the patient distribution. A data repository is used to store patients' historical missed appointment records and hospital's historical consultation records.
2. The intelligent hospital outpatient registration and check-in information management system as described in claim 1, characterized in that: The analysis of the typical consultation times for each disease type and age group is as follows: The hospital retrieves historical medical records and obtains the patient's disease type and age corresponding to each historical medical record. Then, the historical medical records are compared, and the historical medical records corresponding to the same disease type are classified to obtain a number of historical medical records corresponding to each disease type. By comparing the historical medical records corresponding to each disease type, the historical medical records corresponding to the same age are categorized to obtain the historical medical records for each disease type and each age. Extract the historical consultation duration corresponding to each disease type and age group from the historical consultation records. Then, compare the historical consultation durations of each disease type and age group, categorize the same historical consultation durations to obtain the number of historical consultation records corresponding to each consultation duration, and then compare the number of historical consultation records corresponding to each consultation duration. Select the consultation duration corresponding to the largest number of historical consultation records as the habitual consultation duration for that disease type and age group.
3. The intelligent hospital outpatient registration and check-in information management system as described in claim 2, characterized in that: The steps for determining whether a patient is allowed to take a number are as follows: Based on the type of illness of the current patient, determine the department that needs to be registered and record it as the target department. Record patients who have obtained a number for the target department but have not yet visited the doctor as patients waiting for treatment. Extract the age-appropriate consultation duration for each disease type in the target department, and match the age of patients waiting to be seen in the target department to obtain the age-appropriate consultation duration for each patient waiting to be seen in the target department; After extraction and sorting, the patient appointment order displayed on the screen is used to obtain the consultation room corresponding to each patient. The consultation rooms corresponding to each patient are then classified according to the same consultation room to obtain the patients corresponding to each consultation room. The closing time is obtained based on the outpatient opening hours, and the difference between the closing time and the current time is calculated to obtain the remaining consultation time of the clinic. Then, the difference between the remaining consultation time of the clinic and the expected total consultation time of each clinic is calculated to obtain the available time of each clinic. The available time in each clinic was compared, and the maximum available time was selected as the monitoring time. The monitoring duration is compared with the preset valid consultation duration. When the monitoring duration is greater than or equal to the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is allowed to take the number. When the monitoring duration is less than the preset valid remaining consultation duration, it is determined that the patient waiting to take a number is not allowed to take the number.
4. The intelligent hospital outpatient registration and check-in information management system as described in claim 1, characterized in that: The steps for identifying the current patient's identity type are as follows: The patient's age is extracted based on the current patient's medical information, and then compared with a pre-set age threshold. If the current patient's age is greater than or equal to the age threshold, the current patient is determined to be an elderly patient; if the current patient's age is less than the age threshold, the current patient is determined not to be an elderly patient. Extract the current patient's registration type. If the current patient's registration type is a follow-up visit, determine that the current patient is a follow-up visit patient. Based on the current patient's reporting information, the frequency of the current patient's check-in within this working day is extracted. When the patient's check-in frequency is more than once, it is further determined whether the patient has sought medical treatment after the last check-in. If the patient has not sought medical treatment, the patient is determined to be a missed appointment patient. If the current patient does not fall into any of the categories of elderly patient, missed appointment, or follow-up patient, the current patient is judged to be a normal patient.
5. The intelligent hospital outpatient registration and check-in information management system as described in claim 4, characterized in that: The analysis of different priority situations specifically includes the analysis of missed appointment priority index, elderly priority index, and follow-up appointment priority index. If the current patient is a missed appointment patient, the specific steps for performing the missed appointment priority index analysis are as follows: Extract the calling time and current time of patients who missed their turn, and then calculate the time missed by the difference between the current time and the calling time. Extract the historical missed appointment records of patients who missed their appointments, then count the number of such records to obtain the patient's historical missed appointment frequency, and calculate the average of the missed appointment durations for each historical missed appointment record to obtain the patient's habitual missed appointment duration. Substitute the missed appointment time T, the historical missed appointment frequency X0, and the habitual missed appointment time T0 of the patient into the formula. Obtain the current patient's priority index λ for missed appointments. 过号 , where t0 represents the hospital's operating hours, α1 and α2 represent the weights corresponding to the time spent missing appointments and the time spent missing appointments due to habit, respectively, and e represents the natural constant.
6. The intelligent hospital outpatient registration and check-in information management system as described in claim 5, characterized in that: If the current patient is an elderly patient, the steps for performing the elderly priority index analysis are as follows: Substitute the patient's age N for the elderly patient into the formula. Obtain the current patient's priority index for elderly patients (λ) 高龄 , where N0 represents the pre-set age threshold.
7. The intelligent hospital outpatient registration and check-in information management system as described in claim 6, characterized in that: If the current patient is a follow-up visit patient, the steps for performing the follow-up visit priority index analysis are as follows: Substitute the interval JT between the follow-up visit and the previous visit into the analysis formula. Obtain the current patient's priority index for follow-up visits (λ) 复诊 , where JT0 represents the pre-set reference follow-up visit duration.
8. The intelligent hospital outpatient registration and check-in information management system as described in claim 7, characterized in that: The steps for analyzing patient priority in medical visits are as follows: The current patient's priority index λ 过号 Priority Index for the Elderly (λ) 高龄 and the priority index for follow-up visits λ 复诊 Substituting into the formula λ=β1*λ 过号 +β2*λ 高龄 +β3*λ 复诊 The priority λ for special patients is obtained, where β1, β2, and β3 represent the weights of the priority index for missed appointments, the priority index for the elderly, and the priority index for follow-up visits, respectively, and β1+β2+β3=1.
9. The intelligent hospital outpatient registration and check-in information management system as described in claim 4, characterized in that: The specific steps for determining whether there is remaining consultation time in the corresponding consultation room are as follows: The clinic where the returning patient first visited is recorded as the target clinic. The available time corresponding to the target clinic is extracted. Then, the available time corresponding to the target clinic is compared with the pre-set effective consultation time. If the available time is greater than or equal to the pre-set effective remaining consultation time, it is determined that there is remaining consultation time. If the available time is less than the pre-set effective remaining consultation time, it is determined that there is no remaining consultation time.
10. The intelligent hospital outpatient registration and check-in information management system as described in claim 4, characterized in that: The specific analysis and queuing method is as follows: The ratio of the number of patients seeking normal medical care to the number of patients seeking special medical care is used to calculate the patient distribution ratio at the current moment; The patient distribution index is calculated by rounding up to obtain the monitored patient distribution index, and then the calling method is determined based on the monitored patient distribution index.