An information sharing system and method suitable for use in medical services

Abstract

The application discloses an information sharing system and method suitable for medical services, relates to the technical field of information sharing, and solves the technical problem that the medical services cannot predict the registration services and cannot share information according to the prediction results when the medical services are executed in the prior art, specifically, a registration service prediction unit analyzes the registration services of a medical service area, obtains a registration service prediction risk coefficient of the current medical service area through data collection and analysis, generates a registration prediction high-risk signal or a registration prediction low-risk signal according to the coefficient comparison, and sends the signal to a real-time sharing unit, which makes a sharing decision after receiving the signal; and a queuing condition prediction unit analyzes and predicts the queuing conditions of various clinics in the medical service area, generates a queuing high-risk signal or a queuing low-risk signal through analysis and prediction, and sends the signal to the real-time sharing unit, which makes a sharing decision after receiving the signal.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information sharing, in particular to an information sharing system and method suitable for medical services. BACKGROUND

[0002] Medical services refer to health promotion services provided by health technicians in accordance with professional technical specifications, such as care for life, diagnosis and treatment of diseases, and services such as medicines, medical devices, rescue transportation, and hospital accommodation provided to achieve these services; care for life mainly refers to the care and escort of the natural process of life from conception to death, such as prenatal care, childbirth support, hospice care, and preventive care; diagnosis and treatment of diseases mainly refers to the process of identifying the human body after being damaged by the cause, and adjusting the functional disorder or damage that occurs to improve function and restore health.

[0003] However, in the prior art, the medical service cannot predict the registration service when it is executed, cannot share information according to the prediction result, and cannot share information through real-time data analysis. In addition, the current medical service area cannot be predicted for payment service, and cannot be shared and controlled in a targeted manner.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The purpose of the present application is to solve the above-mentioned problems, and to provide an information sharing system and method suitable for medical services.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] An information sharing system suitable for medical services, comprising a service information sharing platform, the service information sharing platform being communicatively connected with:

[0008] A registration service prediction unit for analyzing the registration service of the medical service area, obtaining the registration service prediction risk coefficient of the current medical service area through data collection and analysis, generating a registration prediction high-risk signal or a registration prediction low-risk signal according to the coefficient comparison, and sending it to the real-time sharing unit, which makes a sharing decision after receiving it;

[0009] A queuing condition prediction unit for analyzing and predicting the queuing condition of each clinic in the medical service area, generating a queuing high-risk signal or a queuing low-risk signal, and sending it to the real-time sharing unit, which makes a sharing decision after receiving it;

[0010] The payment service prediction unit is configured to predict the payment service of the current medical service area, generate a payment normal operation signal, a complex planning signal and a simple planning signal through payment service prediction, and send the signals to the real-time sharing unit, which makes a sharing decision after receiving the signals.

[0011] As a preferred embodiment of the present application, the operation process of the registration service prediction unit is as follows:

[0012] The average increase speed of the interval between the start time of the registration period and the actual check-in time in the current medical service area is obtained, and the peak increase speed of the delay time between the end time of the registration period and the actual check-in time in the current medical service area is obtained; the numerical ratio of the reduction speed of the number of registered patients and the reduction speed of the actual number of patients in the current medical service area is obtained; the registration service prediction risk coefficient of the current medical service area is obtained by analysis; and the registration service prediction risk coefficient of the current medical service area is compared with the prediction risk coefficient threshold.

[0013] As a preferred embodiment of the present application, if the registration service prediction risk coefficient of the current medical service area exceeds the prediction risk coefficient threshold, a registration prediction high-risk signal is generated and sent to the real-time sharing unit; if the registration service prediction risk coefficient of the current medical service area does not exceed the prediction risk coefficient threshold, a registration prediction low-risk signal is generated and sent to the real-time sharing unit.

[0014] As a preferred embodiment of the present application, after the real-time sharing unit receives the registration prediction high-risk signal, if the number of registration service demand does not exceed the set threshold, the current medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department; the registration easing area and the shared department are sent to the service information sharing platform; otherwise, if the number of registration service demand exceeds the set threshold, the current medical service area is set as a registration tight area, and the corresponding registration department is set as a shared department; after the real-time sharing unit receives the registration prediction low-risk signal, if the registration surplus exceeds the set threshold, the corresponding medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department; if the registration surplus does not exceed the set threshold, the corresponding medical service area is set as a registration tight area, and the corresponding registration department is set as a shared department.

[0015] As a preferred embodiment of the present application, the operation process of the queuing status prediction unit is as follows:

[0016] The value deviation of the current medical service area is obtained, and the constant mean difference between the queue reduction speed and the queue increase speed under the current cumulative floating deviation is also obtained.

[0017] As a preferred embodiment of the present application, if the value deviation of the current medical service area is greater than the cumulative floating value deviation threshold, or the constant mean difference between the queue reduction speed and the queue increase speed under the current cumulative floating deviation is greater than the constant mean difference threshold, a queue high-risk signal is generated and sent to the real-time sharing unit.

[0018] If the value deviation of the current medical service area is less than the cumulative floating value deviation threshold, and the constant mean difference between the queue reduction speed and the queue increase speed under the current cumulative floating deviation is less than the constant mean difference threshold, a queue low-risk signal is generated and sent to the real-time sharing unit.

[0019] As a preferred embodiment of the present application, after the real-time sharing unit receives the queue high-risk signal, if the same type of medical service department in the current medical service area is a shared department, the same type of medical service department in the current medical service area is sorted and placed last when the number of shared departments is not unique, and the sharing decision is made according to the number of medical service departments in the current medical service area during the sharing process.

[0020] After the real-time sharing unit receives the queue low-risk signal, if the same type of medical service department in the current medical service area is a shared department, the same type of medical service department in the current medical service area is shared preferentially, and the number of registration settings is increased on the next medical service day.

[0021] As a preferred embodiment of the present application, the operation process of the payment service prediction unit is as follows:

[0022] Obtain the probability that the actual time taken to complete complex payment procedures exceeds the set time in the current medical service area and the probability that the actual time taken to complete simple payment procedures exceeds the set time, and the corresponding probability value increase span. At the same time, obtain the numerical ratio of the average increase rate of the time taken to complete complex payment procedures in the current medical service area to the increase rate of the peak value of the time taken to complete simple payment procedures exceeding the set time, and compare them with the probability increase span threshold range and the increase rate value ratio threshold range respectively;

[0023] If the probability that the actual time taken to handle complicated payment procedures in the current medical service area exceeds the set time and the probability that the actual time taken to handle simple payment procedures exceeds the set time correspond to the probability value increase span within the probability increase span threshold range, and the ratio of the increase rate of the average time taken to handle complicated payment procedures in the current medical service area to the increase rate of the simple payment procedures exceeding the set peak time is within the increase rate value ratio threshold range, a normal payment operation signal is generated and sent to the real-time sharing unit. After receiving the normal payment operation signal, the real-time sharing unit will not perform payment division in the current medical service area.

[0024] As a preferred embodiment of the present invention, if the probability that the actual time consumption for complex payment procedures in the current medical service area exceeds the set time consumption and the probability that the actual time consumption for simple payment procedures exceeds the set time consumption corresponds to a probability value increase span that exceeds the probability increase span threshold range, or the ratio of the increase rate of the average time consumption for complex payment procedures in the current medical service area to the increase rate of the simple payment procedures exceeding the set time consumption peak is in the increase rate value ratio threshold range and exceeds the increase rate value ratio threshold range, a complex planning signal is generated and sent to the real-time sharing unit. After receiving the complex planning signal, the real-time sharing unit divides the medical service area into payment windows and sets different windows for complex payment procedures and simple payment procedures. The complex payment window after setting will not handle simple payment procedures. On the contrary, complex payment procedures can be handled when there is no queue at the window where simple payment procedures are set.

[0025] As a preferred embodiment of the present application, if the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span that does not exceed a probability increase span threshold range, or the numerical ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak value is in an increase speed numerical ratio threshold range that does not exceed the increase speed numerical ratio threshold range, a simple planning signal is generated and sent to the real-time sharing unit. After the real-time sharing unit receives the simple planning signal, the medical service area is divided into payment windows, and the complex payment procedure and the simple payment procedure are set in different windows, and the simple payment procedure window after setting does not perform the complex payment procedure. On the contrary, when there is no one in the window of the complex payment procedure, the simple payment procedure can be performed.

[0026] An information sharing method suitable for medical services, the information sharing method steps are as follows:

[0027] Step one, the registration service prediction unit analyzes the registration service of the medical service area, obtains the registration service prediction risk coefficient of the current medical service area through data collection and analysis, generates a registration prediction high-risk signal or a registration prediction low-risk signal according to the coefficient comparison, and sends it to the real-time sharing unit.

[0028] Step two, the queuing condition prediction unit analyzes and predicts the queuing condition of each clinic in the medical service area, generates a queuing high-risk signal or a queuing low-risk signal through analysis and prediction, and sends it to the real-time sharing unit.

[0029] Step three, the payment service prediction unit predicts the payment service of the current medical service area, generates a payment normal operation signal, a complex planning signal and a simple planning signal through payment service prediction, and sends them to the real-time sharing unit.

[0030] Compared with the prior art, the present application has the following advantages:

[0031] 1. In the present invention, the registration service analysis is carried out on the medical service area, and the registration tension in the current medical service area is judged based on the registration service prediction, so as to facilitate timely information sharing, avoid inaccurate registration prediction and failure to guide patients in time, resulting in the current medical service area's registration supply efficiency being unable to maintain the optimal state, and reducing the impact of time difference in sharing medical service information; the queuing status of each clinic in the medical service area is analyzed and predicted, and the department registration sharing is adjusted in real time based on the real-time clinic queuing status analysis, to avoid the current clinic's fluctuating medical demand causing the clinic's medical efficiency to be unable to reach the best, resulting in uneven distribution and utilization of medical resources in each medical service area, reducing the information sharing efficiency of the medical service area, and making it impossible to control the impact of information difference in advance.

[0032] 2. In the present invention, payment service prediction is performed for the current medical service area, and analysis is performed based on the real-time payment demand and payment type of the medical service area to determine whether the payment of the medical service area in the current period needs to be categorized, thereby minimizing the average payment time and preventing patients with simple payment processes from taking too long to pay, thereby reducing the efficiency of payment services. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0034] Figure 1 This is a system principle block diagram of the present invention;

[0035] Figure 2 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0037] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] Example 1

[0039] The embodiment carries out information sharing analysis on multiple medical service areas, please refer to Figure 1 As shown in the figure, an information sharing system suitable for medical services includes a service information sharing platform, which is communicatively connected with a registration service prediction unit, a queuing condition prediction unit, a payment service prediction unit, and a real-time sharing unit.

[0040] The service information sharing platform generates a registration service prediction signal and sends it to the registration service prediction unit. After receiving the registration service prediction signal, the registration service prediction unit analyzes the registration service of the medical service area and determines whether the registration tension of the current medical service area is abnormal according to the registration service prediction, so as to timely share information and avoid inaccurate registration prediction and timely patient guidance, which causes the registration supply efficiency of the current medical service area to be unable to maintain the optimal state, and reduces the sharing time difference of medical service information.

[0041] The average increase speed of the interval between the start time of the registration period and the actual check-in time of the registration in the current medical service area is obtained, and the peak increase speed of the delay time between the end time of the registration period and the actual check-in time of the registration in the current medical service area is obtained. The average increase speed of the interval between the start time of the registration period and the actual check-in time of the registration in the current medical service area is marked as JZS, and the peak increase speed of the delay time between the end time of the registration period and the actual check-in time of the registration in the current medical service area is marked as TGS.

[0042] The numerical ratio of the reduction speed of the number of registered and the actual number of visits in the current medical service area is obtained, and the numerical ratio of the reduction speed of the number of registered and the actual number of visits in the current medical service area is marked as SDB.

[0043] The formula is The registration service prediction risk coefficient G of the current medical service area is obtained, wherein fq1, fq2 and fq3 are respectively the preset proportional coefficients of the average increase speed of the interval, the peak increase speed of the delay time and the numerical ratio of the reduction speed, and β is an error correction factor, and the value is 0.98.

[0044] The registration service prediction risk coefficient of the current medical service area is compared with the prediction risk coefficient threshold value:

[0045] If the predicted risk coefficient of the current medical service area exceeds the predicted risk coefficient threshold, it is determined that the risk of the current medical service area is high, and a high-risk signal of the predicted registration is generated and sent to the real-time sharing unit; after the real-time sharing unit receives the high-risk signal of the predicted registration, the registration capacity of the medical service area is monitored, and the tension degree of the registration service is evaluated in combination with the actual number of patients, such as the number of patients who need registration service does not exceed the set threshold, the current medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department, and the registration easing area and the shared department are sent to the service information sharing platform; otherwise, the number of patients who need registration service exceeds the set threshold, and the current medical service area is set as a registration tense area, and the corresponding registration department is set as a shared department;

[0046] If the predicted risk coefficient of the current medical service area does not exceed the predicted risk coefficient threshold, it is determined that the risk of the current medical service area is low, and a low-risk signal of the predicted registration is generated and sent to the real-time sharing unit; after the real-time sharing unit receives the low-risk signal of the predicted registration, the type of the medical service area is divided according to the monitoring result of the registration capacity, if the registration capacity exceeds the set threshold, the corresponding medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department; if the registration capacity does not exceed the set threshold, the corresponding medical service area is set as a registration tense area, and the corresponding registration department is set as a shared department;

[0047] After the predicted registration service is completed, a predicted queuing condition signal is generated and sent to a predicted queuing condition unit, the predicted queuing condition unit receives the predicted queuing condition signal, analyzes and predicts the queuing condition of each clinic in the medical service area, and performs real-time control of the department registration sharing according to the real-time clinic queuing condition analysis, so as to avoid the fluctuation of the current clinic demand, improve the clinic efficiency, and avoid the unbalanced allocation of medical resources in each medical service area, thereby improving the information sharing efficiency of the medical service area and avoiding the influence of information difference.

[0048] The value deviation of the current medical service area is obtained, the constant mean difference between the queuing number reduction speed and the queuing number increase speed under the current cumulative floating deviation is collected, and the value deviation of the current medical service area is compared with the cumulative floating value deviation threshold and the constant mean difference threshold.

[0049] If the value deviation of the reciprocating cumulative float corresponding to the queue reduction speed of the clinic in the current medical service area exceeds the cumulative float value deviation threshold, or the constant mean difference between the constant mean of the queue reduction speed and the queue increase speed of the clinic under the cumulative float deviation does not exceed the constant mean difference threshold, it is determined that the clinic registration service sharing analysis risk of the current medical service area is high, a queue high risk signal is generated and sent to the real-time sharing unit, and the real-time sharing unit receives the queue high risk signal. After receiving the queue high risk signal, the corresponding medical service area is controlled for sharing. If the same type of medical department of the current medical service area is a shared department, the same type of medical department of the current medical service area is sorted and placed last when the number of same type of shared departments is not unique, and the sharing decision is made according to the number of medical departments of the same type of medical department of the current medical service area during the sharing process. When the difference between the number of medical departments and the current demand is too large, the sharing decision is stopped; otherwise, the sharing decision continues; if the same type of medical department of the current medical service area is a shared department, the same type of medical department of the current medical service area is matched preferentially during the current sharing process, and the number of registration settings of the same type of medical department of the current medical service area is reduced;

[0050] If the value deviation of the reciprocating cumulative float corresponding to the queue reduction speed of the clinic in the current medical service area does not exceed the cumulative float value deviation threshold, and the constant mean difference between the constant mean of the queue reduction speed and the queue increase speed of the clinic under the cumulative float deviation exceeds the constant mean difference threshold, it is determined that the clinic registration service sharing analysis risk of the current medical service area is low, a queue low risk signal is generated and sent to the real-time sharing unit, and the real-time sharing unit receives the queue low risk signal. After receiving the queue low risk signal, the corresponding medical service area is controlled for sharing. If the same type of medical department of the current medical service area is a shared department, the same type of medical department of the current medical service area is preferentially shared, and the number of registration settings is increased on the next medical service day; if the same type of medical department of the current medical service area is a shared department, the same type of medical department of the current medical service area is shared, and the number of registration settings is increased on the next medical service day;

[0051] Embodiment two

[0052] The embodiment analyzes information sharing of a single medical service area, generates a payment service prediction signal after completing the queue status prediction, and sends the payment service prediction signal to a payment service prediction unit. After receiving the payment service prediction signal, the payment service prediction unit predicts the payment service of the current medical service area, analyzes the real-time payment demand and payment type of the medical service area, and determines whether the payment of the medical service area needs to be classified in the current period, thereby minimizing the average payment time, preventing the payment time of patients with simple payment process from being too long, and reducing the efficiency of payment service;

[0053] The probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption are obtained, and the corresponding probability value increase span is obtained. The ratio of the increase speed of the average time consumption of the complex payment procedure in the current medical service area to the increase speed of the peak value of the simple payment procedure exceeding the set time consumption is obtained, and the probability value increase span corresponding to the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption is compared with the probability increase span threshold range and the increase speed ratio threshold range, respectively. The complex payment procedure refers to multiple payment items such as examination fees, hospitalization fees, and reimbursement fees, and vice versa, the simple payment procedure refers to only one payment item.

[0054] If the probability value increase span corresponding to the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption is in the probability increase span threshold range, and the ratio of the increase speed of the average time consumption of the complex payment procedure in the current medical service area to the increase speed of the peak value of the simple payment procedure exceeding the set time consumption is in the increase speed ratio threshold range, it is determined that the payment service prediction of the current medical service area is reasonable, a normal payment operation signal is generated and sent to the real-time sharing unit. After receiving the normal payment operation signal, the real-time sharing unit does not divide the payment of the current medical service area.

[0055] If the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span that exceeds the probability increase span threshold range, or the numerical ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak value is in the increase speed numerical ratio threshold range that exceeds the increase speed numerical ratio threshold range, it is determined that the complex payment procedure service in the medical service area is predicted to be abnormal, a complex planning signal is generated and sent to the real-time sharing unit, and after the real-time sharing unit receives the complex planning signal, the medical service area is divided into payment windows and the complex payment procedure and the simple payment procedure are set in different windows, and the complex payment procedure window after setting does not perform the simple payment procedure, and vice versa, when there is no queuing personnel in the simple payment procedure window, the complex payment procedure can be performed.

[0056] If the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span that does not exceed the probability increase span threshold range, or the numerical ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak value is in the increase speed numerical ratio threshold range that does not exceed the increase speed numerical ratio threshold range, it is determined that the simple payment procedure service in the medical service area is predicted to be abnormal, a simple planning signal is generated and sent to the real-time sharing unit, and after the real-time sharing unit receives the simple planning signal, the medical service area is divided into payment windows and the complex payment procedure and the simple payment procedure are set in different windows, and the simple payment procedure window after setting does not perform the complex payment procedure, and vice versa, when there is no queuing personnel in the complex payment procedure window, the simple payment procedure can be performed.

[0057] Embodiment three

[0058] Please refer to Figure 2 An information sharing method suitable for medical services is shown in the figure, and the steps of the information sharing method are as follows:

[0059] Step one, the registration service prediction unit analyzes the registration service of the medical service area, obtains the registration service prediction risk coefficient of the current medical service area through data collection and analysis, generates a registration prediction high-risk signal or a registration prediction low-risk signal according to the coefficient comparison, and sends it to the real-time sharing unit;

[0060] Step two, the queuing status prediction unit analyzes and predicts the queuing status of each clinic in the medical service area, generates a queuing high-risk signal or a queuing low-risk signal through analysis and prediction, and sends it to the real-time sharing unit;

[0061] Step three, the payment service prediction unit predicts the payment service of the current medical service area, generates a payment normal operation signal, a complex planning signal and a simple planning signal through payment service prediction, and sends them to the real-time sharing unit;

[0062] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and the coefficients in the formula are set by the person skilled in the art according to the actual situation;

[0063] In use, the registration service prediction unit analyzes the registration service of the medical service area, obtains the registration service prediction risk coefficient of the current medical service area through data collection and analysis, generates a registration prediction high-risk signal or a registration prediction low-risk signal according to the coefficient comparison, and sends it to the real-time sharing unit. The real-time sharing unit receives and makes a shared decision; the queuing condition prediction unit analyzes and predicts the queuing condition of each clinic in the medical service area, generates a queuing high-risk signal or a queuing low-risk signal through analysis and prediction, and sends it to the real-time sharing unit. The real-time sharing unit receives and makes a shared decision; the payment service prediction unit predicts the payment service of the current medical service area, generates a payment normal operation signal, a complex planning signal and a simple planning signal through payment service prediction, and sends them to the real-time sharing unit. The real-time sharing unit receives and makes a shared decision.

[0064] The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and do not limit the application to the specific embodiments. Obviously, according to the content of the specification, many modifications and changes can be made. The specification selects and describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited only by the claims and their entire scope and equivalents.

Claims

1. An information sharing system for medical services, characterized by, The service information sharing platform is in communication connection with: The registration service prediction unit is configured to analyze the registration service of the medical service area, obtain a registration service prediction risk coefficient of the current medical service area through data collection and analysis, generate a registration prediction high-risk signal or a registration prediction low-risk signal according to the comparison of the coefficient, and send the signal to the real-time sharing unit, which performs sharing decision after receiving the signal; The queuing condition prediction unit is configured to analyze and predict the queuing condition of each clinic in the medical service area, generate a queuing high-risk signal or a queuing low-risk signal, and send the signal to the real-time sharing unit, which performs sharing decision after receiving the signal; The payment service prediction unit is configured to predict the payment service of the current medical service area, generate a payment normal operation signal, a complex planning signal and a simple planning signal through payment service prediction, and send the signals to the real-time sharing unit, which performs sharing decision after receiving the signals; The operation process of the registration service prediction unit is as follows: The average increase speed of the interval time length between the start time of the registration period and the actual check-in time of the registration in the current medical service area is obtained, and the peak increase speed of the delay time length between the end time of the registration period and the actual check-in time of the registration in the current medical service area is obtained; the numerical value ratio of the reduction speed of the number of registered patients and the reduction speed of the actual number of patients in the current medical service area is obtained; the registration service prediction risk coefficient of the current medical service area is obtained through analysis; and the registration service prediction risk coefficient of the current medical service area is compared with the prediction risk coefficient threshold value; The increase speed of the average interval time length between the start time of the registration period and the actual check-in time in the current medical service area, and the increase speed of the peak delay time length between the end time of the registration period and the actual check-in time in the current medical service area are respectively marked as JZS and TGS. The numerical ratio of the reduction speed of the number of registered patients and the reduction speed of the actual number of patients in the current medical service area is marked as SDB. The formula is as follows: The registration service prediction risk coefficient G of the current medical service area is obtained, wherein fq1, fq2 and fq3 are respectively preset proportional coefficients of the average interval time length increase speed, the peak delay time length increase speed and the numerical ratio of the reduction speed, and β is an error correction factor, and the value is 0.

98. If the registration service prediction risk coefficient of the current medical service area exceeds the prediction risk coefficient threshold value, a registration prediction high-risk signal is generated and sent to the real-time sharing unit; if the registration service prediction risk coefficient of the current medical service area does not exceed the prediction risk coefficient threshold value, a registration prediction low-risk signal is generated and sent to the real-time sharing unit; After the real-time sharing unit receives the registration prediction high-risk signal, if the number of registration service demand does not exceed the set threshold value, the current medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department; the registration easing area and the shared department are sent to the service information sharing platform; otherwise, if the number of registration service demand exceeds the set threshold value, the current medical service area is set as a registration tense area, and the corresponding registration department is set as a shared department; after the real-time sharing unit receives the registration prediction low-risk signal, if the registration surplus exceeds the set threshold value, the corresponding medical service area is set as a registration easing area, and the corresponding registration department is set as a shared department; if the registration surplus does not exceed the set threshold value, the corresponding medical service area is set as a registration tense area, and the corresponding registration department is set as a shared department.

2. The information sharing system for medical services according to claim 1, wherein The operation process of the queuing condition prediction unit is as follows: The value deviation of the reciprocating cumulative float corresponding to the queue reduction speed of the clinic in the current medical service area is obtained, and the constant mean difference between the queue reduction average speed and the queue increase average speed under the current cumulative float deviation is also obtained, and the two are compared with the cumulative float value deviation threshold and the constant mean difference threshold, respectively.

3. The information sharing system for medical services according to claim 2, wherein If the value deviation of the reciprocating cumulative float corresponding to the queue reduction speed of the clinic in the current medical service area exceeds the cumulative float value deviation threshold, or the constant mean difference between the queue reduction average speed and the queue increase average speed under the current cumulative float deviation does not exceed the constant mean difference threshold, a queue high-risk signal is generated and sent to the real-time sharing unit; If the value deviation of the reciprocating cumulative float corresponding to the queue reduction speed of the clinic in the current medical service area does not exceed the cumulative float value deviation threshold, and the constant mean difference between the queue reduction average speed and the queue increase average speed under the current cumulative float deviation exceeds the constant mean difference threshold, a queue low-risk signal is generated and sent to the real-time sharing unit.

4. The information sharing system for medical services according to claim 3, wherein After the real-time sharing unit receives the queue high-risk signal, if the same type of medical department in the current medical service area is a shared department, the same type of medical department in the current medical service area is placed at the end of the sorting when the number of the same type of shared departments is not unique, and the sharing decision is made according to the number of the same type of medical departments in the current medical service area during the sharing process; if the same type of medical department in the current medical service area is a shared department, the current shared department is matched preferentially during the sharing process, and the number of registrations for the same type of medical department in the current medical service area is reduced. After the real-time sharing unit receives the queue low-risk signal, if the same type of medical department in the current medical service area is a shared department, the same type of medical department in the current medical service area is preferentially shared, and the number of registrations is increased on the next medical service day; if the same type of medical department in the current medical service area is a shared department, the same type of medical department in the current medical service area is suspended, and the registration period is reasonably distributed on the next medical service day.

5. The information sharing system for medical services according to claim 1, wherein The operation process of the payment service prediction unit is as follows: The probability of the actual time consumption of complex payment procedures exceeding the set time consumption and the probability of the actual time consumption of simple payment procedures exceeding the set time consumption in the current medical service area are obtained, and the probability value increase span corresponding to the two probabilities is obtained, and the numerical value ratio of the increase speed of the time consumption of complex payment procedures and the increase speed of the peak value of the time consumption of simple payment procedures in the current medical service area is obtained, and the two are compared with the probability increase span threshold range and the increase speed numerical value ratio threshold range, respectively. If the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span within the probability increase span threshold range, and the value ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak is within the increase speed value ratio threshold range, a payment normal operation signal is generated and sent to the real-time sharing unit. After receiving the payment normal operation signal, the real-time sharing unit does not perform payment division in the current medical service area.

6. The information sharing system for medical services according to claim 5, wherein If the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span exceeding the probability increase span threshold range, or the value ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak is within the increase speed value ratio threshold range exceeding the increase speed value ratio threshold range, a complex planning signal is generated and sent to the real-time sharing unit. After receiving the complex planning signal, the real-time sharing unit divides the payment window of the medical service area and sets different windows for the complex payment procedure and the simple payment procedure, and the complex payment procedure window after setting does not perform simple payment procedure, and vice versa. When there is no queuing personnel in the simple payment procedure window, the complex payment procedure can be performed.

7. The information sharing system for medical services according to claim 6, wherein If the probability of the actual time consumption of the complex payment procedure in the current medical service area exceeding the set time consumption and the probability of the actual time consumption of the simple payment procedure exceeding the set time consumption correspond to a probability value increase span not exceeding the probability increase span threshold range, or the value ratio of the increase speed of the complex payment procedure time consumption in the current medical service area and the increase speed of the simple payment procedure exceeding the set time consumption peak is within the increase speed value ratio threshold range not exceeding the increase speed value ratio threshold range, a simple planning signal is generated and sent to the real-time sharing unit. After receiving the simple planning signal, the real-time sharing unit divides the payment window of the medical service area and sets different windows for the complex payment procedure and the simple payment procedure, and the simple payment procedure window after setting does not perform complex payment procedure, and vice versa. When there is no queuing personnel in the complex payment procedure window, the simple payment procedure can be performed.

8. An information sharing method suitable for medical services, characterized by, An information sharing system suitable for medical services according to any one of the preceding claims 1-7.

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