CN114239955A - Hospital outpatient waiting time prediction method and system - Google Patents

Hospital outpatient waiting time prediction method and system Download PDF

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CN114239955A
CN114239955A CN202111533484.2A CN202111533484A CN114239955A CN 114239955 A CN114239955 A CN 114239955A CN 202111533484 A CN202111533484 A CN 202111533484A CN 114239955 A CN114239955 A CN 114239955A
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武青松
张颖聪
马鸣
向璨
陈实
吴建才
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Tongji Medical College of Huazhong University of Science and Technology
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Abstract

The invention discloses a method and a system for predicting the waiting time of outpatient in hospital, which particularly relates to the technical field of medical treatment and comprises the following steps: acquiring a patient registration instruction; department data, data of relevant doctors for sitting and consulting, pre-examination data information of patients and diagnosis and treatment registration queue information are obtained. According to the invention, the information of the departments registered by the patients is collected, and finally, the waiting time of each patient is predicted and integrated by adopting a neural network prediction model in combination with the influence factors and the data, so that the waiting time of the corresponding patient and the time corresponding to diagnosis and treatment are judged, a feedback mechanism is adopted in the neural network prediction model, the actual diagnosis and treatment time of each patient in a waiting queue is continuously updated, the waiting time and the diagnosis and treatment time of subsequent patients are updated according to new waiting patient queue information, the waiting time of the patients can be more accurately judged, and the careless psychology of the patients in the waiting process is prevented from being appealed by the boring waiting process of the patients.

Description

Hospital outpatient waiting time prediction method and system
Technical Field
The invention relates to the technical field of medical treatment, in particular to a method and a system for predicting the waiting time of a patient in a hospital clinic.
Background
With the continuous improvement of the living standard and the medical standard of the public, the health consciousness of people is gradually changed, more and more people can pursue high-quality life and go to the outpatient clinic of a hospital for physical examination and treatment, and therefore the demand of the outpatient clinic is correspondingly improved. The outpatient service is the first link of the patient, especially the outpatient service, entering the hospital to see a doctor, is the necessary component element of the hospital, is the 'face' of the hospital, is the window unit of the hospital for receiving the patient, and patients with different disease conditions can see a doctor in each hospital every day. Patients waiting for treatment are therefore common in hospitals and clinics.
Under the traditional waiting system adopted by a general waiting room, only two ways are available for a patient to acquire the current waiting queuing information, namely, inquiring nurses at a nurse station and inquiring the nurses by the help of a computer; and secondly, the current waiting queue is obtained through a waiting room liquid crystal display and a voice reminding system. The waiting room liquid crystal display and the voice dialing device both acquire the queuing state of the current department in the server through the local area network. Then the display displays the current n pieces of information, generally only displays 5 pieces of information or less, namely n < ═ 5; the voice reminder system will call the patient information and number that is currently about to be seen.
The patient needs to pay attention when waiting for a visit: keeping self emotional stability. The patient who waits for a long time to see a doctor often feels restless and is easy to step on, guesses the state of illness of the patient, and is not good for the health of the patient. After the patients with light illness state can see the health education propaganda materials in the waiting hall after the number is arranged, more knowledge about diseases can be known, and the emotion can be stabilized. The running in disorder in each waiting area of the hospital after registration is avoided. The hospital is a place where various diseases are intersected and gathered, and the comprehensive hospital with good conditions has special waiting areas for various disease patients and no special waiting area, and various diseases are mixed, the resistance of the patients is low, and cross infection is easily caused. To prevent cross-infection, the race is not jumbled as much as possible to reduce the chance of infection. Waiting patients and escorters need to follow the system of hospitals, explain the moral, explain the sanitation, protect the property of hospitals and keep waiting rooms clean. The patient does not need to cry loud and cry, waits in a waiting room for a nurse to call the number, and then makes a diagnosis in sequence. Do not strive for queue breaks, do not spend state at the office doorway or yell out loud. This is not good for other patients and is not good for doctors to see. Since doctors must take medical examinations and auscultations in a quiet environment, the examination of patients also requires protection of the privacy of the patients. The patient runs disorderly and is easy to cause the problem that no one is called by nurses and the timely diagnosis and treatment are influenced after the nurses queue up. The physician can not select to see a doctor or force the physician to make various examinations, prescriptions or false cases in places where the hang-up clinic is not implemented. But the physician can be reminded to make a proof if a pathological condition is needed. In waiting, before doctors visit, patients need to follow the arrangement of triage nurses, and the outpatient triage nurses can prepare the patients before visiting, and mainly measure the body temperature, develop routine laboratory test orders, borrow X-ray films and the like. When special conditions or disease conditions change, the patient can contact with the out-patient nurse or the number-calling person, and the patient can see the doctor in advance after permission. When deaf-dumb, children, patients with inconvenient movement or serious illness go for a doctor, 1-2 family members, relatives or escorts can accompany the doctor to the doctor room to see a doctor, and other accompanying persons wait outside the doctor room.
A large number of patients visit the clinic every day, most of the patients enter the hospital clinic with anxiety and dysphoria, and a series of negative emotions are generated due to complex procedures, environment harmony, pain of diseases and the like in the long-time waiting process. The hospital outpatient nursing staff should accurately grasp the psychological activities of the patients and take necessary intervention measures for the negative emotion generated in the treatment process.
Negative emotional characteristics and causes of patients waiting for diagnosis
1.1 anxiety. The patient with sudden illness is under excessive stress due to unknown illness or complex and difficult to diagnose, and the patient with chronic illness is afflicted with the illness for a long time, is not cured or is aggravated or has no better treatment method after diagnosis, and the like, and all the factors can cause the patient to have anxiety, dysphoria and despair mood.
1.2 fear, due to the strangeness of the environment, the unfamiliarity to medical care personnel, and the affliction of diseases, the feelings of people are fragile, the dependence on the psychological enhancement is enhanced, and the fear psychology is easy to generate.
1.3 Depression. Due to the increase of the economic pressure of families caused by diseases, the suffering of the diseases makes people feel solitary and helpless, and all the diseases can cause people to have different depressive moods.
1.4 doubts. Distrust the nursing staff, suspects that the triage staff do not conduct triage in sequence, especially when the patients who have been treated return to the consulting room after the examination is finished, other patients suspects that they are in-line, and dissatisfaction is caused.
1.5 complain that the patient feels unappreciated because the medical staff is busy and has no time to take the psychological feelings of the patient. And impatience caused by long-time waiting, and the like, which causes dissatisfaction of patients to hospitals and workers.
1.6 angry. Due to the long waiting time or the excessive excellent diagnosis of special personnel (such as soldiers, old people and urgent people), particularly, the workers in the hospital are easy to feel dissatisfied when the workers are inserted into the team to see a doctor, and sometimes even the collective dissatisfaction of the patients waiting for the doctor around is caused, so that quarrel is caused.
In recent years, people have increasingly strengthened health consciousness, so that the number of patients in outpatient service in hospitals is increased year by year. The clinic treatment time of the patient is long, the outpatient service is congested, the emotion of the patient and the family members of the patient is excited and irritated, the patient care contradiction is easy to be excited, the complaint rate is high, the condition of the patient is possibly delayed, various researches show that a plurality of factors can influence the satisfaction degree of the patient on the outpatient service, wherein the waiting time is an important factor: in recent years, a reservation registration technology is gradually introduced into large hospitals, and aims to relieve the outpatient service congestion phenomenon and shorten the waiting time of patients. The implementation of appointment registration fully reflects the important measures of the innovation of medical services by mainly taking patients as centers in the current clinical medical services. The data shows that the prediction amount of special needs and the clinic diagnosis of experts is greatly improved, but the service amount of the general clinic diagnosis is far beyond the service amount of the special needs and the clinic diagnosis of experts, so the prospect is wide, the appointment registration is carried out no matter the general needs, the special needs or the house clinic diagnosis, the flow of people is favorably controlled, the clinical more reasonable planning on medical resources is facilitated, the waiting time is shortened, and the satisfaction degree of patients is further improved.
Some internal medicine outpatients, such as 15 internal medicine special outpatients, including diabetes outpatients, endocrine osteoporosis outpatients, chronic obstructive emphysema outpatients, pacemaker outpatients and the like. The doctor has few consulting rooms, a waiting area is small, the hospitalizing environment is crowded and complex, the calling voices of each special department have mutual interference, and the doctor is easy to bring misunderstandings and tense emotion to waiting patients.
The outpatient service has large flow, long waiting time and short real visiting time;
the outpatient service has large flow, long waiting time and short real visiting time, and becomes a main contradiction in the outpatient service. The clinic of internal medicine is more patients in rural areas and other places, and the patients are afraid to delay the examination of the day and come to see the clinic in advance; the elderly patients are often used to see a doctor before they start. The part of patients have weak appointment awareness and weak appointment capability, and the patients often take numbers and queue for waiting on the day, so that waiting time is increased. In the waiting process, if a doctor goes out of the office on time or an acquaintance of the doctor breaks into a queue, the patient is more likely to be angry and offensive.
The waiting time of patient waiting is divided into objective waiting time and subjective waiting time, wherein the objective waiting time refers to actual waiting time and is not interfered by external factors; the latter refers to the perceived latency of the human being, which is disturbed by a number of factors. Subjective latency may also be referred to as psychological latency.
The emergency treatment of each large hospital is always full of patients, and the limited medical resources and the huge amount of patients in the emergency treatment exacerbate the high risk and the occurrence of the complaints of the emergency treatment. The psychological waiting time of the patient is prolonged due to various factors such as critical illness, anxiety and tension, and the patient usually thinks that the patient has waited for a long time even if the waiting time is not long, and the patient is often a fuse of various medical care disputes. The patients with emergency trauma are characterized by critical illness, less psychological preparation and slow role transformation, and the psychological effect often exaggerates the emergency waiting time in waiting, which is more likely to cause various medical care disputes.
Reasons for the long psychological waiting time of patients include:
the reasons for the patients and family members are as follows: firstly, sudden diseases and wounds are attacked, so that the roles of patients are suddenly switched, and the feeling of scorching emotion is caused; secondly, the family members have little knowledge about the emergency diseases and the emergency treatment, and the hands and feet have no measures to cause the psychological tension of the patients; thirdly, the pain makes the patient feel weak and frightened, and the patient feels fear without help; fourthly, the accident responsibility parties select different treatment opinions to irritate the patients and the like. The negative effect of emotional frustration and emotional short circuit on the psychology of the patient, namely the waiting time is obviously prolonged. Studies have shown that the wait without everything, the wait with a sense of focus, the wait without interpretation appears longer closed.
The reason of the medical staff is as follows: the work is busy, and the psychological feeling of a patient cannot be considered; secondly, the communication skill is lacked, and effective communication is not carried out; and lack of responsibility.
The influence factors of the waiting time of the patients comprise the number of the patients in the waiting queue, different diagnosis and treatment time required by different diseases of different patients is different, meanwhile, different doctors have different diagnosis and treatment habits, the same disease sign also has different diagnosis and treatment time required by different doctors, and meanwhile, the whole diagnosis and treatment time of the corresponding disease signs of different departments is obviously different, so that the waiting time of the patients is linked or influenced by various factors.
The psychological waiting time is longer due to the self-worried emotion and the pain of the disease symptoms of the patient easily in the waiting process of the patient and the family members of the patient, the emotional overstrain and even the influence on the normal medical procedure are easily caused, and the contradiction arouses, so that the waiting time can be more easily received by the patient and the family members of the patient through reasonable waiting time notification, the emotional comforting and the time arrangement of the family members and the patient are convenient, and the method and the system for predicting the waiting time of the patient in the outpatient service of the hospital are needed to solve the problems.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a method and a system for predicting the waiting time of patients in hospital outpatient service, and the technical problems to be solved by the invention are as follows: the psychological waiting time is longer due to the self-anxious emotion and the pain of the disease symptoms of the patients and the family members of the patients in the waiting process, the emotional overstrain and even the influence on the normal medical procedures are easily caused, and the contradiction arouses are caused, so the waiting time can be more easily received by the patients and the family members of the patients through the reasonable waiting time notification, and the emotional comforting and the time arrangement of the waiting family members and the patients are convenient.
In order to achieve the purpose, the invention provides the following technical scheme: a hospital outpatient waiting time prediction method comprises the following steps:
acquiring a patient registration instruction;
acquiring department data, data of relevant doctors for sitting and consulting, pre-examination data information of patients and diagnosis and treatment registration queue information;
predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and displaying the predicted patient visit time.
As a further scheme of the invention: the registration instruction comprises registration department information, registration doctor information and registration time information.
As a further scheme of the invention: the acquiring department data, data of relevant attending physicians and pre-examination data information of patients comprises:
acquiring the average diagnosis and treatment time of the patient corresponding to the department;
diagnosis and treatment data of a doctor in a sitting diagnosis and treatment process and average diagnosis and treatment duration are obtained;
initial diagnosis data of the patient-related disorder is obtained.
As a further scheme of the invention: the method comprises the steps of obtaining initial diagnosis data of relevant diseases of a patient, obtaining preliminary characterization data of the patient through pre-diagnosis when the patient waits for a diagnosis after registration, and obtaining diagnosis and treatment duration according to diagnosis and treatment processes corresponding to the preliminary characterization data.
As a further scheme of the invention: the diagnosis and treatment registration queue information is obtained and comprises the number of patients in the diagnosis and treatment queue, the registration time of each patient and the prediction duration of diagnosis and treatment waiting.
The utility model provides a hospital outpatient service patient waiting time prediction system, includes the information acquisition module, the output of information acquisition module is connected with the input electricity of processing analysis module, the output of processing analysis module is connected with the input electricity of result display module, the information acquisition module includes information input module and patient's preliminary examination module.
As a further scheme of the invention: the information acquisition module is used for acquiring the registration time, the registration department and the doctor in the sitting and consulting department corresponding to the patient;
the system comprises an information acquisition module, a patient pre-inspection module and a diagnosis and treatment module, wherein the information input module in the information acquisition module is used for inputting the average disease diagnosis and treatment duration of relevant departments and the diagnosis and treatment habits of corresponding doctors, and the patient pre-inspection module is used for performing preliminary pre-inspection on the characteristics of patients and preliminarily determining the diagnosis and treatment process;
the processing and analyzing module is used for predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and the result display module is used for displaying the predicted patient visit time.
As a further scheme of the invention: a hospital outpatient waiting time prediction system, characterized by: the analysis and prediction of the processing and analyzing module adopts a neural network prediction model, wherein the neural network prediction model is calculated through a neural network algorithm, and the neural network algorithm comprises the following steps:
the input layer is the actual waiting time hw of the patientkThe output layer is the predicted waiting time pw of the patient, hiddenLayer unit hjThe input weighted sum of:
Figure BDA0003412277300000071
wherein hwkIn units of minutes, as input layer units, with a threshold b1＝1，
Figure BDA0003412277300000072
As weights of input layers to hidden layers, b1Has a weight of
Figure BDA0003412277300000073
Hidden layer unit hjOutput of (2)
Figure BDA0003412277300000074
Figure BDA0003412277300000075
Wherein
Figure BDA0003412277300000076
The method comprises the steps that the hidden layer is output after being activated, and sigmoid functions are adopted as activation functions in the hidden layer and the output layer;
the input weighted sum output of the output layer unit pw is:
Figure BDA0003412277300000077
wherein h iskIs k hidden layer units with another threshold b2With a weight of 1 from hidden layer to output layer
Figure BDA0003412277300000078
b2Has a weight of
Figure BDA0003412277300000079
Beginning of weight matrixThe initial values are all generated at random,
Figure BDA00034122773000000710
wherein ZpwThe output of the activated input layer is also the prediction result finally output by the algorithm;
the total error of the input, hidden and output layers is:
Figure BDA00034122773000000711
wherein target is the actual waiting time of the user, output is the predicted waiting time,
according to the gradient descent method, the weights from the hidden layer to the output layer are updated as:
Figure BDA00034122773000000712
Figure BDA0003412277300000081
updating the threshold weight of the hidden layer:
Figure BDA0003412277300000082
where η is the learning rate, which is taken to be 0.3.
The invention has the beneficial effects that:
according to the invention, the information of the departments for registering patients is acquired, the registration corresponds to the diagnosis and treatment habits of the sitting physicians, the predicted waiting time of each patient in the waiting queue is acquired, the characterization of each patient is preliminarily detected after registration, finally, the waiting time of each patient is predicted and integrated by combining the influence factors and the data through a neural network prediction model, the waiting time of the corresponding patient and the time corresponding to diagnosis and treatment are judged, the actual diagnosis and treatment time of each patient in the waiting queue is continuously updated through a feedback mechanism in the neural network prediction model, the waiting time and the diagnosis and treatment time of the subsequent patients are updated according to the new waiting patient queue information, the waiting time of the patients can be accurately judged, and the phenomenon that the waiting process of the patients without targets has a psychological comforting effect on the urgency of the waiting process of the patients is avoided.
Drawings
FIG. 1 is a schematic flow diagram of a process of the present invention;
FIG. 2 is a schematic diagram of the internal connection structure of the system of the present invention;
fig. 3 is a schematic view of an internal connection structure of the information acquisition module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-3, the present invention provides a method for predicting the waiting time of a patient in a hospital clinic, comprising the following steps:
acquiring a patient registration instruction;
acquiring department data, data of relevant doctors for sitting and consulting, pre-examination data information of patients and diagnosis and treatment registration queue information;
predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and displaying the predicted patient visit time.
The registration instruction comprises registration department information, registration doctor information and registration time information.
Acquiring department data, data of relevant referring physicians and pre-examination data information of patients comprises:
acquiring the average diagnosis and treatment time of the patient corresponding to the department;
diagnosis and treatment data of a doctor in a sitting diagnosis and treatment process and average diagnosis and treatment duration are obtained;
initial diagnosis data of the patient-related disorder is obtained.
Acquiring initial diagnosis data of related diseases of a patient, pre-diagnosing the patient when waiting for a diagnosis after registration to obtain preliminary characterization data of the patient, and obtaining diagnosis and treatment duration according to a diagnosis and treatment process corresponding to the preliminary characterization data.
Acquiring diagnosis and treatment registration queue information, wherein the diagnosis and treatment registration queue information comprises the number of patients in the diagnosis and treatment queue, the registration time of each patient and the prediction duration of diagnosis and treatment waiting.
The utility model provides a hospital outpatient service patient waiting time prediction system, includes information acquisition module, and information acquisition module's output is connected with information acquisition module's input electricity, and information acquisition module's output is connected with processing analysis module's input electricity, and processing analysis module's output is connected with result display module's input electricity, and information acquisition module includes information input module and patient's preliminary examination module.
The information acquisition module is used for acquiring the registration time, the registration department and the doctor of attending a doctor corresponding to the registration corresponding to the patient;
the system comprises an information acquisition module, a patient pre-inspection module, a diagnosis and treatment process determination module and a diagnosis and treatment module, wherein the information input module in the information acquisition module is used for inputting the average disease diagnosis and treatment duration of relevant departments and the diagnosis and treatment habits of corresponding doctors;
the processing and analyzing module is used for predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and the result display module is used for displaying the predicted patient visit time.
The analysis and prediction of the processing and analysis module adopts a neural network prediction model, wherein the neural network prediction model is calculated through a neural network algorithm, and the neural network algorithm comprises the following steps:
the input layer is the actual waiting time of the patienthwkThe output layer is the predicted waiting time pw of the patient, the hidden layer unit hjThe input weighted sum of:
Figure BDA0003412277300000101
wherein hwkIn units of minutes, as input layer units, with a threshold b1＝1，
Figure BDA0003412277300000102
As weights of input layers to hidden layers, b1Has a weight of
Figure BDA0003412277300000103
Hidden layer unit hjOutput of (2)
Figure BDA0003412277300000104
Figure BDA0003412277300000105
Wherein
Figure BDA0003412277300000106
The method comprises the steps that the hidden layer is output after being activated, and sigmoid functions are adopted as activation functions in the hidden layer and the output layer;
the input weighted sum output of the output layer unit pw is:
Figure BDA0003412277300000107
wherein h iskIs k hidden layer units with another threshold b2With a weight of 1 from hidden layer to output layer
Figure BDA0003412277300000108
b2Has a weight of
Figure BDA0003412277300000109
The initial values of the weight matrix are all generated randomly,
Figure BDA00034122773000001010
wherein ZpwThe output of the activated input layer is also the prediction result finally output by the algorithm;
the total error of the input, hidden and output layers is:
Figure BDA00034122773000001011
wherein target is the actual waiting time of the user, output is the predicted waiting time,
according to the gradient descent method, the weights from the hidden layer to the output layer are updated as:
Figure BDA0003412277300000111
Figure BDA0003412277300000112
updating the threshold weight of the hidden layer:
Figure BDA0003412277300000113
where η is the learning rate, which is taken to be 0.3.
In summary, the present invention:
according to the invention, the information of the departments for registering patients is acquired, the registration corresponds to the diagnosis and treatment habits of the sitting physicians, the predicted waiting time of each patient in the waiting queue is acquired, the characterization of each patient is preliminarily detected after registration, finally, the waiting time of each patient is predicted and integrated by combining the influence factors and the data through a neural network prediction model, the waiting time of the corresponding patient and the time corresponding to diagnosis and treatment are judged, the actual diagnosis and treatment time of each patient in the waiting queue is continuously updated through a feedback mechanism in the neural network prediction model, the waiting time and the diagnosis and treatment time of the subsequent patients are updated according to the new waiting patient queue information, the waiting time of the patients can be accurately judged, and the phenomenon that the waiting process of the patients without targets has a psychological comforting effect on the urgency of the waiting process of the patients is avoided.
The points to be finally explained are: first, in the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" should be understood broadly, and may be a mechanical connection or an electrical connection, or a communication between two elements, and may be a direct connection, and "upper," "lower," "left," and "right" are only used to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed;
secondly, the method comprises the following steps: in the drawings of the disclosed embodiments of the invention, only the structures related to the disclosed embodiments are referred to, other structures can refer to common designs, and the same embodiment and different embodiments of the invention can be combined with each other without conflict;
and finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.

Claims (8)

1. A method for predicting the waiting time of a patient in an outpatient service of a hospital is characterized by comprising the following steps:
acquiring a patient registration instruction;
acquiring department data, data of relevant doctors for sitting and consulting, pre-examination data information of patients and diagnosis and treatment registration queue information;
predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and displaying the predicted patient visit time.
2. The hospital outpatient waiting time prediction method according to claim 1, wherein: the registration instruction comprises registration department information, registration doctor information and registration time information.
3. The hospital outpatient waiting time prediction method according to claim 1, wherein: the acquiring department data, data of relevant attending physicians and pre-examination data information of patients comprises:
acquiring the average diagnosis and treatment time of the patient corresponding to the department;
diagnosis and treatment data of a doctor in a sitting diagnosis and treatment process and average diagnosis and treatment duration are obtained;
initial diagnosis data of the patient-related disorder is obtained.
4. The hospital outpatient waiting time prediction method according to claim 3, wherein: the method comprises the steps of obtaining initial diagnosis data of relevant diseases of a patient, obtaining preliminary characterization data of the patient through pre-diagnosis when the patient waits for a diagnosis after registration, and obtaining diagnosis and treatment duration according to diagnosis and treatment processes corresponding to the preliminary characterization data.
5. The hospital outpatient waiting time prediction method according to claim 1, wherein: the diagnosis and treatment registration queue information is obtained and comprises the number of patients in the diagnosis and treatment queue, the registration time of each patient and the prediction duration of diagnosis and treatment waiting.
6. A hospital outpatient waiting time prediction system comprises an information acquisition module, and is characterized in that: the output end of the information acquisition module is electrically connected with the input end of the information acquisition module, the output end of the information acquisition module is electrically connected with the input end of the processing and analyzing module, the output end of the processing and analyzing module is electrically connected with the input end of the result display module, and the information acquisition module comprises an information input module and a patient pre-examination module.
7. The hospital outpatient waiting time prediction system of claim 6, wherein: the information acquisition module is used for acquiring the registration time, the registration department and the doctor in the sitting and consulting department corresponding to the patient;
the system comprises an information acquisition module, a patient pre-inspection module and a diagnosis and treatment module, wherein the information input module in the information acquisition module is used for inputting the average disease diagnosis and treatment duration of relevant departments and the diagnosis and treatment habits of corresponding doctors, and the patient pre-inspection module is used for performing preliminary pre-inspection on the characteristics of patients and preliminarily determining the diagnosis and treatment process;
the processing and analyzing module is used for predicting diagnosis and treatment time of each patient according to department data, relevant doctors for sitting diagnosis and pre-examination data of the patients, and determining the diagnosis time of the registration instruction according to the diagnosis and treatment time of each patient;
and the result display module is used for displaying the predicted patient visit time.
8. The hospital outpatient waiting time prediction system of claim 6, wherein: the analysis and prediction of the processing and analyzing module adopts a neural network prediction model, wherein the neural network prediction model is calculated through a neural network algorithm, and the neural network algorithm comprises the following steps:
the input layer is the actual waiting time hw of the patientkThe output layer is the predicted waiting time pw of the patient, the hidden layer unit hjThe input weighted sum of:
Figure FDA0003412277290000021
wherein hwkIn units of minutes, as input layer units, with a threshold b1＝1，
Figure FDA0003412277290000022
As weights of input layers to hidden layers, b1Has a weight of
Figure FDA0003412277290000023
Hidden layer unit hjOutput of (2)
Figure FDA0003412277290000024
Figure FDA0003412277290000025
Wherein
Figure FDA0003412277290000026
The method comprises the steps that the hidden layer is output after being activated, and sigmoid functions are adopted as activation functions in the hidden layer and the output layer;
the input weighted sum output of the output layer unit pw is:
Figure FDA0003412277290000027
wherein h iskIs k hidden layer units with another threshold b2With a weight of 1 from hidden layer to output layer
Figure FDA0003412277290000031
b2Has a weight of
Figure FDA0003412277290000032
The initial values of the weight matrix are all generated randomly,
Figure FDA0003412277290000033
wherein ZpwThe output of the activated input layer is also the prediction result finally output by the algorithm;
the total error of the input, hidden and output layers is:
Figure FDA0003412277290000034
wherein target is the actual waiting time of the user, output is the predicted waiting time,
according to the gradient descent method, the weights from the hidden layer to the output layer are updated as:
Figure FDA0003412277290000035
Figure FDA0003412277290000036
updating the threshold weight of the hidden layer:
Figure FDA0003412277290000037
where η is the learning rate, which is taken to be 0.3.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114944225A (en) * 2022-07-25 2022-08-26 武汉盛博汇信息技术有限公司 Department management method and device based on patient information

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114944225A (en) * 2022-07-25 2022-08-26 武汉盛博汇信息技术有限公司 Department management method and device based on patient information
CN114944225B (en) * 2022-07-25 2022-09-27 武汉盛博汇信息技术有限公司 Department management method and device based on patient information

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