CN111863214B

CN111863214B - Patient admission time window reservation method and system based on opportunity constraint

Info

Publication number: CN111863214B
Application number: CN202010593823.5A
Authority: CN
Inventors: 陆雨薇
Original assignee: Guangxi University of Science and Technology
Current assignee: Guangxi University of Science and Technology
Priority date: 2020-06-24
Filing date: 2020-06-24
Publication date: 2023-05-30
Anticipated expiration: 2040-06-24
Also published as: CN111863214A

Abstract

The invention discloses a patient admission time window reservation method based on opportunity constraint, which comprises the steps of constructing an admission time window based on earliest admission time and latest admission time; defining an opportunity constraint strategy and establishing a reservation system in combination with the admission time window; the reservation system divides a hospital admission waiting mode into direct waiting and indirect waiting according to the system state information at the current moment; the target patient acquires basic information of the admission time window through the reservation system, and selects to enter a waiting mode or directly leave according to the self condition; the patient who enters waiting is selected to enter the reservation system to wait for receiving the hospitalization notice, so that the uncertainty of the hospitalization time length and the impatience behavior of the patient are overcome, the defect that the hospital cannot provide possible hospitalization time for the patient who enters the period and the patient experiences blind waiting and invalid waiting is overcome, and the hospitalization experience and satisfaction of the patient are improved.

Description

Patient admission time window reservation method and system based on opportunity constraint

Technical Field

The invention relates to the technical field of medical and health resource management, in particular to a patient admission time window reservation method and system based on opportunity constraint.

Background

Tertiary hospitals, especially trimethyl hospitals, have a large number of dominant medical resources, are high in "credibility" and obvious in "brand effect", and key medical resources, especially sickbed resources, are extremely scarce. Due to the deficiency and imperfection of the domestic grading diagnosis and treatment system at present, patients can select the treatment hospitals at will, so that a large number of slight patients can go to the high-grade hospitals for treatment, the high-grade hospitals represented by three-stage hospitals have serious bed adding phenomenon, and the hospitals are in an overload operation state for a long time.

Through investigation, it was found that there was a significant problem with the hospitalization patient admission process during the period of time. The patient in the hospital in the first period enters the waiting queue after submitting the admission application, and the medical staff informs the patient to be in the hospital the day before the sickbed is free according to the first-come first-serve principle. The waiting time length for admission varies from weeks to months according to the characteristics of departments, a large number of hospitalized patients with period selection lose tolerance in a long-time blind waiting process to leave the queue to generate a large number of invalid waiting, the waiting time is Cheng Bei after admission waiting is decocted, the waiting experience is poor, and the satisfaction degree of the patients to hospital services is reduced.

In view of the above problems, existing studies on patient admission including admission studies on inpatients, reservation scheduling, waiting prompt, customer behavior studies and delivery management are mainly focused on allocation schemes of hospital beds, and there is no document to study the procedure and mode of patient admission based on taking patient behavior (related to waiting procedure) into consideration, while studies on waiting prompt and reservation scheduling problems, while considering customer behavior and server utilization rate, have been conducted very deeply, but neither are applicable to the context of patient admission, nor are strategies well performed in the above system applicable to the procedure of admission of inpatients in terms of time of choice, so it is important to find an applicable admission scheduling management method.

Disclosure of Invention

This section is intended to outline some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description summary and in the title of the application, to avoid obscuring the purpose of this section, the description summary and the title of the invention, which should not be used to limit the scope of the invention.

The present invention has been made in view of the above-described problems with existing patient admission studies.

Therefore, the technical problems solved by the invention are as follows: solves the problem that the prior study on patient admission does not consider the influence of patient behaviors in the waiting process on the patient admission process and mode.

In order to solve the technical problems, the invention provides the following technical scheme: constructing an admission time window based on the earliest admission time and the latest admission time; defining an opportunity constraint strategy and establishing a pre-appointment system by combining the admission time window; informing the information of the admission time window at the arrival time of the patient; the information provides the patient with the option of leaving or entering wait autonomously at all; the patient entering the wait schedules an entry time window and the system selectively notifies them of the hospitalization.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the reservation system includes selecting the indirectly waiting target patient, the reservation system not being available to leave until the earliest time of the reservation; if the target patient selects to wait directly and then waits until the latest admittance time is not yet served, enjoying the preferential service; the target patient is admitted sequentially with the earliest admitted time informed.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the basic information acquired at the moment of arrival of the target patient includes the length w of the time window for admission of uniform length, i.e. for any patient i,

wherein W is the direct waiting time length, and the length of the admission time window is set to be identical with the time unit of week.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: when the target patient arrives, the reservation system gives an indirect waiting time length a as a control strategy according to the current state, and the indirect waiting time length a is not smaller than the residual indirect waiting time length of any queuing patient.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the reservation system comprises a definition as follows,

the state at time t is

Wherein s is ₀ Is the number of hospitalized persons;

To wait for vectors directly, by s _i 0 < i.ltoreq.W, where s _i For the number of patients with the remaining direct waiting time of i, LAT is t+i;

To indirectly wait for vectors, by s _W+j ， j>0, wherein s _W+j For the number of patients with the remaining indirect waiting time of j, EAT is t+j.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the reservation system comprises the steps of the occurrence sequence of discrete events in each time period, namely reaching and stopping: the patient arrives, receiving the basic information of the admission time window and selecting whether to join a queue or to generate a stopping behavior; admission: taking the number N of sickbeds as an upper limit, and receiving patients from a direct waiting queue; leaving: the leaving includes, discharging: patient in hospital(s) ₀ ) With probability p _S Discharging; midway exit: each patient waiting directly with probability p _R A midway exit behavior occurs; transfer: a patient(s) waiting for a period of time exceeding the length of the admission time window ₁ ) A transfer occurs; time advance updating the state of waiting for the patient (s _i ＝s _i+1 ,i>0)。

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the reservation system defines the opportunity constraint strategy based on a dimension reduction and recurrence formula, the dimension reduction comprising,

regardless of future arriving patients, system state s ^t Uniquely expressed as a one-dimensional state n= |s ^t ||；

The recursive formula includes a set of values,

there is an unequal relationship between the two,

and at time t the probability of the system population sum being n is,

then the first time period of the first time period,

s is the current system state; t is a time scale; m and n are patient scales; s is(s) ₀ The number of inpatients; s is(s) _i The number of patients with the remaining direct waiting time length of i; t+i is the latest admission time;

considering the probability of the remaining n patients of the system at the time t for m patients for the total body; s is(s) _W+j The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the recursive formula may further comprise a step of,

definition of delta _k For a single patient with eat=t+k, the earliest admission time can be expressed as σ _k ＝0，

Assume that

Known, then->

It can be found by the following recursive formula,

if t < sigma _k ，Δ _k Without leaving the system or admitting, then:

if t > sigma _k Then:

and delta is _k The probability of receiving a admission notification at time t is,

if t=σ _k Then:

wherein delta is _k The single patient with the earliest admittance time of t+k is the single patient; s is the current system state; t is a time scale; m and n are patient scales; s is(s) ₀ Is the number of hospitalized persons; s is(s) _i The number of patients with the remaining direct waiting time length of i; t+i is the latest admission time;

the probability of the remaining n patients of the system at time t is considered for the overall m patients; s is(s) _W+j The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds;

Is at->

Is a probability of a patient exiting and transferring halfway.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: the recursive formula also comprises the following optimization steps that a plurality of patients with the same EAT calculate the system state transition change brought by the patients at the same time; several patients arriving in the same time period can share part of intermediate results; if s is less than N, directly giving control a=q(s) without using state distribution; setting a proper algorithm termination condition f makes the algorithm end as early as possible.

As a preferred embodiment of the opportunity constraint-based patient admission time window reservation method of the present invention, wherein: at a known position

In the event that no stopping behavior occurs in the newly arrived patient, the probability that the patient will be serviced during time period t is,

thus, the service level based opportunity constraint policy can be expressed as:

Is at->

Probability of patient exit and transfer in the middle of the hospital; a is the indirect waiting time length; w is the direct wait time.

The invention has the beneficial effects that: the invention provides a hospital admission scheme based on time window notification for improving patient waiting experience, overcomes uncertainty of hospitalization duration and impatient behavior of patients, solves the problem that hospitals cannot provide possible admission time for hospitalized patients in a preferred period and the patients experience blind waiting and invalid waiting, and through modeling and simulation analysis, the invention obviously increases information transparency, effectively reduces blind and invalid waiting and improves patient hospitalization experience and satisfaction.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:

FIG. 1 is a schematic illustration of a current hospitalization patient admission process;

FIG. 2 is a time window notification admission scheme provided by the present invention;

FIG. 3 is a flow chart of a method provided by the present invention;

FIG. 4 is a graph of SLC policy performance provided by the present invention;

FIG. 5 is a schematic diagram of the improved amplitude of the DFT strategy as compared to the one provided by the present invention.

Detailed Description

So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.

Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.

While the embodiments of the present invention have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the invention. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.

Also in the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

The terms "mounted, connected, and connected" are to be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as, for example: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.

Example 1

Referring to fig. 1, there is a significant problem with the prior art hospitalization procedure in that the hospitalization enters a waiting queue after delivery of the admission request, and the healthcare worker will notify the hospitalization of the patient the day before the hospital bed is free according to the first come first served (fist come first serve, FCFS) principle. The admission waiting time period varies from weeks to months according to the department characteristics. During waiting, the patient may give up waiting for various reasons.

By analyzing the existing admission flow, the following defects are not difficult to find:

(1) All queued patients can receive the admission notification at any time, need to be admitted to receive treatment at any time, and cannot reasonably and normally arrange usual work and life. The inventors consider this waiting process, without waiting for a target, to be a blind one at any time, that is likely to receive service. The resources of the high-grade hospitals are short, the queuing time for the patients to stay in the hospital is long, the boiling degree of the waiting process of the patients is increased, and the patients can never get in the waiting period;

(2) The patient may experience impatient behavior out of the waiting queue due to prolonged blind waiting. These patients experience lengthy wait without being serviced and their wait becomes an ineffective wait. This not only wastes time for the patient but also increases the operating costs of the hospital (informing the patient who has left the queue to admit, maintaining contact with the customers being queued, public praise, branding effects, etc.). The lengthy admission waiting time also exacerbates the probability of ineffective waiting occurring.

Overall, a large number of hospitalized patients with a period of time lost tolerance during the long blind waiting period generate a large number of ineffective waiting periods, the waiting period Cheng Bei for admission is decocted, the waiting experience is poor, and the satisfaction of the patients with the hospital service is reduced. In response to this problem, the processes currently associated therewith include the following:

admission study of inpatients

Hospitalization patient admission plans are typically associated with hospital bed capacity scheduling, and studies of admission plans need to consider constraints on relevant critical resources; uncertainty of patient hospitalization time; and randomly arriving emergency patients. Three important evaluation indexes for evaluating admission scheduling more in the prior research and application are as follows: sickbed turnover rate, average waiting time for admission and fairness for admission. At the same time, the admission plan is closely related to the management mode of the hospital bed, such as whether the hospital bed is dedicated or shared, whether certain hospital beds are closed on weekends, etc. Thus, there is a need to study admission plans for inpatients in conjunction with specific hospital bed management patterns.

Patient admission scheduling is a process whereby patients are assigned to respective beds so that the associated medical needs and patient preferences are maximally met. Other documents related to hospitalization patient admission exist mainly for hospital bed performance planning in a certain hospital or department.

Reservation scheduling

Informing the customer of his admission time, i.e. reservation, at the customer arrival time is a good way to alleviate the customer's long waiting burden. Factors affecting the effectiveness of the appointment scheduling include patient arrival and fluctuations in service time, patient/physician preferences, information technology, and the proficiency of the scheduling personnel.

The main decisions of reservation scheduling are three: a specific date appointment number decision, a specific date customer arrival order decision, and a specific date customer arrival time interval decision.

Reservation scheduling is characterized in that the arrival time of a customer in the system is a decision variable that can be scheduled and that each customer does not arrive at the system until its reservation time. If the previous customer's service exceeds an approximate time, the current customer needs to wait for the previous service to end before starting his service; however, if the previous service ends early, the current customer still arrives at the system at his own reservation time. The server is in an idle state before the arrival of the customers, so shortening the arrival interval between the customers is beneficial to improving the utilization rate of the server, but the customers wait longer, otherwise, the longer arrival interval causes the increase of the idle time of the server. Therefore, the essence of reservation scheduling is to optimize and trade-off server efficiency and customer satisfaction. Overall, the difficulty of reservation scheduling is the uncertainty of service times, the uncertainty of demand arrival, and competing optimization metrics.

Waiting for a prompt

Waiting for a hint policy, a way for a service provider to share system information with a customer before or during waiting for the customer to occur, improves customer satisfaction. At present, the call center is mainly used as an application background for development. In this case, the customer cannot estimate the queue length and the speed of team progress and therefore is more prone to over-estimating the waiting time, meaning that the customer will be waiting for a heavier negative emotion. The main reason for the introduction of waiting prompts is that in order to reduce such psychological misjudgment and improve customer satisfaction, the admission process of patients in hospital at the time of choosing to be taken is just a typical invisible queue, and how to correctly predict waiting time is a very challenging problem.

Research on customer behaviors

The number of studies on impatience behavior of customers in a service system is countless. In general, most of the literature for queuing systems that consider the step-stopping behavior is to analyze the performance of the system under a given control strategy.

Specifically, in the call center system, the impatience behavior of the customer is mainly reflected in whether to leave the team (stop step) or enter the queue immediately after receiving the waiting prompt information; whether to give up waiting and leave the system in the waiting process (exit halfway). It is apparent that the stop behavior is related to the length of the waiting notice information that is notified and the halfway exit behavior is related to the waiting that is actually experienced.

In the reservation scheduling system, the customer behavior is mainly represented by whether the customer arrives at the system to receive service at the reserved time, and the refreshing behavior is not related to waiting prompt information and waiting actually occurring after the customer arrives at the system at the reserved time, so that the refreshing probability is generally set to be a constant of 5% -30%. The refreshing can result in reduced resource utilization and increased latency.

Delivery period management

Delivery management or lead management in the manufacturing industry is also associated with the problems of the present study. Most lead management studies split decisions into two steps, first setting lead for orders, the simplest strategy being to set the same lead for all orders, and then schedule the order's production order according to priority rating rules. Delivery period management selects a balance point primarily between informing and achieving a shorter lead period.

Most of the literature managed in advance ignores the impact of advance notification on customer behavior, with primary focus on combined decision-making of quotes and advance.

In view of the above, current patient admission studies have focused mainly on allocation schemes for hospital beds, and no document has studied the procedure and manner of patient admission taking into account patient behavior (related to waiting procedures). In the waiting prompt and reservation scheduling problems, the research of the customer behavior and the server utilization rate is carried out deeply, but the system is not suitable for the background of patient admission, and the strategy with good performance is not suitable for the admission process of patients in period selection and hospitalization. In particular, the main reason for the significant differences is that:

The general application background of the problem of waiting for a prompt is a telephone call center or a bank number calling system, which is basically assumed that customers can accept service at any time in the whole waiting process. If the patient is required to be admitted at any time in the whole waiting process, the patient is always in blind online waiting, which is contrary to the optimization purpose of the invention;

the problem of appointment scheduling is generally applied to diagnosis and treatment processes such as outpatient service, B-ultrasonic and CT, and is remarkably characterized by fixed shift and service time every day. In the application background, the requirement exceeding basic service capacity can be met by overtime behaviors, so that the system is empty at the initial moment of each shift, and therefore, the scheduling decision of each shift is basically not in coupling relation with the previous scheduling result, and the scheduling decisions among each shift are relatively independent;

the admission time window informing system provided by the invention has similarities with the delivery period management problem, and has larger difference, and comprises the following steps: the decision for delivery management is the order submission time (admission time + production time, typically also including quotation decisions), while the main decision for admission problems for a hospitalized patient in the period is when the patient can be admitted; the patient in the period of time selection is in an off-line background waiting state, so that the hospital admission at any time can not be realized, and the order in the delivery period management problem can be produced at any time once being generated; the fairness requirement of the patient admission sequence is far higher than that of order delivery management, so the invention will strictly follow the first-come first-serve principle; delivery management generally only considers customer stopping behavior, while in-patient mid-way exit behavior is within the contemplation of the present invention.

Accordingly, referring to fig. 2 to 5, the method for reserving a patient admission time window based on opportunity constraint provided by the invention is as follows: a patient admission time window reservation method based on opportunity constraints, comprising:

s1: an admission time window is constructed based on the earliest admission time and the latest admission time.

The steps are as follows:

the following definitions are included in constructing the admission time window:

(1) patient arrival, receiving notification, stop or join in an indirect waiting queue and admission occurs at the beginning of each time period, while discharge, exit in the middle and transfer occur at the end of each time period;

(2) n similar sickbeds work simultaneously, and each patient needs one sickbed;

(3) the length w of the admissions time window, which is signalled at all patient arrival moments, is uniform, i.e. for any patient i,

wherein W is the direct waiting time;

(4) the patient is admitted sequentially by the informed earliest admission time;

(5) when the patient arrives, the system gives an indirect waiting time length a as a control strategy according to the current state, and the indirect waiting time length a is not smaller than the residual indirect waiting time length of any queuing patient;

(6) patients who do not choose to stop the walking cannot leave the system before EAT and then enter a time window, namely a direct waiting stage, so that the patients can possibly enter a hospital or take a midway exit action due to impatience;

(7) The number of newly arrived patients within each time period corresponds to a poisson distribution with a mean value of l, and the patient discharge event corresponds to a geometric distribution with a probability of pS, i.e. average hospitalization duration = 1/pS;

(8) each patient has a fixed probability during each direct waiting period

A midway exit behavior occurs; when the informed indirect waiting time duration a and the time window length are W, the stop probability of the patient is

Wherein a is _B /a _R B is a time window length influencing factor for stop/mid-way exit rate.

Based on the definition made above, it should be noted that:

1. the arbitrary time unit is selected as the length of the time period according to the demands of the discretization accuracy degree in different application contexts. Taking hospitalized patient admission as a background, the time period length can be set as one day, the service capability is generally considered to be variable, such as the adding bed in a sickbed, the overtime time of outpatient service and the like, but under the hospitalized background, even if the adding bed is considered, the maximum service capability has an upper limit, and the more complex condition is avoided, the service capability is considered to be determined and the definition (2) is proposed;

2. based on definition (3), W changes from a decision variable to an input parameter of the system, which is due to: the decision variable of the time window informing the problem can be reduced from two-dimension (ai, wi) to one-dimension ai due to the proposal of the definition, so that the solution difficulty is greatly reduced; since only one type of patient is considered, the order of admission becomes another difficulty if the time window length varies. For example, if the patient i arrives at the time t, the received time window information of admission is (t+1, t+5), and the patient i+1 arrives at the time t+1, the received time window information of admission is (t+2, t+4), and if the system has a bed idle at the time t+3, if the patient i is selected, the possibility of occurrence of a transfer event of the patient i+1 is high, which is not beneficial to the overall benefit of the system, otherwise, the later arriving patient i+1 and the later arriving patient i have no priority difference, but are served in advance, and fairness cannot be guaranteed; most importantly, the fixed time window has strong practicability, the manager is easier to operate, the patient is easier to understand, for example, the time window length of the hospitalized patient is set to be 5/7 days which is consistent with the time unit of week, the patient acceptance degree is high, and the operation of a hospital is simple;

⒊ from the fairness point of view, definition (4) and definition (5) ensure that the order in which patients receive services meets FCFS guidelines, since only patients of the same type are considered. Indeed, due to the constraint of definition (5), there is a possibility that the patient bed is idle, the patient is in an indirect waiting process but cannot be admitted, and the newly arrived patient cannot be inserted for receiving service. However, the application background of the invention is hospitals, and the importance of fairness in the medical service field even exceeds the scarcity of medical resources;

⒋ defines (6) that the patient is required to be serviced only within the informed time window. The traditional reservation scheduling problem is consistent with the time window informing problem under the relaxation condition, only the EAT is given, and the time window informing problem studied by the invention not only gives the EAT but also gives the LAT. But in essence, patients can only be admitted at the immediate waiting stage. Based on definition (6), the patient knows that he cannot be admitted before EAT, and can freely arrange daily life and work without being in a standby state which can be admitted at any time all the time, and the boiling degree of the waiting process can be obviously relieved. On the other hand, if the system can provide time window information with a very close spectrum, for example, the system can accept the customer to a great extent just at the beginning of the time window or the time window is shorter in length, the blind waiting time can be greatly shortened;

⒌ definition (7) is a definition commonly used in the study of problems such as reservation scheduling, waiting for prompting and the like, and description of the patient behavior by definition (8) is referred to the waiting prompting system. Conventional reservation scheduling problems generally consider the refreshing behavior of a given probability to describe the impatience of a customer, the refreshing probability being independent of the direct waiting period it experiences. In the context of hospitalization, patients will go to the hospital to handle hospitalization after receiving the admission notification, and the impatience behavior is obviously related to the direct waiting time, and is described by a single, given probability, of a refreshing behavior, so that the study introduces a halfway exit behavior.

Since the admission information received by the patient includes two factors, namely an indirect waiting time length a and a direct waiting time length W, intuitively, the stopping behavior should satisfy the following conditions: p is p _B (a, W) presenting increasing relationships with a and W, respectively; if b>0 or a>0, all have p _B (a, W) > 0. Due to the lack of reference literature for studying two-parameter stop-motion behavior, the response of a hospitalized patient to time window notification is temporaryThe invention is not focused on describing the customer behavior, and is expressed by the most common and simplest model, and the stopping behavior described in the definition (7) is derived from the common exponential distribution and accords with p _B Conditions (a, W) need to be met.

S2: defining an opportunity constraint strategy and establishing a reservation system by combining an admission time window;

s3: informing the information of the admission time window at the arrival time of the patient;

s4: the root information provides the patient with the option of leaving or entering wait autonomously;

s5: the patient entering the wait schedules an entry time window and the system selectively notifies them of the hospitalization.

Further, a patient entering a wait according to the information of the admission time window may not leave the system until the earliest admittance moment.

Preferably, if the patient enters the time window and waits until the latest entry time is not serviced, the patient enjoys an offer, such as a transfer to a higher level hospital or VIP ward.

It is readily understood that: the waiting of the patient before the earliest admittance moment (earliest admission time, EAT) is called indirect waiting, while the waiting after EAT is direct waiting. In the indirect waiting stage, the patient knows that the patient cannot receive the service, is transparent waiting, has small waiting pressure and can reasonably arrange work and life. Within the admission time window, the patient also needs to wait, and is ready to admit, which is blind. The present invention refers to the constraint that a patient cannot receive service during an indirect waiting process as an admission constraint, and the "on-line" form of indirect waiting is obviously more popular than the "off-line" form of blind direct waiting, which is possible at any time to receive service. On the other hand, after entering the time window, the patient may also give up waiting (mid-way exit) before receiving the admission notification, and the patient taking place the stopping action may be significantly more satisfied with the waiting process than the customers taking the mid-way exit or transfer, since no actual waiting has taken place. Since the patient knows that he or she has not admitted at the end of the time window, he or she will enjoy the preferential service, the degree of blindness in the direct waiting phase under the admission time window notification scheme is significantly weaker than the current situation where no admission information is provided.

It should be noted that:

based on the above definition and description, the state of the system at time t can be defined as

Wherein s is ₀ Is the number of hospitalized persons;

to indirectly wait for vectors, by s _W+j ，j>0, wherein s _W+j For the number of patients with the remaining indirect waiting time of j, EAT is t+j.

For all arriving patients, the way it leaves the system is not unusual for discharge, transfer, exit midway, and stop. Then, it is necessary to make as many patients as possible perform the stop-walking action while securing the utilization of the hospital bed, thereby reducing the number of people who transfer and exit halfway.

Further, the order of occurrence of the discrete events of the system in each time period is given as follows:

step 1, reaching and stopping: the patient arrives, receives the time window notification information and selects whether to add a queue or to generate a stop behavior;

step 2, admission: taking the number N of sickbeds as an upper limit, and receiving patients from the direct waiting queue according to the FCFS principle;

step 3, leaving, wherein the leaving comprises the following steps:

discharge: patient in hospital(s) ₀ ) With probability p _S Discharging;

midway exit: probability p for each patient waiting directly _R The action of exiting midway occurs；

Transfer: directly waiting for a patient(s) whose duration exceeds the length of the time window ₁ ) A transfer occurs;

step 4, time advance, update the state of waiting for patient (s _i ＝s _i+1 ,i>0)。

The dynamically optimized decision variable of the present invention is the indirect waiting time told at the time of arrival of the patient. In comparison with the most similar wait for cues and reservation scheduling problems of the present invention, the time window notification problem has its significant characteristics, as shown in Table 1:

table 1: contrast table of difference between admission time window informing system and waiting prompt and reservation scheduling system

As shown in Table 1, the main difference is that waiting for the prompt message does not affect the time when the customer actually receives the service, i.e. the customer can receive the service at any time, and the phenomenon that the customer queues but cannot receive the service does not occur. Therefore, waiting for a hint strategy has less impact on system performance and system events, and the coupling between decisions is not strong. To reduce blind waiting of hospitalized patients, the present invention proposes admission constraints, i.e. customers are not able to receive service during the indirect waiting phase, which is also a common assumption of reservation scheduling. The different aspects of the basic assumption increase the difficulty of policy resolution for the time window notification decision; on the other hand, a well-behaved waiting reminder strategy is not suitable for use in the admission time window notification system.

In contrast to reservation scheduling, the main differences are: (1) The time window proposed by the present invention is very different from the time slot defined by the conventional reservation scheduling problem, although it is referred to as a period of time. For example, if the length of a certain time slot and time window with the basic unit of hour is 5 hours, then both time slot t and time window t may be defined as (t, t+5), but time slot t+1 is (t+6, t+10), and time window t+1 is (t+1, t+6). This means that the different time windows are partially overlapping, but not between time slots. Thus, at the same system scale, the decision size informed by the admission time window increases significantly. (2) The description of the impatient behavior of the patient is different from that of the traditional reservation scheduling. The application context of traditional appointment scheduling is typically an outpatient or critical device, the measure of service time and waiting time is typically minutes or hours, with the patient in a "background" waiting state (not in the hospital) before the appointment time, and a "field" waiting state (in the hospital) after the appointment time. And the unit of time for hospitalized patient admission problems is days, and all waiting phases of the patient are in a 'background' waiting state. In the traditional appointment scheduling problem, the patient is assumed to have a certain probability of going to the hospital at the appointment moment, but once the patient arrives at the hospital, the patient cannot have impatient behaviors in the waiting process of 'on site'. The turn-down probability may be related to the indirect wait time period but not the direct wait time period. The description of restlessness behavior of an antiperspirant hospitalized patient, being always in a "background" waiting state, is obviously inappropriate with a specific probability of description independent of the actual direct waiting time. Therefore, the invention describes the impatient behavior of the customer in the direct waiting stage by the midway exit, namely the impatient behavior can be taken out of the queue at any time, and the occurrence probability of the impatient behavior is closely related to the actual direct waiting time. Compared with the refreshing behavior, the midway exiting behavior brings higher uncertainty, improves the coupling between the decision and the system event, and increases the difficulty of solving the strategy. (3) Conventional reservation scheduling problems assume that daily tasks can be met by expensive overtime behavior, i.e., the tasks on the day do not remain the next day. This means that the system will "flush out" at a certain period, the scheduling decisions between each flush out period being independent of each other. Thus, conventional reservation scheduling generally divides the decision process into two phases, the first phase being reservation, assigning a specific number of customers to each fixed length time period; the second stage is scheduling, determining the arrival times of customers assigned for each time period. Thus, the difficulty of solving the strategy can be remarkably reduced. So that the hospital bed resource cannot achieve this. The conventional reservation mode based on the time slot allocation capability does not generally consider the reservation strategy from the viewpoint of dynamic optimization due to the differences of time slot and time window definition, periodic emptying behavior of the system and the like, but the optimal schedule given by the reservation scheduling problem of optimizing the arrival time of a given small-batch customer is in a 'roof' shape, and obviously cannot process a large number of customer arrivals for a long time considered by the invention. Therefore, the time window notification decision provided by the invention has obviously stronger coupling, and the policy solving difficulty is obviously increased.

In general, the admission time window informing scheme provided by the invention has obvious difference from the existing queuing system, and the solving difficulty of the informing scheme is obviously higher than that of other problems.

Example 2

Because the admission time window informs the complexity of the original problem, the state of the admission time window needs to be described by a multidimensional vector, and the solution is extremely complex. Even if the optimal control strategy can be obtained under a very small system scale, the rule of the optimal control strategy has little significance on the guidance of heuristic strategy design. Therefore, the system uses a recursion formula which can calculate the state distribution of the patient which is from any known state and is only accommodated by the current system at any time node in the future by ingenious descending and recursion mode on the premise of not changing the system performance and the state transition probability. Based on this formula, an opportunistic constraint strategy is devised that considers the level of service desired by the patient as follows:

regardless of future arriving patients, system state s ^t Uniquely expressed as a one-dimensional state n= |s ^t I, i.e., the sum of the number of all patients in the current system state, and:

since patients in the indirect waiting queue cannot leave the system, and patients with a direct waiting time exceeding W must be transferred, there is an unequal relationship:

And at time t the probability of the system population sum being n is,

time axis t of the recursive algorithm: a first layer recursion cycle is started from time 0 to time t; the people number axis m: the probability of state transition for 1 patient at a time is considered more for the second tier recursion cycle. Recording device

To consider overall the probability of m patients leaving n patients in the system at time t, it is evident that: n is more than or equal to 0, and m is more than or equal to s. At the same time->

Namely +.>

Further, record

Is at->

Is a probability of a patient exiting and transferring halfway. For patients waiting directly (k.ltoreq.W), τ.ltoreq.k-1 is +.>

Otherwise->

For patients waiting indirectly (k > W), the system cannot be left until the moment (i-W), if τ < k-W +.>

If k-W is not less than τ and not more than k-1 +.>

Otherwise->

Thus, the following is obtained:

Further, note delta _k The earliest admission time of a single patient with eat=t+k can be expressed as sigma _k =0 (if k+.w) or σ _k =k-W (if k > W). Assume that

Known, then->

The method can be obtained by the following recursive formula:

case one: if t < sigma _k ，Δ _k No departure from the system (including discharge, transfer, mid-exit) or admission, and therefore:

and a second case: if t > sigma _k And delta _k The patient has been informed of the admission by time t and is still currently in the system, leaving the system only in a discharge; conversely, deltaA _k Only at time t is the admission notification received and a leave system (exit in mid-way, transfer) or admission event occurs, then:

and a third case: if t=σ _k Delta when only the sickbed is idle _k Can receive the admission notification. Stated another way, the patient will stay in the waiting queue until a bed is free. Thus, the first and second substrates are bonded together,

conversely, deltaA _k Will be with probability

Leaving the system, the availability is:

to consider overall m namesProbability of the patient remaining n patients in the system at time t; s is(s) _W+j The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds;

Is at->

Is a probability of a patient exiting and transferring halfway.

The computational complexity of this algorithm is not optimistic when the number of queuing is large, since the state distribution needs to be calculated for each newly arrived patient. The calculation of this formula can be accelerated from the following aspects:

1) Several patients with the same EAT can calculate the system state transition change brought by the patients at the same time;

2) Several patients arriving in the same time period can share part of intermediate results;

3) If s is less than N, directly giving control a=q(s) without using state distribution;

4) A suitable algorithm termination condition f may be set to end the algorithm as early as possible.

The method comprises the following specific steps:

step 1:

pretreatment: when the number of patients taken into account is smaller than N, the admission control a=q(s) is given directly;

For i＝1:h:

if s < N: a=q(s), the system state is updated in consideration of the stop behavior (s≡s+Δ _W+q(s) )；

Otherwise h≡h-i+1 and go to step 2;

step 2:

solving state distribution according to the current system state s, and giving a single decision;

a) Initializing:

solving according to (10-1)

Solving->

Update t+.0, f+.0, m+.s ₀ ；

b)For i＝1:q(s)；

For j=1:si: solving for

Updating m ≡m+s _i ；

Update t++1 and f. If f.noteq.0, go to step 3.

c) According to

Solving a;

step 3:

updating the state distribution and solving the control a by considering all newly arrived patients;

For i＝1:h:

if the current patient does not have stopping behavior under control a, s+.s+delta _a+q(s)

a) For t= 0:t: solving for

b) Updating f;

c) While f=0: update t++1: solving for

And updating f;

d) According to

Solving a;

let a (s, a) be the probability that a newly arrived patient will eventually be admitted within the time window (a, a+w) if no stop action occurs under control a, d being the service level control parameter. At a known position

Is the condition of (1)In the case, the probability that a newly arrived patient can be served in the time period t without stopping behavior is that,

thus, the first and second substrates are bonded together,

the service level based opportunity constraint policy can be expressed as:

the probability of the remaining n patients of the system at time t is considered for the overall m patients; s is(s) _W+j The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds; / >

Is at->

And (3) verification:

a reference strategy (DFT) is defined giving control a=0 in any system state. The strategy reflects the admission flow of the patient in the current period, namely, the admission information is not informed to directly enter the blind direct waiting process.

When the service rate ps= {0.1,0.2,0.4,0.8}, the system load = l/NpS = {0.75,1,1.25,1.5}, the mid-way exit rate ar= {0.1,0.25,0.5,0.75,0.9}, the stop rate ab= {0.05,0.1}, the performance of the SLC strategy of d=0.75 under each parameter is shown in fig. 4, while the statistical information (including maximum/small value, upper/lower quartile, median) and average improvement amplitude (given specific values) of the performance of the SLC strategy of d=0.75 under all parameter combinations (total number of service patients, total number of transfer patients and total number of mid-way exit patients) are shown in fig. 5.

Experiments have found that the SLC strategy with d=0.75 can reduce the transfer and mid-exit behavior by about 90% on average, and even slightly improve the bed utilization. This shows that the hospital benefit (bed utilization) is ensured while the patient's admission experience is greatly improved.

Through experiments, the following steps are found: increasing the value of the control parameter d will significantly reduce the number of exits midway and increase the number of stops. Unexpectedly, the number of hospital transfers remained in a lower range after d was greater than 0.5. Obviously, a larger control parameter d will significantly improve patient satisfaction at the cost of a loss of patient bed utilization. While the rate at which the utilization decreases increases with increasing d. The effectiveness of the recurrence formula is verified experimentally taking d equal to 0.75 as an example.

The invention is significantly different from the existing admission system, in particular to the traditional reservation scheduling problem: a time window notification based admission protocol is presented that improves the patient waiting experience. Overcomes the defects that due to uncertainty of the hospitalization time length and the impatient behavior of the patient, the hospital can not provide possible admission time for the patient in the period of hospitalization, and the patient experiences blind waiting and invalid waiting. The time window notification scheme proposed by the invention divides the waiting process into two parts, namely indirect waiting and direct waiting. By informing the admission time window information, the patient can decide whether to enter an indirect waiting queue according to the self situation; the patient can receive the admission notification at any time after entering the direct waiting from the beginning of the time window; patients who are still waiting at the end of the time window will receive the benefit services.

Modeling and simulation analysis show that the scheme remarkably increases the transparency of information, effectively reduces blindness and invalid waiting, and improves the medical experience and satisfaction of patients: compared with the DFT strategy which reflects the current situation that no admission information is notified and the FDL strategy which reflects the average waiting time length is notified, the SCL strategy designed for the admission time window notification problem can convert a large number of mid-way exit/transfer events into stop events on the premise of not affecting the utilization rate of a sickbed, and can greatly improve the satisfaction degree of patients. In particular, when the service rate is high, the system load is high, and the patient's restlessness to indirect waiting and direct waiting is greatly different, the patient waiting experience is more remarkably improved under the time window informing mechanism.

It should be appreciated that embodiments of the invention may be implemented or realized by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer readable storage medium configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, in accordance with the methods and drawings described in the specific embodiments. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.

Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes (or variations and/or combinations thereof) described herein may be performed under control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications), by hardware, or combinations thereof, executing on one or more processors in common. The computer program includes a plurality of instructions executable by one or more processors.

Further, the method may be implemented in any type of computing platform operatively connected to a suitable computing platform, including, but not limited to, a personal computer, mini-computer, mainframe, workstation, network or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and so forth. Aspects of the invention may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optical read and/or write storage medium, RAM, ROM, etc., such that it is readable by a programmable computer, which when read by a computer, is operable to configure and operate the computer to perform the processes described herein. Additionally, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. When such media includes instructions or programs that, in conjunction with a microprocessor or other data processor, implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media. The invention also includes the computer itself when programmed according to the methods and techniques of the present invention. The computer program can be applied to the input data to perform the functions described herein, thereby converting the input data to generate output data that is stored to the non-volatile memory. The output information may also be applied to one or more output devices such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including specific visual depictions of physical and tangible objects generated on a display.

As used in this application, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, the components may be, but are not limited to: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers. Furthermore, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).

It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, and it should be covered in the scope of the claims of the present invention.

Claims

1. A patient admission time window reservation method based on opportunity constraint is characterized in that: comprising the steps of (a) a step of,

constructing an admission time window based on the earliest admission time and the latest admission time;

defining an opportunity constraint strategy and establishing a reservation system in combination with the admission time window;

informing the information of the admission time window at the arrival time of the patient;

providing the information to the patient, the patient selecting to leave or enter waiting on his own;

entering a waiting patient schedule entry time window, the system selectively informing them of hospitalization;

the reservation system comprises a definition as follows,

the state at time t is

Wherein s is ₀ The number of inpatients;

For direct waiting vectors, by->

，

Composition of->

For the number of patients with the remaining direct waiting time of i, LAT is t+i;

For indirect waiting vector, by->

，j>0 composition, wherein->

For the number of patients with the rest indirect waiting time of j, EAT is t+j;

the reservation system defines the opportunity constraint strategy based on a dimension reduction and recurrence formula, the dimension reduction comprising,

regardless of future arriving patients, system state s ^t Uniquely expressed as a one-dimensional state

；

The recursive formula includes a set of values,

；

there is an unequal relationship between the two,

；

and at time t the probability of the system population sum being n is,

；

then the first time period of the first time period,

；

s is the current system state; t is a time scale; m and n are patient scales;

is the number of hospitalized persons;

The number of patients with the remaining direct waiting time length of i; t+i is the latest admission time;

The probability of the remaining n patients of the system at time t is considered for the overall m patients;

The number of patients with the rest indirect waiting time length j;

Is the earliest admittance time; n is the number of sickbeds.

2. The opportunistic constraint based patient admission time window reservation method of claim 1, wherein: the reservation system includes selecting a target patient waiting indirectly, the reservation system not being available to leave until the earliest admittance time; if the target patient selects to wait directly and then waits until the latest admission time is not yet served, the target patient enjoys the preferential service; the target patient is admitted sequentially with the earliest informed admission time.

3. The opportunistic constraint based patient admission time window reservation method of claim 1 or 2, wherein: the basic information acquired at the moment of arrival of the target patient includes the length w of the time window for admission of uniform length, i.e. for any patient i,

the method comprises the steps of carrying out a first treatment on the surface of the Wherein W is the direct waiting time length, and the length of the admission time window is set to be identical with the time unit of week.

4. The opportunistic constraint based patient admission time window reservation method of claim 3, wherein: when the target patient arrives, the reservation system gives an indirect waiting time length a as a control strategy according to the current state, and the indirect waiting time length a is not smaller than the residual indirect waiting time length of any queuing patient.

5. The opportunistic constraint based patient admission time window reservation method of claim 4, wherein: the reservation system comprises the steps of the occurrence sequence of discrete events in each time period, namely reaching and stopping: the patient arrives, receiving the basic information of the admission time window and selecting whether to join a queue or to generate a stopping behavior;

admission: taking the number N of sickbeds as an upper limit, and receiving patients from a direct waiting queue;

Leaving: the leaving includes the step of,

discharge: patient in hospital

With probability->

Discharging;

midway exit: probability for each patient waiting directly

A midway exit behavior occurs;

transfer: patients with a direct waiting period exceeding the length of the admission time window

A transfer occurs;

time advance, updating the state of waiting for a patient

。

6. The opportunistic constraint based patient admission time window reservation method of claim 5, wherein: the recursive formula may further comprise a step of,

definition of delta _k For a single patient with eat=t+k, the earliest admission time can be expressed as σ _k =0，

Assume that

Known, then->

It can be found by the following recursive formula,

if t<σ _k ，Δ _k Without leaving the system or admitting, then:

；

if t>σ _k Then:

；

；

if t=σ _k Then:

；/>

wherein delta is _k The single patient with the earliest admittance time of t+k is the single patient; s is the current system state; t is a time scale; m and n are patient scales;

is the number of hospitalized persons;

The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds; / >

Is at->

Is a probability of a patient exiting and transferring halfway.

7. The opportunistic constraint based patient admission time window reservation method according to any of claims 4-6, wherein: the recursive formula further comprises the following optimization steps,

a plurality of patients with the same EAT calculate the system state transition change brought by the patients at the same time;

several patients arriving in the same time period can share part of intermediate results;

if it is

Control is given directly without calculating the state distribution>

；

Setting a proper algorithm termination condition f makes the algorithm end as early as possible.

8. The opportunistic constraint based patient admission time window reservation method of claim 7, wherein: at a known position

In the event of a new arriving patient being available +.a probability of the patient being served in time period t if no stop behavior occurs +.>

In order to achieve this, the first and second,

；

；

is the number of hospitalized persons;

For remaining directlyWaiting for the number of patients with the duration of i; t+i is the latest admission time;

The probability of the remaining n patients of the system at time t is considered for the overall m patients; / >

The number of patients with the rest indirect waiting time length j; t+j is the earliest admittance time; n is the number of sickbeds;

Is at->

Probability of patient exit and transfer in the middle of the hospital; a is an indirect waiting time period; w is the direct wait time. />