JP4879147B2 - Information processing apparatus and program - Google Patents

Description

  The present invention relates to an information processing apparatus and a program, and more particularly to a technique for supporting reservation work such as hospital medical appointment reservation.

  In recent years, service provision work such as hospital appointment reservation work has been improved using information processing technology.

For example, in Patent Document 1, in a management time management system using a computer, received patient information waiting for medical care is stored together with medical treatment categories, standard medical treatment time for each medical treatment category is stored, and standard for waiting patients for each medical treatment category is stored. A medical treatment time management system that calculates a medical treatment time and outputs a predicted time until the end of the medical treatment is disclosed.
Japanese Patent Laid-Open No. 11-120225

  Incidentally, the system described in Patent Document 1 stores patient information waiting for medical care, and calculates a standard medical treatment time for a waiting patient for each medical treatment section based on a standard medical treatment time for each medical treatment section. It does not take into account variations in doctor hours. For this reason, in the system configuration described above, it is not possible to support the reservation work in a manner that takes into account detailed circumstances at the site, such as individual differences in the examination time for each doctor or when the doctor consciously adjusts the examination time.

  The present invention has been made in view of such problems, and an object of the present invention is to provide an information processing apparatus and program capable of supporting a reservation work in consideration of the detailed circumstances of the service providing site.

The invention according to claim 1 for achieving the above object is an information processing apparatus for supporting a reservation work when providing a service to a plurality of recipients,
Storage means for storing history data recording service provision history;
Data extracting means for extracting from the history data satisfying a predetermined condition;
Probability distribution generation means for generating a probability distribution of service provision time, which is the time required for the service of each individual recipient, based on the history data extracted by the data extraction means;
Simulation execution means for generating an expected value Ti (i = 1, 2, 3,...) Of the service provision time of each recipient by performing a simulation according to the probability distribution;
Implementation means for summing the expected value Ti of the service provision time of each individual recipient,
When _nk is a variable, the target value of the total service provision time is P, and λ is a predetermined value, each time the simulation is performed, the _nk and the expected value Ti (i = 1, 1). , N _k ), a function f (x) of a deviation x between the total value of service provision times determined from the target value P and f (x) is x ² , max [x, 0], | x |, or (x) ^m (m is a natural number)) and the above-mentioned n _k (k = 1, 2 ) that maximizes the objective function F (n _k ) , which is a difference from the value obtained by multiplying the above λ. , 3...)
The optimum number of recipients, which is the optimum value of the total number of recipients who receive the service , based on a value obtained from n _k (k = 1, 2, 3...) Obtained every time the simulation is performed. and further comprising a best donee number calculation means for calculating a n _0.

  The invention according to claim 2 is the information processing apparatus according to claim 1, wherein the predetermined value λ is determined according to a tolerance of the waiting time of the recipient.

The invention according to claim 3 is the information processing apparatus according to claim 1, wherein the probability distribution generated by the probability distribution generation unit is a logarithmic normalization based on the distribution of the history data itself, the history data. It is assumed that the distribution is at least one of a distribution and a distribution that statistically approximates the probability distribution of the history data.

According to a fourth aspect of the present invention, there is provided the information processing apparatus according to the first aspect, wherein the optimum number of recipients n ₀ is divided by the target value P to provide service for individual recipients. A reservation frame setting means for obtaining time is further provided.

The invention according to claim 5 is the information processing apparatus according to claim 1, wherein the service is a doctor's examination, the recipient is a patient, and the appointment service is an examination appointment service. Suppose that

The invention according to claim 6 is the information processing apparatus according to claim 1, wherein the objective function F (n _k ) is one of the following expressions.

The invention according to claim 7 is a program, and the information processing apparatus includes:
A function for storing history data that records service provision history;
A function of extracting a predetermined condition from the history data;
A function for generating a probability distribution of service provision time, which is the time required for the service of each individual recipient, based on the history data extracted by the data extraction means;
A function of generating predicted values Ti (i = 1, 2, 3,...) Of service providing times of individual recipients by performing a simulation according to the probability distribution;
A function of summing the expected value Ti of the service provision time of each individual recipient,
A function f (x) of a deviation x between a total value of service provision times obtained from the predicted value Ti and the target value P (where f (x) is x ² , max [x, 0], | x |, Alternatively, the value of n _k (k = 1, 2, 3...) That maximizes the objective function (n _k ) , which is the difference from the value obtained by multiplying (x) ^m (m is a natural number) by the λ. The desired function,
The optimum number of recipients, which is the optimum value of the total number of recipients who receive the service, based on a value obtained from n _k (k = 1, 2, 3...) Obtained every time the simulation is performed. The function obtained as n ₀ is realized.

  According to the present invention, it is possible to support reservation work in a form that takes into consideration the detailed circumstances of the service providing site.

  Hereinafter, as an example of an information processing apparatus that supports a reservation work when providing a service to a plurality of recipients, a reservation work support apparatus 1 that supports a work related to a doctor's examination reservation performed at a hospital window or the like will be described. To do.

  FIG. 1 shows a hardware configuration of a computer that realizes the functions of the reservation service support apparatus according to the present embodiment. As shown in FIG. 1, a computer 100 includes a CPU 101, a memory 102 such as a RAM / ROM, a large-capacity storage device 103 such as a hard disk, an input device 104 such as a keyboard and a mouse, and a display device such as a liquid crystal display and a cathode ray tube display. 105, and a communication device 106 that is an interface for connecting to a communication network such as a LAN (Local Area Network) or a WAN (Wide Area Network).

  FIG. 2 shows functions of the reservation work support apparatus 1. The reservation work support apparatus 1 includes a condition reception unit 211, a data extraction unit 212, a distribution designation reception unit 213, a consultation time distribution generation unit 214, a simulation execution unit 215, an optimization condition reception unit 216, an optimization calculation execution unit 217, an optimum It has functions such as an examination number output unit 218 and a reservation frame setting unit 219. These functions are realized by the hardware of the information processing apparatus 100 or when the CPU 101 executes a program stored in the memory 102.

  FIG. 3 is a flowchart for explaining processing for setting the examination time (reservation frame) for each patient, which is performed by the reservation work support apparatus 1. Hereinafter, it demonstrates with this flowchart. In the following description, the letter “S” means a step.

  First, the condition receiving unit 211 receives a predetermined condition (hereinafter referred to as a simulation condition) when the user performs a simulation described later (S311). In the next S312, the user designates simulation conditions so that data acquired in a situation as close as possible to the situation that the user is trying to predict is extracted.

  Next, the data extraction unit 212 converts the data corresponding to the simulation conditions received by the condition reception unit 211 from the examination time result data 251 which is data (history data) in which the results of the examination time (service provision history) are recorded. This is extracted and output as extracted data 252 (S312). The examination time result data 251 is acquired from, for example, an apparatus (waiting time notification apparatus) that is connected to the information processing apparatus 100 via a communication network and predicts and notifies the waiting time until the examination.

  FIG. 4 shows an example of the examination time result data 251. The examination time result data 251 shown in the figure includes items such as a medical treatment date 2511, a medical department name 2512, a doctor number 2513, a patient number 2514, a medical examination time 2515, a reexamination presence / absence 2516, a reservation presence / absence 2517, an examination presence / absence 2518, and the like. It is composed of a plurality of record groups.

  The simulation conditions when the examination time record data 251 has the configuration shown in FIG. 4 include, for example, a doctor number, season, day of the week, medical department, presence / absence of reexamination, presence / absence of reservation, presence / absence of examination, and the like. As an example, the data extraction unit 212 extracts data corresponding to the simulation condition that the medical treatment date 2511 is “June 28, 2007” and the medical treatment department name 2512 is “internal medicine” from the examination time result data 251 of FIG. The extracted data 252 in this case is shown in FIG.

  In S313, the distribution designation accepting unit 213 accepts designation of a probability distribution to be used when a simulation execution unit 215 described later performs a simulation from the user. For example, the user designates a probability distribution such as a distribution of actual values (hereinafter referred to as an actual distribution), a normal distribution, a lognormal distribution, or the like. Note that when a normal distribution, a log normal distribution, or the like is used, the calculation load of the simulation is reduced as compared with the case where the actual distribution is used.

  In S <b> 314, the examination time distribution generation unit 214 generates an examination probability (hereinafter, referred to as examination time distribution 253) of the examination time of each patient (time required for the service of each recipient) based on the extracted data 252. Is generated. FIG. 6 shows an example of the examination time distribution 253 generated.

  As the examination time distribution 253, the graph shows a graph obtained by log normalizing the actual distribution (log normal distribution) and a bar graph based on the actual results (result distribution).

  Next, the optimization condition receiving unit 216 receives from the user the designation of conditions (hereinafter referred to as optimization conditions) imposed on the optimization calculation when the optimization calculation execution unit 217 (to be described later) performs the optimization calculation. (S315). The optimization conditions include the number of simulations k, the total examination time target P (target value of the total value of service provision time), and the penalty coefficient λ.

  The total examination time target P is set, for example, when the optimum number of people accepted during the opening time is desired. If you want to find the optimal number of people in the morning, the morning opening hours are set.

  The penalty coefficient λ is an amount corresponding to the tolerance for patient waiting time. For example, if you want to set a large tolerance for patient waiting time, such as when you want to see a large number of patients even if the examination end time is longer than planned (even if the patient waiting time is slightly longer), the penalty coefficient λ Set the value to a smaller value. Further, when it is desired to set the tolerance for the patient waiting time to be small, such as when it is desired to finish the examination end time within the scheduled time, the value of the penalty coefficient λ is set to a large value.

  In S316, the simulation execution unit 215 performs a simulation based on the examination time distribution 253 generated by the examination time distribution generation unit 214, and the expected value Ti (i = 1, 2,...) ) (Reference numeral 254).

  Note that the simulation uses, for example, an inverse transformation method using a cumulative distribution function, and a random number (examination time Ti) according to a distribution (normal distribution, lognormal distribution, actual distribution, etc.) received by the distribution designation receiving unit 213. It is done by generating. An example of the predicted value Ti254 of the examination time for each patient generated by the simulation is shown in FIG.

Next, the optimization calculation execution unit 217 maximizes the value of the objective function F (n _k ) expressed by the following equation for each simulation (hereinafter referred to as the number n _k (reference number 255)). ) Is obtained (S317).

Note that f (x) is x ² , max [x, 0], | x |, or (x) ^m (m is a natural number ) . Incidentally, for example, using x ² if you want to reduce the deviation from the total examination time objective P, when it is desired to reduce the delay from eg examination time goal P uses max [x, 0].

  In S318, the simulation execution unit 215 determines whether or not the simulation has been performed the specified number of times received by the optimization condition reception unit 216 in S315. If the number of simulations has not reached the specified number (S318: NO), the process returns to S316. If the number of simulation executions has reached the specified number (S318: YES), the process proceeds to S319.

In S319, the number of examinations n _k (k = 1, 2, 3,... K) (reference numeral 255) selected based on a certain criterion from _nk obtained each time the simulation is performed by the optimization calculation execution unit 217. It outputs as the optimal examination number n ₀ (symbol 256).

This is because the number of examinations _nk does not necessarily become a constant value for each simulation, and actually varies as shown in FIG. 8, for example. Therefore, for example, an optimal medical examination number n _{0 in} which the mode value that can be read from the figure or the cumulative probability from the lower limit value is 10% may be adopted. Incidentally, as shown in FIG. 8, a difference in the optimum examination number n ₀ is caused by changing the penalty factor lambda.

In S320, the reservation frame setting unit 219 obtains the appointment slots based on the optimum examination number _{n 0} obtained. For example, when the penalty coefficient λ is 1 (the patient's tolerance for waiting time is large) and the optimal number of patients n ₀ is calculated to be 71, and the medical examination time is 7 hours (for example, the hospital is opened at 9:00 and closed at 17:00, the daytime In the case of taking a break for 1 hour), the reservation frame is calculated as 7 hours / 71 people≈5.9 minutes / person. If the penalty coefficient λ is 100 (small patient tolerance for waiting time) and the optimal number of patients n ₀ is calculated to be 68 people, and the medical treatment time is 7 hours, the appointment frame is 7 hours / 68 people≈6 .2 minutes / person required. For example, when there are a plurality of examination rooms, the number of patients accepted by each examination room can be obtained by dividing the obtained optimal examination number n ₀ by the number of examination rooms.

As described above, the reservation work support apparatus 1 determines the service provision time (individual patient's service provision time) of the individual recipient (patient) based on the actual service provision history (consultation results). A probability distribution of (consultation time) is generated, and a simulation based on this probability distribution is performed to predict the service provision time of each individual recipient (consultation time of each patient). Then, n _k (number of medical examinations) that maximizes the above-described objective function is obtained using this predicted value, and the optimum number of recipients n ₀ (optimal number of medical examinations) is obtained using this _nk .

In this way, by performing a simulation using a probability distribution based on the history of services actually performed, the difference in service provision time for each service provider (doctor) and the service provider is aware of the service provision time. manner such as when adjusted, it is possible to obtain the optimum donee number n ₀ in the form of friendly fine circumstances of providing site service.

In addition, by optimizing using the above formulas that can set the predetermined value λ and the target value P, the optimum number of recipients n ₀ is obtained in consideration of the detailed circumstances of the service providing site (medical site). Can do.

Furthermore, by setting the predetermined value λ of the objective function described above to a value according to the tolerance of the recipient's waiting time (examination waiting time), the optimum recipient is provided in consideration of the tolerance of the recipient's waiting time. The number n ₀ can be obtained.

  By the way, description of the above embodiment is for making an understanding of this invention easy, and does not limit this invention. The present invention can be changed and improved without departing from the gist thereof, and the present invention includes the equivalents thereof.

  For example, the above explanation has been made regarding a medical examination reservation business as an example of a reservation business when providing services to a plurality of recipients. For example, when using a playground equipment at a theme park or the like, or a process with a production line The present invention can be applied to various scenes in which reservation is made in advance and the service is enjoyed, such as the optimum number of pieces received per unit time from the previous process, and scenes in which the received quantity is planned and processed in advance.

It is the hardware constitutions of the information processing apparatus which implement | achieves the function of the reservation work assistance apparatus 1 of this invention. This is a function of the reservation service support apparatus 1 of the present invention. It is a flowchart explaining the process which sets the examination time (reservation frame) of each patient performed by the reservation work assistance apparatus 1 of this invention. It is an example of examination time performance data 251. It is an example of the extraction data 252. It is an example of the examination time distribution 253. It is an example of the expected value Ti of the examination time for every patient. It is an example of the distribution of the optimum examination number n _0.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Reservation work support apparatus 211 Condition reception part 212 Data extraction part 213 Distribution designation reception part 214 Examination time distribution generation part 215 Simulation execution part 216 Optimization condition reception part 217 Optimization calculation execution part 218 Optimal examination number output part 219 Reservation frame setting Part 251 Examination time result data 252 Extracted data 253 Examination time distribution 254 Expected value Ti of examination time for each patient Ti
255 Examination number n _k
256 Optimal consultation number n ₀

Claims (7)

An information processing apparatus that supports a reservation work when providing a service to a plurality of recipients,
Storage means for storing history data recording service provision history;
Data extracting means for extracting from the history data satisfying a predetermined condition;
Probability distribution generation means for generating a probability distribution of service provision time, which is the time required for the service of each individual recipient, based on the history data extracted by the data extraction means;
A simulation execution means for generating an expected value Ti (i = 1, 2, 3,...) Of the service provision time of each recipient by performing a simulation according to the probability distribution;
Implementation means for summing the expected value Ti of the service provision time of each individual recipient,
When _nk is a variable, the target value of the total service provision time is P, and λ is a predetermined value, each time the simulation is performed, the _nk and the expected value Ti (i = 1, 1). , N _k ), a function f (x) of a deviation x between the total value of service provision times determined from the target value P and f (x) is x ² , max [x, 0], | x |, or (x) ^m (m is a natural number)) and the above-mentioned n _k (k = 1, 2 ) that maximizes the objective function F (n _k ) , which is a difference from the value obtained by multiplying the above λ. , 3...)
The optimum number of recipients, which is the optimum value of the total number of recipients who receive the service , based on a value obtained from n _k (k = 1, 2, 3...) Obtained every time the simulation is performed. the information processing apparatus characterized by comprising an optimum donee number calculation means for calculating a n _0. The information processing apparatus according to claim 1,
The information processing apparatus according to claim 1, wherein the predetermined value λ is determined according to a tolerance of the waiting time of the recipient. The information processing apparatus according to claim 1,
The probability distribution generated by the probability distribution generation means is at least one of a distribution of the history data itself, a lognormal distribution based on the history data, or a distribution statistically approximated to the probability distribution of the history data. An information processing apparatus characterized by The information processing apparatus according to claim 1,
By dividing the optimum donee number n ₀ at the target value P, the information processing apparatus further comprising a reservation frame setting means for determining a service providing time of each of the providers.   The information processing apparatus according to claim 1, wherein the service is a doctor's examination, the recipient is a patient, and the appointment work is an examination appointment work. The information processing apparatus according to claim 1,
The objective function F (n _k ) is one of the following expressions

An information processing apparatus characterized by the above. In the information processing device,
A function for storing history data that records service provision history;
A function of extracting a predetermined condition from the history data;
A function for generating a probability distribution of service provision time, which is the time required for the service of each individual recipient, based on the history data extracted by the data extraction means;
A function of generating predicted values Ti (i = 1, 2, 3,...) Of service providing times of individual recipients by performing a simulation according to the probability distribution;
A function of summing the expected value Ti of the service provision time of each individual recipient,
A function f (x) of a deviation x between a total value of service provision times obtained from the predicted value Ti and the target value P (where f (x) is x ² , max [x, 0], | x |, Alternatively, the value of n _k (k = 1, 2, 3...) That maximizes the objective function (n _k ) , which is the difference from the value obtained by multiplying (x) ^m (m is a natural number) by the λ. The desired function,
The optimum number of recipients, which is the optimum value of the total number of recipients who receive the service, based on a value obtained from n _k (k = 1, 2, 3...) Obtained every time the simulation is performed. program for realizing a function of obtaining a n _0.

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