Apparatus and method for ordering processing of commodity in medical institution, and program

Abstract

To provide an apparatus, a method, and a program for improving efficiency of ordering processing of a commodity in a medical institution.SOLUTION: In a commodity ordering method, an apparatus is configured to set a reference time point such as a reference date (S201). Then, the apparatus is configured to obtain (S202) predicted demand data up to the reference time point. The apparatus is configured to calculate a predicted stock quantity at the reference time point (S203) on the basis of the predicted demand data. Next, the apparatus is configured to determine whether or not the predicted stock quantity on the reference date is equal to or less than or less than a first stock quantity determined to be less than the reference stock quantity (S204). When the predicted stock quantity is equal to or less than or less than the first stock quantity, the apparatus is configured to determine an ordering quantity of a commodity so as to be equal to or more than difference between the first stock quantity and the predicted stock quantity (S205). Since each commodity has a minimum order unit, the order quantity is a multiple of the minimum order unit. Then, the apparatus is configured to transmit an ordering proposal of the determined ordering quantity to medical facility terminals (S206).SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an apparatus, a method, and a program for processing product orders in a medical institution. [Background technology]

[0002] Pharmacies and other medical institutions purchase medicines from wholesalers and other distributors, prepare one or more prescribed medicines as needed, and dispense them to patients who visit the pharmacy. Because medical institutions need to dispense medicines according to patient requests, they strive to maintain sufficient stock of both types and quantities.

[0003] Each drug is assigned a code to identify it. Even if the active ingredients are the same, different products may be assigned different codes if they are made by different manufacturers. In actual distribution, each product is sold in a certain unit, such as a sales packaging unit, which is the minimum order unit, or a primary packaging unit, which contains multiple products of the same sales packaging unit. Codes are also assigned to identify these packaging units, and a coding system called GS1 is used internationally. For example, a sales packaging unit consisting of 10 PTP packaging sheets containing 10 Loxonin 60 mg tablets is assigned the code "14987081105400" according to the GS1 system. Medical institutions specify these codes to purchase the required types and quantities of products. Summary of the Invention [Problem to be solved by the invention]

[0004] However, currently, medical institutions are unable to properly manage which types of products to order, how much to order, and when. Instead, they process orders based on past experience, which leads to inefficiencies such as running out of stock and having to request urgent deliveries, or, conversely, ending up with excess inventory.

[0005] The present invention has been made in view of the above problems, and its object is to improve the efficiency of product ordering processes in medical institutions. [Means for solving the problem]

[0006] In order to achieve this object, a first aspect of the present invention is a method for processing orders for products at a medical institution, comprising the steps of: setting a reference date; obtaining a first predicted value of the demand quantity at the medical institution on a daily or date / time basis for each product represented by a first code until the reference date; obtaining a second predicted value of the inventory quantity for each product on a daily or date / time basis until the reference date; calculating a predicted inventory quantity for each product after the close of business on the reference date based on the first predicted value and the second predicted value; determining for each product whether the predicted inventory quantity is less than or equal to a first inventory quantity that is less than a reference inventory quantity set for each product at the medical institution; and, if the determination result is positive, proposing to order an order quantity equal to or greater than the difference between the first inventory quantity and the predicted inventory quantity, at least the number of delivery days or delivery time required before the reference date.

[0007] A second aspect of the present invention is the method of the first aspect, wherein the first predicted value is an expected value.

[0008] A third aspect of the present invention is the method according to the first aspect, wherein the first predicted value is a lower limit value of a confidence interval obtained by interval estimation.

[0009] Furthermore, a fourth aspect of the present invention is a method according to any one of the first to third aspects, wherein the order quantity is a multiple of the quantity included in an order unit represented by a second code different from the first code.

[0010] A fifth aspect of the present invention is the method according to the fourth aspect, wherein the order quantity is equal to or greater than the difference between the reference stock quantity and the predicted stock quantity.

[0011] In addition, a sixth aspect of the present invention is a method of the fifth aspect, wherein the order quantity is less than or equal to the difference between a second inventory amount exceeding the standard inventory amount and the predicted inventory amount, which is determined for each product depending on the inventory amount that can be secured for all products at the medical institution.

[0012] In addition, a seventh aspect of the present invention is a method of any of the first to sixth aspects, comprising the steps of: acquiring actual values ​​of the demand quantity at the medical institution on that day in units of hours, minutes, or seconds for each product represented by the first code; calculating an estimated inventory quantity for each product on that day after the close of business on that day based on the actual values ​​for that day; determining for each product whether the estimated inventory quantity for that day is less than or equal to the first inventory quantity at the medical institution; and, if the determination result is positive, proposing to order for same-day delivery an order quantity equal to or greater than the difference between the first inventory quantity and the estimated inventory quantity for that day.

[0013] In addition, an eighth aspect of the present invention is a method for processing orders for products at a medical institution, comprising the steps of receiving an order request for a product represented by a first code from a medical institution terminal used by the medical institution, setting a reference date after the delivery date of the product ordered based on the order request, obtaining a first predicted value of the demand quantity of the product at the medical institution on a daily or daily basis until the reference date, obtaining a second predicted value of the inventory quantity of the product on a daily or daily basis until the reference date, calculating a predicted inventory quantity for each product after the close of business on the reference date based on the first predicted value and the second predicted value, determining whether the predicted inventory quantity is less than or equal to a first inventory quantity that is less than a reference inventory quantity set for each product at the medical institution, and if the determination result is positive, proposing to order an order quantity equal to or greater than the difference between the first inventory quantity and the predicted inventory quantity, the order being placed more than the required delivery days or required delivery time before the reference date.

[0014] In addition, a ninth aspect of the present invention is a program for causing a computer to execute a method for processing orders for products at a medical institution, the method including the steps of: setting a reference date; obtaining a first predicted value of the demand quantity at the medical institution on a daily or date / time basis for each product represented by a first code until the reference date; obtaining a second predicted value of the inventory quantity for each product on a daily or date / time basis until the reference date; calculating a predicted inventory quantity for each product after the close of business on the reference date based on the first predicted value and the second predicted value; determining for each product whether the predicted inventory quantity is less than or equal to a first inventory quantity that is less than a reference inventory quantity set for each product at the medical institution; and, if the determination result is positive, proposing to order an order quantity equal to or greater than the difference between the first inventory quantity and the predicted inventory quantity, at least the number of delivery days or time required for delivery before the reference date.

[0015] In addition, a tenth aspect of the present invention is a device for processing orders for products at a medical institution, which sets a reference date, obtains a first predicted value of the demand quantity at the medical institution on a daily or date / time basis for each product represented by a first code until the reference date, obtains a second predicted value of the inventory quantity for each product on a daily or date / time basis until the reference date, calculates a predicted inventory quantity for each product after the close of business on the reference date based on the first predicted value and the second predicted value, determines for each product whether the predicted inventory quantity is less than or equal to a first inventory quantity that is less than a reference inventory quantity set for each product at the medical institution, and if the determination result is positive, proposes ordering an order quantity equal to or greater than the difference between the first inventory quantity and the predicted inventory quantity, the order being placed more than the required delivery days or delivery time before the reference date. [Effects of the Invention]

[0016] According to one aspect of the present invention, the predicted inventory amount for each product on the reference date is compared with a first inventory amount set for each product at the medical institution, and an appropriate ordering suggestion is made if the predicted inventory amount is equal to or less than the first inventory amount, thereby reducing the possibility of inventory shortages for each product on the reference date. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a diagram showing a device for ordering products according to a first embodiment of the present invention. [Figure 2] FIG. 1 is a diagram showing the flow of a product ordering method according to a first embodiment of the present invention. [Figure 3] FIG. 3 is a diagram showing a change in inventory amount accompanying product ordering according to the first embodiment of the present invention. [Figure 4] FIG. 10 is a diagram for explaining a change in inventory amount accompanying a product order according to the second embodiment of the present invention. [Figure 5] FIG. 10 is a diagram showing the flow of a product ordering method according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0019] (First embodiment) 1 shows an apparatus for ordering products according to a first embodiment of the present invention. The apparatus 100 transmits an ordering proposal to a medical institution terminal 110 used by a medical institution based on predicted demand data, and after receiving an order request from the medical institution terminal 110, transmits order data to a distributor terminal (not shown) as necessary. The predicted demand data includes a predicted value of the demand quantity per day or per date for each product represented by a first code, and the order data includes a value of the order quantity per day or per date for each packaging unit identified by a second code corresponding to the first code.

[0020] The device 100 includes a communication unit 101 such as a communication interface, a processing unit 102 such as a processor or CPU, and a storage unit 103 including a storage device or storage medium such as a memory or hard disk, and can be configured by executing a program for performing each process. The device 100 may include one or more devices, computers, or servers. The program may include one or more programs, and may be recorded on a computer-readable storage medium to form a non-transitory program product. The program may be stored in a storage device or storage medium accessible from the storage unit 103 or the device 100, and executed by the processing unit 102. FIG. 1 illustrates a database 104 as a storage device or storage medium accessible from the device 100. The database 104 may be a component constituting the device 100, and the data stored therein may be stored in the storage unit 103.

[0021] Database 104 stores inventory data that associates first codes with inventory amounts of products represented by the first codes. When an ordered product arrives, the inventory amount of the product increases, and when a product prescribed to a patient is sold and shipped, the inventory amount of the product decreases. For example, the inventory amount after business hours the next day is calculated by adding the inventory amount at the calculation time of the current day to the predicted in-stock amount from the calculation time of the current day until the close of business the next day, and subtracting the predicted out-stock amount from the calculation time of the current day until the close of business the next day. More generally, the predicted inventory amount at the reference time point the next day is calculated by adding the inventory amount at the calculation time of the current day to the predicted in-stock amount from the calculation time of the current day to the reference time point the next day, and subtracting the predicted out-stock amount from the calculation time of the current day to the reference time point the next day. Even more generally, the predicted inventory amount at the reference time point is calculated by adding the inventory amount at the calculation time point to the predicted in-stock amount from the calculation time point to the reference time, and subtracting the predicted out-stock amount from the calculation time point to the reference time point, where the reference time point may be a date and time several days later or a date and time after the calculation time point of the current day. Also, in this specification, "stocking" means that goods are received and added to inventory, and "shipping" means that goods are sold and removed from inventory.

[0022] The device 100 according to this embodiment determines the date on which to order a product so that the predicted inventory amount of the product at the reference time point is not equal to or less than the first inventory amount, thereby efficiently preventing inventory shortages. This will be described in detail below. In this specification, the term "reference inventory amount" refers to a standard inventory amount determined for each product by a medical institution, the term "first inventory amount" refers to an inventory amount less than the reference inventory amount determined for each product by a medical institution, and the term "second inventory amount" refers to an inventory amount exceeding the reference inventory amount determined for each product by a medical institution. The first inventory amount may be, for example, a safety inventory amount. The second inventory amount may be, for example, a maximum inventory amount for the product determined based on the maximum inventory amount that can be secured for all products at the medical institution.

[0023] First, the device 100 sets a reference time point such as a reference date (S201). For example, the reference time point may be set to a time point after the closing time of the next day. Next, the device 100 acquires predicted demand data up to the reference time point (S202). The predicted demand data may be generated using various data, such as past delivery history data, order history data, and prescription data, of the medical institution that processes the order, either alone or in combination. It is also possible to use data from medical institutions other than the medical institution. The predicted demand data may be received by the device 100 via a computer network or may be generated by the device 100 itself.

[0024] The forecast demand data is, for example, a forecast value of the demand quantity for each product on a daily or daily basis represented by a first code, where the first code is a code for identifying each product in inventory management. Specifically, a YJ code or a unique management code may be used. For example, the forecast value of the demand quantity may be expressed as an expected value, an interval estimate, or the lower limit of a confidence interval based on the interval estimate.

[0025] The device 100 calculates the predicted inventory quantity at the reference time point based on the predicted demand data (S203). When ordering a product, for example, the delivery date or delivery time is determined depending on the supplier. Therefore, by associating the delivery date or delivery time of each ordered product with order data in the database 104, the device 100 can predict the quantity of each product scheduled to be stocked between the calculation time point and the reference time point by accessing the order data before stocking and the associated delivery date or delivery time. Since the predicted outbound volume up to the reference time point can be predicted based on the predicted demand data, the device 100 can calculate the predicted inventory quantity at the reference time point. The delivery date or delivery time may be included as part of the order data as needed. Furthermore, if the reference time point is after or before business hours, the delivery time is not required, but only the delivery date is required. Furthermore, the demand quantity is not required, but only the outbound volume on a daily basis is required. Furthermore, the inventory quantity at the time of calculation can be the actual inventory quantity at that time or an amount corresponding to it, and does not necessarily have to be the inventory quantity at that time exactly. Here, when the upper limit value of the confidence interval obtained by interval estimation is used as the predicted value of the demand quantity, the predicted inventory quantity becomes the lower limit value of that confidence interval. For simplicity, the reference point will be referred to as the reference day after the closing time of business on the reference day including the reference point, but it should be noted that the present invention is also applicable when the reference point is a time during business hours.

[0026] Next, device 100 determines whether the predicted inventory quantity on the reference date is equal to or less than the first inventory quantity (S204). The first inventory quantity may be defined for each product as a quantity that should not fall below that quantity and stored in database 104. While this determination can be made on the same day or several days later, for simplicity, the following description assumes the reference date to be after the closing time of business several days later. Furthermore, while the period from ordering to delivery may vary depending on the supplier and the product, it is assumed that if an order is placed by a predetermined time on the same day, delivery will occur by the closing time of business the following day, and the predicted inventory quantity is calculated before that predetermined time.

[0027] If the predicted inventory amount is equal to or less than the first inventory amount, the device 100 determines an order quantity for the product so that the order quantity is equal to or greater than the difference between the first inventory amount and the predicted inventory amount (S205). Since each product has a minimum order unit, the order quantity is a multiple of the minimum order unit. The device 100 then transmits an order proposal for the determined order quantity to the medical institution terminal 110 (S206). The order proposal preferably includes an order deadline date or date and time that is at least the required delivery days or required delivery time before the reference date, so that the product will be in stock by the reference date.

[0028] After receiving an order request corresponding to the order proposal from the medical institution terminal 110, the device 100 can generate order data corresponding to the order proposal and transmit it to the seller terminal. The generation of order data may be performed simultaneously with or before the transmission of the order proposal. The device 100 may receive an order request with content different from the order proposal and, if necessary, transmit order data corresponding to the received content to the seller terminal. As an example, the order proposal may be transmitted as HTML format data with changeable order conditions on the display screen of the medical institution terminal 110, and an order request for a quantity different from the determined order quantity included in the order proposal may be received. It is also possible that the order quantity is not determined in the device 100 and the order proposal does not include a specified order quantity. Similarly, the delivery deadline may be variable or not included at all.

[0029] If the predicted inventory amount is greater than or equal to the first inventory amount, device 100 may reset the base date, for example by incrementing the base date. If the base date is reset, the same process is repeated. Also, even if the predicted inventory amount is greater than or equal to the first inventory amount, if a predetermined condition is met, device 100 may proceed to determining the order quantity and transmitting an order proposal.

[0030] FIG. 3 shows a schematic diagram of inventory fluctuations resulting from ordering processing according to this embodiment. The horizontal axis represents the date, and the vertical axis represents the inventory amount after closing time. Here, the expected inventory amount is an interval estimate, with the solid line representing the expected value, the dotted line above the solid line representing the upper limit of the confidence interval, and the dotted line below the solid line representing the lower limit of the confidence interval. As the medical institution's business days progress, the expected inventory amount decreases. If it is determined that the first inventory amount, which is set to a level below the reference inventory amount on the reference date, falls below the lower limit, the required delivery date is assumed to be one day, and the required order date is one business day before that. By placing an order on the required order date, the ordered quantity of goods is received on the reference date the following day, preventing the lower limit of the confidence interval from falling below the minimum inventory amount, as shown in the figure.

[0031] The order quantity is preferably a multiple of the quantity included in the order unit represented by a second code, such as a GS1 code, different from the first code, and the ordered quantity will be equal to or greater than the reference inventory quantity when it is received. In the illustrated example, a quantity is ordered such that the expected value of the forecasted inventory quantity exceeds the reference inventory quantity.

[0032] Furthermore, it is preferable to determine the order quantity so that the predicted value of the predicted inventory amount is equal to or less than the second inventory amount of the target medical institution. In the illustrated example, if the expected value is the predicted value, the inventory amount exceeds the reference inventory amount and is less than the second inventory amount, but if the upper limit of the confidence interval is the predicted value, the inventory amount exceeds the second inventory amount. In order to increase the possibility of avoiding the risk that the inventory amount will exceed the second inventory amount, it is preferable to set the upper limit to be equal to or less than the second inventory amount.

[0033] As mentioned above, since the order quantity is a multiple of the quantity included in the order unit represented by the second code, it is not preferable to place an additional order until the ordered quantity is received and is equal to or less than the second inventory amount. In Figure 3, the orderable date represents the first day when the next day's expected inventory amount plus the quantity of the minimum order unit is equal to or less than the second inventory amount.

[0034] As explained above, by comparing the predicted inventory quantity for each product on the reference date with a first inventory quantity that is less than the standard inventory quantity set for each product at the medical institution, and making an order proposal if the predicted inventory quantity is less than or equal to the first inventory quantity, the possibility of running out of inventory for each product on the reference date can be reduced.

[0035] (Second embodiment) FIG. 4 is a diagram illustrating fluctuations in inventory due to ordering processing according to this embodiment. The horizontal axis represents the date, and the vertical axis represents the inventory amount after closing time. The inventory amount of a certain product decreases from February 1st, an order is placed on February 5th, and an amount that reaches the standard inventory amount is received on February 6th. After that, the inventory amount decreases and increases repeatedly, and by February 16th, it has fallen below the first inventory amount. This is not expected to occur if ordering processing according to this embodiment is performed, but it can occur if the demand amount on the 16th greatly exceeds expectations. In such a case, the medical institution needs to request an urgent delivery during business hours on the 16th. To this end, in the second embodiment, the actual value of the change in inventory amount on the day in units of hours, minutes, or seconds is acquired (S501), and it is determined whether the estimated inventory amount after the closing time estimated based on the actual value (S502) will be equal to or less than the first inventory amount (S503), and if the determination result is positive, the device 100 determines the order quantity (S504) and transmits an order proposal based on the delivery conditions for same-day delivery to the medical institution terminal 110 (S505). The inventory quantity and order quantity can be determined by any of the methods described in the first embodiment.

[0036] As in the first embodiment, the device 100 may receive an order request with content different from the order proposal and, if necessary, transmit order data corresponding to the received content to the seller terminal. For example, the order proposal may be transmitted as HTML format data with changeable order conditions on the display screen of the medical institution terminal 110, and an order request for a quantity different from the determined order quantity included in the order proposal may be received. It is also possible that the order quantity is not determined in the device 100, and the order proposal does not include a specified order quantity. Similarly, the delivery deadline may be variable or not included at all.

[0037] (Third embodiment) In the second embodiment, a proposal to place an order on a mandatory order date is mainly described as being sent to the medical institution terminal 110, but in the third embodiment, a proposal to delay the order is made in cases where a medical institution makes an order request in advance. Specifically, when the device 100 receives an order request for a product represented by a first code from the medical institution terminal 110, it sets a base date that is either before or after the delivery date of the order based on the order request. Thereafter, the same processing as in the second embodiment is performed.

[0038] If the base date is set after the delivery date of the order based on the order request, the resulting order proposal sent from the device 100 to the medical institution terminal 110 will be an order with a delivery date later than the original delivery date. If the base date is set to the same as the delivery date of the order based on the order request, when the expected inventory amount is less than the first inventory amount, the delivery date will be the same even if an order proposal is sent, so it is preferable to proceed with the order based on the original order request without sending an order proposal. Also, if the order amount based on the order request is less than the difference between the first inventory amount and the expected inventory amount on the base date, an order proposal with a more preferable order amount may be sent even if the delivery date is the same.

[0039] In this way, it is possible to reduce the frequency of deliveries to a medical institution by sending an order proposal with a delayed delivery date when possible in response to an order request received from the medical institution terminal 110. For a medical institution, optimizing the frequency of deliveries reduces the workload of pharmacies, leading to reduced labor costs.

[0040] Furthermore, reducing delivery frequency also reduces the workload of distributors, who can offer a certain discount on product prices if the delivery frequency is reduced. Therefore, one example of an order proposal for a delayed delivery date could include a discount on the product price, which can increase the likelihood that a medical institution will accept the order proposal for a delayed delivery date.

[0041] It should be noted that in the above embodiments, unless the word "only" is used, such as "based only on," "depending only on," or "only in the case of," this specification assumes that additional information may also be taken into consideration. Also, as an example, it should be noted that the phrase "do b when a" does not necessarily mean "always do b when a" or "do b immediately after a" unless explicitly stated otherwise. Furthermore, the phrase "each a constituting A" does not necessarily mean that A is composed of multiple components, but includes the case where the component is singular.

[0042] Also, just to be clear, even if there is an aspect of a method, program, terminal, device, server, or system (hereinafter referred to as a "method, etc.") that performs an operation different from that described in this specification, each aspect of the present invention is directed to an operation that is identical to one of the operations described in this specification, and the existence of an operation different from that described in this specification does not make the method, etc. outside the scope of each aspect of the present invention.

[0043] Furthermore, the "start" and "end" shown in FIG. 2 are merely examples, and do not necessarily mean that the method according to this embodiment starts at S201 or ends at S205. [Explanation of symbols]

[0044] 100 devices 101 Communications Department 102 Processing section 103 Storage section 104 Database 110 Medical Institution Terminals

Claims

1. A method for processing an order for a product at a medical institution, comprising: A step in which a computer sets a reference date; The computer acquires a first predicted value of the demand quantity for each product at the medical institution up to the reference date; The computer acquires a second forecast value of the inventory quantity for each of the products up to a reference date; calculating a predicted inventory quantity on the reference date based on the first predicted value and the second predicted value by the computer; a step of determining by the computer whether the predicted inventory amount is equal to or less than a first inventory amount determined for each product; when the determination result is affirmative, the computer proposes to order an amount equal to or greater than the difference between the first inventory amount and the predicted inventory amount; Includes:

2. 10. The method of claim 1, The method further includes a step in which the computer transmits an order proposal with a delayed delivery date for the product if the determination result is negative.

3. 3. The method of claim 1 or claim 2, receiving an order request from a medical institution terminal by the computer; sending an order proposal with a more preferable order quantity when the order quantity based on the order request is less than the difference between the first inventory quantity and the predicted inventory quantity on the reference date; Further includes:

4. A program for causing a computer to execute a method for processing an order for a product at a medical institution, the method comprising: setting a reference date; obtaining a first predicted value of the demand quantity for each product at the medical institution up to the reference date; obtaining a second forecast value of the inventory quantity for each of the products up to a reference date; calculating a predicted inventory amount on the reference date based on the first predicted value and the second predicted value; determining whether the predicted inventory amount is equal to or less than a first inventory amount determined for each product; If the determination result is positive, proposing to order an amount equal to or greater than the difference between the first inventory amount and the predicted inventory amount; Includes.

5. A device for processing product orders at a medical institution, Set the base date, obtaining a first predicted value of the demand quantity for each product at the medical institution up to the reference date; obtaining a second forecast value of the inventory quantity for each of the products up to the reference date; calculating a predicted inventory amount on the reference date based on the first predicted value and the second predicted value; determining whether the predicted inventory amount is equal to or less than a first inventory amount determined for each product; If the determination result is positive, the computer proposes to order an amount equal to or greater than the difference between the first inventory amount and the predicted inventory amount.

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