A device, method, and program for managing multiple patients who visit a pharmacy.

Abstract

A method for managing multiple patients who visit a pharmacy, which determines whether or not they have a chronic disease and enables the management of patients with chronic diseases. [Solution] First, the device 100 acquires multiple prescription information (S201). Next, the device 100 determines whether each prescription information contains a single drug that represents a chronic disease on its own (S202). Next, if the device 100 determines that there is no single drug that represents a chronic disease on its own, it determines whether the prescription information contains a set of drugs that represent a chronic disease in combination (S203). Then, the device 100 determines that patients associated with prescription information containing a single drug or a set of drugs are chronic disease patients, and calculates the return visit rate within a predetermined period for one or more determined chronic disease patients (S204).

Description

Technical Field

[0001] The present invention relates to an apparatus, a method, and a program therefor for managing a plurality of patients who have visited a pharmacy.

Background Art

[0002] Diseases include those that can be cured in one visit and those that require a follow-up visit for continuous treatment. For example, in the case of a cold, if the patient recovers from the cold, subsequent hospital visits and pharmacy visits are unnecessary. On the other hand, in the case of hypertension, due to the need to continue treatment as a lifestyle disease, subsequent hospital visits and pharmacy visits are expected.

Summary of the Invention

Problems to be Solved by the Invention

[0003] There are also not a few patients who interrupt treatment on their own judgment despite the need for continuous treatment. This is particularly evident in chronic diseases such as lifestyle diseases that do not present symptoms such as pain. Alternatively, although the treatment has not been interrupted, the patient may go to another pharmacy. Currently, pharmacies conduct statistical management such as how many prescriptions are received per month, but these problems are due to the inability to manage whether the patient's disease is a chronic disease or not.

[0004] The present invention has been made in view of such problems, and an object thereof is to provide an apparatus, a method, and a program therefor for managing a plurality of patients who have visited a pharmacy, which can determine whether a disease is a chronic disease and manage patients with chronic diseases.

Means for Solving the Problems

[0005] To achieve this objective, a first aspect of the present invention is a method for managing multiple patients who visit a pharmacy, comprising the steps of: acquiring multiple prescription information; determining whether each prescription information includes one or more drugs that represent a chronic disease, either individually or in combination; and calculating the number of patients with chronic diseases who revisited the pharmacy within a predetermined period of time, or a corresponding value, among the one or more prescription information determined to include the one or more drugs.

[0006] Furthermore, a second aspect of the present invention is the method of the first aspect, wherein the value is the return visit rate or discontinuation rate within a predetermined period for the one or more chronic disease patients.

[0007] Furthermore, a third aspect of the present invention is the method of the first or second aspect, wherein the calculation is performed separately according to the past visit history of each of the one or more chronic disease patients.

[0008] Furthermore, a fourth aspect of the present invention is a method according to any of the first to third aspects, wherein the predetermined period is a period based on the prescription duration of at least some of the one or more drugs.

[0009] Furthermore, a fifth aspect of the present invention is a method according to any one of the first to fourth aspects, further comprising the step of generating intervention support information for intervening in at least one of the one or more patients with chronic diseases.

[0010] Furthermore, a sixth aspect of the present invention is a method according to the fifth aspect, further comprising the step of determining the priority of the intervention.

[0011] Furthermore, a seventh aspect of the present invention is the method of the sixth aspect, further comprising the step of predicting when the patient will return to the pharmacy, wherein the priority is given higher to patients who have passed the return visit date but before the predetermined period has elapsed than to patients who have passed the predetermined period.

[0012] Furthermore, an eighth aspect of the present invention is a method according to any fifth to seventh aspect, wherein the intervention support information includes a telephone number used for the intervention.

[0013] Furthermore, a ninth aspect of the present invention is a method according to any fifth to eighth aspect, further comprising the step of calculating the number of patients who have received intervention among the one or more chronic disease patients, or a corresponding value, who have returned to the pharmacy within a predetermined period.

[0014] Furthermore, a tenth aspect of the present invention is a method according to any of the first to ninth aspects, wherein the determination step includes a first step of determining whether each prescription information contains a single drug that represents a chronic disease on its own, and a second step of determining, if the single drug is not included, whether each prescription information contains a set of drugs that represent a chronic disease in combination.

[0015] Furthermore, an eleventh aspect of the present invention is the method of the tenth aspect, wherein the determination of whether or not the set of drugs is included is performed only when the single drug is not included.

[0016] Furthermore, a twelfth aspect of the present invention is a method according to the tenth or eleventh aspect, wherein the determination of whether or not the set of drugs is included is made using the prescription durations of at least some of the drugs included in each prescription information.

[0017] Furthermore, a thirteenth aspect of the present invention is the method of the eleventh or twelfth aspect, wherein the determination of whether or not the set of drugs is included is made using an estimation model generated by machine learning.

[0018] Furthermore, a fourteenth aspect of the present invention is a program for causing a computer to perform a method for managing multiple patients who have visited a pharmacy, the method comprising the steps of: acquiring multiple prescription information; determining whether each prescription information includes one or more drugs that represent a chronic disease, either individually or in combination; and calculating the number of patients with chronic diseases who have revisited the pharmacy within a predetermined period of time, or a corresponding value, among the one or more prescription information determined to include the one or more drugs.

[0019] Furthermore, a fifteenth aspect of the present invention is a device for managing multiple patients who visit a pharmacy, which acquires multiple prescription information, determines whether each prescription information includes one or more drugs that represent a chronic disease, either individually or in combination, and calculates the number of patients with chronic diseases who revisited the pharmacy within a predetermined period of time, or a corresponding value, among the one or more prescription information that is determined to include the one or more drugs. [Effects of the Invention]

[0020] According to one aspect of the present invention, it becomes possible to quantitatively manage patients at a pharmacy by inferring whether or not multiple patients who visit the pharmacy have a chronic disease based on multiple prescription information associated with each patient, and by calculating the number of patients with chronic diseases who revisited the pharmacy within a predetermined period or a corresponding value. [Brief explanation of the drawing]

[0021] [Figure 1] This figure shows a device for managing multiple patients who have visited a pharmacy according to a first embodiment of the present invention. [Figure 2] This figure shows the flow of a method for managing multiple patients who visit a pharmacy according to the first embodiment of the present invention. [Figure 3] This figure shows the return visit rate for patients with chronic diseases according to the first embodiment of the present invention. [Figure 4] This figure shows an example of an intervention support screen according to the first embodiment of the present invention. [Figure 5] The flowchart shows the method for calculating the conversion rate of interventions according to the third embodiment of the present invention. [Figure 6] The figure shows an example of an intervention and its results according to the third embodiment of the present invention.

Embodiments for Carrying Out the Invention

[0022] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0023] (First Embodiment) Fig. 1 shows an apparatus for managing patients who visit a pharmacy according to the first embodiment of the present invention. The apparatus 100 acquires a plurality of prescription information and estimates whether the patient associated with each prescription information has a chronic disease. In addition to the number of prescription information, that is, the number of patients who visit the pharmacy, it is possible to calculate the number of patients with chronic diseases.

[0024] The apparatus 100 includes a communication unit 101 such as a communication interface, a processing unit 102 such as a processor and a CPU, and a storage unit 103 including a storage device or a storage medium such as a memory and a hard disk. In the processing unit 102, it can be configured by executing a program for performing each process. The apparatus 100 may include one or more devices, computers or servers. Also, the program may include one or more programs, and can be recorded on a computer-readable storage medium to form a non-transitory program product. The program can be stored in a storage device or a storage medium such as a database 104 accessible via an IP network from the storage unit 103 or the apparatus 100, and can be executed in the processing unit 102. The data described as being stored in the storage unit 103 below may be stored in the database 104, and vice versa.

[0025] Prescription information can be generated by capturing a two-dimensional code representing the information written on a prescription received from a patient visiting the pharmacy using a computer equipped with an image sensor located in the pharmacy. Prescription information may also be generated by manual input into a computer located in the pharmacy. The generated prescription information can be input into device 100 directly or indirectly from the computer. Alternatively, prescription information can be input into device 100 by transmitting it to device 100 via an IP network such as the Internet. In any case, it is sufficient that prescription information, including the information written on the prescription, is input into device 100.

[0026] Figure 2 shows the flow of a method for managing multiple patients who visit a pharmacy according to the first embodiment of the present invention. First, the device 100 acquires multiple prescription information (S201). Next, the device 100 determines whether each prescription information includes a single drug that represents a chronic disease on its own (S202).

[0027] Each prescription entry includes at least one of the drug name and a drug identifier that identifies the drug, and may also include the number of days the drug is prescribed. Furthermore, each prescription entry includes at least one of the patient name or a patient identifier that identifies the patient associated with that prescription entry.

[0028] The above determination can be made by referring to a first correspondence between one or more drugs and the type of disease for which each drug is used, based on the acquired prescription information. These types include, for example, chronic, acute, and unknown. If the type of disease associated with any of the drugs included in the prescription information is chronic, then that drug can be determined to be a single drug representing a chronic disease.

[0029] For example, if a prescription includes PL Combination Granules, Loxonin Tablets 60mg, and Amaryl 1mg Tablets, it is determined that the prescription includes a single drug representing a chronic disease because Amaryl 1mg Tablets are used to treat diabetes, a chronic disease. PL Combination Granules are a combination cold medicine and therefore have acute properties, while Loxonin Tablets 60mg are an antipyretic and analgesic used for acute illnesses such as colds, as well as chronic illnesses such as rheumatoid arthritis and osteoarthritis. Therefore, it is unclear from the individual drug names whether the patient associated with the prescription has a chronic or acute illness.

[0030] The first correspondence can more generally be a correspondence between one or more drugs and whether or not each drug represents a chronic disease. Whether or not each drug represents a chronic disease can be described as representing, not representing, or unknown, or it can be described by the probability that each drug represents a chronic disease. For example, a threshold can be set for each drug or for all drugs, and if the probability is above or above the threshold, it can be determined that the drug represents a chronic disease. Alternatively, the first correspondence can be a correspondence between one or more drugs, the number of days each drug is prescribed, and whether or not each drug represents a chronic disease, and the differences in applicable diseases can be distinguished according to the number of days prescribed. As an example, the first correspondence may be a predictive model generated by machine learning using combinations of drugs, their prescription days, and labels indicating whether or not they represent a chronic disease as training data.

[0031] Next, if the device 100 determines that there are no single drugs that represent a chronic disease on their own, it determines whether the prescription information includes a set of drugs that represent a chronic disease in combination (S203). Even if it is unclear whether a drug represents a chronic disease on its own, it may represent a chronic disease in combination, and this determination can be made by referring to a second correspondence between one or more sets of drugs and whether each set of drugs represents a chronic disease.

[0032] The determination referencing the second correspondence based on multiple drugs included in the prescription information may be performed only when the prescription information acquired by the device 100 does not contain a single drug that represents a chronic disease on its own, or it may be performed even when a single drug that represents a chronic disease on its own is included. Furthermore, the second correspondence may be referenced not only on the multiple drugs included in the prescription information, but also on the prescription duration of at least some of those multiple drugs. As an example, the second correspondence may be a predictive model generated by machine learning using combinations of multiple drugs and their prescription durations and labels indicating whether or not they represent a chronic disease as training data.

[0033] The device 100 then determines that patients associated with prescription information containing a single drug or a set of drugs are patients with chronic diseases, and calculates the return visit rate within a predetermined period for one or more determined patients with chronic diseases (S204).

[0034] The prescribed period can be a set number of days common to all patients with chronic diseases, or it can be a period determined based on the number of days prescribed for a single drug or a set of drugs included in the prescription information associated with each patient with a chronic disease. For example, if a single drug representing a chronic disease is prescribed for 28 days, assuming the patient takes the medication from the prescription date, they would have finished taking the medication 28 days after the prescription date. In reality, patients may forget to take their medication, and some medication may remain after 28 days, with the patient continuing to take it. Therefore, the prescribed period can also be set by adding a predetermined number of days to the number of days prescribed. In this specification, the period during which medication may have continued beyond the number of days prescribed from the prescription date is sometimes referred to as the "suspected continuation" period. In any case, the prescribed period is set based on the number of days prescribed, and if the patient returns to the pharmacy within that prescribed period, it can be evaluated that treatment is continuing; otherwise, it can be evaluated that treatment has been interrupted and the patient has withdrawn.

[0035] Figure 3 shows the return visit rate according to the first embodiment of the present invention. In the return visit rate display screen 300 in Figure 3, for each month from May to July 2021, the number of patients with chronic diseases who visited the clinic in that month is used as the denominator, and the number of patients with chronic diseases who made a return visit within a predetermined period is used as the numerator to calculate the next return visit rate.

[0036] Regarding the denominator, the number of patients with chronic diseases, if the same patient visits the pharmacy multiple times in the same month and multiple prescription records are generated, they may or may not be counted as separate patients with chronic diseases. Similarly, if the same patient visits the pharmacy in the same month for a different chronic disease and multiple prescription records are generated, they may or may not be counted as separate patients with chronic diseases. Here, patients who visit the pharmacy on a monthly basis are treated as one group of patients, but they may be treated on different units.

[0037] In Figure 3, patients visiting the pharmacy each month are shown separately as new chronic disease patients and returning chronic disease patients. A new chronic disease patient is, for example, a patient whose past prescription information, associated with that patient, does not include prescription information containing a single drug or a set of drugs representing the same chronic disease, and for whom device 100 has not obtained such information. A returning chronic disease patient is, for example, a patient whose past prescription information, associated with that patient, includes prescription information containing a single drug or a set of drugs representing the same chronic disease, and for whom device 100 has obtained such information, and for whom the date of visit has not exceeded the prescribed period based on the prescription duration of the single drug or set of drugs included in that past prescription information. In Figure 3, patients whose past prescription information, associated with that patient, includes prescription information containing a single drug or a set of drugs representing the same chronic disease, has been obtained by device 100, and for whom the date of visit has exceeded the prescribed period based on the prescription duration of the single drug or set of drugs included in that past prescription information, are distinguished and displayed as returning new chronic disease patients. However, they may also be displayed without distinction from new chronic disease patients. Alternatively, as shown in Figure 3, the denominator may be the total number of chronic disease patients who visited the pharmacy each month, without distinguishing them based on their past visit history.

[0038] If a patient returns to the pharmacy within a specified period, the device 100 stores the fact of the return visit in association with the prescription information acquired during the previous visit. Whether or not a patient has returned can be determined, for example, by checking whether the prescription information acquired during the current visit includes one or more medications that represent the same chronic disease as the one or more medications determined to represent in the prescription information acquired during the previous visit. Furthermore, a return visit does not necessarily have to be to the same pharmacy; it is sufficient if the prescription information generated during the visit is obtainable from the device 100, for example, a visit to a different store operated by the same business operator.

[0039] As explained above, by inferring whether or not multiple patients who visit the pharmacy have a chronic disease based on multiple prescription information associated with each patient, and by calculating the return visit rate of patients with chronic diseases within a predetermined period, quantitative patient management becomes possible at that pharmacy.

[0040] The explanation so far has focused on calculating the return visit rate, but the same effect can be achieved by calculating the dropout rate, which is the percentage of chronic disease patients who did not visit the pharmacy within a specified period. Alternatively, instead of calculating the return visit rate or dropout rate, the pharmacy could calculate the number of chronic disease patients who visited the pharmacy or the number of patients who did not visit within a specified period. In either case, the pharmacy can understand the subsequent visit status of chronic disease patients who visited during a unit period such as one month, and achieve a similar effect. The number of patients who did not visit is a number that can be logically determined once the number of patients who visited is fixed, and is a value corresponding to the number of patients who visited. Similarly, the return visit rate and dropout rate are also values ​​corresponding to the number of patients who visited.

[0041] In the above explanation, the presence or absence of a drug that causes a chronic disease on its own and the presence or absence of a drug that causes a chronic disease in combination are described as being determined in separate processes. However, it is also acceptable to determine these in the same process without distinguishing between them.

[0042] (Second embodiment) The device 100 according to the first embodiment enables pharmacies to quantitatively understand patients with chronic diseases, and the pharmacy may want to take action to encourage patients with chronic diseases to return to the pharmacy. Therefore, in this embodiment, the device 100 further generates intervention support information for at least one of one or more patients with chronic diseases.

[0043] Figure 4 shows an example of an intervention support screen according to a second embodiment of the present invention. The intervention support screen 400 is for supporting intervention for at least one of one or more patients who are presumed to have a chronic disease based on prescription information, and more specifically, it shows patients who have not returned to the pharmacy after a predetermined period has elapsed since the prescription date included in the prescription information. This makes it possible to individually determine one or more patients who should be encouraged to return to the pharmacy.

[0044] Figure 4 shows the patient's status as of June 17, 2021. Patient Masaji Sakai was scheduled to finish taking the medication prescribed on June 2, and 15 days have passed since then, so it is preferable for the pharmacy to intervene and encourage him to return to the pharmacy. If the false continuation period is set at 30 days, patient Tokuko Ozawa has not only exceeded the prescribed number of days but has also exceeded the false continuation period, making it highly likely that she has discontinued treatment, and therefore has a lower priority for intervention than patients who have not yet exceeded the false continuation period. Patient Tadaharu Shimabukuro is similar to patient Tokuko Ozawa in terms of the time elapsed since the scheduled visit, but has not returned to the pharmacy despite intervention by telephone from the pharmacy pharmacist on June 2, so his priority is rated even lower. Patient Yoshinori Shimura has exceeded the first additional period of false continuation, which is longer than a second additional period such as 60 days, so his priority is rated lower than patients who have exceeded the first additional period. In this way, the device 100 determines the priority of intervention as needed.

[0045] The device 100 may also predict when the patient will return to the pharmacy, and this is shown as the next scheduled visit date on the intervention support screen 400. The scheduled return visit date may be set, for example, as the day after the prescription date when the prescribed number of days have elapsed, or within a few days before or after that date. To improve accuracy, a predictive model may be generated by machine learning using combinations of a single drug and its prescription duration, or a set of drugs and their prescription durations, and the next visit date as training data.

[0046] The intervention support screen 400 can be viewed by receiving the HTML-formatted intervention support information generated by the device 100 on a terminal used by a pharmacist and displaying it in a web browser. Alternatively, it can be viewed by running an application installed on the terminal used by the pharmacist and displaying the intervention support screen 400 using the intervention support information generated by the device 100 within that application.

[0047] Pharmacists who view the intervention support screen 400 can intervene using means such as SMS, telephone, or chat. If the device 100 has stored the patient's phone number, that phone number can be displayed on the intervention support screen 400. Many patients at pharmacies are elderly, and intervention via SMS using their phone number is particularly effective.

[0048] Although the first embodiment describes a system where the pharmacy views the intervention support screen 400 to consider interventions after quantitatively understanding the condition of patients with chronic diseases using the method described above, depending on the needs of the pharmacy, the device 100 may also be configured to generate intervention support information without calculating return visit rates or other quantitative data.

[0049] (Third embodiment) A pharmacist who has viewed the intervention support screen 400 displayed according to the method of the second embodiment will individually intervene with one or more patients who should be encouraged to return to the pharmacy as appropriate. When an intervention is performed, the pharmacist can input intervention information, including the patient's name or patient identifier and the date of the intervention, into the device 100. If an intervention is possible through operations on the intervention support screen 300, the device 100 only needs to store the intervention information regarding the intervention that was performed.

[0050] Figure 5 shows the flow of a method for calculating the conversion rate of an intervention according to the third embodiment of the present invention. The device 100 acquires multiple prescription information (S501), and for each prescription information, it determines whether the prescription information contains one or more drugs that represent a chronic disease, either individually or in combination, as described in the first embodiment, and infers whether the disease of the patient associated with the prescription information is a chronic disease (S502). If it is determined that one or more drugs are included, intervention support information for intervention for the patient associated with the prescription information is generated and transmitted to a terminal used by the pharmacist (S503). The pharmacist performs interventions on the patient as appropriate, and the device 100 stores that the patient associated with each prescription information has returned to the pharmacy (S504). Then, the number of patients who returned to the pharmacy is calculated relative to the number of patients who received intervention (S505).

[0051] Figure 6 shows an example of an intervention and its results according to a third embodiment of the present invention. On the conversion rate display screen 600, there were 175 return visits for 201 interventions, resulting in a conversion rate of 82.4%. Although not shown in the figure, by including the pharmacist's name or pharmacist identifier in the intervention information, it becomes possible to calculate the conversion rate for each pharmacist. The values ​​to be calculated, with the number of patients who received the intervention as the denominator, can be the number of patients who returned, the number of patients who did not return, the return visit rate (which is the conversion rate), the dropout rate, etc., as in the first embodiment.

[0052] Furthermore, in the embodiments described above, unless the word "only" is used, such as "based only on XX," "according only to XX," or "in the case of XX only," it is assumed in this specification that additional information may also be considered. Also, as an example, the statement "if a, then b" does not necessarily mean "always b in the case of a" or "b immediately after a," unless explicitly stated otherwise. In addition, the statement "each a constituting A" does not necessarily mean that A is composed of multiple components, but includes the possibility that the component is singular.

[0053] Furthermore, for the sake of clarity, even if there are aspects of operation in some method, program, terminal, device, server, or system (hereinafter referred to as "method, etc.") that differ from the operation described herein, each aspect of the present invention is intended to cover the same operation as any of the operations described herein, and the existence of operation different from the operation described herein does not mean that such method, etc. is outside the scope of each aspect of the present invention.

[0054] Furthermore, the "start" and "end" shown in Figures 2 and 5 are merely examples, and do not necessarily mean that the method according to this embodiment will always start with S201 and S501, or always end with S204 and S505. [Explanation of Symbols]

[0055] 100 devices 101 Communications Department 102 Processing Unit 103 Storage section 104 Databases 300 Repeat visit rate display screen 400 Intervention support screen 600 Conversion Rate Display Screen

Claims

1. A method for managing multiple patients who visit a pharmacy, The computer retrieves multiple prescription information, The computer generates intervention support information for at least one of the patients who did not return to the pharmacy, among the one or more patients associated with one or more prescription records. Includes.

2. A program for causing a computer to perform a method for managing multiple patients who have visited a pharmacy, wherein the method is: The computer acquires multiple prescription information, The computer generates intervention support information for at least one of the patients who did not return to the pharmacy, among the one or more patients associated with one or more prescription records. Includes.

3. A device for managing multiple patients who visit a pharmacy, Obtain multiple prescription information, It is configured to generate intervention support information for at least one of the patients who did not return to the pharmacy, among the one or more patients associated with one or more prescription records.

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