Device, method, and program for managing plural patients who visited pharmacy

Abstract

To provide a method for managing plural patients who visited a pharmacy, the method determining whether the patients have a chronic disease and managing patients if they have a chronic disease.SOLUTION: A device 100 first acquires plural pieces of prescription information (S201). Then, the device 100 determines whether each piece of prescription information includes a single medicine which indicates a chronic disease on its own (S202), and determines whether the prescription information includes a pair of medicines which indicate a chronic disease by combination (S203) if the device 100 has determined that there is no single medicine which indicates a chronic disease on its own.SELECTED DRAWING: Figure 2

Description

[Technical field]

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

[0002] There are diseases that can be treated in one visit, and diseases that require repeat visits for continued treatment. For example, in the case of a cold, once the patient recovers from the cold, there is no need for further visits to the hospital. On the other hand, in the case of high blood pressure, it is expected that further visits will be required due to the need to continue treatment as it is a lifestyle-related disease. Summary of the Invention [Problem to be solved by the invention]

[0003] Even though continuous treatment is necessary, many patients discontinue treatment of their own volition. For example, this is particularly noticeable in chronic diseases such as lifestyle-related diseases that are not accompanied by symptoms such as pain. In other cases, patients may go to another pharmacy even though their treatment is not discontinued. Currently, pharmacies manage statistics such as how many prescriptions are filled each month, but these problems arise from the fact that they are unable to manage whether a patient's disease is chronic or not.

[0004] The present invention has been made in consideration of these points, and its objective is to provide an apparatus, method, and program for managing multiple patients who visit a pharmacy, which can determine whether or not a patient has a chronic disease and manage patients with a chronic disease. [Means for solving the problem]

[0005] To achieve these objectives, a first aspect of the present invention is a method for managing a plurality of patient visits to a pharmacy, comprising obtaining a plurality of prescriptions and determining whether each prescription contains one or more medications that, either alone or in combination, are indicative of a chronic condition.

[0006] In addition, a second aspect of the present invention is the method of the first aspect, further comprising a step of calculating the number of patients who have returned to the clinic within a specified period of time among one or more chronic disease patients associated with one or more prescription information determined to contain the one or more drugs, or a value corresponding thereto.

[0007] A third aspect of the present invention is the method of the second aspect, wherein said value is a revisit rate or dropout rate of said one or more chronic disease patients within a predetermined period of time.

[0008] A fourth aspect of the present invention is the method according to the second or third aspect, wherein the calculation is performed separately according to a past visit history of each of the one or more chronic disease patients.

[0009] A fifth aspect of the present invention is the method according to the second or third aspect, wherein the predetermined period is based on the number of days for which at least a portion of the one or more drugs are prescribed.

[0010] In addition, a sixth aspect of the present invention is a method of any one of the first to third aspects, further comprising a step of generating intervention support information for intervening in at least one patient among one or more chronic disease patients associated with one or more prescription information determined to contain the one or more drugs.

[0011] A seventh aspect of the present invention relates to the method of the sixth aspect, further comprising the step of determining a priority of the intervention.

[0012] An eighth aspect of the present invention is the method of the seventh aspect, further comprising a step of predicting a time when the patient will revisit the clinic, and the priority is given to a patient who has passed the time to revisit but before the specified period has elapsed, higher than a patient who has passed the specified period.

[0013] A ninth aspect of the present invention is the method according to the sixth aspect, wherein the intervention support information includes a telephone number to be used for intervention.

[0014] In addition, a tenth aspect of the present invention is the method of the sixth aspect, further comprising a step of calculating the number of patients who have undergone intervention among the one or more chronic disease patients and who have returned to the clinic within a specified period of time, or a value corresponding thereto.

[0015] In addition, an eleventh aspect of the present invention is the method of any one of the first to third aspects, wherein the determining step includes a first step of determining whether each of the prescription information includes a single drug that alone represents a chronic disease, and if the single drug is not included, a second step of determining whether each of the prescription information includes a set of drugs that in combination represent a chronic disease.

[0016] A twelfth aspect of the present invention is the method of the eleventh aspect, wherein the determination of whether the set of drugs is included is performed only if the single drug is not included.

[0017] A thirteenth aspect of the present invention is the method of the eleventh aspect, wherein the determination of whether the set of drugs is included is made using the prescription days of at least some of the multiple drugs included in each of the prescription information.

[0018] Further, a fourteenth aspect of the present invention is the method according to the eleventh aspect, wherein the determination of whether or not the set of drugs is included is performed using an estimation model generated by machine learning.

[0019] In addition, a 15th aspect of the present invention is a method of any one of the first to third aspects, further comprising a step of setting up automatic transmission of an intervention message to one or more chronic disease patients associated with one or more prescription information determined to contain the one or more drugs, the chronic disease patients meeting predetermined conditions.

[0020] A sixteenth aspect of the present invention is the method of the fifteenth aspect, wherein the predetermined condition is a new patient, a patient within a specified age range, a patient prescribed a specific medication, or a patient suspected of having a specific disease.

[0021] A seventeenth aspect of the present invention is the method according to the fifteenth aspect, wherein the predetermined condition is that the patient has not visited the clinic even after a predetermined number of days have passed since the next scheduled visit.

[0022] An 18th aspect of the present invention is the method according to the 15th aspect, wherein the automatic transmission setting includes designating a transmission date and time that is a predetermined number of days after the next scheduled visit date.

[0023] In addition, a 19th aspect of the present invention is a program for causing a computer to execute a method for managing a plurality of patients visiting a pharmacy, the method including the steps of obtaining a plurality of prescription information and determining whether each prescription information includes one or more medications that, either alone or in combination, indicate a chronic disease.

[0024] In addition, a twentieth aspect of the present invention is an apparatus for managing a plurality of patients visiting a pharmacy, which obtains a plurality of prescription information and determines whether each prescription information includes one or more drugs that, either alone or in combination, indicate a chronic disease. Effect of the Invention

[0025] According to one aspect of the present invention, quantitative patient management at a pharmacy is enabled by predicting whether or not multiple patients who visit a pharmacy have a chronic disease based on multiple prescription information associated with each patient, and calculating the number of patients with chronic diseases who return to the pharmacy within a specified period of time or a value corresponding thereto. [Brief description of the drawings]

[0026] [Figure 1] FIG. 1 is a diagram showing an apparatus for managing a plurality of patients visiting a pharmacy according to a first embodiment of the present invention. [Diagram 2] FIG. 1 is a diagram showing the flow of a method for managing a plurality of patients who visit a pharmacy according to a first embodiment of the present invention. [Diagram 3]FIG. 2 is a graph showing the revisit rate of patients with a chronic disease according to the first embodiment of the present invention. [Figure 4] FIG. 11 is a diagram showing an example of an intervention support screen according to the second embodiment of the present invention. [Diagram 5] FIG. 13 is a diagram showing an example of an automatic transmission setting screen according to the third embodiment of the present invention. [Figure 6] 13 shows the flow of a method for calculating a conversion rate of an intervention according to a fourth embodiment of the present invention. [Figure 7] FIG. 13 is a diagram showing an example of an intervention and its outcome according to the fourth embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

[0028] (First embodiment) 1 shows a device for managing patients who visit a pharmacy according to a first embodiment of the present invention. The device 100 acquires a plurality of prescription information items and infers whether a patient associated with each prescription information item has a chronic disease or not. It is possible to calculate the number of prescription information items, i.e., the number of patients who visit the pharmacy, as well as the number of patients with chronic diseases.

[0029] 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 a hard disk, and can be configured by executing a program for performing each process or operation in the processing unit 102. The device 100 may include one or more devices, computers, or servers. The program may include one or more programs, and may be recorded in a computer-readable storage medium to form a non-transient program product. The program may be stored in a storage device or storage medium such as the storage unit 103 or a database 104 accessible from the device 100 via an IP network, and may be executed by at least one processor of the processing unit 102. Data described below as being stored in the storage unit 103 may be stored in the database 104, and vice versa.

[0030] The prescription information can be generated by capturing an image of a two-dimensional code representing information written on a prescription received from a patient visiting the pharmacy using a computer having an imaging element disposed in the pharmacy. The prescription information may also be generated by manual input to a computer disposed in the pharmacy. The generated prescription information can be input to the device 100 directly or indirectly from the computer. The prescription information can also be input to the device 100 by transmitting it to the device 100 via an IP network such as the Internet. In any case, it is sufficient that the prescription information including information written on the prescription is input to the device 100.

[0031] 2 shows a flow of a method for managing a plurality of patients who visit a pharmacy according to the first embodiment of the present invention. First, the device 100 acquires a plurality of pieces of prescription information (S201). Next, the device 100 determines whether each piece of prescription information includes a single drug that represents a chronic disease by itself (S202).

[0032] Each prescription information includes at least one of a drug name and a drug identifier that identifies the drug, and may include the number of days for which the drug is prescribed. Each prescription information also includes at least one of a patient name of a patient associated with each prescription information or a patient identifier that identifies the patient.

[0033] The above determination can be made based on the acquired prescription information by referring to a first correspondence between one or more drugs and the type of disease for which each drug is used. The types include, for example, chronic, acute, and unknown, and when the type of disease associated with any drug included in the prescription information is chronic, the drug can be determined to be a single drug representing a chronic disease.

[0034] For example, if prescription information includes PL Granules, Loxonin Tablets 60 mg, and Amaryl 1 mg Tablets as drugs, Amaryl 1 mg Tablets is a drug for the chronic disease of diabetes, and therefore it is determined that the prescription information includes a single drug that alone represents a chronic disease. PL Granules is a general cold medicine and therefore a drug with acute attributes, and Loxonin Tablets 60 mg is an antipyretic analgesic that can be used for acute diseases such as colds as well as chronic diseases such as rheumatoid arthritis and osteoarthritis, so it is unclear from the single drug name whether the disease of the patient associated with the prescription information is chronic or acute.

[0035] More generally, the first correspondence can be a correspondence between one or more drugs and whether each drug represents a chronic disease. Whether each drug represents a chronic disease can be described as representing, not representing, or unknown, and can also 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 in general, and a drug can be determined to represent a chronic disease when it is equal to or greater than the threshold. In addition, the first correspondence can be a correspondence between one or more drugs, the number of prescription days of each drug, and whether each drug represents a chronic disease, and can distinguish between different applicable diseases according to the number of prescription days. As an example, the first correspondence may be a prediction model generated by machine learning using a combination of a drug, its number of prescription days, and a label indicating whether or not the drug represents a chronic disease as training data.

[0036] Next, when it is determined that the prescription information does not include a single drug that represents a chronic disease by itself, the device 100 determines whether the prescription information includes a set of drugs that represents a chronic disease in combination (S203). Even if it is unclear whether a single drug represents a chronic disease, the combination of drugs may represent a chronic disease, 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.

[0037] The determination with reference to the second association based on the plurality of drugs included in the prescription information may be performed only when the prescription information acquired by the device 100 does not include a single drug that represents a chronic disease by itself, or may be performed when a single drug that represents a chronic disease by itself is included. The second association may be referenced based on the prescription days of at least some of the plurality of drugs in addition to the plurality of drugs included in the prescription information. As an example, the second association may be a prediction model generated by machine learning using a combination of the plurality of drugs, their prescription days, and a label indicating whether or not the plurality of drugs represents a chronic disease as training data.

[0038] The device 100 then determines that the patients associated with the prescription information including a single drug or a set of drugs are chronic disease patients, and calculates a revisit rate within a predetermined period of time for the determined chronic disease patients or patients (S204).

[0039] The predetermined period can be a predetermined number of days common to all chronic disease patients, or a period determined based on the number of prescription days of a single drug or a set of drugs included in the prescription information associated with each chronic disease patient. For example, if a single drug representing a chronic disease is prescribed for 28 days, the drug will be taken from the prescription date and will be taken 28 days after the prescription date. In reality, patients may forget to take the drug, and even after 28 days have passed, the drug may remain and the patient may continue taking the drug. Therefore, the period obtained by adding a predetermined number of days to the number of prescription days can be determined as the predetermined period. In this specification, the period during which the drug may be taken beyond the prescription date may be referred to as a "suspected continuation" period. In any case, the period determined based on the number of prescription days is determined as the predetermined period, and if the patient revisits the pharmacy within the predetermined period, the treatment is continued, and if not, the treatment is interrupted and withdrawn.

[0040] The revisit rate according to the first embodiment of the present invention is shown in Figure 3. In the revisit rate display screen 300 in Figure 3, for each month from May to July 2021, the next revisit rate is calculated by using the number of chronic disease patients among those who visited the pharmacy in that month as the denominator and the number of chronic disease patients who revisited within a specified period as the numerator.

[0041] Regarding the number of chronic disease patients, which is the denominator, if the same patient visits the pharmacy multiple times in the same month and multiple prescription information is generated, they may or may not be counted as different chronic disease patients. If the same patient visits the pharmacy for different chronic diseases in the same month and multiple prescription information is generated, they may or may not be counted as different chronic disease patients. Here, patients who visit the pharmacy on a monthly basis are considered to be one group of patients, but they may be considered in different units.

[0042] In FIG. 3, patients who visit the pharmacy each month are divided into new chronic disease patients and returning chronic disease patients. As an example, a new chronic disease patient refers to a patient whose past prescription information associated with the patient, including a single drug or a set of drugs representing the same chronic disease, has not been acquired by the device 100. As an example, a returning chronic disease patient refers to a patient whose past prescription information associated with the patient, including a single drug or a set of drugs representing the same chronic disease, has been acquired by the device 100, and whose visit date has not passed a predetermined period based on the number of prescription days of the single drug or set of drugs included in the past prescription information. In FIG. 3, a patient whose past prescription information associated with the patient, including a single drug or a set of drugs representing the same chronic disease, has been acquired by the device 100, and whose visit date has passed a predetermined period based on the number of prescription days of the single drug or set of drugs included in the past prescription information, is displayed as a new chronic disease patient who visits the pharmacy again, but may be displayed without being distinguished from a new chronic disease patient. In addition, instead of distinguishing patients with chronic diseases according to their past visit history as in Figure 3, the denominator may be the total number of patients with chronic diseases who visited the clinic each month.

[0043] When the patient revisits the pharmacy within a predetermined period, the revisit is stored in association with the prescription information acquired by the device 100 during the previous visit. Whether the patient has revisited the pharmacy can be determined, for example, by whether the prescription information acquired during the current visit contains one or more drugs that represent the same chronic disease as the chronic disease determined to be represented by one or more drugs included in the prescription information acquired during the previous visit. In addition, the revisit does not necessarily have to be a revisit to the same pharmacy, and it is sufficient that the prescription information generated during the visit can be acquired from the device 100. For example, the revisit may be to a different store operated by the same business operator.

[0044] As described above, by predicting whether or not multiple patients who visit a pharmacy have a chronic disease based on multiple prescription information associated with each patient and calculating the rate at which patients with chronic diseases return to the pharmacy within a specified period of time, quantitative patient management is possible at the pharmacy.

[0045] In the explanation so far, the revisit rate has been calculated, but the same effect can be obtained by calculating the withdrawal rate, which is the proportion of chronic disease patients who did not visit the pharmacy within a specified period. Also, even if the number of chronic disease patients who visited the pharmacy within a specified period or the number of chronic disease patients who did not visit the pharmacy is calculated instead of the revisit rate or withdrawal rate, the pharmacy can obtain the same effect by grasping the subsequent visit status of chronic disease patients who visited the pharmacy in a unit period such as one month. The number of patients who did not visit the pharmacy is a number that is logically determined when the number of patients who visited the pharmacy is determined, and is a value corresponding to the number of patients who visited the pharmacy. Similarly, the revisit rate and the withdrawal rate are values ​​corresponding to the number of patients who visited the pharmacy.

[0046] In the above explanation, the presence or absence of a drug that indicates a chronic disease alone and the presence or absence of a drug that indicates a chronic disease in combination are determined in separate processes, but these may also be determined in the same process without distinguishing between them.

[0047] Second embodiment The device 100 according to the first embodiment enables a pharmacy to quantitatively grasp the chronic disease patients, and the pharmacy may wish to intervene to encourage the chronic disease patients to return to the pharmacy. Therefore, in this embodiment, the device 100 further generates intervention support information for intervening with at least one of one or more chronic disease patients.

[0048] 4 shows an example of an intervention support screen according to the second embodiment of the present invention. The intervention support screen 400 is for supporting an intervention for at least one of one or more patients who are suspected to have a chronic disease based on prescription information, and more specifically, shows patients who have not revisited the clinic 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 revisit the clinic.

[0049] Figure 4 shows the status of patients as of June 17, 2021. A patient named Masatsugu Sakai is 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 the patient to return to the pharmacy. If the period of false continuation is set at 30 days, a patient named Noriko Ozawa has not only passed the number of prescription days, but also the false continuation period, and is likely to have discontinued treatment, so the priority of intervention is lower than that of patients before the false continuation period has passed. A patient named Chuji Shimabukuro is similar to a patient named Noriko Ozawa in terms of the time that has passed since the scheduled visit date, but has not returned to the pharmacy despite a phone call intervention by a pharmacist at the pharmacy on June 2, so the priority is evaluated to be even lower. A patient named Yoshinori Shimura has passed a second additional period, such as 60 days, which is longer than the first additional period, the false continuation period, and is evaluated to have a lower priority than patients who have passed the first additional period. In this manner, the device 100 determines the priority of intervention, if necessary.

[0050] The device 100 may 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 determined, for example, as the day on which the prescription days have passed since the prescription date or within a few days before or after that date, and in order to improve accuracy, it may be a prediction model generated by machine learning using as training data a combination of a single drug and its prescription days or a set of drugs and their prescription days, and the next visit date.

[0051] The intervention support screen 400 can be viewed by receiving the intervention support information in HTML format generated by the device 100 on a terminal used by a pharmacist and displaying it on a web browser. Alternatively, the intervention support screen 400 can be viewed by running an application installed on the terminal used by the pharmacist and displaying the intervention support screen 400 on the application using the intervention support information generated by the device 100.

[0052] A pharmacist who views the intervention support screen 400 can perform intervention using means such as SMS, telephone, chat, etc. If the patient's telephone number is stored in the device 100, the telephone number can be displayed on the intervention support screen 400. Since many of the patients at pharmacies are elderly, intervention by SMS using a telephone number is particularly effective.

[0053] In the above description, after quantitatively grasping the condition of a chronic disease patient using the method according to the first embodiment, the pharmacy considers intervention by viewing the intervention support screen 400. However, depending on the needs of the pharmacy, the device 100 may be configured to generate intervention support information without calculating the re-visit rate or the like for quantitative grasping.

[0054] (Third embodiment) In this embodiment, the device 100 automatically sets up an intervention for at least one of the one or more chronic disease patients instead of, or in addition to, generating intervention support information for intervening in at least one of the one or more chronic disease patients.

[0055] FIG. 5 shows an example of an automatic transmission setting screen for intervention according to this embodiment. The automatic transmission setting screen 500 is for setting automatic transmission of a message for intervention by means of SMS, e-mail, etc., and has a condition input field 501 for selecting a patient group to be transmitted. In the example of FIG. 5, the condition is specified as a patient who is suspected to have a chronic disease and is a new patient. As another example, the target patient group may be specified as a condition of patients who are suspected to have a chronic disease and who have not visited the pharmacy even after a predetermined number of days have passed since the next scheduled visit date. As a further example, the target patient group may be specified as a condition of patients who are suspected to have a chronic disease and who are in a predetermined age range, such as young people. Since the dropout rate is high for young people, the significance of intervention is great. Alternatively, the target patient group may be specified as a condition of patients taking a specific high-risk drug. Since the degree of side effects occurring in patients is large and the dropout rate is high, the significance of intervention is great. Furthermore, the target patient group may be specified as a condition of patients who are presumed to have a specific disease, such as lifestyle-related chronic diseases, glaucoma, etc. By limiting the disease, it is possible to send an automatically sent message according to the disease.

[0056] When the selection conditions for the patient group to be transmitted do not include no visit within a predetermined number of days, such as 14 days, from the next scheduled visit, the automatic transmission setting screen 500 may have a transmission date and time input field 502 for specifying a transmission date and time after a predetermined number of days have passed since the next scheduled visit as the transmission timing. The transmission timing can also be considered as one of the conditions for setting the automatic transmission.

[0057] The automatic transmission setting screen 500 may have a message input field 503 for specifying a message to be transmitted to the selected target patient group. The device 100 can perform automatic transmission setting of an intervention message to those chronic disease patients who meet the above-mentioned predetermined conditions.

[0058] Preferably, if a patient for whom a message has been set to be automatically sent visits the pharmacy before the date and time of sending the message, the device 100 cancels the automatic sending setting. More specifically, the device 100 may cancel the automatic sending setting when the device 100 obtains prescription information associated with the patient, the prescription information including a drug or a set of drugs representing a disease that matches a predetermined condition for the automatic sending setting.

[0059] In addition to the above, the conditions for the automatic transmission setting may be conditions according to prescription information associated with the patient, the intervention status for the patient, the response status to the intervention for the patient, etc. In addition, the automatic transmission setting may be performed for patients who would benefit from the intervention, or the automatic transmission setting may be suggested, based on a trained model generated by machine learning using training data in which a label indicating whether or not the patient visited the pharmacy after the message was sent is added to at least one of the predetermined conditions for the automatic transmission setting of the message and the predetermined transmission message.

[0060] (Fourth embodiment) A pharmacist viewing the intervention support screen 400 displayed according to the method of the second embodiment can individually perform an intervention on one or more patients who should be encouraged to return to the pharmacy as appropriate. When the pharmacist performs an intervention, the pharmacist can input intervention information including the patient name or patient identifier and the intervention date to the device 100. If an intervention is possible by operating the intervention support screen 300, the device 100 can store the intervention information regarding the intervention that has been performed.

[0061] FIG. 6 shows the flow of the method for calculating the conversion rate of intervention according to the third embodiment of the present invention. The device 100 acquires a plurality of prescription information (S601), and, as described in the first embodiment, determines whether the prescription information contains one or more drugs that represent a chronic disease alone or in combination, thereby inferring whether the disease of the patient associated with the prescription information is a chronic disease (S602). On the condition that it is determined that the prescription information contains the one or more drugs, intervention support information for intervention for the patient associated with the prescription information is generated and transmitted to the terminal used by the pharmacist (S603). The pharmacist appropriately performs intervention for the patient, and the device 100 stores that the patient associated with each prescription information has revisited the pharmacy (S604). Then, the number of patients who revisited the pharmacy relative to the number of patients who received intervention is calculated (S605).

[0062] FIG. 7 is a diagram showing an example of interventions and their results according to the third embodiment of the present invention. In the conversion rate display screen 700, there are 175 revisits for 201 interventions, resulting in a conversion rate of 82.4%. Although not shown, by including a pharmacist name or pharmacist identifier in the intervention information, it is possible to calculate the conversion rate for each pharmacist. As with the first embodiment, the calculated value is the number of patients who have undergone intervention as the denominator, and in addition to the number of patients who have revisited, the number of patients who have not revisited, the revisit rate which is the conversion rate, the dropout rate, and other values ​​according to the number of patients who have revisited can be used.

[0063] In the above embodiment, it should be noted that unless there is a statement of "only" such as "based on XX", "depending only on XX", or "only in the case of XX", it is assumed in this specification that additional information may be taken into consideration. Also, as an example, it should be noted that the statement "do b in the case of a" does not necessarily mean "always do b in the case of a" or "do b immediately after a" unless expressly stated. Also, the statement "each a constituting A" does not necessarily mean that A is composed of multiple components, but includes the case where the component is singular.

[0064] 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 the same as any 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.

[0065] Furthermore, the "start" and "end" shown in Figures 2 and 5 are merely examples, and do not mean that the method of this embodiment necessarily starts with S201 and S501, or necessarily ends with S204 and S505. [Explanation of symbols]

[0066] 100 devices 101 Communications Department 102 Processing section 103 Storage section 104 Database 300 Repeat visit rate display screen 400 Intervention support screen 600 Conversion rate display screen

Claims

1. 1. A method for managing a plurality of patient visits to a pharmacy, comprising: obtaining a plurality of prescriptions; determining whether each prescription contains one or more medications that, alone or in combination, are indicative of a chronic condition; Includes:

2. 10. The method of claim 1, The method further includes a step of calculating the number of patients with one or more chronic diseases associated with the one or more prescription information items determined to contain the one or more drugs who have returned to the pharmacy within a specified period of time, or a value corresponding thereto.

3. 3. The method of claim 2, The value is the re-visit rate or dropout rate of the one or more chronic disease patients within a predetermined period of time.

4. 4. The method according to claim 2 or 3, The calculation is performed separately according to the past visit history of each of the one or more chronic disease patients.

5. 4. The method according to claim 2 or 3, The predetermined period is a period based on the number of prescription days for at least some of the one or more drugs.

6. 4. A method according to any one of claims 1 to 3, comprising: The method further includes generating intervention support information for intervening in at least one patient among one or more chronic disease patients associated with one or more prescription information determined to include the one or more medications.

7. 7. The method of claim 6, Further comprising determining a priority for the intervention.

8. 8. The method of claim 7, and predicting when the patient will return to the clinic. The priority is given to a patient who has passed the revisit time but before the predetermined period has elapsed, higher than that of a patient who has passed the predetermined period.

9. 7. The method of claim 6, The intervention support information includes a telephone number to be used for intervention.

10. 7. The method of claim 6, The method further includes a step of calculating the number of patients who have undergone intervention and who have returned to the clinic within a predetermined period of time, or a value corresponding thereto.

11. 4. A method according to any one of claims 1 to 3, comprising: The determining step includes: a first step of determining whether each prescription information includes a single medication that alone represents a chronic disease; if the single medication is not included, a second step of determining whether each prescription information includes a set of medications that, in combination, represent a chronic condition; Includes:

12. 12. The method of claim 11, The determination of whether the set of drugs is included is performed only if the single drug is not included.

13. 12. The method of claim 11, The determination of whether or not the set of drugs is included is made using the prescription days for at least some of the drugs included in each piece of prescription information.

14. 12. The method of claim 11, The determination of whether or not the set of drugs is included is made using an estimation model generated by machine learning.

15. 4. A method according to any one of claims 1 to 3, comprising: The method further includes a step of setting up automatic transmission of an intervention message to one or more chronic disease patients associated with one or more prescription information determined to include the one or more drugs, and who meet predetermined conditions.

16. 16. The method of claim 15, The predetermined conditions include being a new patient, being a patient within a predetermined age range, being a patient prescribed a specific drug, or being a patient suspected of having a specific disease.

17. 16. The method of claim 15, The predetermined condition is that the patient has not visited the clinic even after a predetermined number of days have passed since the next scheduled visit date.

18. 16. The method of claim 15, The automatic transmission setting includes specifying a transmission date and time after a predetermined number of days have passed since the next scheduled visit date.

19. A program for causing a computer to execute a method for managing a plurality of patients visiting a pharmacy, the method comprising: obtaining a plurality of prescriptions; determining whether each prescription contains one or more medications that, alone or in combination, are indicative of a chronic condition; Includes:

20. A device for managing a plurality of patients visiting a pharmacy, comprising: Obtain multiple prescription information, For each prescription, the system is configured to determine whether it includes one or more medications that, alone or in combination, are indicative of a chronic condition.

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