Billing delay analysis device, notification device, and billing delay analysis system

Abstract

To provide a charge delay analyzer, a notification device, and a charge delay analysis system that can elaborately analyze the reason of charge delay of a statement of medical expenses or the influence of the delay.SOLUTION: In a charge delay analysis system, a charge delay analyzer 1 includes: an acquisition unit 11 for acquiring a charge delay notification record generated by a medical institution for a predetermined period of time if a statement of medical expenses was not submitted when it was supposed to be submitted, the record including the report on the charge delay of the medical expenses; and an analysis unit 12 for performing predetermined statistic processing by using a charge delay notification record and outputting the result of analysis on the charge delay.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to a claim delay analysis device, a notification device, and a claim delay analysis system for analyzing a delay in submitting a medical fee statement.

Background Art

[0002] A medical facility creates a medical fee statement (also called a receipt) that describes the details of a medical act and requests a review from a review and payment institution in order to claim a part of the fee for the medical act performed on an insured person from the insurer. The review and payment institution reviews the content of the receipt and, if there are no problems, causes the insurer to pay the fee.

[0003] The deadline for submitting the receipt during the review and payment period is set monthly. If the deadline for each month is exceeded, the receipt cannot be submitted during the current month, so the medical facility needs to resubmit the receipt after the next month. In this specification, not being able to submit the receipt in the month when it should originally be submitted and submitting it after the next month is referred to as a claim delay.

[0004] A claim delay occurs, for example, when a person in charge of a medical facility notices a mistake in the receipt before submitting it. Patent Document 1 discloses a medical support program that can automatically detect errors in a receipt and efficiently correct them.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] If billing is delayed, the medical facility will not be able to receive the compensation it would have otherwise earned in that month, resulting in a decrease in its monthly revenue. When this happens repeatedly, it can impact the management of the medical facility. Therefore, there is a demand to reduce billing delays by analyzing the reasons for them and their impact.

[0007] The purpose of this disclosure is to provide a billing delay analysis device, a notification device, and a billing delay analysis system that can analyze in detail the reasons for and impact of delays in billing of medical fee statements. [Means for solving the problem]

[0008] The billing delay analysis device disclosed herein comprises: an acquisition unit that acquires billing delay report records, including reports on billing delays for medical fees, generated at medical facilities when they are unable to submit medical fee statements by the due date, for a predetermined period of time; and an analysis unit that performs predetermined statistical processing using the billing delay report records and outputs analysis results regarding the billing delays. The analysis unit, in the statistical processing, divides the reason sentences indicating the reason for the billing delay included in the billing delay report record into words, counts the number of occurrences of each word in the reason sentences included in multiple billing delay report records, extracts words whose occurrence count exceeds a threshold number, performs clustering on the extracted words, and uses the results of the clustering as the analysis result. .

[0009] The notification device of this disclosure includes a notification unit that provides notification based on the analysis results by the above-mentioned billing delay analysis device.

[0010] The billing delay analysis system of this disclosure comprises the billing delay analysis device described above and the notification device described above. [Effects of the Invention]

[0011] According to the present invention, it is possible to analyze in detail the reasons for delays in billing of medical fee statements and their impact. [Brief explanation of the drawing]

[0012] [Figure 1] A conceptual diagram illustrating how the billing delay analysis system is used. [Figure 2] Block diagram showing an example of the configuration of a billing delay analysis system. [Figure 3] A flowchart illustrating an example of how the billing delay analysis system works. [Figure 4] Block diagram showing an example of the configuration of a billing delay analysis device. [Figure 5] Flowchart explaining the analysis process using the billing delay analysis device. [Figure 6] Flowchart to explain the process of analyzing the reasons for billing delays. [Figure 7] A diagram showing an example of categorization of billing delays. [Figure 8] Block diagram showing an example of the configuration of a notification device. [Figure 9] This diagram shows an example of a display screen showing the monthly trend in the number of delayed billing cases at a certain pharmacy. [Modes for carrying out the invention]

[0013] Embodiments of this disclosure will be described in detail below with reference to the drawings. However, unnecessarily detailed explanations, such as detailed explanations of already well-known matters or redundant explanations of substantially identical configurations, may be omitted.

[0014] Figure 1 is a conceptual diagram illustrating an example of how the billing delay analysis system is used. Figure 1 shows multiple pharmacies (Ph) and a headquarters (HQ) that oversees the multiple pharmacies (Ph). In this embodiment, the multiple pharmacies (Ph) correspond to, for example, individual stores belonging to a pharmacy chain. The headquarters (HQ) is, for example, an organization that manages the operations of each store belonging to the pharmacy chain. The pharmacies in this embodiment are an example of a medical facility in this disclosure. In this embodiment, the case where the medical facility is a pharmacies is described, but in this disclosure, medical facilities may include not only pharmacies but also various other medical facilities (hereinafter referred to as medical institutions), such as hospitals, clinics, and dental clinics that provide insured medical services.

[0015] Each dispensing pharmacy (Ph) is equipped with a terminal device (TE). The terminal device (TE) accepts various input operations from staff members (such as pharmacists) belonging to the dispensing pharmacy (Ph).

[0016] The terminal device TE of each dispensing pharmacy Ph is connected to the claim delay analysis system 100 arranged at the headquarters HQ via the network NW. The claim delay analysis system 100 is a system that performs various analyses on the claim delays that occur at each dispensing pharmacy Ph.

[0017] Note that, as described above, a claim delay means that each dispensing pharmacy Ph fails to submit a receipt to the payment review agency in the month when it should originally be submitted due to deficiencies in the medical fee statement (receipt), etc., and submits it after the following month. A claim delay may occur, for example, when a person in charge of a dispensing pharmacy Ph who has confirmed the content before submitting the receipt discovers a deficiency in the receipt.

[0018] The network NW is, for example, a public communication network such as the Internet, or an intranet.

[0019] When a claim delay of a receipt occurs, at each dispensing pharmacy Ph, an input of a claim delay report reporting the occurrence of the claim delay is made by the person in charge via the terminal device TE. In the terminal device TE, for example, an input of one claim delay report is made for one claim delay. As a result, the terminal device TE generates one claim delay report record for one input and transmits it to the claim delay analysis system 100 arranged at the headquarters HQ via the network NW.

[0020] Note that the claim delay report record includes information (such as an identification number) for identifying the receipt that could not be claimed, information indicating the month when the claim delay occurred, information regarding the amount that could not be claimed due to the claim delay, information regarding a sentence indicating the reason for the claim delay, etc. The information regarding the sentence indicating the reason for the claim delay is generated when the person in charge of the dispensing pharmacy Ph inputs a sentence or selects from a plurality of fixed sentences using the terminal device TE.

[0021] In the following explanation, a statement indicating the reason for a delayed claim may be referred to as a "statement of reason." A statement of reason may include not only sentences such as "The insurance card has expired," or "The income category is not indicated on the prescription," but also combinations of words or phrases such as "Incorrect symbol / number," or "Forgot to submit the claim." A statement of reason may also contain two or more sentences, words, or phrases.

[0022] Reports of delayed claims may be entered at a predetermined time by each pharmacy (Ph), or at any time of their choosing. A predetermined time is, for example, a specific day within a month (for example, the last day of the month). Any time of their choosing is, for example, when a delay in claim processing occurs, or when the pharmacy staff member has free time.

[0023] <Billing Delay Analysis System 100> The billing delay analysis system 100 will be described in detail below. Figure 2 is a block diagram showing an example of the configuration of the billing delay analysis system 100. As shown in Figure 2, the billing delay analysis system 100 comprises a billing delay analysis device 1, a notification device 2, and a storage unit 3.

[0024] The storage unit 3 stores various information used in the processing performed by the billing delay analysis device 1 and the notification device 2. In particular, the storage unit 3 has a billing delay report database (DB) that stores billing delay report records received from the terminal device TE of each dispensing pharmacy Ph.

[0025] The billing delay analysis device 1 analyzes the reasons for past billing delays based on the information stored in the memory unit 3. The notification device 2 provides various notifications based on the information stored in the memory unit 3 and the analysis results of the billing delay analysis device 1.

[0026] Figure 3 is a flowchart illustrating an example of the overall operation of the billing delay analysis system 100.

[0027] In step S1, the storage unit 3 stores the billing delay report records received via the network NW from the terminal device TE located in the dispensing pharmacy Ph in the billing delay report DB.

[0028] In step S2, the billing delay analysis device 1 performs an analysis on the billing delay based on the accumulated billing delay report records. Details of the analysis process performed by the billing delay analysis device 1 will be described later.

[0029] In step S3, the notification device 2 performs various notification processes based on the analysis results. Details of the notification processes performed by the notification device 2 will be described later.

[0030] <Invoice Delay Analysis Device 1> Figure 4 is a block diagram showing an example of the configuration of the billing delay analysis device 1. As shown in Figure 4, the billing delay analysis device 1 comprises an acquisition unit 11 and an analysis unit 12.

[0031] The acquisition unit 11 retrieves the necessary billing delay report records from the billing delay report DB in the storage unit 3.

[0032] The analysis unit 12 performs various analyses on billing delays that occurred at dispensing pharmacies based on billing delay report records accumulated in the billing delay report DB.

[0033] [Example of operation of the billing delay analysis device 1] The following describes an example of the operation of the billing delay analysis device 1. Figure 5 is a flowchart illustrating the analysis process performed by the billing delay analysis device 1. The flowchart shown in Figure 5 corresponds to step S2 in Figure 3. The analysis process shown in Figure 5 may be performed, for example, at predetermined intervals, or at the timing requested by the administrator of the billing delay analysis system 100. Specifically, the analysis process only needs to be performed once a month, when a billing delay report record is sent from the dispensing pharmacy Ph.

[0034] The analysis process shown in Figure 5 is performed for each of the multiple dispensing pharmacy Phs that send billing delay report records to the headquarters HQ where the billing delay analysis system 100 is installed (see Figure 1).

[0035] In step S11, the billing delay analysis device 1 performs a billing delay reason analysis process. The billing delay reason analysis process is performed based on the reason statement included in the billing delay report record.

[0036] In step S12, the billing delay analysis device 1 performs a cash flow simulation process that takes billing delays into account.

[0037] In step S13, the billing delay analysis device 1 performs a simulation of the profit amount taking into account the billing delay.

[0038] In step S14, the billing delay analysis device 1 performs a simulation of inventory fluctuations at the dispensing pharmacy Ph to be processed. Inventory fluctuations refer to the monthly fluctuations in drug inventory at the dispensing pharmacy Ph.

[0039] The details of each step in the analysis process are described below.

[0040] (Analysis of the reasons for the billing delay) Figure 6 is a flowchart illustrating the process for analyzing the reasons for billing delays.

[0041] In step S21, the billing delay analysis device 1 extracts a reason statement from each billing delay report record.

[0042] In step S22, the billing delay analysis device 1 divides all reason statements into words. The billing delay analysis device 1 may also divide the reason statements into phrases instead of words. In this disclosure, the division of reason statements into words or phrases by the billing delay analysis device 1 may be simply described as the billing delay analysis device 1 dividing the reason statements into words.

[0043] Furthermore, when the billing delay analysis device 1 divides the reason statement into words, it may refer to a dictionary that includes medical terminology. This allows for accurate word division even when the reason statement contains uncommon terms, such as industry jargon and abbreviations. Specifically, a dictionary that includes words such as "receipt computer," which is an abbreviation for a medical claims computer used to create medical fee statements (receipts), could be used.

[0044] Then, in step S23, the billing delay analysis device 1 counts the words contained in all the reason sentences. In step S23, the billing delay analysis device 1 may also classify the separated words by part of speech and count them.

[0045] Next, in step S24, the billing delay analysis device 1 extracts words whose count result is greater than or equal to a threshold number. The threshold number is a value set in advance by the administrator of the billing delay analysis system 100. The threshold number can be set appropriately based on, for example, the number of reason sentences acquired by the billing delay analysis device 1 in step S21.

[0046] Next, in step S25, the billing delay analysis device 1 performs predetermined statistical processing based on the extracted word group and the counting results of each word. Examples of predetermined statistical processing include correlation analysis, cluster analysis, and multidimensional scaling.

[0047] This results in the formation of clusters of words that appear relatively frequently and have a close distance or similarity to each other. The word groups included in each cluster are those that are likely to be found in a single reason statement. The number of clusters may be set as appropriate by, for example, the administrator of the billing delay analysis system 100.

[0048] Note that the distance between words refers to the distance between words contained in the reason statement. That is, in the reason statement, "There is a mistake in the date of birth field," the distance between the word "date of birth" and the word "field" is 1 (the particle "no" is not counted). Similarly, the distance between the word "date of birth" and the word "mistake" is 2.

[0049] Similarity is a measure of the semantic closeness between two or more different words. Similarity can be expressed as a correlation coefficient between two or more different words, for example, calculated using correlation analysis. Alternatively, similarity may be expressed as a value obtained by learning, through machine learning or other methods, how often one word is used together with another word in reason sentences.

[0050] Furthermore, during cluster analysis, clustering may be performed using information such as the pharmacy Ph that created the billing delay report record containing the reason sentence from which each word was extracted, the region where the pharmacy Ph that created the billing delay report record is located, or the time (year, month, day, etc.) when the billing delay report record was created. This makes it possible to extract billing delays that are highly associated with, for example, a specific medical facility, region, or time period.

[0051] In step S26, the billing delay analysis device 1 generates categories based on the clusters obtained in this way. Specifically, the billing delay analysis device 1 defines a billing delay category as a group of words that have close distances and similarities between words and satisfy certain conditions. Satisfying certain conditions means, for example, that the group of words belongs to one cluster as a result of clustering, or even if they belong to different clusters, they are a group of words that corresponds to a billing delay category classified in the existing category data.

[0052] Figure 7 shows an example of categorization of billing delays. While 13 categories are shown, this is just an example, and a different number of categories may be generated.

[0053] Through the above process, the billing delay analysis device 1 generates categories based on existing billing delay report records. Information indicating the generated categories is stored in the storage unit 3.

[0054] Through this processing, the billing delay analysis device 1 can not only classify the reasons for billing delays indicated by the reason statements included in the billing delay report records stored in the memory unit 3 into the same categories as existing category data, but can also generate new categories. A new category is, for example, a category that does not match existing categories and may include billing delays specific to a particular medical facility, region, or time period. Specifically, for example, if there is a deficiency in the business process of a certain pharmacy, many billing delays may occur at that pharmacy, and in this case, the billing delay analysis device 1 can set the fact that the pharmacy generated a medical fee statement as a new category of reason for billing delay. Or, if there is a localized outbreak of infectious disease in a certain region, the number of billing delays related to that infection may increase at pharmacies in that region, and in this case, the billing delay analysis device 1 can set the fact that pharmacies in that region generated a medical fee statement as a new category of reason for billing delay. Furthermore, for example, when changes occur in the rules for calculating medical fees due to the impact of a revision of medical fees, it is also possible to classify the reasons for billing delays that increase due to the changes during a predetermined period from the revision of medical fees into a new category separate from the existing categories.

[0055] Furthermore, the billing delay analysis device 1 may determine whether the category classification in the existing category data is accurate based on the clustering results and the existing category data. For example, if the clustering results and the existing category data are far apart, it may be determined that either the clustering results or the existing category classification is inaccurate. If it is determined that either the clustering results or the existing category classification is inaccurate, the billing delay analysis device 1 may notify the result of this determination via the notification device 2.

[0056] Furthermore, if the billing delay analysis device 1 was generated by another billing delay analysis system, it may learn using data on the word groups included in the billing delays used when generating the existing category data, and perform category classification based on the learning results. Alternatively, if the billing delay analysis system 100 has previously performed category classification using past billing delay report records, it may learn using data on the word groups included in the billing delays used during past category classification, and perform category classification based on the learning results.

[0057] Returning to the explanation of Figure 6, in step S27, the billing delay analysis device 1 outputs data regarding the category classification results to the notification device 2 and the storage unit 3. The storage unit 3 stores the data regarding the new category classification. This completes the billing delay reason analysis process in the billing delay analysis device 1.

[0058] As explained above, the billing delay analysis device 1 can classify billing delays into a predetermined number of categories based on the billing delay report records stored in the storage unit 3. The category classification by the billing delay analysis device 1 is performed by clustering the words contained in the reason sentences of the billing delay report records, while referring to existing category classifications of billing delays. In this way, the billing delay analysis device 1 can classify the billing delays indicated by the reason sentences contained in the billing delay report records into various categories. It can also determine whether existing category classifications are accurate or not.

[0059] Furthermore, since the billing delay analysis device 1 performs categorization based on numerous billing delay report records entered by multiple dispensing pharmacies, it can perform categorization with higher accuracy compared to, for example, categorization based on billing delay report records entered only by a specific medical facility.

[0060] Furthermore, the billing delay analysis device 1 can set up new categories corresponding to specific medical facilities, regions, or time periods if the billing delays in the billing delay report records stored in the memory unit 3 are highly correlated with specific medical facilities, regions, or time periods. Therefore, for example, in cases where operations are stalled due to a shortage of personnel at a specific medical facility, when an infectious disease is prevalent in a specific region, or when billing delays are increasing due to the impact of revisions to medical fees, the device can immediately and appropriately categorize the reasons for billing delays. As a result, the billing delay analysis device 1 can analyze a variety of reasons, not just those that fall into existing categories.

[0061] (Cash flow simulation process) Next, we will explain the cash flow simulation process, which corresponds to step S12 in Figure 5.

[0062] The billing delay analysis device 1 retrieves monthly information from the memory unit 3, including past and present sales and expenses, as well as unbilled amounts that could not be billed during the current month due to billing delays. The billing delay analysis device 1 then calculates the correlation between specific months or seasons and the amount of receipts and unbilled amounts, as well as the monthly fluctuations in the amount of receipts and unbilled amounts. Furthermore, based on the calculation results, the billing delay analysis device 1 simulates the future cash flow of the pharmacy Ph.

[0063] Regarding the method for calculating correlations and the method for simulating cash flows based on the calculation results, known methods can be appropriately adopted.

[0064] (Profit simulation process) Next, we will explain the profit simulation process, which corresponds to step S13 in Figure 5.

[0065] The billing delay analysis device 1 simulates the future profit amount of the dispensing pharmacy Ph based on the cash flow simulation results described above. A known method can be appropriately adopted for simulating the profit amount.

[0066] As described above, the billing delay analysis device 1 can perform various analyses related to billing delays. The analysis results are stored in the storage unit 3 and output to the notification device 2, where they are used for notification processing by the notification device 2. The configuration and operation of the notification device 2 will be described below.

[0067] (Inventory fluctuation simulation process) Next, we will explain the inventory fluctuation simulation process, which corresponds to step S14 in Figure 5. Inventory fluctuation refers to the monthly change in drug inventory at pharmacy Ph.

[0068] The billing delay analysis device 1 retrieves monthly inventory data for the target pharmacy Ph from the memory unit 3, from the past to the present. The billing delay analysis device 1 then calculates the correlation between a specific month or season and inventory levels, the correlation between the number of billing delays and inventory levels, and the monthly fluctuations in inventory levels. Furthermore, based on the calculation results, the billing delay analysis device 1 simulates future inventory fluctuations for the pharmacy Ph.

[0069] Regarding the method for calculating correlations and the method for simulating inventory fluctuations based on the calculation results, known methods can be appropriately adopted.

[0070] <Notification device 2> Next, the notification device 2 will be described. Figure 8 is a block diagram showing an example of the configuration of the notification device 2. As shown in Figure 8, the notification device 2 comprises a receiving unit 21 and a notification unit 22.

[0071] The receiving unit 21 receives information regarding the analysis results of billing delays output from the billing delay analysis device 1.

[0072] The notification unit 22 has a display unit such as a liquid crystal display, and notifies the administrator of the billing delay analysis system 100 via the display unit. The notification by the notification unit 22 is not limited to display on the display unit, but may also be made by emitting sound via an audio output unit such as a speaker.

[0073] Furthermore, depending on the content of the notification, the notification unit 22 will also notify the person in charge at the dispensing pharmacy via the terminal device TE at the dispensing pharmacy (see Figure 1).

[0074] The notification process by notification device 2 will be explained in detail below. The target of notification will also be explained for each process.

[0075] (Notification processing) The information notified by notification device 2 includes various items such as: (1) categorization of reasons for billing delays, (2) monthly trends in the number of billing delays, (3) alerts regarding billing delays, (4) simulation results of appropriate inventory levels, (5) cash flow simulation results, (6) profit amount simulation results, and (7) alerts to pharmacies. Each of these will be explained below.

[0076] (1) Notification regarding the categorization of reasons for billing delays The notification device 2 notifies the administrator of the billing delay analysis system 100 via the display unit of the results of the categorization of the reasons for billing delay performed by the billing delay analysis device 1. For simplicity, the results of the categorization of the reasons for billing delay will be simply referred to as the classification results below.

[0077] The classification results can be notified at predetermined times, such as the end or beginning of the month, or at times requested by the administrator of the billing delay analysis system 100. When the notification device 2 displays the category classification results, it can be displayed in a table format, such as shown in Figure 7.

[0078] The notification device 2 displays, for example, the results of the categorization of the reasons for billing delays by the billing delay analysis device 1. This allows administrators of the billing delay analysis system 100 to check what the reasons for billing delays are.

[0079] (2) Reporting on the monthly trend in the number of delayed billing cases Furthermore, the notification device 2 notifies the administrator of the billing delay analysis system 100 via the display unit of the monthly trend in the number of billing delays. Notification regarding the trend in the number of billing delays can be made at predetermined times, such as the end or beginning of the month, or at times requested by the administrator of the billing delay analysis system 100, similar to the classification results.

[0080] Figure 9 shows an example of a display screen showing the monthly trend in the number of late billing cases at a certain pharmacy. Figure 9 shows the trend in the number of late billing cases along with the trend in the amount received (expected amount received). With such a display screen, administrators of the late billing analysis system 100 can understand the trend in the number of late billing cases for each pharmacy and the impact of late billing on the amount received.

[0081] Note that while the example shown in Figure 9 was a display screen for a single pharmacy, it may also display the total number of billing delays across all stores, or the total number of billing delays at pharmacies within a particular area.

[0082] (3) Alerts regarding delayed billing The notification device 2 issues an alert to the administrator of the billing delay analysis system 100 via the display unit when predetermined conditions are met. The predetermined conditions are those set by, for example, the administrator of the billing delay analysis system 100. One example of a predetermined condition is whether the number of billing delay report records containing a reason statement corresponding to a specific category of billing delay among the billing delay report records for a predetermined period is greater than a predetermined number. Another example of a predetermined condition is whether the number of billing delay report records entered by a specific dispensing pharmacy Ph among the billing delay report records for a predetermined period is greater than a predetermined number.

[0083] Multiple predetermined conditions are set in advance for the notification device 2 to determine whether or not to issue a notification. The notification device 2 may decide whether or not to issue a notification based on any one of the conditions, or it may decide whether or not to issue a notification based on a combination of multiple conditions. For example, the notification device 2 may issue a notification regarding billing delays classified into a category when the number of billing delay report records, including a statement of reason for billing delay, exceeds a predetermined number in a particular dispensing pharmacy Ph.

[0084] The content of the notification by notification device 2 will be explained with a specific example. For example, suppose a predetermined condition is set that, within a predetermined period, a particular pharmacy has a category with a count result that exceeds a predetermined number. In this case, notification device 2 counts each category of billing delay report records generated at specific pharmacy A within the predetermined period and extracts the categories with a count result that exceeds the predetermined number. In this case, notification device 2 will issue a notification regarding the categories with a count result that exceeds the predetermined number, for example, "At pharmacy A, there have been many billing delays in the ○○ category."

[0085] Furthermore, the specified conditions may be set in more detail. For example, conditions may be set using the elements of each category shown in Figure 7 (classification name, cause, example of reason statement). For example, suppose that the specified condition is that among the billing delay report records for the previous month generated at a specific pharmacy, the number of records in which the reason statement for billing delay is "medication history not created" and the cause is "pharmacy" is greater than or equal to a specified number (see Figure 7). In this case, the notification device 2 counts the records among the billing delay report records for the previous month entered at specific pharmacy A where the reason is "medication history not created" and the cause is "pharmacy," and issues a notification if the count result is greater than the specified number. The content of the notification may be, for example, "Pharmacy A has experienced many billing delays due to the failure to create medication history." The content of the notification can be set, for example, by the administrator of the billing delay analysis system 100, along with the specified conditions. In addition to messages like those in the example above, notification by the notification device 2 may also be provided by, for example, displaying an icon indicating that a particular pharmacy has a high number of billing delays for a specific reason, or playing a specific alarm sound indicating that a particular pharmacy has a high number of billing delays for a specific reason.

[0086] Furthermore, it is assumed that a predetermined condition is set that, among the billing delay report records entered by all dispensing pharmacies Ph during the one month following the revision of medical fees, the number of records in which the classification name of the reason statement contained in each billing delay report record is "Calculation method unknown" is greater than a predetermined number. In this case, notification device 2 counts the records in which the classification name of the reason statement contained in each billing delay report record contained in all dispensing pharmacies Ph during the one month following the revision of medical fees, and notifies if the count result is greater than the predetermined number. The content of the notification may be, for example, "Due to the revision of medical fees, there are an increasing number of cases where the calculation rules are unclear. Please call on each pharmacy to take note."

[0087] In the example described above, the content of the notification was set by the administrator of the billing delay analysis system 100 along with predetermined conditions. However, for example, a learning model could be generated using predetermined conditions set in the past and the content of notifications made based on those conditions as training data, and when a new notification based on predetermined conditions is to be made, the appropriate content of the notification could be generated based on the learning model. In this case, the effort required of the administrator of the billing delay analysis system 100 to set the content of the notification can be reduced.

[0088] Furthermore, the notification device 2 may provide notifications based on predetermined conditions and also suggest methods for resolving billing delays. For example, if a particular pharmacy A experiences many billing delays due to failure to create patient medication records, the suggestion of a solution may be made by displaying a message such as, "Please ensure that patient medication records are created reliably at pharmacy A." The solution may be pre-set for each billing delay by, for example, the administrator of the billing delay analysis system 100, or it may be generated at the time of notification based on predetermined conditions, based on a learning model that has been pre-generated using billing delays and previously suggested solution methods as training data.

[0089] (4) Notification of the results of the cash flow simulation The notification device 2 notifies the administrator of the billing delay analysis system 100 via the display unit of the results of the cash flow simulation conducted for each pharmacy. At this time, the notification device 2 may also notify the administrator of the billing delay analysis system 100 of the information on past sales, expenses, and unbilled amounts used for the simulation, along with the simulation results. This allows the administrator of the billing delay analysis system 100 to understand the impact of past billing delays on cash flow and to predict future cash flow for each pharmacy.

[0090] Specifically, the notification device 2 calculates, for example, the amount of impact on cash flow due to a billing delay (hereinafter simply referred to as the impact amount) as follows: (Amount of compensation not paid due to delayed billing) × (Number of delayed billing cases) = (Amount of impact) In this formula, the parameter (amount of remuneration not paid due to delayed billing) is, for example, the average amount of remuneration that was not paid due to delayed billing in the past at a particular pharmacy.

[0091] (5) Notification regarding the results of the profit simulation The notification device 2 notifies the administrator of the billing delay analysis system 100 via the display unit of the results of the profit simulation conducted for each dispensing pharmacy. At this time, the notification device 2 may also notify the administrator of the billing delay analysis system 100 of the information used for the simulation, which concerns changes in profit amounts from the past to the present, along with the simulation results. This allows the administrator of the billing delay analysis system 100 to understand the impact of past billing delays on cash flow and to predict future cash flow for each dispensing pharmacy.

[0092] Specifically, the notification device 2 calculates, for each pharmacy, a first profit amount that takes into account the impact amount and a second profit amount that does not take into account the impact amount, based on the pharmacy's past profit amounts, and notifies the pharmacy of the difference between the first profit amount and the second profit amount as the profit improvement target amount. The profit improvement target amount is a simulation of the amount by which the pharmacy's profit amount can be improved by eliminating the billing delay. In this case, the manager who receives notification of the profit improvement target amount can notify the pharmacy of the profit improvement target amount and request that they achieve the target amount, thereby minimizing the impact on the pharmacy's profit amount due to the billing delay.

[0093] (6) Notification regarding the results of the simulation of optimal inventory levels The notification device 2 notifies the administrator of the billing delay analysis system 100 via the display unit of the results of the simulation of appropriate inventory levels conducted for each dispensing pharmacy. At this time, the notification device 2 may also notify the administrator of the billing delay analysis system 100 of the information on inventory fluctuations from the past to the present that was used for the simulation, along with the simulation results. This allows the administrator of the billing delay analysis system 100 to understand the impact of past billing delays on inventory levels and the appropriate inventory levels for each dispensing pharmacy in the future.

[0094] Specifically, notification device 2 calculates, for each pharmacy, a first inventory value that takes into account the impact amount and a second inventory value that does not take into account the impact amount, based on the pharmacy's past expenses, and notifies the pharmacy of the difference between the first inventory value and the second inventory value as the inventory reduction target amount. The inventory value corresponds to the expenses incurred by the pharmacy for purchasing inventory. The inventory reduction target amount is a simulation of the amount by which the pharmacy's inventory situation can be improved by eliminating the billing delay. In this case, the manager who receives notification of the inventory reduction target amount can notify the pharmacy of the target amount and have them adjust their inventory to achieve the target amount, thereby minimizing the impact of the billing delay on inventory at the pharmacy.

[0095] The notifications (4) to (6) above by the notification device 2 may be made at predetermined times, such as the end or beginning of the month, or at times requested by the administrator of the billing delay analysis system 100, similar to the classification results.

[0096] (7) Notification regarding alerts to dispensing pharmacies The notification device 2 issues an alert to the staff member of the dispensing pharmacy via the terminal device TE of the dispensing pharmacy when predetermined conditions are met. For example, if a patient who has previously caused billing delays visits a dispensing pharmacy, and the staff member enters information about the patient via the terminal device TE, the notification device 2 will issue an alert to the staff member based on that information. The alert may be issued by displaying a message such as, "Mr. / Ms. XX forgot their insurance card last time. Please be careful to present your insurance card," or by illuminating a light to draw the staff member's attention. In this case, the notification device 2 should hold information indicating the conditions under which an alert should be issued to the dispensing pharmacy, and should automatically issue an alert to the dispensing pharmacy when the conditions are met. The information indicating the conditions may be pre-set by, for example, the administrator of the billing delay analysis system 100.

[0097] The conditions under which the notification device 2 issues an alert may include conditions attributable to the patient, such as the patient forgetting their insurance card, as exemplified above, as well as conditions attributable to the dispensing pharmacy. Examples of conditions attributable to the dispensing pharmacy include the staff member forgetting to fill in the form or making a mistake in the information they fill in.

[0098] Furthermore, the notification device 2 may also notify, along with the alert, information regarding the difficulty of recovering any billing delays that may occur in relation to that alert. The difficulty of recovery indicates the degree of difficulty in resolving the cause of a billing delay in order to resubmit a claim to the review and payment organization for that billing delay. The difficulty of recovery can be expressed in two stages, for example, "high" and "low". A "high" difficulty of recovery applies when the billing delay was caused by the patient, while a "low" difficulty of recovery applies when the billing delay was caused by the pharmacy. The reason why the difficulty of recovery for billing delays caused by the patient is "high" is that it is difficult for the headquarters HQ of the pharmacy chain to control the patient's behavior. The reason why the difficulty of recovery for billing delays caused by the pharmacy is "low" is that problems that occur within the pharmacy are relatively easy to deal with and control.

[0099] The difficulty of recovery may be expressed in three stages: "high," "medium," and "low," or in more stages.

[0100] Furthermore, alerts to pharmacies are triggered, for example, when the number of delayed billing for a specific reason at a particular pharmacy exceeds a predetermined threshold during a given month. In this case, the alert only needs to be triggered at a specific time, such as the end of the month.

[0101] As explained above, the notification device 2 displays the results of the billing delay category classification performed by the billing delay analysis device 1. This allows administrators of the billing delay analysis device 1 to recognize that if the billing delays in the billing delay report records stored in the memory unit 3 are highly correlated with a specific medical facility, region, or time period, a new category corresponding to that specific medical facility, region, or time period has been set. Therefore, administrators of the billing delay analysis device 1 can more easily recognize problems such as, for example, that operations are stalled due to a shortage of personnel at a specific medical facility, that an infectious disease is prevalent in a specific region, or that billing delays are increasing after a revision of medical fees due to the impact of the revision.

[0102] Furthermore, the notification device 2 issues a notification corresponding to a predetermined condition when the counting result of the billing delay report records stored in the storage unit 3 meets a predetermined condition. Therefore, the administrator of the billing delay analysis device 1 can easily understand the points to be aware of in order to reduce billing delays by setting conditions in advance.

[0103] Furthermore, the notification device 2 provides notifications based on predetermined conditions, along with suggestions for resolving billing delays. This allows administrators of the billing delay analysis device 1 to easily understand what measures should be taken to reduce billing delays.

[0104] <Mechanism of action, effect> As explained above, the billing delay analysis system described in this disclosure can categorize and notify users of past billing delays based on the reason. Furthermore, based on the billing delay information, the billing delay analysis system can provide various notifications, such as predictions of future billing delays, forecasts of cash flow and profits for medical facilities considering the impact of billing delays, and forecasts of appropriate inventory levels considering billing delays. In addition, it is possible to send sudden alerts to terminal devices in medical facilities.

[0105] Therefore, the billing delay analysis system described in this disclosure allows for the acquisition of various insights regarding billing delays and facilitates improvements to address the reasons for these delays. As a result, the number of billing delays can be reduced across the entire group of medical facilities that implement the billing delay analysis system.

[0106] <Variation> The above description has described one embodiment of the present disclosure. The present disclosure is not limited to the embodiment described above, and various modifications may be made as described below.

[0107] In the above-described embodiment, the operation of the billing delay analysis device 1 to classify billing delays into a predetermined number of categories based on billing delay report records stored in the storage unit 3 was explained. However, the billing delay analysis device 1 may, for example, acquire the reason statement for a billing delay report record in real time via the network NW while the reason statement is being entered at the terminal device TE of the dispensing pharmacy Ph, and determine which category the billing delay indicated by the acquired reason statement corresponds to. In this case, if the reason statement entered at the dispensing pharmacy Ph is not appropriate for the determined category, the billing delay analysis device 1 may send a message to the terminal device TE of the dispensing pharmacy via the network NW indicating that the reason statement should be corrected, and display it. Furthermore, the billing delay analysis device 1 may present information necessary for creating a billing delay report record according to the category to which the reason statement entered at the dispensing pharmacy Ph belongs. Specifically, the billing delay analysis device 1 should display a message on the terminal device TE such as, "The reason statement you are currently entering appears to fall under the billing delay category XX. Reporting billing delays in the XX category requires data from XX." [Industrial applicability]

[0108] This disclosure is useful for a billing delay analysis system that analyzes delays in billing for medical fee statements. [Explanation of symbols]

[0109] 100 Billing Delay Analysis System 1. Billing delay analysis device 11 Acquisition Department 12 Analysis Department 2. Notification device 21 Receiving unit 22 Hochi Department 3 Storage section

Claims

1. When a medical fee statement is not submitted by the time it should be submitted, the acquisition unit acquires a record of delayed billing, including a report on the delay in billing of medical fees, generated by the medical facility for a predetermined period. An analysis unit that performs predetermined statistical processing using the aforementioned billing delay report record and outputs the analysis results regarding the billing delay, Equipped with, The analysis unit, in the statistical processing, divides the reason sentences indicating the reason for the billing delay included in the billing delay report record into words, counts the number of occurrences of each word in the reason sentences included in multiple billing delay report records, extracts words whose occurrence count exceeds a threshold number, performs clustering on the extracted words, and uses the results of the clustering as the analysis results. Invoice delay analysis device.

2. The analysis unit classifies the reasons included in the billing delay report record into several categories based on the analysis results of those reasons. The billing delay analysis apparatus according to claim 1.

3. The analysis unit classifies the reasons into the plurality of categories based on the analysis results and category data indicating existing reasons. The billing delay analysis apparatus according to claim 2.

4. The aforementioned analysis unit is Based on the monthly number of billing delays included in the aforementioned billing delay report record, predict the monthly number of billing delays in the future. The billing delay analysis apparatus according to claim 1.

5. The analysis unit predicts future monthly inventory fluctuations based on monthly inventory fluctuations. The billing delay analysis apparatus according to claim 1.

6. The analysis unit predicts future monthly cash flows based on the monthly sales and expenses of the medical facility, as well as the unbilled amount that could not be billed during the month due to the billing delay. The billing delay analysis apparatus according to claim 1.

7. The analysis unit predicts the monthly profit amount for the medical facility in the future, based on the monthly profit amount of the medical facility. The billing delay analysis apparatus according to claim 1.

8. The device comprises a notification unit that provides notification based on the analysis results obtained by the billing delay analysis device described in claim 1, Notification device.

9. A claim delay analyzer according to any one of claims 1 to 7, The notification device according to claim 8, A billing delay analysis system equipped with the necessary components.

Images