JP2020080190A - Information processing apparatus, control method of the same, information processing system, and program - Google Patents

Abstract

To provide a mechanism configured to allocate image-reading requests to diagnostic radiologists who read medical images, according to expertise of each of radiologists.SOLUTION: An information processing apparatus includes: acquisition means for acquiring a request for reading medical image data including attribute information; management means for managing parameters corresponding to attribute included in the attribute information in the medical image data and set to each of a plurality of diagnostic radiologists; and allocation means for allocating the image-reading request acquired by the acquisition means to one of the plurality of diagnostic radiologists, on the basis of the parameters corresponding to the attribute included in the attribute information in the medical image data corresponding to the image-reading request and set to each of the diagnostic radiologists.SELECTED DRAWING: Figure 9

Description

  The present invention relates to an information processing apparatus, a control method therefor, an information processing system, and a program, and more particularly to a technique for assigning an image to be interpreted to a doctor who interprets a medical image.

  Conventionally, a patient is imaged by a medical image device such as CT (Computed Tomography) or MRI (Magnetic Resonance Imaging), and the medical image obtained by the image interpretation is performed. When interpreting a medical image, a person in charge of distribution work (hereinafter, clerical worker) assigns a request for the interpretation in consideration of the field and schedule of each interpreting doctor. In other words, the clerical staff makes the judgment based on his/her own experience and manually assigns the image interpretation request, which takes time and labor for the clerical staff. In addition, when the experience of the clerical staff is insufficient, the assignment of interpretation requests is biased, and the load is not properly distributed among the interpretation doctors.

  In Patent Document 1, managing received schedule information of a plurality of doctors, receiving a medical image from a remote place, automatically assigning a doctor who interprets the medical image based on the schedule information, and distributing via a communication line. The mechanism is disclosed.

JP, 2002-329190, A

  However, in Patent Document 1, the image interpretation request is automatically assigned simply in consideration of the image interpretation doctor's schedule, and the image interpretation doctor's specialty (specialized area based on examination type, region, etc.) and its skill level are determined. Do not consider. Therefore, when the interpretation of a medical image in a specialized area that is capable of interpretation but is not very good is assigned, there is a problem that the interpretation takes time.

  Therefore, it is an object of the present invention to provide a mechanism capable of assigning an image interpretation request to an image interpretation doctor who performs image interpretation of a medical image according to the specialty of each image interpretation doctor.

  In order to achieve the above object, the information processing apparatus of the present invention has the following configuration. In other words, the information processing apparatus is an acquisition unit that acquires an image interpretation request for medical image data including attribute information, and a parameter set for each of a plurality of image interpreting physicians that corresponds to an attribute included in the attribute information of the medical image data. Managing means for managing the image reading request obtained by the obtaining means, and the parameters set in each of the plurality of image reading doctors corresponding to the attributes included in the attribute information of the medical image data corresponding to the image reading request. Based on the above, there is an allocating means for allocating to any of the plurality of image interpretation doctors.

  According to the present invention, it is possible to assign an image interpretation request to an image interpretation doctor who interprets a medical image according to the specialty of the image interpretation doctor.

The figure which shows the example of the system configuration which concerns on this embodiment. The figure which shows the example of the hardware constitutions of the information processing apparatus which concerns on this embodiment. The figure which shows the example of a function structure of the remote interpretation server which concerns on this embodiment. Overall flow chart. The flowchart of request application processing. The flowchart of the initial value setting process of distribution characteristic. The flowchart of a request reception process. The flowchart of request distribution processing. The flowchart of an automatic distribution process. The figure which shows an example of a request facility work list screen. The figure which shows an example of a request application screen. The figure which shows an example of an image interpretation center work list screen. The figure which shows an example of a request reception screen. The figure which shows an example of a specialty setting screen. The figure which shows an example of a distribution screen. The figure which shows the example of a display of the automatic distribution result on a distribution screen. The figure which shows the structural example of an inspection kind table. The figure which shows the structural example of a site|part table. The figure which shows the structural example of a classification table. The figure which shows the structural example of a distribution characteristic master table. The figure which shows the structural example of the number point addition table. The figure which shows the structural example of a point setting table. The figure which shows the structural example of a distribution characteristic mapping table. The figure which shows the structural example of a specialty table. The figure which shows the structural example of an image interpretation doctor exclusion table. The figure which shows the structural example of an image interpretation doctor schedule table. The figure which shows the structural example of a request information table. The figure which shows the state after a sort of a request information table. The figure which shows the state after distribution of a request information table. The figure which shows an automatic distribution determination result. The figure which shows the image after automatic allocation of the image interpretation doctor schedule. The flowchart of the request distribution process which concerns on 2nd embodiment. The flowchart of the automatic distribution process which concerns on 2nd embodiment. The flowchart of the automatic distribution process which concerns on 2nd embodiment. The figure which shows an example of a distribution condition setting screen. The figure which shows the structural example of a facility information table for interruption.

<First embodiment>
Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the configurations shown below are examples, and the present invention is not limited thereto.

[System configuration]
FIG. 1 shows an example of the overall configuration of a remote image interpretation system as an information processing system according to this embodiment. In the present embodiment, the remote interpretation system includes a data center, a request facility, an interpretation center, and the home of an image interpretation doctor as each location, and each location is communicably connected via a network 115.

  Each user who uses the remote image interpretation system authenticates by the authentication function provided by the authentication server 116 at the time of starting access from the PC (109, 112, 113, 114) which is a client terminal arranged at each base. After successful authentication, the user is presented with a portal screen (not shown) provided by the portal server 102. Further, the user can exchange messages between users using the SNS server 104.

  At the requested facility, image data (medical image data) used for remote interpretation is photographed by the modality 111, which is a photographing device, and then transmitted to the image relay client 110. Examples of the image data here include image data in DICOM (Digital Imaging and Communication in Medicine) format. The image relay client 110 archives the image data transmitted from the modality 111, and then transmits the image data to the image relay server 107 arranged in the data center. The image relay server 107 processes the image data transmitted from the request facility and transmits it to the storage management server 105. The storage management server 105 issues a unique ID (identification information) to each image data and stores it in the external storage device 117. The person in charge of the image interpretation requesting work of the requesting facility inputs the information (request information) required at the time of the image interpretation request using the request terminal 109, and the request information is transmitted to the data center together with the image data. Each request information is stored in the database 108 on the data center side. In this specification, request information and image data correspond to each other, and request information allocation (sorting) is treated as image data allocation.

  The image interpretation doctor who performs image interpretation uses the image interpretation terminal 113 (or image interpretation terminal 114 located at home) arranged in the image interpretation center to deliver the image data for image interpretation corresponding to the assigned image interpretation request to the distribution server 106. Download from and refer to and read the image. Thereafter, the image interpretation doctor creates a report of the image interpretation result by using an application (not shown) operating on the image interpretation terminal 113. The created report is transmitted to the report server 103 and stored in the database 108. Here, as the image interpretation terminal, an example of the image interpretation center and the home of the image interpretation doctor is shown, but it may be arranged at any place, and may be referred to by using a mobile terminal or the like.

  FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device such as various servers and terminals. The CPU 201 centrally controls each device and controller connected to the system bus 204. The ROM 202 or the external memory 211 stores a BIOS (Basic Input/Output System), an operating system (OS), and various programs necessary for realizing the functions of each terminal.

  The RAM 203 functions as a main memory, a work area, etc. of the CPU 201. The CPU 201 implements various operations by loading a program or the like required for executing the processing from the ROM 202 or the external memory 211 into the RAM 203 and executing the program. The input controller 205 controls input from a pointing device (not shown) such as a keyboard (KB) 209 or a mouse. The video controller 206 controls display on a display 210 such as a CRT display.

  The memory controller 207 controls access to the external memory 211 that stores various data and the like. Examples of the external memory 211 include an external storage device (HD), a flexible disk (FD), and a CompactFlash (registered trademark) memory connected to a PCMCIA card slot via an adapter. The communication I/F controller 208 performs connection and communication control with an external device via a network (for example, the network 115 shown in FIG. 1). The communication I/F controller 208 can perform communication using TCP/IP, for example.

  Various programs for implementing the present invention are recorded in the external memory 211 and are executed by the CPU 201 by being loaded into the RAM 203 as needed. Further, the definition file and various information tables used when the program is executed are also stored in the external memory 211, and detailed description thereof will be given later.

[Function configuration]
FIG. 3 is a diagram showing a functional configuration example of the remote image interpretation server 101 according to the present embodiment.

  Upon receiving a request for data required to display a request application screen or the like from the request terminal 109 located in the request facility, the remote image interpretation server 101 analyzes the request using the request search function 301. Then, the remote image interpretation server 101 searches the request information table 2700 included in the database 108, and returns the display information (for example, Web page) to the request terminal 109. That is, the request search function 301 is a functional unit that executes the processes of S202 and S402 in the process flow described later. Upon receiving the request application request from the request terminal 109, the remote interpretation server 101 analyzes the request using the request application function 302 and updates the request information table 2700 included in the database 108. That is, the request application function 302 is a functional unit that executes the process of S101 in the process flow described later.

  Upon receiving the request acceptance request from the request terminal 109, the remote image interpretation server 101 analyzes the request by the request acceptance function 303 and updates the request information table 2700 included in the database 108. That is, the request receiving function 303 is a functional unit that executes the process of S102 in the process flow described later. Upon receiving the request automatic allocation request from the requesting terminal 109, the remote image interpretation server 101 executes the request automatic allocation function 304. That is, the data such as the request information table 2700, the specialty table 2400, and the image interpretation doctor schedule table 2600 included in the database 108 are read, and the automatic allocation is performed. After that, the remote image interpretation server 101 returns the processing result to the request terminal 109. That is, the request automatic distribution function 304 is a functional unit that executes the process of S103 in the process flow described later. When receiving the request for distribution saving from the request terminal 109, the remote image interpretation server 101 analyzes the request with the request update function 305 and updates the request information table 2700 included in the database 108.

[Processing flow]
FIG. 4 is a diagram showing the flow of the entire processing according to this embodiment. Although only the request terminal 109 and the business terminal 112, which are the starting points of the processing, are shown here, it is assumed that each terminal performs processing in cooperation with the remote image interpretation server 101 in each step. Further, in this embodiment, it is assumed that the request terminal 109 and the business terminal 112 do not directly exchange data.

  In addition, in the present embodiment, as described above, it is assumed that the image data captured in advance by the modality 111 of the requesting facility is transmitted to the data center and registered in the external storage device 117 in a timely manner. In response to this, information (request information) of the image interpretation request corresponding to the image data is registered in the database 108 in group units such as patient, date, and examination type. Then, it is assumed that one or more pieces of image data are associated with one piece of request information. In addition, in the registered state, the distribution application is not made yet, and the status is assumed to be unapplied and is managed in the database 108.

  In S101, the request terminal 109 executes the request application process shown in FIG. 5 based on the user's instruction. Details of the request application process will be described later with reference to FIG.

  In S102, the business terminal 112 executes the request acceptance process shown in FIG. 7 based on the user's instruction. Details of the request reception process will be described later with reference to FIG. 7.

  In S103, the business terminal 112 executes the request distribution process shown in FIG. 8 based on the user's instruction. Details of the request distribution process will be described later with reference to FIG.

(Request application processing)
FIG. 5 is a diagram showing a flowchart of a request application process executed by the request terminal 109 and the remote image interpretation server 101 in cooperation with each other. The following processing is realized by the CPUs of the request terminal 109 and the remote image interpretation server 101 reading and executing the programs stored in the respective storage units.

  In S201, the requesting terminal 109 displays the requested facility work list screen 1000 shown in FIG. 10 according to the user's instruction. The display here may be performed using a Web browser (not shown) provided in the request terminal 109, or may be displayed via a predetermined application. The request terminal 109 issues an instruction to the remote image interpretation server 101 to acquire request information whose status is not applied, in order to acquire the request information displayed on the requested facility work list screen 1000. The various statuses regarding the request information will be described later together with the table.

  In S202, the remote image interpretation server 101 returns to the request terminal 109 the request information whose status is not applied among the request information shown in FIG. 27 according to the instruction from the request terminal 109. Specifically, in the request information table 2700 shown in FIG. 27, request information whose status 2702 is “waiting for application” is returned. Then, the request terminal 109 displays the received request information on the requested facility work list screen 1000.

  In S<b>203, the request terminal 109 receives the selection of the request to be applied from the user via the requested facility work list screen 1000. Specifically, the selection of the application target is accepted by accepting the designation of the display button 1001 on the requested facility work list screen 1000. Then, the request terminal 109 acquires the request ID 2701 of the selected application target.

  In S204, the request terminal 109 displays the request application screen 1100 shown in FIG. 11 in order to display the request information corresponding to the request ID 2701 acquired in S203. In the request application screen 1100, patient information, information necessary for image interpretation (for example, patient symptoms, etc.), etc. are input. The input information may be manually input by the client, or may be automatically input according to the input of identification information such as the patient number 1103, or an attached file may be designated.

  In S205, the request terminal 109 determines whether or not the request application button 1113 is pressed on the request application screen 1100. When request application button 1113 is pressed (YES in S205), the process proceeds to S206.

  In S206, the requesting terminal 109 acquires request information including the inspection type 1109, the site 1110, etc. input on the request application screen 1100.

  In S207, the request terminal 109 transmits the request information acquired in S206 to the remote image interpretation server 101.

  In S208, the remote image interpretation server 101 receives the request information transmitted from the request terminal 109.

  In S209, the remote image interpretation server 101 sets the initial value of the distribution characteristic based on the request information received in S208. Details of the processing here will be described later with reference to FIG.

  In S210, the remote image interpretation server 101 adds the initial value of the distribution characteristic set in S209 to the request information received in S208 and saves it in the database 108. At this time, as the status of the request information, the value of the state 2702 becomes “waiting for reception”. Then, this processing flow ends.

(Initial value setting process for distribution characteristics)
FIG. 6 is a diagram showing a processing flow executed by the remote image interpretation server 101 to set the initial value of the distribution characteristic to the applied request information. This processing flow corresponds to the processing of S209 in FIG. In the present embodiment, information called distribution characteristics is used as information used when distributing the image interpretation data to each person in charge. The specific configuration of the distribution characteristic will be described together with the processing.

  In S301, the remote image interpretation server 101 determines whether or not the request information received from the request terminal 109 includes information necessary for the mapping process for determining the initial value of the distribution characteristic. The necessary information here is the examination type, site, classification, patient age, and patient sex. If it is determined that the necessary information is included (YES in S301), the remote image interpretation server 101 determines that the initial value of the distribution characteristic can be set, and the process proceeds to S302. On the other hand, when it is determined that it is not included (NO in S301), the remote image interpretation server 101 determines that the initial value setting of the distribution characteristic is impossible, and the process proceeds to S305.

  In S302, the remote image interpretation server 101 sets all the values of the examination type, site, classification, patient age, and patient sex as condition values (keys), and stores the distribution characteristic mapping table 2300 shown in FIG. The distribution characteristic ID 2301 of is searched. The patient age may be calculated from the examination date and the patient birth date included in the request information.

  In S303, the remote image interpretation server 101 determines whether or not the number of distribution characteristic IDs 2301 detected in S302 is one. When the number of cases is one (YES in S303), the remote image interpretation server 101 determines that mapping of the distribution characteristic has succeeded, and proceeds to S304. When the number of cases is 0 or 2 or more (NO in S303), the remote image interpretation server 101 determines that mapping of the distribution characteristic has failed, and proceeds to S305.

  In S304, the remote image interpretation server 101 sets one distribution characteristic ID 2301 retrieved in S303 as the initial value in the request information. Then, this processing flow ends.

  In S305, the remote image interpretation server 101 ends this processing flow without setting the distribution characteristic ID 2301 in the request information.

(Request acceptance process)
FIG. 7 is a diagram showing a processing flow of a request reception processing executed by the business terminal 112 and the remote image interpretation server 101 in cooperation with each other. The following processing is realized by the CPUs of the business terminal 112 and the remote image interpretation server 101 reading and executing the programs stored in the respective storage units.

  In S401, the business terminal 112 displays the image interpretation center work list screen 1200 shown in FIG. 12 in accordance with the user's instruction. The display here may be performed using a Web browser (not shown) provided in the business terminal 112, or may be displayed via a predetermined application. In order to acquire the request information displayed on the image interpretation center work list screen 1200, the business terminal 112 issues an instruction to the remote image interpretation server 101 to acquire the request information whose status is waiting for acceptance.

  In S402, the remote image interpretation server 101 returns to the business terminal 112, among the request information shown in FIG. 27, request information whose status is waiting for acceptance, in response to an instruction from the business terminal 112. Specifically, in the request information table 2700, request information in which the value of the status 2702 is “waiting for reception” is returned. Then, the business terminal 112 displays the received request information on the image interpretation center work list screen 1200.

  In step S403, the business terminal 112 receives the selection of the request to be received from the user via the image interpretation center work list screen 1200. Specifically, by accepting the designation of the display button 1201 on the image interpretation center work list screen 1200, the acceptance target selection is accepted. Then, the business terminal 112 acquires the request ID 2701 of the selected reception target.

  In S404, the business terminal 112 displays the request acceptance screen 1300 shown in FIG. 13 in order to display the request information corresponding to the request ID acquired in S403. The request reception screen 1300 displays various information input when the request application is made.

  In S405, the business terminal 112 displays the distribution characteristic selection list 1313 on the request reception screen 1300.

  In S406, the business terminal 112 sets the distribution characteristic selection list 1313 on the request reception screen 1300 to the initial value of the distribution characteristic set in the process of FIG. 6 as a selected value. As a result, the user can directly use the distribution characteristic set as the initial value on the business terminal 112 without performing any setting work. If the initial value is not set in the process of FIG. 6, it may be possible to display that the selection is made from the list. Even if the initial value of the distribution characteristic is set, it can be changed by accepting the selection from the list.

  In S407, the business terminal 112 determines whether or not the request reception button 1314 on the request reception screen 1300 has been pressed. If the request reception button 1314 is pressed (YES in S407), the process proceeds to S408.

  In S408, the business terminal 112 acquires the request information input on the request reception screen 1300. The request information here includes an inspection type, a part, a distribution characteristic, and the like.

  In step S409, the business terminal 112 transmits the request information acquired in step S408 to the remote image interpretation server 101.

  In S410, the remote image interpretation server 101 receives the request information transmitted from the business terminal 112.

  In S411, the remote image interpretation server 101 stores the request information received in S410 in the database 108. At this time, as the status of the request information, the value of the state 2702 becomes “allocation waiting”. Then, this processing flow ends.

(Request distribution process)
FIG. 8 is a diagram showing a processing flow of request distribution processing executed by the business terminal 112 and the remote image interpretation server 101 in cooperation with each other. The following processing is realized by the CPUs of the business terminal 112 and the remote image interpretation server 101 reading and executing the programs stored in the respective storage units.

  In S501, the business terminal 112 displays the request distribution screen 1500 shown in FIG. 15 according to the user's instruction. The display here may be performed using a Web browser (not shown) provided in the business terminal 112, or may be displayed via a predetermined application. The request distribution screen 1500 includes an area for displaying the request information list 1501 and an area for displaying the image interpretation doctor schedule 1503. The business terminal 112 issues an instruction to the remote image interpretation server 101 to obtain each piece of information in order to obtain the request information and the image interpretation doctor schedule information displayed on the request distribution screen 1500.

  In S502, the remote image interpretation server 101 returns the request information whose status is waiting for distribution and the image interpretation doctor schedule table 2600 shown in FIG. 26 to the business terminal 112 in the request information table 2700 shown in FIG. Then, the business terminal 112 displays the received request information and the image interpretation doctor schedule table 2600 on the request distribution screen 1500.

  In step S<b>503, the business terminal 112 acquires the request information of the automatic distribution target selected by the user via the request distribution screen 1500.

  In step S<b>504, the business terminal 112 determines whether the automatic distribution button 1504 has been pressed on the request distribution screen 1500. When the automatic distribution button is pressed (YES in S504), the process proceeds to S505.

  In step S<b>505, the business terminal 112 transmits the request information of the automatic distribution target acquired in step S<b>503 to the remote image interpretation server 101.

  In step S<b>506, the remote image interpretation server 101 receives the automatic allocation target request information transmitted from the business terminal 112.

  In step S<b>507, the remote image interpretation server 101 performs automatic distribution processing on each piece of request information targeted for automatic distribution, and sets distribution information. Here, the distribution information is information including a doctor who performs a requested image interpretation work and an image interpretation date. Details of the process in this step will be described later with reference to FIG.

  In S508, the remote image interpretation server 101 transmits the distribution information set in S507 to the business terminal 112.

  In step S<b>509, the business terminal 112 displays the distribution information received from the remote image interpretation server 101 on the request distribution screen 1500. The business terminal 112 displays, in the request information list 1501 on the request distribution screen 1500, information about the image interpretation doctors and image interpretation dates that have been distributed in association with each request information. Further, the business terminal 112 displays the number of scheduled allocations for each image interpretation doctor on the image interpretation doctor schedule 1503. FIG. 16 shows an image of a screen displayed after sorting. The request allocation screen 1600 shown in FIG. 16 includes a save button 1604 for accepting confirmation of the result of automatic allocation and a cancel button 1603 for accepting cancellation.

  In S510, the business terminal 112 confirms whether or not the save button 1604 is pressed on the request allocation screen 1600. When save button 1604 is pressed (YES in S510), the process proceeds to S512. When cancel button 1603 is pressed (NO in S510), the process proceeds to S511.

  In S511, the business terminal 112 discards the distribution information received in S509. All the sorting information displayed on the request sorting screen 1600 is returned to the state before display (that is, the state of FIG. 15). Then, this processing flow ends.

  In step S512, the business terminal 112 transmits the distribution information, which has been instructed by the user, to the remote image interpretation server 101.

  In S513, the remote image interpretation server 101 receives the distribution information from the business terminal 112.

  In S514, the remote image interpretation server 101 updates the request information stored in the database 108 by adding the distribution information received in S513. At this time, as the status of the request information, the value of the state 2702 becomes “allocated”. Then, this processing flow ends.

(Automatic sorting process)
FIG. 9 is a diagram showing a processing flow of automatic distribution performed by the remote image interpretation server 101, and corresponds to the processing of S507 in FIG.

  In step S<b>601, the remote image interpretation server 101 acquires various tables stored in the database 108. The tables used here are the distribution characteristic master table 2000, the number-of-sheets point addition table 2100, the point setting table 2200, and the distribution characteristic mapping table 2300. Further, a specialty table 2400, an image interpretation doctor exclusion table 2500, and an image interpretation doctor schedule table 2600. 20 to 26 show configuration examples of each table.

  In step S<b>602, the remote image interpretation server 101 excludes, from the automatic distribution target request information, the request information for which the distribution characteristic is not set, from the automatic distribution target. It is assumed that the distribution characteristic included in the request information is set via the request reception screen 1300 shown in FIG. 13. However, if the request information does not correspond to the distribution characteristic registered in advance, it is not set. Therefore, since such request information cannot be automatically distributed using the distribution characteristic, it is excluded from the automatic distribution target in S602. Incidentally, such request information may be manually distributed as in the conventional case. When there is such request information, a screen display or the like may be displayed that prompts the user (for example, clerical staff) to manually distribute the information.

  In S603, the remote image interpretation server 101 sorts the request information to be automatically sorted in the order of the request date of the request information. In other words, as a result of the sorting, the request information positioned at the top has a higher priority and is preferentially distributed. The request date of the request information is the request date 2704 of the request information table 2700 of FIG.

  In S604, the remote image interpretation server 101 sorts the results sorted in S603 in the order of the number of image interpretation doctors who can handle the distribution characteristic of the request information for those having the same request date. The number of image interpretation doctors here is determined based on the specialty table 2400 shown in FIG. For example, of the request information in the request information table 2700, the request information with the request ID “7” in S602 is excluded from the automatic distribution target. Then, when sorting is performed in S603 and S604 based on the request date 2704 and the specialty table 2400, the order is as shown in FIG.

  In S605, the remote image interpretation server 101 sets the loop counter N to 1 in order to sequentially execute the loop processing for the request information sorted in S604 (N=1).

  In step S606, the remote image interpretation server 101 extracts the Nth request information item of the request information items sorted in step S604, and sets the Nth request information item as the target distribution target.

  In step S<b>607, the remote image interpretation server 101 sets all the image interpretation doctors included in the image interpretation doctor schedule table 2600 acquired in step S<b>601 as distribution candidate image interpretation doctors.

  In S608, the remote image interpretation server 101 refers to the specialty table 2400 acquired in S601, and sets the specialty setting value (distribution characteristic value) for the distribution characteristic of the request information extracted in S606 to "0". The existing image interpretation doctor is excluded from the distribution candidate image interpretation doctors set in S607. Here, the specialization setting value of the distribution characteristic being "0" means that the radiologist does not have the specialized knowledge (specialty) for performing the image interpretation in the predetermined field. If the value is other than "0", it means that the skill level of the field increases as the value increases. The specialty setting value can be used not only as a degree of specialized knowledge possessed by the image interpreting doctor, but also as a degree of desire indicating how much the image interpreting doctor wants to perform image interpretation in a predetermined field. That is, when the image interpretation doctor sets the specialty setting value higher for a certain distribution characteristic, the request information having the distribution characteristic is preferentially distributed to the image interpretation doctor. In other words, if there is a distribution characteristic that the diagnosing reading doctor wants to read, the specialty set value corresponding to this distribution characteristic may be set higher. In this way, the specialty setting value can be used as the degree of preference (priority) of the image interpretation doctor.

  In step S609, the remote image interpretation server 101 refers to the image interpretation doctor exclusion table 2500 acquired in step S601, and determines the image interpretation doctor set as an exclusion target in accordance with the requested facility included in the request information extracted in step S606. It is excluded from the sorting candidate image interpretation doctor set in.

  In S610, the remote image interpretation server 101 sets the loop counter D to “0” (D=0) in order to sequentially perform the loop processing for each distribution target day of the image interpretation doctor schedule table 2600 acquired in S601.

  In S611, the remote image interpretation server 101 sets today + day D as the distribution target day. The remote image interpretation server 101 sets the current distribution candidate image interpretation doctor as the distribution candidate image interpretation doctor on the distribution target day.

  In S612, the remote image interpretation server 101 compares the sorting target date with the sorting possible date, and determines whether the sorting target date exceeds the sorting possible date. The sortable date here indicates, for example, a range from today to a predetermined number of days later. It should be noted that the sortable date may be set in advance by the user. If it does not exceed the possible allocation date (YES in S612), the remote image interpretation server 101 determines that the allocation target date exists, and moves the process to S613. On the other hand, when it exceeds (NO in S612), the remote interpretation server 101 determines that the sorting target date does not exist, and moves the process to S619.

  In step S<b>613, the remote image interpretation server 101 refers to the allocation target date of the image interpretation doctor schedule, and the number of possible remaining image interpretations is 0, or the remaining image interpretation possible point is less than the request point that is the object of distribution. The image interpretation doctor is excluded from the distribution candidate image interpretation doctors on the distribution target day. In the present embodiment, the number of points that can be left for image interpretation is (the number of items that can be distributed)×(one standard point 2201 of the point setting table 2200) as a reference value, and the doctor who interprets the images has already been distributed on the allocation target date It is calculated by subtracting the total points. In other words, the point indicates the load on the image interpretation, and when the image interpretation request is distributed and the load becomes high, control is performed so that new distribution is not performed. Here, the reference value of the image interpretation possible point is set as the upper limit of the load per day for each image interpretation doctor. Note that the method of calculating the points capable of residual image interpretation is not limited to this, and may be calculated using weighting or an upper limit value set for each image interpreting doctor, for example.

  Further, the points of the request to be distributed are calculated using the request information extracted in S606, the distribution characteristic master table 2000, the number-of-sheets point addition table 2100, and the point setting table 2200. In this embodiment, the points of the request to be distributed are (one standard point 2201 of the point setting table 2200)+(addition point 2003 of distribution characteristics indicated by the distribution information)+(image indicated by the distribution information It is calculated by the number of added points 2103). That is, the load of image interpretation due to the combination of the inspection type and the site to be inspected and the load due to the large number of images to be interpreted are taken into consideration. In other words, the higher the points, the higher the load. By considering not only the number of cases of image interpretation but also the load of each image interpretation by points, it becomes possible to perform distribution in consideration of load distribution. Further, it is desirable to calculate the point of the request that is the distribution target when executing the automatic distribution. This is because an image to be interpreted may be additionally sent after receiving the interpretation request.

  In S614, the remote image interpretation server 101 determines whether or not the number of distribution candidate image interpretation doctors on the distribution target day is 0. If not 0 (YES in S614), the remote image interpretation server 101 determines that there is a distribution candidate image interpretation doctor on the distribution target day, and moves the process to S616. When the number is 0 (NO in S614), the remote image interpretation server 101 determines that there is no distribution candidate image interpretation doctor on the distribution target day, and moves the process to S615.

  In S615, the remote image interpretation server 101 increments the loop counter D by 1 (D=D+1), and shifts the processing to S611.

  In S616, the remote interpretation server 101 refers to the image interpretation doctor schedule table 2600 for all the distribution candidate image interpretation doctors on the distribution target day, and calculates the number of possible residual distributions (number of possible image interpretations 2603). Further, the remote image interpretation server 101 refers to the specialty table 2400 and acquires the specialty setting value. Then, the remote image interpretation server 101 calculates the distribution appropriateness by multiplying the possible number of remaining distributions by the specialty setting value. For example, when the number of possible remaining distributions of a certain distribution candidate image interpretation doctor is 2 and the specialty setting value is “10”, the distribution appropriateness is “20”. The calculation formula of the distribution appropriateness is not limited to this, and other calculation formulas such as weighting for each distribution characteristic may be used.

  In S617, the remote image interpretation server 101 sets one interpretation doctor having the highest distribution appropriateness as distribution information based on the distribution appropriateness of each distribution candidate image interpretation doctor calculated in S616. In addition, when there are a plurality of highest interpretation doctors, for example, one interpretation doctor having a young interpretation doctor ID is set in the distribution information as a distribution target.

  In step S618, the remote image interpretation server 101 subtracts one remaining number of possible image interpretations (number of possible image interpretations 2603) from the distribution schedule of the distribution target day for the image interpretation doctor who is the distribution target set in step S617. Further, the remote image interpretation server 101 subtracts the points of the distribution target request from the remaining image interpretation possible points.

  In S619, the remote image interpretation server 101 determines that the distribution target image interpretation doctor and the image interpretation date do not exist for the distribution target request, and does not set the distribution information. Then, the process proceeds to S620.

  In S620, the remote image interpretation server 101 increments the loop counter N by 1 (N=N+1).

  In S621, the remote image interpretation server 101 determines whether or not the value of N is less than the total number of request information items for automatic distribution. When it is determined that the number is less than the total number (YES in S621), the remote image interpretation server 101 determines that the request for the automatic distribution target remains, and shifts the processing to S606. When it is determined that the number is not less than the total number (NO in S621), the remote image interpretation server 101 determines that the automatic distribution processing has been completed for all requests for automatic distribution target, and ends this processing flow.

[Screen configuration example]
FIG. 10 shows a configuration example of the requested facility work list screen 1000 displayed on the display of the requesting terminal 109 when the user on the requesting facility side applies for a request. When the display button 1001 of the request list 1006 is pressed, a transition is made to the request application screen 1100 for applying the request information of the pressed line. When the search button 1005 is pressed, the request information table 2700 shown in FIG. 27 is searched based on the conditions such as the patient number 1002, the examination type 1003, and the part 1004 designated by the user, and the display contents of the request list 1006. To update.

  FIG. 11 shows a configuration example of the request application screen 1100 displayed on the display of the request terminal 109 when the user on the request facility side inputs the request application content for the request application. The request source 1101 is displayed according to the request facility to which the user on the request facility side belongs. The request date 1102 is information on the date and time to which today's date is set when the request is applied. The patient number 1103, the patient name 1104, the gender 1105, the date of birth 1106, the modality 1107, and the number of images 1108 are set and displayed based on the examination information (DICOM information) included in the image data. When the request application button 1113 is pressed, the information input to the inspection type 1109, the part 1110, the film designation 1111 and the request content 1112 is registered in the request information table 2700.

  FIG. 12 shows a configuration example of the image interpretation center work list screen 1200 displayed on the display of the business terminal 112 when the user on the image interpretation center side receives a request. When the display button 1201 of the request list 1207 is pressed, the screen transits to a request reception screen 1300 for receiving the request information of the pressed line. When the search button 1206 is pressed, the request information table 2700 is searched based on the conditions such as the requested facility 1202, the patient number 1203, the examination type 1204, and the part 1205, and the display content of the request list 1207 is updated.

  FIG. 13 shows a configuration example of a request acceptance screen 1300 displayed on the display of the business terminal 112 when the user on the image interpretation center side inputs the request acceptance content for request acceptance. Based on the request information set in the request information table 2700, the requester 1301, the request date 1302, the patient number 1303, the patient name 1304, the gender 1305, the date of birth 1306, the modality 1307, and the number of images 1308 are displayed. Furthermore, the inspection type 1309, the part 1310, the film 1311, and the request content 1312 are displayed. The distribution characteristic selection list 1313 displays a list of the distribution characteristics registered in the distribution characteristic master table 2000 shown in FIG. When the request reception button 1314 is pressed, the distribution characteristic selected in the distribution characteristic selection list 1313 is registered in the request information table 2700.

  FIG. 14 shows a configuration example of the specialty setting screen 1400 displayed on the display of the business terminal 112 when the user at the image interpretation center side updates the content of the specialty table 2400 shown in FIG. When the save button 1402 is pressed after the user inputs a value indicating the specialty for each distribution characteristic to the specialty setting value 1401, the specialty table 2400 is updated. The larger the value here, the higher the specialty. If no value is entered, it means that the subject is out of the field (or the image cannot be interpreted).

  FIG. 15 shows a configuration example of the request distribution screen 1500 displayed on the display of the business terminal 112 when the user on the image interpretation center side distributes the request information to the image interpretation doctor. When the automatic distribution button 1504 is pressed, automatic distribution is performed on the request information selected by the distribution target selection check box 1502 on the request information list 1501 and the distribution result (FIG. 16) is displayed. Is displayed. When the cell of the image interpretation doctor schedule 1503 is selected by the user, the image interpretation doctor and the distribution target date indicated by the cell are distributed to the request information selected by the distribution target selection check box 1502 on the request information list 1501. Then, the request information table 2700 is updated. That is, by pressing the automatic distribution button 1504, it is possible to manually distribute the image interpretation request instead of automatically distributing the image interpretation request to the image interpreting doctor.

  FIG. 16 is a screen displayed on the display of the business terminal 112 as a distribution result when the user on the image interpretation center side instructs automatic distribution. When the automatic allocation is executed, an image interpretation date column 1601 and an image interpretation doctor column 1602 are newly added and displayed, and the image interpretation date and image interpretation doctor as a result of the assignment are displayed here. Further, the total number of cases and the number of new cases after distribution are displayed in the cells of the image interpretation days and image interpretation doctors that are distributed in the image interpretation doctor schedule 1605.

  When the cancel button 1603 is pressed, the provisionally displayed interpretation date and the contents of the interpreting doctor are discarded. As a result, the image interpretation date column 1601 and the image interpretation doctor column 1602 are hidden, and the distribution count of the image interpretation doctor schedule 1605 is deleted. When the save button 1604 is pressed, the displayed interpretation date and the contents of the interpreting doctor are registered in the request information table 2900 as shown in FIG.

[Table configuration example]
17, 18, and 19 show examples of the configuration of the master table stored in the database 108. The data registered in the examination type table 1700 of FIG. 17, the part table 1800 of FIG. 18, and the classification table 1900 of FIG. 19 are used as candidate values for inputting request information on the request application screen 1100 shown in FIG. For example, it is displayed in a list display.

  FIG. 20 shows a configuration example of the distribution characteristic master table 2000 stored in the database 108. The distribution characteristic according to the present embodiment is defined by a combination of each value of the inspection type shown in FIG. 17 and each value of the part shown in FIG. The distribution characteristic is not limited to this, and may be combined for each value of a more detailed item. In that case, it is possible to define a more detailed specialty. The distribution characteristic master table 2000 includes a distribution characteristic ID 2001, a distribution characteristic name 2002, and an addition point 2003. When the points of the request information are calculated, the additional points 2003 are added to the one standard point 2201 (FIG. 22) in accordance with the distribution characteristic set in the request information.

  FIG. 21 shows a configuration example of the number-of-coins-points addition table 2100 stored in the database 108. The number-of-sheets addition table 2100 includes a lower limit 2101, the upper limit 2102, and an addition point 2103. When calculating the points of the request information in S613 and S618 of FIG. 9, an addition point 2103 of a record that falls within the range of the number-of-images lower limit 2101 and the number-of-images upper limit 2102 is added to one standard point 2201 according to the number of images of the request information. To be done.

  FIG. 22 shows a configuration example of the point setting table 2200 stored in the database 108. The point setting table 2200 includes one standard point 2201. Used as the standard point value for each request.

  FIG. 23 shows a configuration example of the distribution characteristic mapping table 2300 stored in the database 108. The distribution characteristic mapping table 2300 includes a distribution characteristic ID 2301, a distribution characteristic name 2302, a test type ID 2303, a site ID 2304, a classification ID 2305, a patient age 2306, a patient gender lower limit value 2307, and a patient gender 2308. The same distribution characteristic ID 2301 can have a combination of different examination type IDs 2303, site IDs 2304, classification IDs 2305, patient ages 2306, patient gender lower limit values 2307, and patient genders 2308.

  FIG. 24A shows a configuration example of the specialty table 2400 stored in the database 108. The specialty table 2400 includes an image interpretation doctor ID 2401, a distribution characteristic ID 2402, and a specialty setting value 2403. The value (parameter) input on the specialty setting screen 1400 of FIG. 14 is registered. This parameter indicates the specialty of each radiologist, and the higher the value, the higher the specialty. FIG. 24(B) expresses the relationship between the values shown in FIG. 24(A) in a two-dimensional table format with the image interpretation doctor and the distribution characteristic as axes.

  FIG. 25 is a configuration example of the image interpretation doctor exclusion table 2500 stored in the database 108. The image interpretation doctor exclusion table 2500 includes a requested facility ID 2501 and an image interpretation doctor ID 2502. The image interpretation doctor exclusion table 2500 is used to exclude image interpretation doctors who are not requested by the requesting facility who applied for the request information from the candidate image interpretation doctors. In addition, here, the interpreting doctor to be excluded is designated for each requesting facility, but the present invention is not limited to this. For example, the interpreting doctor to be excluded may be designated for each patient, each examination type, etc. Good.

  FIG. 26A shows a configuration example of the image interpretation doctor schedule table 2600 stored in the database 108. The image interpretation doctor schedule table 2600 includes an allocation target date 2601, an image interpretation doctor ID 2602, and an image interpretation possible number 2603. FIG. 26(B) expresses the data values of FIG. 26(A) in a two-dimensional table format centering on the day to be sorted and the image interpreting doctor.

  FIG. 27 shows a configuration example of the request information table 2700 stored in the database 108. The request information table 2700 includes a request ID 2701, a status 2702, a requested facility ID 2703, a request date 2704, a patient number 2705, a patient name 2706, a date of birth 2707, and a gender 2708. Further, it includes an examination type ID 2709, a site ID 2710, an examination date 2711, a classification (film) ID 2712, an image number 2713, a distribution characteristic ID 2714, an image interpretation date 2715, and an image interpretation doctor ID 2716. These are the attribute information included in the request information. In particular, in the present embodiment, the processing is performed by using the combination of the examination type indicated by the examination type ID 2709 and the imaging region indicated by the region ID 2710 in association with the specialty of the image interpretation doctor. FIG. 28 shows a state after sorting the data of the request information table 2700 shown in FIG. 27 (a state after executing the processing of S601 to S604).

  FIG. 29 shows a state as a result of completion of the flowchart of FIG. 9 for the data of the request information table 2700 shown in FIG. An interpretation target day and a distribution interpretation doctor as a result of automatic distribution are set in the interpretation date 2901 and the interpretation doctor 2902. Note that this data is not stored in the database 108 of the data center when the flowchart of FIG. 9 is completed, and the user has instructed to save the data via the request allocation screen 1600 in S514 of the flowchart of FIG. Will be registered at the time.

  FIG. 30 is a diagram showing the state of the data of the request information table 2700 at the time when the flowchart of FIG. 9 is completed. The calculation point 3001 indicates the calculation point of the request calculated in S613 of FIG. The calculated distribution appropriateness 3002 indicates the distribution appropriateness of the image interpretation doctor for each distribution target day calculated in S616 of FIG. The distribution information interpretation date 3003 and the distribution information interpretation doctor 3004 indicate the interpretation date and the result of the interpretation doctor set as the distribution target in S617.

  FIG. 31 shows each allocation target date at the time when the flowchart of FIG. 9 is completed, and the number of assigned cases, the number of assignable cases, the assigned points, and the assignable points of the data of the request information table 2700. Indicates the state of points.

<Second embodiment>
By using the mechanism described as the first embodiment, the interpretation request accepted by the interpretation center can be automatically distributed in consideration of the specialty of the radiologist and the load of the request. However, if the number of requests is larger than the number of cases that can be interpreted daily, the requests generated after automatic allocation are always distributed after the allocated requests even if the requests are highly urgent. Therefore, when it is desired to interrupt the request, it is necessary to manually adjust the distribution, and there is a problem that the readjustment takes time.

  Also, when it is desired to allocate the request of the same patient to the same interpretation doctor on the same day to improve the interpretation efficiency, it is necessary to manually adjust the distribution.

  There is also a demand for preferentially distributing request information from a predetermined request source.

  In the present embodiment, in order to solve the above problem, when it is desired to interrupt the request, a frame for interruption is prepared at the time of automatic allocation without filling all the frames that can be interpreted. With this configuration, it is possible to interrupt a request generated after distribution while maintaining the distribution already made. Furthermore, in this embodiment, requests from the same patient are grouped. By grouping, requests for the same patient or the like can be allocated to the same image interpretation doctor or the same image interpretation date without fail, and the labor of manual adjustment of allocation can be reduced.

  Hereinafter, the above mechanism will be described as a second embodiment. It should be noted that description of processes, screen examples, and data configurations common to the above-described first embodiment will be omitted, and portions different from the first embodiment will be described.

  In the present embodiment, the user can set the urgency of the interpretation request via the request application screen 1100. At this time, a request request with high urgency may be set only by a specific user or a specific request source.

[Processing flow]
(Request distribution process)
FIG. 32 is a diagram showing a processing flow of request distribution processing executed by the business terminal 112 and the remote image interpretation server 101 in cooperation with each other. The following processing is realized by the CPUs of the business terminal 112 and the remote image interpretation server 101 reading and executing the programs stored in the respective storage units.

  In step S<b>504, the business terminal 112 determines whether the automatic distribution button 1504 has been pressed on the request distribution screen 1500. When the automatic distribution button 1504 is pressed (YES in S504), the process proceeds to S3201.

  In S3201, the business terminal 112 acquires the distribution condition for automatic distribution selected by the user via the request distribution condition input screen 3400 shown in FIG. The distribution condition may be set by displaying the request distribution condition input screen 3400 when the automatic distribution button 1504 is pressed, or by displaying the request distribution condition input screen 3400 in advance as a preset. The selection from may be accepted. The screen configuration of the request distribution condition input screen 3400 will be described later. When the business terminal 112 detects the pressing of the distribution start button 3409, the business terminal 112 acquires the distribution condition input on the requested distribution condition input screen 3400, and advances the processing to S505.

  In step S<b>505, the business terminal 112 transmits the request information of the automatic distribution target acquired in step S<b>503 and the distribution condition acquired in step S<b>3201 to the remote image interpretation server 101.

(Automatic sorting process)
33A and 33B are diagrams showing a processing flow of automatic distribution performed by the remote image interpretation server 101 according to this embodiment, and correspond to the processing of S507 in FIG.

  In step S<b>601, the remote image interpretation server 101 acquires various tables stored in the database 108. The tables acquired here are the distribution characteristic master table 2000, the number-of-sheets point addition table 2100, the point setting table 2200, and the distribution characteristic mapping table 2300. Further, a specialty table 2400, an image interpretation doctor exclusion table 2500, an image interpretation doctor schedule table 2600, and an interrupt facility information table 3500. An example of the configuration of each table is shown in FIGS. The tables other than the interrupt facility information table 3500 have the same configuration as that described in the first embodiment.

  In S3301, the remote image interpretation server 101 determines whether or not division of similar requests is prohibited based on the distribution condition input via the request distribution condition input screen 3400. Specifically, in the setting of the similar request division 3401, it is determined whether or not the division of similar requests is prohibited. The “similarity request” here refers to request information that is similar to each other based on a predetermined attribute. The predetermined attribute here is set on the request distribution condition input screen 3400 shown in FIG. For example, when “same patient” is set as the similar condition on the request distribution condition input screen 3400, the image interpretation requests related to the same patient are treated as mutual similar requests.

  If the division of the similar request is prohibited (YES in S3301), S602 is skipped and the process proceeds to S3302. If the division of the similar request is not prohibited (NO in S3301), the process proceeds to S602. When the division of the similar request is not prohibited, the interpretation request for which the distribution characteristic is not set is excluded from the distribution target as in the first embodiment, so that the distribution processing is made efficient. On the other hand, when the division of the similar request is prohibited, even if the image interpretation request does not have the distribution characteristic set, if this is a similar request, it is regarded as the distribution target. Therefore, in this case, the report having no distribution characteristic is not excluded from the distribution target.

  In S3302, the remote image interpretation server 101 confirms whether or not to consider an interrupt under the designated automatic distribution condition. Specifically, it is determined whether or not to consider in the setting of the interrupt interpretation frame 3406 of the request distribution condition input screen 3400. "Consider interrupts" here means that when the number of cases that can be interpreted is larger than the number of requests, a space is created without filling all the frames. In other words, it is a mechanism that makes it possible to interrupt a priority request with a high degree of urgency that occurs after allocation (process an image reading request with a high degree of urgency in advance). With this configuration, even if a preferential request is generated after the distribution, the distribution can be performed without canceling the once determined distribution. When considering an interrupt (YES in S3302), the process proceeds to S3303. When the interrupt is not considered (NO in S3302), the process proceeds to S603.

  In S3303, the remote image interpretation server 101 sorts the request information to be automatically distributed. As the sort criterion, the interrupt consideration time sequence 3502 set for the requested facility of the request information in the interrupt facility information table 3500 of FIG. 35 is used as the first sort key. Further, the request date 2704 of the request information in the request information table 2700 of FIG. 27 is used as the second sort key. Then, the sort keys are sorted in ascending order. In other words, as a result of the sorting, the request information positioned at the top has a higher priority and is preferentially distributed. In S3303, the request from the requesting facility having a higher order in the interrupt consideration sequence 3502 is preferentially distributed. Then, the process proceeds to S604.

  After the processing of S604, in S3304, the remote image interpretation server 101 generates a link of the similar request for the request information based on the condition of the similar request (setting items 3402 to 3405) specified by the distribution condition. The remote image interpretation server 101 extracts request information one by one from the top of the request information sorted in S604, and sets a request that matches the condition of the similar request from the request information after the request information as a similar request. Here, it suffices that the similar requests are linked to each other, and the specific linking method is not particularly limited. Alternatively, the link may not be set in advance, and the similar request may be searched for the first time in S3307 described later. Then, the process proceeds to S605.

  In S612, the remote image interpretation server 101 compares the sorting target date and the sortable date, and if the sortable date is not exceeded (YES in S612), the process proceeds to S3305. In step S3305, the remote image interpretation server 101 sums up the number of possible residual image interpretations of all image interpretation doctors on the distribution target date at the time of this processing when the specified automatic distribution condition considers an interrupt. , It is determined whether or not it exceeds the interrupting interpretation frame. The “interpretation frame for interruption” here refers to the number of possible image interpretations that are vacant in advance for each sorting target day in consideration of an urgent request for interruption. The interrupt interpretation frame is determined for each distribution target date based on the distribution condition frame ratio 3407 and the increase type 3408, which are set via the requested distribution condition input screen 3400 of FIG. 34. For example, when the frame ratio 3407 is “5%” and the increase type 3408 is “linear”, and the total number of image interpretation doctors on the first day of the distribution target day is 200, the frame ratio is 5%. Therefore, the interrupting interpretation frame on the first day of the distribution target day is “10 cases”. In addition, if the total number of image interpretation doctors on the day following the sorting target date is 180, the percentage of the frame is 10% because the increase type is linear, and the interpretation frame for interruption on the day following the sorting target date is “18 "It becomes. The setting of the interpretation frame for interruption will be described later together with the explanation of the screen.

  If the total number of possible residual interpretations by all the interpretation doctors on the distribution target day at the time of this processing exceeds the interpretation frame for interrupts (YES in step S3305), the remote interpretation server 101 determines that it is for interrupts. It is determined that there is no frame that can be interpreted in the sorting target day in consideration of the image interpretation frame, and the process proceeds to S615. On the other hand, if it does not exceed (NO in S3305), the remote image interpretation server 101 determines that distribution is still possible on the distribution target date, and proceeds to the processing of S613.

  In S614, the remote image interpretation server 101 determines whether or not the number of distribution candidate image interpretation doctors on the distribution target day is 0, and when it is not 0 (YES in S614), the process proceeds to S3306. .. In step S3306, the remote image interpretation server 101 determines whether or not similar request division is prohibited as a distribution condition for automatic distribution, and a similar request exists in a distribution target request. If this condition is satisfied (YES in S3306), the remote image interpretation server 101 determines that distribution including the similarity request is necessary, and transitions to the process of S3307. On the other hand, if similar request division is permitted as the automatic distribution condition, or if similar request division is prohibited but there is no similar request in the distribution target request (NO in S3307), the remote The image interpretation server 101 determines that distribution of similar requests is unnecessary. Then, the process proceeds to S616.

  In step S3307, the remote image interpretation server 101 determines whether it is possible to distribute the distribution target request and all similar requests to all the distribution candidate image interpretation doctors on the distribution target date, and the possible distribution candidate image interpretation is possible. Make a temporary assignment to the doctor. Then, the remote image interpretation server 101 excludes from the distribution candidate image interpretation doctors other than the image interpretation doctor who can distribute the distribution target request and all the similar requests. That is, the remote image interpretation server 101 identifies the request to be distributed and the total number of similar requests of the request, and extracts the image interpretation doctor who has the number of possible image interpretations that is equal to or larger than this total number on the distribution target day. Further, the remote image interpretation server 101 calculates the residual image interpretation possible point of the image interpretation doctor, the extracted summation value of the points of the allocation request and the similar request of the request based on the calculation method described above in S613. . Then, the remote image interpretation server 101 further identifies, from the extracted image interpretation doctors, image interpretation doctors whose remaining image interpretation possible points are equal to or greater than the summed value. The image interpretation doctor thus identified becomes a distribution candidate image interpretation doctor who can process the request for distribution and the similar request. Interpreting doctors other than this are excluded from the distribution candidate interpreting doctors. Then, the process proceeds to S616.

  After the processing of S616, in S3308, the remote interpretation server 101 assigns one interpretation doctor having the highest degree of appropriateness of assignment based on the appropriateness of assignment of each candidate of interpretation doctor calculated in S616. Set in the distribution information of the request. When there are a plurality of image interpretation doctors having the highest degree of appropriateness of distribution, for example, the remote image interpretation server 101 may set one image interpretation doctor with a young image interpretation doctor ID as distribution target in the distribution information. Good. Further, when there is a similar request in the distribution target request, the remote image interpretation server 101 assigns one interpretation doctor having the highest distribution appropriateness of the original distribution target request to the distribution information of the similar request. Set to. The similar request distributed in S3308 is excluded from the subsequent request distribution targets so that the distribution does not overlap.

  In S3309, the remote image interpretation server 101 subtracts one possible number of remaining image interpretations from the distribution schedule of the distribution target day for the image interpretation doctor who is the distribution target set in S3308. Further, the remote image interpretation server 101 subtracts the points of the distribution target request from the remaining image interpretation possible points. When there are similar requests in the distribution target requests, the remote interpretation server 101 can subtract the number of all similar requests from the number of possible residual image interpretations, and further can perform the residual interpretation of points for all similar requests. Subtract from points. Then, the process proceeds to S620.

[Screen configuration example]
FIG. 34 shows a configuration example of the request distribution condition input screen 3400 displayed on the display of the business terminal 112 when the user on the image interpretation center side distributes the request information to the image interpretation doctor. The request distribution condition input screen 3400 is displayed, for example, when the automatic distribution button 1504 of the request distribution screen 1500 of FIG. 15 is pressed. When the distribution start button 3409 is pressed, automatic distribution is performed for the request information selected in the distribution target selection check box 1502 on the request information list 1501 on the request distribution screen 1500 of FIG. .. After that, the distribution result (FIG. 16) is displayed.

  The similar request division 3401 is an item for dividing similar requests and setting whether to permit or prohibit allocation to the image interpretation doctor. Here, in the case of prohibiting, it becomes impossible to divide similar requests and allocate them to different image interpreting doctors. Setting items 3402 to 3405, which are similar conditions, set conditions for determining that the items of request information are similar. According to the conditions set here, each interpretation request is classified as a kind of group. For example, when the setting item 3402 is checked, the request information for the same patient is treated as being similar. Here, similar conditions include the same patient, the same test type, the same test date, and the same request date, but the present invention is not limited to this. That is, any of the attribute information included in the data of each image interpretation request can be used as the classification attribute, and in addition to the above, a case where the requester or the request source is the same may be selected.

  The interrupt interpretation frame 3406 is an item for setting whether or not to perform distribution in consideration of interruption. The frame ratio 3407 becomes effective when “consider” is selected in the interrupting interpretation frame 3406. The frame ratio 3407 provides, as an option, a percentage (ratio) that serves as a reference when calculating the interrupting interpretation frame based on the total number of cases that can be interpreted. The ratio of the frame may have a configuration in which a predefined value can be selected, or the user may input an arbitrary value. The increase type 3408 sets a large number of interpretation frames for interruption each time the allocation target day passes by one day, and specifies the increase rate. As the increase type, it is possible to provide “linear”, “exponential”, etc. as options, but it is not limited to this. For example, when "linear" is designated, it means that the value increases linearly with respect to the value of the frame ratio 3407. Specifically, when “5%” is set as the frame ratio, the first day, the second day, the third day,. ． ． The ratio becomes 5%, 10%, 15%,. ． ． Is calculated as

[Table configuration example]
FIG. 35 is a configuration example of the interrupt facility information table 3500 stored in the database 108. The interrupt facility information table 3500 includes a requested facility ID 3501 and an interrupt consideration sequence 3502. The interrupt facility information table 3500 is used for ordering the request information to be distributed preferentially when considering interrupts when considering interrupts under the distribution condition during automatic distribution. It

  In the present embodiment, in the automatic allocation, the interrupt is taken into consideration, and the allocation is performed by providing a vacant number of cases that can be interpreted. When request information having a high degree of urgency is received after distribution, the user may manually distribute the request information having a high degree of urgency including the empty portion to the image interpreting doctor. .. Alternatively, the remote image interpretation server may execute the automatic distribution again, and distribute the request information set with a high degree of urgency including the empty part while maintaining the request information already distributed.

  When the remote image interpretation server automatically distributes request information set with a high degree of urgency, automatic distribution may be executed at the timing when the request information set with a high degree of urgency is received. Alternatively, the reception of the request information may be regularly monitored, and if the request information is received, the automatic allocation may be performed. Further, when the request information having a high degree of urgency is distributed, the remote image interpretation server may notify the image interpretation doctor who is the distribution destination.

<Other embodiments>
The present invention is also realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or device via a network or various storage media, and the computer (or CPU, MPU, etc.) of the system or device reads the program. This is the process to be executed.

101... Remote interpretation server, 108... Database, 109... Request terminal, 112... Business terminal, 113, 114... Interpretation terminal

Claims (21)

Acquisition means for acquiring a medical image data interpretation request including attribute information;
Management means for managing the parameters set for each of the plurality of radiogram interpreters, which correspond to the attributes included in the attribute information of the medical image data,
The image interpretation request acquired by the acquisition unit, based on the parameters set in each of the image interpretation doctors, which correspond to the attributes included in the attribute information of the medical image data corresponding to the image interpretation request, An information processing device, comprising: an assigning unit that assigns to any of the doctors. The attribute information includes at least an inspection type and an attribute of an imaging region,
The information processing apparatus according to claim 1, wherein the parameter is a value that is set for each combination of attributes included in the attribute information and that indicates the specialty of the image interpretation for each image interpretation doctor. The management unit further manages the number of images that can be interpreted by the image interpretation doctor per day,
The information processing apparatus according to claim 1, wherein the assigning unit further determines an image interpretation doctor to be assigned using the number of cases. Further comprising means for accepting a setting of a frame left open for interruption among the number of cases that can be interpreted by a radiogram interpreter per day managed by the management means,
The information processing apparatus according to claim 3, wherein when the frame is set, the allocation unit allocates the image interpretation request based on the number of cases excluding the frame.   The information processing apparatus according to claim 4, wherein the setting of the frame is specified by a ratio with respect to the number of images that can be interpreted by an image interpretation doctor per day.   The information processing apparatus according to claim 4, wherein the setting of the frame includes an increasing method when increasing the number of frames every day.   When the acquisition unit receives an image interpretation request with a high degree of urgency, the assignment unit is set to a high degree of urgency based on the number of cases including the frame while maintaining the already performed assignment. The information processing apparatus according to any one of claims 4 to 6, wherein an image interpretation request can be assigned.   The information processing apparatus according to any one of claims 3 to 7, wherein the allocation unit allocates the medical image data to each of the plurality of image interpretation doctors on a day-by-day basis. The acquisition means acquires medical image data in units of a predetermined group,
9. The information processing apparatus according to claim 1, wherein the assigning unit assigns to the image interpretation doctor in units of the predetermined group.   The information processing apparatus according to claim 9, further comprising a unit that receives a setting of a classification attribute used when classifying the medical image data into a predetermined group.   The information processing apparatus according to claim 10, wherein the classification attribute includes at least one of a patient, an examination type, an examination date, and a request date. The assigning means,
Determine the priority based on any of the attributes included in the attribute information,
The information processing apparatus according to any one of claims 1 to 11, wherein allocation is performed from the medical image data having a high priority. The reference is the date and time when the medical image data was acquired,
13. The information processing apparatus according to claim 12, wherein the allocating unit gives higher priority to medical image data having an older acquired date and time.   13. The information processing apparatus according to claim 12, wherein the assigning unit gives higher priority to medical image data having a smaller number of image interpreting doctors that can be assigned. The management means further defines a parameter that defines a load during image interpretation for each combination of attribute values of the attribute information, and a parameter that defines a load during image interpretation for each number of images forming the medical image data. Manage,
15. The information processing apparatus according to claim 1, wherein the allocation unit further performs allocation using a parameter that defines the load.   The information processing apparatus according to any one of claims 1 to 15, further comprising means for providing a screen for setting parameters managed by the management means. The management unit further manages an exclusion table defined so that medical image data having attribute information including a value of a predetermined attribute is not assigned to a predetermined image interpretation doctor,
The information processing apparatus according to any one of claims 1 to 16, wherein the allocation unit performs allocation based on the exclusion table.   The information processing apparatus according to any one of claims 1 to 17, further comprising means for providing a screen displaying a result of the allocation by the allocation means. An acquisition step of acquiring a medical image data interpretation request including attribute information;
A management step of managing parameters set for each of a plurality of image interpreting doctors, which correspond to the attributes included in the attribute information of the medical image data,
The image interpretation request acquired in the acquisition step is associated with the attributes included in the attribute information of the medical image data corresponding to the image interpretation request, based on the parameters set for each of the image interpretation doctors. A method for controlling an information processing device, comprising: Computer,
Acquisition means for acquiring a medical image data interpretation request including attribute information,
Management means for managing the parameters set for each of the plurality of image interpretation doctors, which correspond to the attributes included in the attribute information of the medical image data,
The image interpretation request acquired by the acquisition unit, based on the parameters set in each of the image interpretation doctors, which correspond to the attributes included in the attribute information of the medical image data corresponding to the image interpretation request, A program to function as an assigning means to be assigned to any of the doctors. Acquisition means for acquiring a medical image data interpretation request including attribute information;
Management means for managing the parameters set for each of the plurality of radiogram interpreters, which correspond to the attributes included in the attribute information of the medical image data,
The image interpretation request acquired by the acquisition unit, based on the parameters set in each of the image interpretation doctors corresponding to the attributes included in the attribute information of the medical image data corresponding to the image interpretation request, the plurality of image interpretation An information processing system characterized by being assigned to one of medical doctors.

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