JP2019179501A - Information processor - Google Patents

Abstract

To recommend an appropriate doctor according to a symptom or a request of a patient.SOLUTION: A respondent selection part 34 selects N (N is an integral value less than M) doctors among M (M is an integral value equal to larger than 1) doctors based on a request or a situation of a patient itself or a person related to the patient and information on the M doctors as a respondent. A patient information provision part 35 provides information on the patient necessary for responding of the N doctors as patient information to each of the N doctors. A response information acquisition part 36 acquires response information indicating a response from each of the N doctors. A user notification information generation part 37 generates information notifying a user as user notification information based on the respective response information of the N doctors.SELECTED DRAWING: Figure 4

Description

  The present invention relates to an information processing apparatus.

  Conventionally, a doctor selection system for selecting a doctor according to a medical condition or request of a patient has been proposed (see, for example, Patent Document 1). In addition, a second opinion support system that can further reduce the burden on a patient who wants to obtain a second opinion has been proposed (see, for example, Patent Document 2).

JP 2004-13268 A JP 2003-303240 A

  However, in the prior art including Patent Document 1 and Patent Document 2, it is not always necessary to select a doctor who performs an answer to a patient by storing in the system information disclosed publicly regarding a medical institution or doctor. It was difficult to say that a doctor who would give an appropriate answer for the patient was selected.

  This invention is made | formed in view of such a condition, and it aims at selecting appropriately the doctor who can perform a more suitable answer with respect to a patient's medical condition and request | requirement.

In order to achieve the above object, an information processing apparatus of one embodiment of the present invention provides:
Based on the request or situation of the patient himself / herself or the person related to the patient and information on the doctors of M people (M is an integer value of 1 or more), N of the M people (N is an integer value less than M) ) To select respondents as respondents,
Patient information providing means for providing information on the patient necessary for the N doctors to answer as patient information to the N doctors, respectively.
Answer information acquisition means for acquiring answer information indicating an answer from each of the N doctors;
User notification information generating means for generating, as user notification information, information to notify the user based on the answer information of each of the N doctors;
Is provided.

According to the present invention, information that is publicly disclosed regarding hospitals or doctors and information that exists in a closed environment such as an information site for doctors can be effectively used according to the medical condition or request of the patient. It is possible to provide an information processing apparatus that recommends a special doctor.
In addition, the present invention can provide an information processing apparatus that enables multi-opinions by appropriate specialists according to a patient's medical condition or request.

It is a schematic diagram which shows an example of the outline | summary of the service provided using the information processing apparatus of this invention. It is a block diagram which shows the structure of the information processing system containing the server which concerns on one Embodiment of the information processing apparatus of this invention. It is a block diagram which shows an example of a hardware structure of a server among the information processing systems of FIG. It is a functional block diagram which shows an example of a functional structure for performing a user notification information provision process among the functional structures of the server of FIG. It is a flowchart explaining an example of the flow of the user notification information presentation process performed by the server which has a functional structure of FIG. It is a figure which shows the specific example of the doctor information which the memory | storage part of the server which has the functional structure of FIG. 4 stores. It is a figure which shows the specific example of the question screen for obtaining the reply from a doctor among the screens displayed on the doctor terminal which has a functional structure of FIG. It is a figure which shows the specific example of the investigation result screen as an example of the screen as which the user notification information of the best doctor selection is displayed among the screens displayed on the doctor terminal which has the functional structure of FIG.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a schematic diagram showing an example of an outline of a service (hereinafter referred to as this service) provided by using the information processing apparatus of the present invention.
This service provides useful information to patients based on opinions of N people (M is an arbitrary integer less than M) selected from M doctors (M is an arbitrary integer) It is a service.
Here, the patient is a broad concept including not only the examinee but also the non-examinee. That is, a natural person who does not have an attending physician and who wishes to see or diagnose his / her body or the like (may be considered to be a healthy body when actually diagnosed) is also included in the patient. In other words, a person who has a desire to get involved with a medical institution or doctor as a patient is a patient.
From the viewpoint of the provider of this service, M doctors can also be users. Hereinafter, unless otherwise specified, the user means a patient.

In FIG. 1, a doctor member group DG is a group composed of the M doctors described above. Here, the provider of this service operates a Web site (hereinafter referred to as “doctor member site”) that allows M doctors constituting the doctor member group DG to be used as members. And The site for doctor members has a function of posting information useful for engaging in medical activities as articles and allowing members to browse. Further, the site for doctor members has a function of presenting various questionnaires, questions, etc. to the members and receiving responses from the members.
The provider of this service obtains a log of each member's actions (activities on the site for doctor members) for each member (doctor) using the various functions of the site for doctor members including these two functions. Can be managed.

  In the example of FIG. 1, an outline of two services called multi-opinion and best doctor selection among the present services is shown. Hereinafter, each of the multi opinion and the best doctor selection will be described individually in that order.

  A multi-opion is a plurality of doctors (three doctors in the example of FIG. 1) who are diagnosed or diagnosed by a predetermined doctor (not limited to the doctor members constituting the doctor member DG). It is a service that can get opinions from). In other words, a multi-opion is a service that realizes a so-called second opinion more quickly with less burden on more doctors with higher expertise.

Hereinafter, the multi opinion will be described in detail.
In the example of FIG. 1, a multi-opion is performed on the patient P1. It is assumed that the patient P1 is a medical examinee who has undergone a medical examination or diagnosis by a predetermined doctor.
Patient P1 usually does not know much about the many clinics and doctors. For this reason, a predetermined doctor is often determined based on an uncertain reputation and ease of consultation that suits the convenience of the patient P1.
However, depending on the state of mind and body of the patient P1, it may be preferable to avoid immediately following the judgment of a predetermined doctor so as to be cautious in determining the diagnosis itself and the treatment policy and method based on the diagnosis. .
In such a case, the patient P1 operates his / her own terminal (for example, a patient terminal 3 in FIG. 2 described later), and receives information RQ1 such as “I want to refer to a general opinion of a specialist” as a server (for example, described later). To the server 1) of FIG.

  The server selects a group of three doctors DG1 including, for example, three doctors based on the information RQ1 from the patient P1 and information on M doctors belonging to the doctor member group DG.

Each of the three doctors belonging to the group of three doctors DG1 accesses the doctor member site by operating his / her terminal (for example, the doctor terminal 2 in FIG. 2 described later), and receives information RQ1 from the patient P1 or The patient information PD and the like such as the examination value and MRI image for the patient P1 are acquired. Hereinafter, information RQ1, patient information PD, and the like are collectively referred to as “information about patient P1”.
Then, each of the three doctors belonging to the three doctor group DG1 operates his / her terminal, inputs information OP indicating each answer through the doctor member site, and transmits it to the server.

  Based on the information OP, the server generates information AN1 including the answers of the three doctors belonging to the three doctor group DG1, and transmits it to the terminal of the patient P1.

The multi-opinion has been described above. Next, the best doctor selection will be described.
Best doctor selection is a service that recommends doctors and medical institutions with a proven track record that are suitable for the needs and circumstances of patients based on the opinions of a plurality of doctors (30 persons in the example of FIG. 1).

Hereinafter, the best doctor selection will be specifically described.
In the example of FIG. 1, the best doctor selection for the patient P2 is performed. Patient P2 may be a person who has been examined or who has not been examined.
The patient P2 operates his / her own terminal (for example, the patient terminal 3 in FIG. 2 described later), and sends information RQ2 such as “I am looking for a good doctor in Ibaraki” to a server (for example, the server 1 in FIG. 2 described later). ).

  Based on the information RQ2 from the patient P2 and information on M doctors belonging to the doctor member group DG, the server selects, for example, a group of 30 doctors DG2 including 30 doctors.

Each of the 30 doctors belonging to the 30-doctor group DG2 accesses his / her doctor member site by operating his / her own terminal (for example, the doctor terminal 2 of FIG. 2 described later), and receives information RQ2 from the patient P2, etc. Information (hereinafter referred to as “information relating to patient P2”).
Then, each of the 30 doctors belonging to the group of 30 doctors DG2 operates his / her terminal, inputs information RC indicating each answer through the doctor member site, and transmits it to the server.

  Based on the information RC, the server considers the answers of each of the 30 doctors belonging to the group of 30 doctors DG2, and based on the consideration results, information including medical institutions and doctors to be recommended to the patient P2 in Ibaraki. AN2 is generated and transmitted to the terminal of patient P2.

As described above, the multi-opinion and the best doctor selection have been described with reference to FIG. 1, but these are only examples of the service as described above.
In other words, this service suffices if the following processing is executed by the server.

First, based on the request or situation of the patient himself / herself or a person related to the patient, and the information on the doctors of M people (M is an integer value of 1 or more), the server N of M people (N is M (Integer value less than) is selected as the respondent.
In the above-described example, the information RQ1 and the information RQ2 correspond to information (hereinafter referred to as “request status information”) indicating a request or status of the patient himself or a person related to the patient (for example, the patient's family).

It should be noted here that as a method for selecting N doctors (respondents), a method that considers not only the patient's request status information but also information on M doctors who are candidates for respondents is adopted. It is a point.
Thereby, matching with a patient and a doctor is attained, and N doctors suitable for a patient's demand and situation are selected.
Here, as information regarding M doctors, it is possible to adopt only information that has been publicly disclosed by a person other than the provider of this service (hereinafter referred to as “public information”). Instead of or together with this, it is preferable to adopt information on the doctors of the M members on the doctor member site. This is because, since information that cannot be obtained only by public information is taken into consideration and matching between the patient and the doctor is performed, more suitable N doctors can be selected according to the patient's request and situation.
Here, as information other than public information, specifically, for example, information indicating a history of one or more predetermined activities of a member on a doctor member site can be employed. The one or more predetermined activities correspond to respective actions (activities in the site for doctor members) that the member (doctor) uses various functions of the site for doctor members. As described above, these logs are acquired and managed for each member in the server.

  In many cases, the patient desires that the attending physician does not want to know that the service is used. In order to cope with such a case, in the present embodiment, the server prohibits a doctor (including the attending doctor itself) belonging to the same medical institution as the patient's attending doctor from being included in the respondent candidates.

  In addition, the respondent may be selected based on the intention of the provider of the service, but in order to obtain a better answer, it may be better to be selected by a doctor who actively wants to answer. In order to cope with such a case, in this embodiment, the server includes a doctor who has expressed in advance that an answer is desired as a candidate for the answerer, and selects the answerer from the candidates.

  When the server selects N respondents in this way, information related to the patient (for example, patient information PD and request status information RQ1 for patient P1 and patient P2 for patient P1) Request status information RQ2) is provided to N doctors (respondents).

Then, the server acquires information indicating the answer (hereinafter referred to as “answer information”) from each of the N doctors (respondents). For example, information OP and information RC are examples of answer information.
The server generates information to be notified to the user (patient) (hereinafter referred to as “user notification information”) based on the answer information of each of the N doctors. For example, information AN1 and AN2 are examples of user notification information.

Here, it suffices that the user notification information is generated based on the answer information of N doctors, and the generation method and the form thereof are not particularly limited.
For example, in the case of a multi-opinion, it is preferable to generate, as user notification information, information in which the answers of three doctors are posted as they are because of their characteristics. On the other hand, if it is the best doctor selection, rather than publishing the answers of 30 doctors as facts as it is, we consider these answers and summarize the contents and summaries based on the consideration results. It is preferable to generate user notification information including the contents and the like.
Furthermore, if it is the best doctor selection, in addition to the answers of each of the N doctors, the server further includes past user notification information (information on another patient or information based on the answers of another doctor). User notification information may be generated based on the result of the consideration. This makes it possible for a patient to consider not only N doctors' answers but also the answers of similar past cases, that is, a recommendation based on more specialized opinions, which is beneficial to the patient.

An information processing apparatus (server) capable of realizing such a service, that is, a server that is an embodiment of an information processing apparatus to which the present invention is applied will be described below.
FIG. 2 is a block diagram showing a configuration of an information processing system including a server according to an embodiment of the information processing apparatus of the present invention.

  The information processing system shown in FIG. 2 includes a server 1 managed by a provider of this service, doctor terminals 2-1 to 2-M operated by M doctors, and a patient terminal operated by a patient P1. 3-1, and a patient terminal 3-2 used for the patient P2.

In addition, when it is not necessary to distinguish each of the doctor terminals 2-1 to 2-M individually, these are collectively referred to as “doctor terminal 2”.
Similarly, when there is no need to individually distinguish between the patient terminal 3-1 and the patient terminal 3-2, these are collectively referred to as “patient terminal 3”. The number of patient terminals 3 is not limited to two in the example of FIG. That is, if there is another patient not shown in FIG. 1, there is actually a patient terminal 3 operated by the other patient.

FIG. 3 is a block diagram illustrating an example of a hardware configuration of the server 1 in the information processing system of FIG.
The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an output unit 16, an input unit 17, A storage unit 18, a communication unit 19, and a drive 20.

  The CPU 11 executes various processes according to a program recorded in the ROM 12 or a program loaded from the storage unit 18 to the RAM 13.

  The RAM 13 appropriately stores data necessary for the CPU 11 to execute various processes.

  The CPU 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output interface 15 is also connected to the bus 14. An output unit 16, an input unit 17, a storage unit 18, a communication unit 19, and a drive 20 are connected to the input / output interface 15.

The output unit 16 includes a display, a speaker, and the like, and outputs images and sounds.
The input unit 17 includes various buttons and the like, and inputs various types of information according to user instruction operations.
The storage unit 18 is configured by a hard disk, a DRAM (Dynamic Random Access Memory), or the like, and stores various data such as doctor information to be described later.
The communication unit 19 controls communication performed with other devices (the doctor terminal 2 and the patient terminal 3).

  A removable medium 21 made of a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is appropriately attached to the drive 20. The program read from the removable medium 21 by the drive 20 is installed in the storage unit 18 as necessary. The removable medium 21 can also store various data such as doctor information stored in the storage unit 18 in the same manner as the storage unit 18.

FIG. 4 is a functional block diagram illustrating an example of a functional configuration for executing the user notification information providing process among the functional configurations of the server of FIG.
The user notification information providing process is a process on the server 1 side for providing the service described above.

When the user notification information providing process is executed, in the CPU 11 of the server 1, the doctor member site management unit 31, the doctor information acquisition unit 32, the request status information acquisition unit 33, the respondent selection unit 34, and the patient information The providing unit 35, the answer information acquiring unit 36, the user notification information generating unit 37, the user notification information presenting unit 38, and the feedback information acquiring unit 39 function.
Further, a doctor DB 51 and a patient information DB 52 are provided in one area of the storage unit 18 of the server. The doctor DB 51 stores doctor information described later with reference to FIG.

  The doctor member site management unit 31 manages the doctor member dedicated site described above.

The doctor information acquisition unit 32 acquires information on M doctors (members) who can use the doctor member dedicated site as doctor information and stores the information in the doctor DB 51.
The doctor information acquisition unit 32 includes a public information acquisition unit 41 and a member activity information acquisition unit 42.
The public information acquisition unit 41 acquires first type information publicly disclosed for each of M doctors, that is, public information, from an external communication network C such as the Internet.
The member activity information acquisition unit 42, as the second type information on the members about each of the M doctors on the doctor member dedicated site that M doctors can use as members, Information (log information) indicating the history of the predetermined activity is acquired. Such log information is hereinafter referred to as “member activity information”.
Specifically, for example, here, the member activity information acquisition unit 42 acquires information on the activity of the member on the site for the doctor member, for example, information indicating the tendency of the action of the doctor on the site for the doctor member. In addition, for example, the member activity information acquisition unit 42 acquires information related to a doctor's answer in the service (multi-opinion, best doctor selection, etc.), for example, the actual number of answers of the doctor.

The request status information acquisition unit 33 acquires information on the request or status of the patient himself or the person related to the patient as request status information.
For example, in the case of a multi opinion, the information RQ1 and the like in FIG. 1 are acquired as the request status information. If it is the best doctor selection, information RQ2 etc. of FIG. 1 etc. are acquired as request condition information.

  The provider of the request status information is the patient terminal 3 in this embodiment, but is not particularly limited to this, and may be a medium such as a memory stick or paper.

The respondent selection unit 34 includes request status information acquired by the request status information acquisition unit 33 and doctor information (public information and member activity) regarding M doctors acquired by the doctor information acquisition unit 32 and stored in the doctor DB 51. Based on the information, matching processing between the patient and each of the M doctors is executed. The respondent selection unit 34 selects N persons as respondents from the M doctors based on the execution result of the matching process.
By this, for example, the optimal doctor who can appropriately respond to the request or situation of patients etc. by comparing the data such as the treatment history facility of the target disease that is public, the working group of rare diseases, etc. Can be selected as respondent.
Note that the M doctors who are candidates for respondents may be extended to doctors who are cooperating with the trial of the provider of this service.

  Here, in the present embodiment, the respondent selection unit 34 includes, as a candidate of the respondent, if there is a doctor who has expressed in advance that an answer is desired among the M doctors. Select respondents from the candidates.

  Further, in the present embodiment, the respondent selection unit 34 prohibits inclusion of doctors (including the attending doctors themselves) belonging to the same medical institution as the patient's attending doctors as respondent candidates.

In the present embodiment, the respondent selection unit 34 considers feedback information to be described later in addition to the request status information and the doctor information regarding the M doctors when selecting the respondent.
As a result, the evaluation by a patient who has received this service in the past (this may be the patient who is the subject of this service or may be another patient) is also considered. It can be selected more appropriately.

  Further, not only feedback from the patient side (evaluation on the patient side, etc.) but also the result of machine learning using past information on the doctor side may be taken into account to select the respondent. Specifically, for example, which doctor will give the best answer by combining past questionnaire response results, analysis of behavior trends within the site for doctor members, and thesis writing information that is public information May be used for machine learning, and the result of the machine learning may be used for selecting the respondent.

The patient information providing unit 35 provides N doctors with information related to patients necessary for N doctors to answer.
Here, the information about the patient includes, for example, the request status information acquired by the request status information acquisition unit 33 (the information RQ1 in FIG. 1 if it is a multi opinion, and the information RQ2 in FIG. 1 if it is the best doctor selection). Is included).
Further, in the case of a multi-opinion, patient information (for example, patient information PD in FIG. 1) stored in the patient information DB 52 is also included in the patient-related information.

Here, in the present embodiment, the patient information providing unit 35 processes at least information identifying the patient among the information related to the patient, which is shaded in the doctor terminals 2 of N doctors (for example, in FIG. 4). Stuff).
Here, the processing method and form are not particularly limited, but in the present embodiment, the patient information providing unit 35 anonymizes the patient's personal information in order to protect the patient. The anonymization method is not particularly limited, and for example, a method of deleting all the patient personal information such as name and age included in the image diagnostic result of the patient using a viewer can be employed.

The reply information acquisition unit 36 acquires information indicating the answers of the N doctors as reply information from the doctor terminals 2 of the N doctors.
For example, in the multi opinion, information (for example, information OP in FIG. 1) including an opinion of consent or disagreement with respect to the diagnosis of the attending physician is acquired as answer information.
In addition, for example, in the best doctor selection, information indicating a recommended medical institution or doctor (for example, information RC in FIG. 1) is acquired as answer information.

The user notification information generation unit 37 generates user notification information based on the answer information of each of N doctors.
For example, in the multi opinion, information (for example, information AN1 in FIG. 1) in which the answers of N doctors (N = 3) are arranged is generated as user notification information.
In addition, for example, in the best doctor selection, in addition to the contents of the answers of N doctors (N = 30), information including the results of consideration of these answers (for example, information AN2 in FIG. 1) is generated as user notification information. Is done. Here, the method of consideration is not particularly limited, but in the present embodiment, since past user notification information is accumulated, the trends of past reports are also referred to, and the responses of N doctors are considered. . In this case, the past user notification information may be, for example, that of another patient having the same target disease, the same patient having the same target disease, or the like.

  Further, for example, in the best doctor selection, the user notification information generation unit 37 may generate user notification information based on feedback information described later in addition to the reply information of each of N doctors.

The user notification information presentation unit 38 presents user notification information to the patient via the patient terminal 3.
By doing so, for example, depending on the conventional second opinion, the patient P1 who uses the multi-opion is not subject to restrictions on time and movement, which would be a heavy burden when collecting opinions from three specialists. It becomes.

The feedback information acquisition unit 39 acquires feedback information from the user with respect to the user notification information from the patient terminal 3 and stores it in, for example, the doctor DB 51.
The feedback information may be, for example, an evaluation of respondents (three doctors) or the content of responses in a multi opinion, or an evaluation of recommended content (a recommended medical institution or doctor) in, for example, Best Doctor Selection. It may be.

  FIG. 5 is a flowchart for explaining an example of the flow of user notification information presentation processing executed by the server 1 having the functional configuration of FIG.

In step S <b> 1, the request status information acquisition unit 33 acquires request status information about the user (patient) from the patient terminal 3 of the user.
In step S2, the respondent selection unit 34 selects N out of M doctors based on the request situation information acquired in step S1 and the doctor information on the M doctors stored in the doctor DB 51. Select as respondent.
In step S3, the patient information providing unit 35 provides information on the user (patient) including the request status information acquired in step S1 to the doctor terminals 2 of the N doctors selected in step S2.
In step S4, the reply information acquisition unit 36 acquires reply information including a reply to the information regarding the user (patient) provided in step S3 from the doctor terminals 2 of the N doctors.
In step S5, the user notification information generation unit 37 generates user notification information based on the answer information of each of the N doctors acquired in step S4.
In step S <b> 6, the user notification information presentation unit 38 transmits the user notification information to the patient terminal 3 to present it to the patient.
As a result, the user notification information presentation process ends.

  Next, specific examples of various types of information used in the user notification information presentation process will be described with reference to FIGS.

FIG. 6 is a diagram illustrating a specific example of doctor information stored in a server having the functional configuration of FIG.
The doctor information is stored in the doctor DB 51, for example, in a data configuration as shown in FIG.
In the example of FIG. 6, for convenience of explanation, one predetermined line corresponds to one doctor.
The predetermined one line of doctor information is public information (first type information) about the doctor corresponding to the one line. It consists of member activity information (type 2 information) and feedback information.
As the public information, “doctor name”, “affiliation institution”, “region”, “specialty”, “target disease”, “number of clinic cases”, and “number of articles” are stored.
As the member activity information, “response record” and “in-site action” are stored.
“Patient feedback” is stored as feedback information.

Here, one doctor may belong to a plurality of institutions and act as a doctor, specialize in a plurality of departments, and handle a plurality of target diseases.
That is, in the example of FIG. 6, one predetermined line is associated with one doctor, but in reality, “institution”, “region”, “special”, or “ A predetermined line may correspond to each “target disease”.
In other words, the doctor information relating to one doctor is composed of one line in the example of FIG. 6, but may be composed of a plurality of lines as a matter of course.

The name of the doctor corresponding to the one line is stored in the item of “doctor name” in a predetermined line. In addition, you may replace with the item which stores the information which a doctor can specify uniquely, for example, an identification number.
A medical institution to which a doctor corresponding to the one row belongs is stored in the item “affiliation institution” in a predetermined row. With this item, for example, when selecting a multi-opinion respondent, a doctor who belongs to the same medical institution as the patient's primary doctor can be excluded from the respondent.
The location of the medical institution to which the doctor corresponding to the predetermined line belongs is stored in the item “Region” of the predetermined line. By this item, especially when selecting respondents for the best doctor selection, pick up doctors who have a high probability of giving appropriate answers to questions that recommend local medical institutions and doctors according to the patient's needs and circumstances. Is easily possible.
In the “specialty” item in a predetermined line, a doctor's specialized department corresponding to the line is stored. The item of “target disease” in a predetermined line stores a disease name or the like that can be examined by a doctor corresponding to the line. These “specialties” and “target diseases” also help in selecting respondents that are more suitable for the needs and circumstances of patients.

The item “number of clinic cases” in a predetermined line includes the number of cases of “target disease” in the one line for the medical institution to which the doctor corresponding to the line belongs, that is, the “institution” in the one line. Stored. That is, in each row corresponding to a plurality of doctors belonging to the same medical institution, the same value is stored in the item “number of clinic cases”.
By doing so, it becomes possible to easily select a doctor who belongs to a medical institution with a large number of cases for the target disease as an answerer.

The number of articles written in a predetermined line stores the number of articles written by the doctor corresponding to the line corresponding to the target disease in the line.
By doing in this way, it becomes possible to easily select doctors who have high expertise in the target disease as respondents.

The number of answers to medical questions and consultations on the site dedicated to doctor members, including the answers of this service, for the doctors corresponding to the one line is stored in the item of “response results” in a predetermined line. The
The item of “in-site action” in a predetermined line indicates information on the activity on the doctor member site for the doctor corresponding to the one line, for example, the tendency of the doctor's action in the doctor member site. Information is stored.
Member activity information such as “response results” and “in-site behavior” is valuable doctor information that can be obtained only by the provider of this service that manages a site dedicated to doctor members, which cannot be obtained by public information. Since it is possible to select respondents that take into account such valuable doctor information, doctors that better match the patient's needs and circumstances are selected more appropriately as respondents than when selecting only public information. It becomes possible to do.

The item of “patient feedback” in a predetermined line stores feedback information such as an evaluation from the doctor himself / herself corresponding to the one line or an answer content of the doctor.
This item helps to determine whether or not a doctor corresponding to the one line is selected as an answerer such as a multi-op. In addition, this item helps to determine whether or not the doctor corresponding to the one row can be a doctor recommended on the best doctor selection, for example.

  FIG. 7 is a diagram showing a specific example of a question screen for obtaining an answer from a doctor among screens displayed on a doctor terminal having the functional configuration of FIG.

The question screen in the example of FIG. 7 is displayed on the doctor terminal 2 of the doctor selected as the respondent in the best doctor selection.
In this question screen, only a rough current address and age can be displayed as information about the patient, which can make it extremely difficult for respondents to identify the patient, thus protecting the patient's privacy. Can do.
In addition, on this question screen, an input field for entering the reason is displayed in addition to the name of the hospital and the name of the doctor whose count is recommended. By doing this, not only the ranking of hospitals and doctors recommenders, but also reports (user notification information) that clearly indicate the general opinions of specialists with reference to the patient's medical condition, treatment status and other information Will be easy to present to the patient.

  By using such a question screen, the respondent must clearly indicate a general opinion and recommend a hospital and a doctor. By referring to the reason, the patient can refer to the reason for the recommendation of hospitals and doctors with the highest number of recommenders, and can find the best hospital and doctor even if the number of recommenders is not higher. It becomes a reference opinion.

FIG. 8 is a diagram showing a specific example of a survey result screen as an example of a screen on which user notification information of the best doctor selection is displayed among screens displayed on the doctor terminal having the functional configuration of FIG.
The survey result screen may be provided to the patient as some form of electronic data or printed matter.

On the survey result screen, medical institutions (hospitals) and doctors recommended by the best doctor selection are displayed as a list of candidates for patient visits.
By doing in this way, it becomes possible for a patient to easily list potential candidates as a medical examination destination.

On the survey result screen, the continuation as the survey result information exists after the next page, and more detailed information of influential candidates as consultation destinations is individually displayed.
By doing in this way, it becomes possible for a patient to examine an effective candidate as a consultation destination individually or in comparison based on a sufficient amount of individual information.

In addition, consideration may be added to the survey result screen to assist the judgment of the patient's consultation destination.
Here, the discussion can include an individual assessment of whether it is considered relevant in the relationship with the patient, rather than just facts about the hospital and the physician. Specifically, for example, individual requests for each patient such as “I think that radiation therapy will be necessary in the future from the patient's situation, and it is good that radiation therapy is possible in the vicinity of your home,” Personalized assessments based on the situation can be included in the discussion.
By doing in this way, the information used as the evaluation with respect to the hospital and doctor from the patient side can be referred, and it becomes possible to assist the judgment of a patient's consultation destination effectively.

  As mentioned above, although embodiment of this invention was described, this invention is not restricted to embodiment mentioned above. In addition, the effects described in the present embodiment are merely a list of the most preferable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the present embodiment.

In the above-described embodiment, as described above, the doctor information stored in the doctor DB 51 other than the papric information and the member activity information is the feedback information, but is not limited thereto. For example, the credibility rating of the doctor's answer may be given and stored.
In this way, the respondent selection unit 34 can exclude doctors with low credibility from respondents based on the credibility rating included in the doctor information stored in the doctor DB 51.

  In the above-described embodiment, the patient P1 obtains image data, etc. from the hospital, and collects the data manually, such as recording it on a medium such as a CD and mailing it to the provider of this service. Information PD may be collected on behalf of a hospital on the service provider side.

  When the processing of each functional block is executed by software, a program constituting the software is installed on a computer or the like from a network or a recording medium.

  The computer may be a computer incorporated in dedicated hardware. The computer may be a computer capable of executing various functions by installing various programs, for example, a general-purpose smartphone or personal computer other than a server.

  A recording medium including such a program is not only constituted by a removable medium distributed separately from the apparatus main body in order to provide the program to each user, but also provided to each user in a state of being incorporated in the apparatus main body in advance. It is composed of a provided recording medium or the like.

In the present specification, the steps for describing the program recorded on the recording medium are not limited to the processing performed in time series according to the order, but may be performed in parallel or individually even if not necessarily performed in time series. The process to be executed is also included.
Further, in the present specification, the term “system” means an overall apparatus configured by a plurality of devices, a plurality of means, and the like.

In summary, the information processing apparatus to which the present invention is applied only needs to have the following configuration, and can take various embodiments.
That is, an information processing apparatus to which the present invention is applied
Based on the request or situation of the patient himself / herself or the person related to the patient and information on the doctors of M people (M is an integer value of 1 or more), N of the M people (N is an integer value less than M) ) Respondent selection means (for example, the respondent selection unit 34 in FIG. 4) for selecting a doctor as a respondent;
Patient information providing means (for example, patient information providing unit 35 in FIG. 4) for providing information on the patient necessary for the N doctors to answer, as patient information, to the N doctors,
Response information acquisition means (for example, the response information acquisition unit 36 in FIG. 4) for acquiring response information indicating responses from each of the N doctors,
User notification information generating means (for example, the user notification information generating unit 37 in FIG. 4) that generates information to notify the user as user notification information based on the answer information of each of the N doctors;
It is enough to have
By applying the information processing apparatus having such a configuration, it is possible to appropriately select a doctor who can make a more appropriate answer to a patient's medical condition or request.

DESCRIPTION OF SYMBOLS 1 ... Server, 2 ... Doctor terminal, 3 ... Patient terminal, 11 ... CPU, 12 ... ROM, 13 ... RAM, 14 ... Bus, 15 ... Input / output Interface: 16 ... Output unit, 17 ... Input unit, 18 ... Storage unit, 19 ... Communication unit, 20 ... Drive, 21 ... Removable media, 31 ... Doctor member site Management unit, 32 ... Doctor information acquisition unit, 33 ... Request status information acquisition unit, 34 ... Respondent selection unit, 35 ... Patient information provision unit, 36 ... Response information acquisition unit, 37 User notification information generation unit 38 User notification information presentation unit 39 Feedback information acquisition unit 41 Public information acquisition unit 42 Member activity information acquisition unit 51・ Doctor DB, 52 ... Patient information DB, AN1 ... Yu Notification information, AN2 ... User notification information, C ... External communication network, DG ... Doctor member group, DG1 ... Third doctor group, DG2 ... Thirty doctor group, OP ... Reply Information, P1 ... Patient, P2 ... Patient, PD ... Patient information, RC ... Response information, RQ1 ... Request status information, RQ2 ... Request status information, NW ... Network

Claims (11)

Based on the request or situation of the patient himself / herself or the person related to the patient and information on the doctors of M people (M is an integer value of 1 or more), N of the M people (N is an integer value less than M) ) To select respondents as respondents,
Patient information providing means for providing information on the patient necessary for the N doctors to answer as patient information to the N doctors, respectively.
Answer information acquisition means for acquiring answer information indicating an answer from each of the N doctors;
User notification information generating means for generating, as user notification information, information to notify the user based on the answer information of each of the N doctors;
An information processing apparatus comprising: The respondent selection means includes a doctor who has expressed in advance that he / she wants an answer as a candidate for the respondent, and selects the respondent from the candidates.
The information processing apparatus according to claim 1. The respondent selection means prohibits a doctor belonging to the same medical institution as the patient's attending physician from being included in the respondent candidates.
The information processing apparatus according to claim 1 or 2. As the information on the M doctors, the first type information publicly disclosed about each of the M doctors and the M website on the membership system website that the M doctors can use as members. The information processing apparatus according to any one of claims 1 to 3, further comprising an acquisition unit configured to acquire second type information relating to a member of each of human doctors. The second type information includes information indicating a history of one or more predetermined activities of the member on the membership system website,
The information processing apparatus according to claim 4. The respondent selection means is configured to perform matching between the patient and each of the M doctors based on the request or the situation of the patient or the person related to the patient and information on the M doctors. Executing a process, and selecting the N doctors as the respondent based on the execution result of the process;
The information processing apparatus according to any one of claims 1 to 5. The patient information providing means provides, as the patient information, information obtained by processing at least information identifying the patient among the information on the patient, respectively, to the N doctors.
The information processing apparatus according to any one of claims 1 to 6. The user notification information generating means considers the answer information of each of the N doctors, and generates the user notification information based on the consideration result.
The information processing apparatus according to any one of claims 1 to 7. The user notification information generating means further considers the past user notification information in addition to the reply information of each of the N doctors, and generates the user notification information based on the consideration result.
The information processing apparatus according to claim 8. Feedback information acquisition means for acquiring feedback information from the user for the user notification information;
Further comprising
The respondent selection means selects the respondent based on the feedback information in addition to the request or the situation of the patient or the person related to the patient,
The information processing apparatus according to any one of claims 1 to 9. Feedback information acquisition means for acquiring feedback information from the user for the user notification information;
Further comprising
The user notification information generating means generates the user notification information based on the feedback information in addition to the answer information of each of the N doctors.
The information processing apparatus according to any one of claims 1 to 9.

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