Patent Publication Number: US-2018046828-A1

Title: Information processing apparatus, information processing system and information processing method

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2016-159387, filed on Aug. 15, 2016, and the Japanese Patent Application No. 2016-224042, filed on Nov. 17, 2016, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The embodiments discussed herein are related to an information processing apparatus, an information processing system and an information processing method. 
     BACKGROUND 
     In recent years, there is an increasing demand for big data analysis. In order to obtain more accurate and more useful analysis results in big data analysis, it is desirable to collect as many data samples as possible. 
     The government of Japan has a plan to carry out policy to promote big data analysis in the domestic medical field in the future. This plan aims at a situation where pieces of data of electronic medical records are collected from hospitals, the collected pieces of data are processed to anonymous data, and groups that wish to use the anonymous data are provided with the data as data available for big data analysis. 
     An electronic medical record is data including much personal information that is related to privacy of patients. Thus, it is desirable that measures be taken to prevent leaks of personal information when a great amount of this kind of data is collected. 
     Techniques that collect and use gene information are also known (see Patent Documents 1 and 2 for example). 
     Patent Document 1: Japanese Laid-open Patent Publication No. 11-353404 
     Patent Document 2: Japanese Laid-open Patent Publication No. 2004-287847 
     SUMMARY 
     According to an aspect of the embodiments, an information processing apparatus includes a memory, a processor coupled to the memory and a communication interface circuit. The memory stores a plurality of pieces of information transferred respectively from a plurality of information provision institutions. The processor extracts a plurality of pieces of analysis target information that are to be provided to an analysis device, respectively from the plurality of pieces of information stored in the memory. The communication interface circuit transfers the plurality of pieces of information to a first storage device via a first communication network and transfers the plurality of pieces of analysis target information to a second storage device connected to a second communication network. The second communication network is separated from the first communication network and the analysis device is connected to the second communication network. 
     The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a configuration diagram of an electronic-medical-record analysis system; 
         FIG. 2  illustrates a data provision sequence; 
         FIG. 3  illustrates a data analysis sequence; 
         FIG. 4  is a configuration diagram of a first information processing system; 
         FIG. 5  is a flowchart of an information extraction process; 
         FIG. 6  illustrates a specific example of an information processing system of medical record information; 
         FIG. 7  illustrates a functional configuration diagram of a virtual machine; 
         FIG. 8  illustrates logical volumes of medical record information and analysis target information; 
         FIG. 9  illustrates an example of an input screen of consultation information; 
         FIG. 10  illustrates medical record information of hospital A; 
         FIG. 11  illustrates medical record information of hospital B; 
         FIG. 12  illustrates analysis target item information; 
         FIG. 13  illustrates analysis target information of hospital A; 
         FIG. 14  illustrates analysis target information of hospital B; 
         FIG. 15  illustrates integrated analysis target information of a hospital; 
         FIG. 16  illustrates an analysis process of medical record information; 
         FIG. 17A  illustrates an information extraction sequence of hospital A (first part); 
         FIG. 17B  illustrates the information extraction sequence of hospital A (second part); 
         FIG. 18A  illustrates an information extraction sequence of hospital B (first part); 
         FIG. 18B  illustrates the information extraction sequence of hospital B (second part); 
         FIG. 19  illustrates a first information analysis sequence; 
         FIG. 20  illustrates a server system and a storage system; 
         FIG. 21  illustrates a first volume-allocation sequence; 
         FIG. 22  illustrates a specific example of an information processing system of purchase information; 
         FIG. 23  illustrates an input screen of purchase information; 
         FIG. 24  illustrates purchase information of convenience store A; 
         FIG. 25  illustrates analysis target information of convenience store A; 
         FIG. 26  illustrates analysis target information of convenience store B; 
         FIG. 27  illustrates integrated analysis target information of convenience stores; 
         FIG. 28  illustrates analysis process of purchase information; 
         FIG. 29  is a configuration diagram of a second information processing system; 
         FIG. 30  is a flowchart of an information obtainment process; 
         FIG. 31  is a configuration diagram of an analysis system; 
         FIG. 32  illustrates a first table; 
         FIG. 33  illustrates a second table; 
         FIG. 34  illustrates a second volume-allocation sequence; 
         FIG. 35  illustrates a second information analysis sequence; and 
         FIG. 36  illustrates a hardware configuration of an information processing apparatus. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Hereinafter, detailed explanations will be given for the embodiments by referring to the drawings. 
       FIG. 1  illustrates a configuration example of a hypothetical electronic-medical-record analysis system that collects and analyzes electronic medical records in accordance with the policy of the government of Japan. In the electronic-medical-record analysis system illustrated in  FIG. 1 , an information provision institution is a hospital that provides data of electronic medical records, an information analysis institution is an institution such as the government etc. that collects and analyzes data of electronic medical records, and an information using institution is an institution such as a research institution, a pharmaceutical company, etc. that uses analysis results. 
     The electronic-medical-record analysis system illustrated in  FIG. 1  includes a hospital system  101 - 1  of hospital A, a hospital system  101 - 2  of hospital B, an analysis system  102  of an information analysis institution and a user system  103  of an information using institution. The number of the hospital systems is not limited to two, and three or more hospital systems may exist when there are three or more hospitals. For example, a plurality of hospitals existing across the country may serve as information provision institutions. 
     The hospital system  101 - i  (i=1, 2) includes a personal computer (PC)  111 - i,  a PC  112 - i  and a storage device  113 - i.  The PCs  111 - i  and  112 - i  and the storage device  113 - i  are connected via for example a local area network (LAN). The PCs  111 - 1  and  112 - 1  have electronic-medical-record clients  141 - i  and  142 - i  installed as applications in them, respectively. 
     The analysis system  102  includes a sever  121 , a collection storage device  122 , an analysis device  123  and a server  124 . The collection storage device  122  includes a collection database (DB)  151 , and the server  124  includes an analysis result DB  152 . The analysis device  123  is for example a PC of an analyzer. The user system  103  includes a PC  131  and a PC  132 . 
     In the electronic-medical-record analysis system illustrated in  FIG. 1 , an electronic medical record is analyzed in for example the following order. 
     (P1) A doctor of each hospital uses the electronic-medical-record client  141 - i  or the electronic-medical-record client  142 - i  so as to input consultation information of a patient. 
     (P2) The storage device  113 - i  stores input consultation information, as medical record information  143 - i.    
     (P3) The doctor stores, in a Digital Versatile Disk (DVD)  114 - i,  a copy of the medical record information  143 - i  stored in the storage device  113 - i.    
     (P4) Each hospital delivers the DVD  114 - i  to an information analysis institution. 
     (P5) An analyzer in the information analysis institution uses the analysis device  123  so as to read the medical record information  143 - i  from the delivered DVD  114 - i,  and stores the copy of the medical record  143 - i  in the collection DB  151 . 
     (P6) The analyzer uses the analysis device  123  so as to obtain the medical record information  143 - i  of a plurality of patients from the collection DB  151 , and analyzes the obtained medical record information  143 - i.    
     (P7) The analyzer uses the analysis device  123  so as to confidentialize personal information included in analysis results, and stores the confidentialized analysis results in the analysis result DB  152 . Thereby, the analysis results are processed into anonymous data. 
     (P8) The information analysis institution provides the analysis results to the user system  103  of the information using institution, and a user of the information using institution uses the PC  131  or  132  so as to obtain the analysis results from the analysis result DB  152 . 
       FIG. 2  illustrates an example of a data provision sequence in the hospital system  101 - 1  and the hospital system  101 - 2 . In the hospital system  101 - 1 , the electronic-medical-record client  141 - i  in the PC  111 - 1  inputs consultation information of a patient in accordance with manipulation conducted by a doctor of hospital A (step  201 ), and writes the medical record information  143 - 1  to the storage device  113 - 1  (step  202 ). 
     Next, in accordance with manipulation by the doctor, the electronic-medical-record client  141 - 1  instructs the storage device  113 - 1  to write the medical record information  143 - 1  (step  203 ). Then, the storage device  113 - 1  writes a copy of the medical record information  143 - 1  to the DVD  114 - 1  (step  204 ). 
     In the hospital system  101 - 2 , the electronic-medical-record client  141 - 2  in the PC  111 - 2  inputs consultation information of a patient in accordance with manipulation conducted by a doctor of hospital B (step  205 ), and writes the medical record information  143 - 2  to the storage device  113 - 2  (step  206 ). 
     Next, in accordance with manipulation by the doctor, the electronic-medical-record client  141 - 2  instructs the storage device  113 - 2  to write the medical record information  143 - 2  (step  207 ). Then, the storage device  113 - 2  writes a copy of the medical record information  143 - 2  to the DVD  114 - 2  (step  208 ). 
       FIG. 3  illustrates an example of a data analysis sequence in the analysis system  102  illustrated in  FIG. 1 . First, in accordance with an instruction from an analyzer of an information analysis institution, the server  121  reads the medical record information  143 - 1  from the DVD  114 - 1  (step  301 ), and writes the medical record information  143 - 1  to the collection DB  151  of the collection storage device  122  (step  302 ). 
     Next, the server  121  reads the medical record information  143 - 2  from the DVD  114 - 2  in accordance with an instruction from the analyzer (step  303 ), and writes the medical record information  143 - 2  to the collection DB  151  (step  304 ). 
     Next, in accordance with manipulation from the analyzer, the analysis device  123  reads the medical record information  143 - 1  and the medical record information  143 - 2  from the collection DB  151  (step  305 ). Next, in accordance with manipulation by the analyzer, the analysis device  123  analyzes the medical record information  143 - 1  and the medical record information  143 - 2  (step  306 ), and confidentializes personal information included in the analysis results (step  307 ). Then, the analysis device  123  stores the confidentialized analysis results in the analysis result DB  152  of the server  124  (step  308 ). 
     Next, the server  124  provides the PC  131  of the user system  103  with the analysis results stored in the analysis result DB  152  (step  309 ). 
     In the electronic-medical-record analysis system illustrated in  FIG. 1 , the medical record information  143 - i  is collected by physically carrying the DVD  114 - i  from each hospital to an information analysis institution, and accordingly it takes time and effort to collect information, making real-time collection of information difficult. 
     Also, because analyzers of an information analysis institution that manages the collection DB  151  are allowed to refer to the medical record information  143 - i  that has not been confidentialized, there is a possibility that consultation information of a patient will leak from the analyzers. 
     Note that this problem arises not only in a case when electronic medical records of hospitals are collected, but also in a case when other types of information are collected in other types of information provision institutions. 
       FIG. 4  illustrates a configuration example of a first information processing system of an embodiment. An information processing system  401  illustrated in  FIG. 4  includes a storage device  411 , a storage device  412  and an information processing apparatus  413  (computer), and the information processing apparatus  413  includes a storage unit  421 , an extraction unit  422  and a transfer unit  423 . 
     The storage device  411  is connected to a communication network  431 , and stores a plurality of pieces of information transferred respectively from a plurality of information provision institutions. The storage device  412  is connected to a communication network  432 , and stores a plurality of pieces of analysis target information provided to the analysis device  414 . The communication network  432  is separated from the communication network  431 , and the analysis device  414  is connected to the communication network  432 . 
     The information processing apparatus  413  receives the plurality of pieces of information respectively from the plurality of information provision institutions, and the transfer unit  423  transfers the plurality of pieces of received information to the storage device  411  via the communication network  431 . Then, the information processing apparatus  413  obtains the plurality of pieces of information from the storage device  411  so as to store them in the storage unit  421 . The extraction unit  422  and the transfer unit  423  perform an information extraction process for the plurality of pieces of information stored in the storage unit  421 . 
       FIG. 5  is a flowchart illustrating an example of a first information extraction process that is performed by the information processing apparatus  413  illustrated in  FIG. 4 . First, the extraction unit  422  extracts the plurality of pieces of analysis target information respectively from the plurality of pieces of information stored in the storage unit  421  (step  501 ). Then, the transfer unit  423  transfers the plurality of pieces of analysis target information to the storage device  412  (step  502 ). 
     The information processing system  401  as described above makes it possible to reduce the risk of information leak in a case when pieces of information collected from a plurality of information provision institutions are analyzed. 
       FIG. 6  illustrates a specific example of the information processing system  401  illustrated in  FIG. 4 . An information processing system  600  illustrated in  FIG. 6  includes a hospital system  601 - 1  of hospital A, a hospital system  601 - 2  of hospital B, an analysis system  602  of an information analysis institution and a user system  603  of an information using institution. Similarly to the electronic-medical-record analysis system illustrated in  FIG. 1 , the number of the hospital systems may be three or more. 
     The hospital system  601 - i  (i=1, 2) includes a PC  611 - i  and a PC  612 - i.  The PCs  611 - i  and  612 - i  have electronic-medical-record clients  641 - i  and  642 - i  installed as applications in them, respectively. 
     The analysis system  102  includes a sever  621 , a storage device  622 , a storage device  623 , a management server  624 , an aggregating device  625 , a storage device  626 , an analysis device  627  and a server  628 . The sever  621 , the storage device  622 , the storage device  623  and the management server  624  are connected to the communication network  661 . Also, the storage device  623 , the aggregating device  625 , the storage device  626  and the analysis device  627  are connected to the communication network  662 . 
     The sever  621  and the storage device  622  are a cloud system provided on a communication network such as the Internet, and are operated by a virtual machine (VM)  651 - 1  of hospital A and a VM  651 - 2  of hospital B in the sever  621 . The storage device  622  includes a DB  652 - 1  of hospital A and a DB  652 - 2  of hospital B. 
     The storage device  623  includes an analysis target DB  653 - 1  of hospital A and a analysis target DB  653 - 2  of hospital B, and stores analysis target item information  654 . The analysis target item information  654  is information that specifies an item as an analysis target from among a plurality of items included in medical record information of each patient of each hospital. The analysis target item information  654  may be set by an information analysis institution or may be set by an information provision institution. For an item as an analysis target, for example an item other than personal information of a patient by which the person is not identified is specified. 
     The storage device  622  and the storage device  623  respectively correspond to the storage device  411  and the storage device  412  of  FIG. 4 , and the sever  621  corresponds to the information processing apparatus  413 . The communication network  661  and the communication network  662  respectively correspond to the communication network  431  and the communication network  432 , and are separated by the storage device  623 . 
     The management server  624  allocates the physical volumes of the DB  652 - i  and the analysis target DB  653 - i  to each VM  651 - i.  The aggregating device  625  generates integrated analysis target information  655 , and the storage device  626  stores the integrated analysis target information  655 . The analysis device  627  is for example a PC of an analyzer, and stores an analysis pattern  656 . The analysis pattern  656  is information that specifies a pattern of an analysis process on the integrated analysis target information  655 . The server  628  includes an analysis result DB  657 . The user system  603  includes a PC  631  and a PC  632 . 
     In the information processing system  600  illustrated in  FIG. 6 , an electronic medical record is analyzed in for example the following order. 
     (P11) A doctor of each hospital uses the electronic-medical-record client  641 - i  or the electronic-medical-record client  642 - i  so as to input consultation information of a patient. Consultation information is input in a common format that is common among all hospitals. 
     (P12) The electronic-medical-record client  641 - i  or the electronic-medical-record client  642 - i  transmits input consultation information to the sever  621  of the analysis system  602  as medical record information. 
     (P13) VM  651 - i  in the sever  621  transfers received medical record information to the storage device  622  via the communication network  661 . 
     (P14) The storage device  622  stores received medical record information in the DB  652 - i.    
     (P15) The VM  651 - i  refers to the analysis target item information  654  so as to extract information of an item as an analysis target from medical record information, and transfers the extracted information to the storage device  623  via the communication network  661 . 
     (P16) The storage device  623  stores received information in the analysis target DB  653 - i  as analysis target information. 
     (P17) The aggregating device  625  obtains a plurality of pieces of analysis target information from the analysis target DB  653 - 1  and the analysis target DB  653 - 2  of the storage device  623  via the communication network  662 , and merges the obtained pieces of analysis target information so as to generate the integrated analysis target information  655 . Then, the aggregating device  625  transfers the integrated analysis target information  655  to the storage device  626  via the communication network  662 . For example, the aggregating device  625  may generate the integrated analysis target information  655  when an information using institution has made a request to an information analysis institution for an analysis result. 
     (P18) The storage device  626  stores received integrated analysis target information  655 . 
     (P19) An analyzer of an information analysis institution uses the analysis device  627  so as to make a request to the storage device  626  for the integrated analysis target information  655  corresponding to the analysis pattern  656 . Then, the storage device  626  transmits the integrated analysis target information  655  to the analysis device  627  via the communication network  662 . 
     (P20) The analyzer uses the analysis device  627  so as to analyze the integrated analysis target information  655  and transmit the analysis result to the server  628 . 
     (P21) The server  628  stores received analysis result in the analysis result DB  657 . 
     (P27) The information analysis institution provides the analysis result to the user system  603  of an information using institution, and an user of the information using institution uses the PC  631  or  632  so as to obtain the analysis result. 
     The information processing system  600  as described above eliminates the need to provide a database in the hospital system  601 - i  because each hospital utilizes the DB  652 - i  in the cloud system. In such a case, doctors of each hospital do not need to deliver medical record information to information analysis institutions and can transmit medical record information to the DB  652 - i  by using the PC  611 - i  or the PC  612 - i,  saving the efforts of collecting information and making real-time collection possible. 
     Also, by using the storage device  623  to separate the communication network  661  and the communication network  662 , accesses from the aggregating device  625  or the analysis device  627  to the storage device  622  that stores medical record information are prohibited. Meanwhile, in the storage device  623  that can be accessed from the aggregating device  625  and the analysis device  627 , analysis target information in which personal information of a patient included in medical record information has been confidentialized is stored. This reduces the risk that personal information of a patient will leak though analyzers. 
     Also, by inputting consultation information of respective hospitals in a common format and extracting analysis target information from medical record information in a common format, a plurality of hospitals have unified items as analysis target information, making easy to merge such pieces of analysis target information. Further, by the analysis device  627  storing the analysis pattern  656 , it is possible to automatically make a request for the integrated analysis target information  655  of the same pattern when an analysis process is to be performed. 
       FIG. 7  illustrates a functional configuration example of the VM  651 - i  of  FIG. 6 . The VM  651 - i  illustrated in  FIG. 7  includes an electronic-medical-record service  701 - i,  a memory  702 - i,  a DB  703 - i  and an analysis target DB  704 - i.  The electronic-medical-record service  701 - i  is an application executed by the VM  651 - i,  and provides the function of the extraction unit  422  illustrated in  FIG. 4 . The memory  702 - i  corresponds to a storage area in the storage unit  421  illustrated in  FIG. 4 , and stores a mode flag  711 - i  and a patient list  712 - i.    
     The mode flag  711 - i  indicates whether or not to provide medical record information of each hospital to an information analysis institution, and indicates that medical record information is to be provided when it is logic “1”, and indicates that medical record information is not to be provided when it is logic “0”. When it is not desirable for a hospital to provide medical record information, the extraction of analysis target information can be prohibited by setting the mode flag  711 - i  of the corresponding VM  651 - i  to logic “0”. Accordingly, even a hospital that does not provide medical record information can use the DB  652 - i  of the information processing system  600 . 
     The patient list  712 - i  includes a correspondence relationship between the name of a patient who had consultation in each hospital in the past and the identification information (ID) assigned to that patient. Provision of the patient list  712 - i  makes it possible to determine whether or not new medical record information that has been added to the DB  652 - i  is medical record information of a patient who had consultation. 
     The DB  703 - i  is a logical volume corresponding to the physical volume of the DB  652 - i,  and the analysis target DB  704 - i  is a logical volume corresponding to the physical volume of the analysis target DB  653 - i.  Provision of the VM  651 - i  for each hospital reduces the risk of information leak between hospitals. 
       FIG. 8  illustrates an example of logical volumes of medical record information and analysis target information in the information processing system  600 . The storage device  622  includes a network interface unit  801  connected to the communication network  661 . Also, the storage device  623  includes a network interface unit  802  connected to the communication network  661  and a network interface unit  803  connected to the communication network  662 . 
     The network interface unit  801 , the network interface unit  802  and the network interface unit  803  are communication circuits (network interface circuits) such as a network interface card (NIC) etc. 
     The VM  651 - i  of the sever  621  accesses the storage device  622  via the communication network  661  so as to hold the logical volume corresponding to the physical volume of the DB  652 - i  as the DB  703 - i.  The network interface unit  801  of the storage device  622  can transmit medical record information of the physical volume to the sever  621  in accordance with a request from the VM  651 - i.    
     Also, the VM  651 - i  accesses the storage device  623  via the communication network  661  so as to hold the logical volume corresponding to the physical volume of the analysis target DB  653 - i  as the DB  704 - i.  The network interface unit  802  of the storage device  623  can transmit analysis target information of the physical volume to the sever  621  in accordance with a request from the VM  651 - i.    
     The aggregating device  625  accesses the storage device  623  via the communication network  662  so as to hold the logical volume corresponding to the physical volume of the analysis target DB  653 - i  as the analysis target DB  811 - i.  The network interface unit  803  of the storage device  623  can transmit analysis target information of the physical volume to the aggregating device  625  in accordance with a request from the aggregating device  625 . 
     Connecting the network interface unit  802  and the network interface unit  803  of the storage device  623  respectively to the communication network  661  and the communication network  662  makes it possible to physically separate these communication networks. Also, because the storage device  623  usually includes an operating system (OS) dedicated for storages, the risk that analysis target information will leak from the storage device  623  is reduced very much in comparison with versatile OSs. 
     Thereby, it is possible to permit accesses to the DB  652 - i  of the storage device  622  connected to the communication network  661  only to the user of the hospital system  601 - i  and prohibit analyzers of information analysis institutions from making such accesses. 
       FIG. 9  illustrates an example of an input screen, displayed by the PC  611 - i  or the PC  612 - i,  of consultation information that uses a common format. The input screen illustrated in  FIG. 9  includes items of name of patient, sex, birth date, address, blood type, health insurance card ID, hospital name, allergy, prescription, examination result and disease name. 
       FIG. 10  illustrates an example of medical record information stored in the DB  652 - 1  of hospital A. The medical record information of  FIG. 10  includes items of ID, name, birth date, sex, address, blood type, health insurance card ID, hospital name, allergy, prescription, examination result and disease name. An ID is an ID assigned to a patient by each hospital, and a health insurance card ID is an ID assigned to an insured person by an insurer. 
     Allergy represents an allergy that a patient has, prescription represents prescription determined through consultation, an examination result represents an examination result that was referred to during consultation, and a disease name represents the disease name determined through consultation. In the example illustrated in  FIG. 10 , pieces of medical record information of the two patients corresponding to IDs “1” and “2” have been registered in the DB  652 - 1 . 
       FIG. 11  illustrates an example of medical record information stored in the DB  652 - 2  of hospital B. The medical record information of  FIG. 11  has similar items to those of the medical record information of  FIG. 10 . In the example illustrated in  FIG. 11 , pieces of medical record information of the two patients corresponding to IDs “1” and “2” have been registered in the DB  652 - 2 . 
       FIG. 12  illustrates an example of the analysis target item information  654 . The items of the analysis target item information  654  illustrated in  FIG. 12  correspond to the items of medical record information illustrated in  FIG. 10  and  FIG. 11 , and include a symbol of either “o” or “x”. 
     “o” represents information that can be provided without being confidentialized, and corresponds to an item as an analysis target. “x” represents information that is to be confidentialized, and corresponds to an item as a non analysis target. In this example, “o” is set for the birth date, the sex, the blood type, the hospital name, the allergy, the prescription, the examination result and the disease name, and “x” is set for the name, the address, and the health insurance card ID. 
     Provision of the analysis target item information  654  as described above makes it possible to extract information of an item as an analysis target from medical record information of each hospital in accordance with a common criterion for judgment. Also, even when a criterion for judgment has been changed by an information analysis institution etc., the operation of the analysis system  602  can be continued just by changing the setting of the analysis target item information  654 . 
       FIG. 13  illustrates an example of analysis target information generated from the medical record information illustrated in  FIG. 10  on the basis of the analysis target item information  654  illustrated in  FIG. 2 . The analysis target information illustrated in  FIG. 13  includes the items of ID, birth date, sex, address, blood type, hospital name, allergy, prescription, examination result, and disease name. In such a case, because the name and the health insurance card ID are specified by the analysis target item information  654  as information to be confidentialized, the name or the health insurance card ID are not extracted as analysis target information. 
     While the address is also specified as information to be confidentialized, a confidentialization process of omitting the block number etc. included in the character string of the address is applied so that it has been processed to information that does not allow the identification of the person. For example, the address of the patient having ID “1” has been converted into a simplified character string of “Kita-ku, Yokohama city”, and the address of the patient having ID “2” has been converted into a simplified character string of “Midori-ku, Osaka city”. 
       FIG. 14  illustrates an example of analysis target information generated from the medical record information illustrated in  FIG. 11  on the basis of the analysis target item information  654  illustrated in  FIG. 12 . The analysis target information of  FIG. 14  also has similar items as those of the analysis target information of  FIG. 13 . 
       FIG. 15  illustrates an example of the integrated analysis target information  655  that is generated by merging the analysis target information of  FIG. 13  and the analysis target information of  FIG. 14 . The integrated analysis target information  655  of  FIG. 15  has similar items as those of the analysis target information of  FIG. 13  and  FIG. 14 . However, IDs in  FIG. 15  are IDs assigned by the aggregating device  625 , and is different from the IDs of the respective hospitals. 
       FIG. 16  illustrates an example of an analysis process for the integrated analysis target information  655  of  FIG. 15 . In the analysis process of  FIG. 16 , in order to extract an allergy that patients whose blood type is B have, the analysis pattern  656  including the items of blood type and allergy is used. As a result, “none” is extracted as the allergy of the patient who has the ID “2” and whose blood type is B, and “pollen” is extracted as the allergy of the patient who has the ID “3” and whose blood type is B. 
     When entries of other patients having allergies are included in the integrated analysis target information  655  in addition to the patients having the ID “1” through the ID “4”, a pie graph  1601  representing the ratio of each of the plurality of allergies among all entries for the patients whose blood type is B is generated. Then, the analysis result including the pie graph  1601  is stored in the analysis result DB  657 . The pie graph  1601  indicates that there are many allergies of “pollen” and “atopy” among patients whose blood type is B. 
       FIG. 17A  and  FIG. 17B  illustrate an example of an information extraction sequence that extracts the analysis target information of hospital A in the analysis system  602 . First, the electronic-medical-record client  641 - 1  inputs the consultation information of a patient to the VM  651 - 1  in accordance with manipulation conducted by a doctor of hospital A (step  1701 ). Then, the VM  651 - 1  writes the input consultation information to the DB  652 - 1  of the storage device  622  as medical record information (step  1702 ). 
     Next, the VM  651 - 1  checks the mode flag  711 - 1  (step  1703 ), and when the mode flag  711 - 1  is logic “0” (NO in step  1703 ), the process is terminated. When the mode flag  711 - 1  is logic “1” (YES in step  1703 ), the VM  651 - 1  checks whether or not an extraction time that was scheduled beforehand has arrived (step  1704 ). 
     When the extraction time has not arrived (NO in step  1704 ), the VM  651 - 1  repeats the process instep  1704 . When the extraction time arrives (YES in step  1704 ), the VM  651 - 1  refers to the patient list  712 - 1  so as to check whether or not the patient of the medical record information written to the DB  652 - 1  had consultation in the past (step  1705 ). When the name in the medical record information is included in the patient list  712 - 1 , the VM  651 - 1  determines that the patient had consultation, and when the name in the medical record information is not included in the patient list  712 - 1 , the VM  651 - 1  determines that the patient did not have consultation. 
     When determining that the patient did not have consultation (NO in step  1705 ), the VM  651 - 1  issues a new ID, and registers the name of the patient and the issued ID in an associated manner in the patient list  712 - 1  (step  1706 ). Then, the VM  651 - 1  assigns the issued ID to the medical record information written to the DB  652 - 1 . 
     When the patient had consultation (YES in step  1705 ), the VM  651 - 1  obtains the ID corresponding to the name of that patient from the list  712 - 1  (step  1707 ). Then, the VM  651 - 1  assigns the obtained ID to the medical record information written to the DB  652 - 1 . 
     Next, the VM  651 - 1  reads medical record information written after the last extraction time as difference medical record information (step  1708 ), and reads the analysis target item information  654  from the storage device  623  (step  1709 ). Then, the VM  651 - 1  refers to the analysis target item information  654  (step  1710 ), and extracts information of an item as an analysis target from the difference medical record information. In doing so, the VM  651 - 1  may also extract information of an item as a non analysis target temporarily and apply a confidentialization process to the information so as to process the information to information that does not allow the identification of a person such as the addresses in  FIG. 13  and  FIG. 14 . 
     Next, the VM  651 - 1  again checks the determination result instep  1705  (step  1712 ). When the patient did not have consultation (NO in step  1712 ), the VM  651 - 1  writes the extracted information to the analysis target DB  653 - 1  of the storage device  623  as analysis target information of a new patient (step  1713 ). 
     When the patient had consultation (YES in step  1712 ), the VM  651 - 1  uses the extracted information to update the analysis target information of the same ID as that stored in the analysis target DB  653 - 1  (step  1714 ). For example, when the extracted information corresponds to prescription, an examination result or a hospital name, the extracted information is added to the information of the item included in the existing analysis target information. Alternatively, the existing analysis target information is rewritten to the extracted information. 
       FIG. 18A  and  FIG. 18B  illustrate an example of an information extraction sequence that extracts analysis target information of hospital B in the analysis system  602 . The processes in step  1801  through step  1814  are similar to those in step  1701  through  1714 . 
       FIG. 19  illustrates an example of a first information analysis sequence in the analysis system  602 . First, the PC  631  of the user system  603  makes a request to the analysis device  627  for the analysis result in accordance with manipulation conducted by an user of an information using institution (step  1901 ). In accordance with manipulation conducted by an analyzer, the analysis device  627  receives the request from the PC  631  (step  1902 ) and instructs the aggregating device  625  to collect analysis target information (step  1903 ). 
     The aggregating device  625  obtains analysis target information of hospital A from the analysis target DB  653 - 1  of the storage device  623  (step  1904 ) and obtains analysis target information of hospital B from the analysis target DB  653 - 2  (step  1905 ). Next, the aggregating device  625  merges the analysis target information of hospital A and the analysis target information of hospital B so as to generate the integrated analysis target information  655  (step  1906 ). Then, the aggregating device  625  writes the integrated analysis target information  655  to the storage device  626  (step  1907 ), and reports the completion of the writing to the analysis device  627  (step  1908 ). 
     The analysis device  627  checks whether or not the request from the user corresponds to the analysis pattern  656  of the past. When the request from the user does not correspond to the analysis pattern  656  of the past (NO in step  1909 ), the analysis device  627  generates new analysis pattern  656  in accordance with manipulation conducted by the analyzer (step  1910 ). Then, the analysis device  627  makes a request to the storage device  626  for the integrated analysis target information  655  corresponding to the generated analysis pattern  656 , and receives the integrated analysis target information  655  from the storage device  626  (step  1911 ). 
     When the request from the user corresponds to the analysis pattern  656  of the past (YES in step  1909 ), the analysis device  627  makes a request to the storage device  626  for the integrated analysis target information  655  corresponding to that analysis pattern  656  (step  1911 ). Then, the analysis device  627  receives the integrated analysis target information  655  from the storage device  626 . 
     Next, in accordance with manipulation conducted by the analyzer, the analysis device  627  analyzes the received integrated analysis target information  655  (step  1912 ), and stores the analysis result in the analysis result DB  657  of the server  628  (step  1913 ). Then, the server  628  transmits the analysis result to the PC  631  of the user system  603  (step  1914 ). 
     While the analysis system  602  includes each one of the sever  621 , the storage device  622  and the storage device  623 , the analysis system  602  may include a plurality of servers and a plurality of storage devices when many hospitals provide medical record information. Thereby, it is possible to perform an information extraction process and an analysis process even when the number of hospitals that provides medical record information increases. 
       FIG. 20  illustrates configuration examples of a server system and a storage system provided to the analysis system  602 . In such a case, the sever  621 , the storage device  622  and the storage device  623  illustrated in  FIG. 6  are respectively replaced with a server system  2001 , a storage system  2002  and a storage system  2003 . 
     In the server system  2001 , VMs  2011 - 1  through  2011 -N of N (N is an integer equal to or greater than two) hospitals operate. The server system  2001  includes a plurality of servers (not illustrated), and one or more VMs  2011 - i  (i=1 through N) operate in each of the servers. The VM  2011 - i  has a configuration in which the DB  703 - i  and the analysis target DB  704 - i  in the VM  651 - i  of  FIG. 7  have been respectively replaced with a DB  2012 - i  and an analysis target DB  2013 - i.    
     The storage system  2002  includes DBs  2021 - 1  through  2021 -N of N hospitals. The storage system  2002  corresponds to a storage pool including a plurality of storage devices (not illustrated), and each of the storage devices includes one or more DBs  2021 - i.    
     The storage system  2003  includes analysis target DBs  2031 - 1  through  2031 -N of N hospitals. The storage system  2003  corresponds to a storage pool including a plurality of storage devices (not illustrated), and each of the storage devices includes one or more analysis target DBs  2031 - i.    
     The storage system  2003  includes a network interface unit  2041  connected to the communication network  661  and a network interface unit  2042  connected to the communication network  662 . 
     The VM  2011 - i  of the server system  2001  accesses the storage system  2002  via the communication network  661  and holds the logical volume corresponding to the physical volume of the DB  2021 - i  as the DB  2012 - i.  Also, the VM  2011 - i  accesses the storage system  2003  via the communication network  661  and holds the logical volume corresponding to the physical volume of the analysis target DB  2031 - i  as the analysis target DB  2013 - i.    
     The aggregating device  625  accesses the storage system  2003  via the communication network  662  and holds the logical volume corresponding to the physical volume of the analysis target DB  2013 - i  as the analysis target DB  2041 - i.    
       FIG. 21  illustrates an example of a first volume-allocation sequence in which a physical volume is allocated to the VM  2011 - i  of the i-th hospital (i=1 through N) in the analysis system  602  that has the configuration illustrated in  FIG. 20 . The hospital system  601 - i  of the i-th hospital includes the PC  611 - i  and the electronic-medical-record client  641 - i  has been installed in the PC  611 - i.  A server  2101  is included in the server system  2001 , a storage device  2102  and storage device  2103  are included in the storage system  2002 , and a storage device  2104  is included in the storage system  2003 . 
     First, in accordance with manipulation conducted by a doctor of the i-th hospital, the electronic-medical-record client  641 - i  transmits an application for the use of an electronic-medical-record service (step  2111 ). An application for use includes information representing whether or not to permit the provision of medical record information to an information analysis institution. 
     The management server  624  instructs the server  2101  to generate a VM (step  2112 ), and the server  2101  generates a VM  2011 - i  (step  2113 ). When the application for the user permits the provision of medical record information, the server  2101  sets the mode flag  711 - i  of the VM  2011 - i  to logic “1”, and when the application for the user does not permit the provision of medical record information, the server  2101  sets the mode flag  711 - i  to logic “0”. 
     Next, the management server  624  instructs the storage device  2102  to allocate a physical volume (step  2114 ), and the storage device  2102  generates a physical volume of the DB  2021 - i  (step  2115 ). 
     Next, the management server  624  checks the mode flag  711 - i  of the VM  2011 - i  (step  2116 ). When the mode flag  711 - i  is logic “0” (NO in step  2116 ), the management server  624  reports the completion of the generation of a VM to the PC  611 - i  (step  2117 ). 
     When the mode flag  711 - i  is logic “1” (YES in step  2116 ), the management server  624  instructs the storage device  2104  to allocate a physical volume (step  2118 ). Then, the storage device  2104  generates a physical volume of the analysis target DB  2031 - i  (step  2119 ), and the management server  624  reports the completion of the generation of a VM to the PC  611 - i  (step  2120 ). 
     In the information processing system  600  illustrated in  FIG. 6 , the information provision institution may be an institution other than a hospital that provides consultation information of a patient. Examples of an information provision institution may include a store that provides purchase information of a customer, an educational institution such as a school, a cram school, etc. that provides grade information of a student or a financial institution such as a bank etc. that provides balance in account, a transaction record, etc. of a customer. 
     When an information provision institution is a store, purchase information of a customer is collected instead of medical record information, and analysis result representing tastes etc. of the customer is provided to an information using institution such as a restaurant etc. When an information provision institution is an educational institution, grade information of a student is collected and analysis result representing tendency etc. for each subject is provided to an information using institution such as a teaching material production company etc. When in information provision institution is a financial institution, balance in account, a transaction record, etc. of a customer is collected and analysis result representing the use state of a loan etc. is provided to an information using institution such as a loan company etc. 
       FIG. 22  illustrates a specific example of the information processing system  401  in a case when an information provision institution is a convenience store. An information processing system  2200  illustrated in  FIG. 22  has a configuration in which the hospital systems  601 - 1  and  601 - 2  have been replaced with a Point Of Sales (POS) system  2201 - 1  and a POS system  2201 - 2  in the information processing system  600  illustrated in  FIG. 6 . The POS system  2201 - 1  is a system of convenience store A, and the POS system  2201 - 2  is a system of convenience store B. 
     The POS system  2201 - i  (i=1, 2) includes a POS terminal  2211 - i  and a POS terminal  2212 - i.  In the POS terminal  2211 - i  and the POS terminal  2212 - i,  POS client  2221 - i  and POS client  2222 - i,  which are applications, are installed, respectively. The POS system  2201 - i  may include as many POS terminals as there are stores. 
     In such a case, the VM  651 - i  of  FIG. 7  executes a POS service instead of the electronic-medical-record service  701 - i,  and the DB  652 - i  stores purchase information of a customer instead of medical record information. The user system  603  is for example a system of an information using institution such as a restaurant. 
       FIG. 23  illustrates an example of an input screen, displayed by the POS terminal  2211 - i  or the POS terminal  2212 - i,  of purchase information that uses a common format. The input screen illustrated in  FIG. 23  includes items of name of customer, sex, birth date, address, customer ID, occupation, name of store of purchase, date of purchase, purchased article, and the number of purchased articles. 
     A customer ID is for example an ID that is assigned to a customer by a provider of a point card, and when the customer presents the point card upon purchasing an article at a convenience store, a clerk can input the customer ID. When the registration information of the point card includes name, sex, birth date, address and occupation, such pieces of information are also input upon a purchase of an article. 
       FIG. 24  illustrates an example of purchase information stored in the DB  652 - 1  of convenience store A. The purchase information illustrated in  FIG. 24  includes items of ID, name, birth date, sex, address, customer ID, occupation, name of store of purchase, date of purchase, purchased article and the number of purchased articles. An ID is an ID assigned to a customer by each convenience store, a purchased article is the name of an article that the customer has purchased, and the number of purchased articles is the number of the articles that the customer has purchased. In the example of  FIG. 24 , purchase information of two customers corresponding to ID “1” and ID “2” are registered in the DB  652 - 1 . 
       FIG. 25  illustrates an example of analysis target information generated from the purchase information of  FIG. 24  on the basis of the analysis target item information  654 . The analysis target information of  FIG. 25  includes items of ID, birth date, sex, address, occupation, name of store of purchase, date of purchase, purchased article and the number of purchased articles. In such a case, because the names and customer IDs are specified as information to be confidentialized by the analysis target item information  654 , they have not been extracted as analysis target information. Similarly to the analysis target information of  FIG. 13 , the addresses have been processed to information that does not allow the identification of the person. 
       FIG. 26  illustrates an example of analysis target information generated from purchase information of convenience store B on the basis of the analysis target item information  654 . The analysis target information of  FIG. 26  has similar items to those of the analysis target information of  FIG. 25 . 
       FIG. 27  illustrates an example of the integrated analysis target information  655  generated by merging the analysis target information of  FIG. 25  and analysis target information of  FIG. 26 . The integrated analysis target information of  FIG. 27  has similar items to those of the analysis target information of  FIG. 25  and  FIG. 26 . 
       FIG. 28  illustrates an example of an analysis process for the integrated analysis target information  655  of  FIG. 27 . In the analysis process illustrated in  FIG. 28 , the analysis pattern  656  including the items of birth date and the purchased article is used in order to extract the age group of customers who purchased “salmon rice ball”. As a result, “Nov. 13, 1998” is extracted as the birth date of the customer with ID “1” who purchased “salmon rice ball”, and “Sep. 3, 2001” is extracted as the birth date of the customer with ID “4” who purchased the same article. 
     When an entry of a customer who purchased “salmon rice ball” is included in the integrated analysis target information  655  in addition to the customers with IDs “1” and “4”, age distribution  2801  is generated from the birth dates of such customers. Then, the analysis result including the age distribution  2801  is stored in the analysis result DB  657 . The age distribution  2801  indicates that young people has a tendency to like “salmon rice ball”. 
     Incidentally, in the analysis system  602  illustrated in  FIG. 20 , the aggregating device  625  collects pieces of analysis target information from N hospitals from the analysis target DBs  2031 - 1  through  2031 -N of the storage system  2003 . Thus, an increase in the number of hospitals also increases the data amount of analysis target information, leading to longer collection time for collecting analysis target information. 
     For example, even when an analyzer wishes to use only the analysis target information of a specific hospital, the analysis system  602  illustrated in  FIG. 20  collects the analysis target information of all the hospitals, and thus the collection time is not different from collection time in a case where analysis target information of all the hospitals is analyzed. Accordingly, it is desirable that an arrangement that allows the aggregating device  625  to obtain only analysis target information of a specific hospital be provided. 
       FIG. 29  illustrates a configuration example of a second information processing system in which such an arrangement is provided. An information processing system  2901  of  FIG. 29  includes a server system  2911 , a storage system  2912 , a storage system  2913  and an information processing apparatus  2914 . 
     The server system  2911  includes VMs  2921 - 1  through  2921 -N of N information provision institutions. The storage system  2912  includes storage areas  2922 - 1  through  2922 -N, the storage system  2913  includes storage areas  2923 - 1  through  2923 -N, and the information processing apparatus  2914  includes an obtainment unit  2931  and a storage unit  2932 . 
     The storage system  2912  includes a plurality of storage devices (not illustrated), and the storage area  2922 - i  (i=1 through N) is included in any of the storage devices. The storage system  2913  includes a plurality of storage devices (not illustrated) and the storage area  2923 - i  is included in any of the storage devices. 
     The storage system  2912  stores information transferred from the i-th information provision institution in the storage area  2922 - i.  The VM  2921 - i  extracts analysis target information from the information stored in the storage area  2922 - i  and stores the extracted analysis target information in the storage area  2923 - i.    
     The storage unit  2932  of the information processing apparatus  2914  stores first information  2941  and second information  2942 . The first information  2941  represents a correspondence relationship between the VMs  2921 - 1  through  2921 -N and the storage areas  2923 - 1  through  2923 -N, and the second information  2942  represents a correspondence relationship between the N information provision institutions and the VMs  2921 - 1  through  2921 -N. 
       FIG. 30  is a flowchart illustrating an example of an information obtainment process performed by the information processing apparatus  2914  of  FIG. 29 . First, on the basis of the first information  2941  and the second information  2942 , the obtainment unit  2931  identifies a specific storage area that stores analysis target information of a specific information provision institution from among the storage areas  2923 - 1  through  2923 -N. Then, the obtainment unit  2931  obtains analysis target information of the specific information provision institution from a storage device including the identified storage area (step  3002 ). 
     The information processing system  2901  as described above makes it possible to reduce the risk of information leak and to reduce time for collecting pieces of analysis target information of a specific information provision institution, in a case when pieces of information collected from a plurality of information provision institutions are analyzed. The information processing system  600  illustrated in  FIG. 6  corresponds to the specific example of the information processing system  2901  of  FIG. 29 . 
       FIG. 31  illustrates a configuration example of the analysis system  602  included in the specific example of the information processing system  2901  of  FIG. 29 . The analysis system  602  illustrated in  FIG. 31  employs a configuration in which a reception server  3101  is added to the analysis system  602  of  FIG. 6 . However, the sever  621 , the storage device  622  and the storage device  623  of  FIG. 6  have been replaced with the server system  2001 , the storage system  2002  and the storage system  2003  of  FIG. 20 , respectively. 
     The server system  2001  corresponds to the server system  2911  of  FIG. 29 , and the VM  2011 - i  corresponds to the VM  2921 - i.  The server system  2002  corresponds to the storage system  2912 , and the physical volume of the DB  2021 - i  corresponds to the storage area  2922 - i.  The storage system  2003  corresponds to the storage system  2913 , and the physical volume of the analysis target DB  2031 - i  corresponds to the storage area  2923 - i.  The aggregating device  625  corresponds to the information processing apparatus  2914 . 
     The management server  624  stores the first table  3111 , and the reception server  3101  stores the second table  3112 . The first table  3111  corresponds to the first information  2941 , and represents a correspondence relationship between the VMs  2011 - 1  through  2011 -N and the physical volumes of the analysis target DBs  2031 - 1  through  2031 -N. The second table  3112  corresponds to the second information  2942 , and represents a correspondence relationship between N hospitals and the VMs  2011 - 1  through  2011 -N. 
     The aggregating device  625  obtains the first table  3111  from the management server  624 , and obtains the second table  3112  from the reception server  3101 . On the basis of the first table  3111  and the second table  3112 , the aggregating device  625  identifies the physical volume of the analysis target DB  2031 - i  of the specific hospital. Then, the aggregating device  625  obtains analysis target information of that hospital from the storage device including the physical volume of the identified analysis target DB  2031 - i.    
       FIG. 32  illustrates an example of the first table  3111 . The first table  3111  of  FIG. 32  includes items of VMID and physical volume ID. A VMID is the ID of the VM  2011 - i,  and a physical volume ID is the ID of the physical volume of the analysis target DB  2031 - i.  The first table  3111  stores each physical volume ID and its corresponding VMID in an associated manner. In this example, VMID “1” is the ID of the VM  2011 - 1  of hospital A, and physical volume ID “A2” is the ID of the physical volume of the analysis target DB  2031 - 1  of hospital A. 
       FIG. 33  illustrates an example of the second table  3112 . The second table  3112  of  FIG. 33  includes items of hospital name and VMID. The second table  3112  stores each VMID and the hospital name of its corresponding hospital in an associated manner. 
       FIG. 34  illustrates an example of a second volume-allocation sequence in which a physical volume is allocated to the VM  2011 - i  of the i-th hospital in the analysis system  602  that has the configuration illustrated in  FIG. 31 . 
     First, the electronic-medical-record client  641 - i  transmits an application for use of an electronic-medical-record service to the reception server  3101  of the analysis system  602  in accordance with manipulation conducted by a doctor of the i-th hospital (step  3401 ). Then, the reception server  3101  instructs the management server  624  to generate a VM (step  3402 ). The processes in the subsequent steps  3403  through  3410  are similar to the processes in steps  2112  through  2119  of  FIG. 21 . 
     Thereafter, the management server  624  generates an entry, for the first table  3111 , that associates the ID of the VM  2011 - i  generated in step  3404  and the ID of the physical volume of the analysis target DB  2031 - i  generated in step  3410  (step  3411 ). Then, the management server  624  reports the completion of the generation of the VM to the reception server  3101  (step  3412 ). 
     Next, the reception server  3101  generates an entry, for the second table  3112 , that associates the hospital name of the i-th hospital, which transmitted the application for use in step  3401 , and the ID of the VM  2011 - i  generated in step  3404  (step  3413 ). Then, the reception server  3101  reports the completion of the generation of the VM to the PC  611 - i  (step  3414 ). 
       FIG. 35  illustrates an example of a second information analysis sequence that analyzes only analysis target information of hospital A in the analysis system  602  employing the configuration illustrated in  FIG. 31 . First, in accordance with manipulation conducted by a user of an information using institution, the PC  631  of the user system  603  makes a request to the analysis device  627  for the analysis result (step  3501 ). The analysis device  627 , in accordance with manipulation conducted by an analyzer, receives the request from the PC  631  (step  3502 ), and instructs the aggregating device  625  to collect pieces of analysis target information of hospital A (step  3503 ). 
     The aggregating device  625  obtains the first table  3111  from the management server  624  (step  3504 ), and obtains the second table  3112  from the reception server  3101  (step  3505 ). Then, the aggregating device  625  uses the first table  3111  and the second table  3112  so as to identify the physical volume of the analysis target DB  2031 - 1  of hospital A (step  3506 ). In doing so, the aggregating device  625  obtains VMID “1” corresponding to hospital A from the second table  3112  of  FIG. 33  and obtains physical volume ID “A2” corresponding to VMID “1” from the first table  3111  of  FIG. 32 . 
     Next, the aggregating device  625  obtains analysis target information of hospital A from the storage device  2104  including the physical volume of the analysis target DB  2031 - 1 , which is represented by physical volume ID “A2” (step  3507 ). Then, the aggregating device  625  writes analysis target information of hospital A to the storage device  626  as the integrated analysis target information  655  (step  3508 ) and reports the completion of the writing to the analysis device  627  (step  3509 ). 
     The processes in the subsequent steps  3510  through  3515  are similar to the processes in steps  1909  through  1914  of  FIG. 19 . 
     An information analysis sequence as described above makes it possible to collect pieces of analysis target information of a specific hospital alone, eliminating the necessity of collecting pieces of analysis target information of other hospitals that are not used for the analysis, and thus makes it possible to reduce the collection time. 
     It is also possible to collect pieces of analysis target information of a plurality of specific hospitals alone instead of collecting pieces of analysis target information of a single hospital alone. In this case too, it is not necessary to collect pieces of analysis target information of hospitals other than the plurality of specific hospitals, making it possible to reduce the collection time. In the configuration illustrated in  FIG. 31 , the information provision institution may be a store, an educational institution, a financial institution, etc. 
     The information processing system  401  illustrated in  FIG. 4 , the information processing system  600  illustrated in  FIG. 6 , the information processing system  2200  illustrated in  FIG. 22  and the information processing system  2901  illustrated in  FIG. 29  are just exemplary, and some of the constituents may be omitted or changed in accordance with the purposes or conditions of the information processing systems. For example, when the analysis device  627  generates the integrated analysis target information  655  in the information processing system  600  illustrated in  FIG. 6  and the information processing system  2200  illustrated in  FIG. 22 , the aggregating device  625  and the storage device  626  may be omitted. 
     The configuration of the VM  651 - i  illustrated in  FIG. 7  is just exemplary, and some of the constituents may be omitted or changed in accordance with the purposes or conditions of the information processing systems. 
     The configurations of the storage device  622  and the storage device  623  illustrated in  FIG. 8  are just exemplary, and some of the constituents may be omitted or changed in accordance with the configurations or conditions of the information processing systems. 
     The configurations of the server system  2001 , the storage system  2002  and the storage system  2003  illustrated in  FIG. 20  and  FIG. 31  are just exemplary, and some of the constituents may be omitted or changed in accordance with the configurations or conditions of the information processing systems. 
     The flowcharts illustrated in  FIG. 5  and  FIG. 30  and the operation sequences illustrated in  FIG. 17A  through  FIG. 19 ,  FIG. 21 ,  FIG. 34  and  FIG. 35  are just exemplary, and some of the processes may be omitted or changed in accordance with the configurations or conditions of the information processing systems. For example, in the information analysis sequences illustrated in  FIG. 19  and  FIG. 35 , the analysis device  627  may start an analysis process in response to a different event as a trigger instead of a request from an information using institution. The analysis device  627  in place of the aggregating device  625  may perform the processes in step  1904  through step  1906  of  FIG. 19 . 
     The input screens illustrated in  FIG. 9  and  FIG. 23 , the medical record information illustrated in  FIG. 10  and  FIG. 11 , the purchase information illustrated in  FIG. 24 , the analysis target item information illustrated in  FIG. 12 , the analysis target information illustrated in  FIG. 13 ,  FIG. 14 ,  FIG. 25  and  FIG. 26  and the integrated analysis target information illustrated in  FIG. 15  and  FIG. 27  are just exemplary. The first table  3111  illustrated in  FIG. 32  and the second table  3112  illustrated in  FIG. 33  are also just exemplary. These pieces of information may vary in accordance with the purposes or conditions of the information processing systems. The analysis processes illustrated in  FIG. 16  and  FIG. 28  are just exemplary, and the pattern of an analysis process may vary in accordance with a request from an information using institution. 
       FIG. 36  illustrates a hardware configuration example of an information processing apparatus that is used as the information processing apparatus  413  illustrated in  FIG. 4 , the sever  621 , the management server  624 , the aggregating device  625  and the analysis device  627  illustrated in  FIG. 6  and  FIG. 22  and the information processing apparatus  2914  illustrated in  FIG. 29 . The information processing apparatus illustrated in  FIG. 36  includes a Central Processing Unit (CPU)  3601 , a memory  3602 , an input device  3603 , an output device  3604 , an auxiliary storage device  3605 , a medium driving device  3606  and a network connection device  3607 . These constituents are connected to each other via a bus  3608 . 
     The memory  3602  is for example a semiconductor memory such as a Read Only Memory (ROM), a Random Access Memory (RAM), a flash memory, etc., and stores a program and data used for processes. The memory  3602  can be used as the storage unit  421  illustrated in  FIG. 4  when the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  413 . The memory  3602  can be used as the storage unit  2932  illustrated in  FIG. 29  when the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  2914 . 
     When the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  413 , the CPU  3601  (processor) executes a program by using for example the memory  3602  so as to operate as the extraction unit  422  illustrated in  FIG. 4 . In such a case, the electronic-medical-record service  701 - i  illustrated in  FIG. 7  corresponds to a program executed by the CPU  3601 . 
     When the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  2914 , the CPU  3601  executes a program by using for example the memory  3602  so as to operate as the obtainment unit  2931  illustrated in  FIG. 29 . 
     The input device  3603  is for example a keyboard, a pointing device, etc., and is used for inputting instructions or information from an operator or a user. The output device  3604  is for example a display device, a printer, a speaker, etc., and is used for outputting inquiries to the operator or the user or for outputting process results. When the information processing apparatus illustrated in  FIG. 36  is the analysis device  627 , the process result may be an analysis result. 
     The auxiliary storage device  3605  is for example a magnetic disk device, an optical disk device, a magneto-optical disk device, a tape device, etc. The auxiliary storage device  3605  may be a hard disk drive. The information processing apparatus can store a program and data in the auxiliary storage device  3605  beforehand so as to load them onto the memory  3602  and use them. When the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  413 , the auxiliary storage device  3605  may be used as the storage unit  421  illustrated in  FIG. 4 . When the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  2914 , the auxiliary storage device  3605  may be used as the storage unit  2932  illustrated in  FIG. 29 . 
     The medium driving device  3606  drives a portable recording medium  3609  so as to access information recorded in it. The portable recording medium  3609  is a memory device, a flexible disk, an optical disk, a magneto-optical disk, etc. The portable recording medium  3609  may be a DVD, a Compact Disk Read Only Memory (CD-ROM), a Universal Serial Bus (USB) memory, etc. The operator or the user can store a program and data in the portable recording medium  3609  so as to load them onto the memory  3602  and use them. 
     As described above, a computer-readable recording medium that stores a program and data used for processes is a physical (non-transitory) recording medium such as the memory  3602 , the auxiliary storage device  3605  or the portable recording medium  3609 . 
     The network connection device  3607  is a communication interface circuit that is connected to a communication network such as a LAN, a Wide Area Network (WAN), etc. so as to perform data conversion accompanying communications. When the information processing apparatus illustrated in  FIG. 36  is the information processing apparatus  413 , the network connection device  3607  may be used as the transfer unit  423  illustrated in  FIG. 4 . The information processing apparatus can receive a program and data from an external device via the network connection device  3607  and load them onto the memory  3602  and use them. 
     Note that it is not necessary for the information processing apparatuses to include all the constituents illustrated in  FIG. 36 , and some of the constituents can be omitted in accordance with the purposes or conditions. For example, when it is not necessary to input instructions or information from the operator or the user, the input device  3603  can be omitted, and when it is not necessary to output inquiries to the operator or the user or to output process results, the output device  3604  can be omitted. When the portable recording medium  3609  is not used, the medium driving device  3606  can be omitted. 
     A similar information processing apparatus to that illustrated in  FIG. 36  can be used as the PC  611 - i  and the PC  612 - i  illustrated in  FIG. 6 , the PC  2211 - i  and the PC  2212 - i  illustrated in  FIG. 22 , the PC  631  and the PC  632  illustrated in  FIG. 6  and  FIG. 22  and the reception server  3101  illustrated in  FIG. 31 . 
     All examples and conditional language provided herein are intended for the pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although one or more embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.