AU2019273572A1 - Subject candidate extracting method, and subject candidate extracting system - Google Patents

Subject candidate extracting method, and subject candidate extracting system Download PDF

Info

Publication number
AU2019273572A1
AU2019273572A1 AU2019273572A AU2019273572A AU2019273572A1 AU 2019273572 A1 AU2019273572 A1 AU 2019273572A1 AU 2019273572 A AU2019273572 A AU 2019273572A AU 2019273572 A AU2019273572 A AU 2019273572A AU 2019273572 A1 AU2019273572 A1 AU 2019273572A1
Authority
AU
Australia
Prior art keywords
subject
criteria
patients
clinical trial
subject candidate
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
AU2019273572A
Inventor
Akihisa MITAKE
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Cmic Healthcare Institute Co Ltd
CMIC Holdings Co Ltd
Original Assignee
Cmic Healthcare Institute Co Ltd
CMIC Holdings Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Cmic Healthcare Institute Co Ltd, CMIC Holdings Co Ltd filed Critical Cmic Healthcare Institute Co Ltd
Publication of AU2019273572A1 publication Critical patent/AU2019273572A1/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Business, Economics & Management (AREA)
  • General Business, Economics & Management (AREA)
  • Biomedical Technology (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • Educational Administration (AREA)
  • Economics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)

Abstract

The objective of the present invention is to provide a subject candidate extracting method with which it is possible for a subject candidate matching a clinical trial plan document to be extracted in a short time period and with a high degree of accuracy. This subject candidate extracting method includes: a step of acquiring input data in an extraction format, created on the basis of electronic medical record information, from a database in which the electronic medical record information is recorded; a step of inputting reference information defined in a clinical trial plan document; a step of extracting a subject candidate matching the clinical trial plan document from among a plurality of patients, by subjecting the input data to an extraction process using the reference information; and a step of outputting the results of the extraction process as output data in a list format.

Description

Description
Title of Invention: SUBJECT CANDIDATE EXTRACTING METHOD,
AND SUBJECT CANDIDATE EXTRACTING SYSTEM
Technical Field
[0001]
The present invention relates to a subject candidate
extraction method and a subject candidate extraction
system for extracting subject candidates matching a
clinical trial protocol from multiple patients.
Background Art
[0002]
When a pharmaceutical company conducts a clinical
trial, the task of finding subject candidates matching a
clinical trial protocol of the pharmaceutical company is
conventionally done at medical institutions. However, no
system has existed in the past that can extract subject
candidates matching a clinical trial protocol in a short
time and with high accuracy.
[0003]
There has been a proposal of a system in which
patient information extracted from medical service fee
claiming systems of hospitals and the like is registered
as a database at a website on the Internet and
registration is made from a medical institution at a patient's wish before emergence of a clinical trial drug
(see Patent Literature 1, for example).
Citation List
Patent Literature
[0004]
Patent Literature 1: Japanese Patent Laid-Open No. 2003
337864
Summary of Invention
Technical Problem
[0005]
However, such a conventional system is still not
able to extract subject candidates matching a clinical
trial protocol in a short time and with high accuracy.
[0006]
In view of the challenge above, an object of the
present invention is to provide a subject candidate
extraction method that can extract subject candidates
matching a clinical trial protocol in a short time and
with high accuracy.
Solution to Problem
[0007]
A subject candidate extraction method according to
the present invention is a subject candidate extraction
method performed in a subject candidate extraction system for extracting subject candidates matching a clinical trial protocol from a plurality of patients for whom electronic health record information has been registered, the subject candidate extraction method including the steps of: acquiring input data in extraction format created based on the electronic health record information from a database in which the electronic health record information is registered; receiving an input of criteria information defined in the clinical trial protocol; extracting subject candidates matching the clinical trial protocol from the plurality of patients by performing an extraction process with the criteria information on the input data; and outputting a result of the extraction process as output data in list format.
[0008]
This allows easy extraction of subject candidates
matching the clinical trial protocol from multiple
patients. Here, subject candidates can be extracted in a
short time and with high accuracy even with an extremely
large number of patients as a population of subject
candidates.
[0009]
In the subject candidate extraction method of the
present invention, the criteria information may include
selection criteria, and in the extraction process,
subject candidates who match the selection criteria may
be selected from the plurality of patients.
[0010]
This makes it possible to appropriately select
patients who should be selected (patients satisfying the
selection criteria) as subject candidates from multiple
patients in conformance with the selection criteria
defined by the clinical trial protocol.
[0011]
In the subject candidate extraction method of the
present invention, the criteria information may include
exclusion criteria, and in the extraction process,
subject candidates who match the exclusion criteria may
be excluded from the plurality of patients.
[0012]
This makes it possible to appropriately exclude
patients who should be excluded (patients satisfying the
exclusion criteria) among multiple patients from subject
candidates in conformance with the exclusion criteria
defined by the clinical trial protocol.
[0013]
A subject candidate extraction system according to
the present invention is for extracting subject
candidates matching a clinical trial protocol from a
plurality of patients for whom electronic health record
information has been registered, the subject candidate
extraction system including: an input data acquisition
unit that acquires input data in extraction format
created based on the electronic health record information from a database in which the electronic health record information is registered; a criteria information input unit to which criteria information defined in the clinical trial protocol is input; an extraction processing unit that extracts subject candidates matching the clinical trial protocol from the plurality of patients by performing an extraction process with the criteria information on the input data; and an output unit that outputs a result of the extraction process as output data in list format.
[0014]
This system also facilitates extraction of subject
candidates matching a clinical trial protocol from
multiple patients as with the method above. Here,
subject candidates can be extracted in a short time and
with high accuracy even with an extremely large number of
patients as a population of subject candidates.
[0015]
In the subject candidate extraction system of the
present invention, the criteria information may include
selection criteria, and in the extraction process,
subject candidates who match the selection criteria may
be selected from the plurality of patients.
[0016]
This makes it possible to appropriately select
patients who should be selected (patients satisfying the
selection criteria) as subject candidates from multiple patients in conformance with the selection criteria defined by the clinical trial protocol.
[0017]
In the subject candidate extraction system of the
present invention, the criteria information may include
exclusion criteria, and in the extraction process,
subject candidates who match the exclusion criteria may
be excluded from the plurality of patients.
[0018]
This makes it possible to appropriately exclude
patients who should be excluded (patients satisfying the
exclusion criteria) among multiple patients from subject
candidates in conformance with the exclusion criteria
defined by the clinical trial protocol.
Advantageous Effect of Invention
[0019]
The present invention can extract subject candidates
matching a clinical trial protocol in a short time and
with high accuracy.
Brief Description of Drawings
[0020]
[Figure 1] Figure 1 is a block diagram of a subject
candidate extraction system in an embodiment of the
present invention.
[Figure 2] Figure 2 shows a first example of a subject
candidate extraction process in an embodiment of the
present invention.
[Figure 3] Figure 3 shows a second example of a subject
candidate extraction process in an embodiment of the
present invention.
[Figure 4] Figure 4 shows a third example of a subject
candidate extraction process in an embodiment of the
present invention.
[Figure 5] Figure 5 shows a fourth example of a subject
candidate extraction process in an embodiment of the
present invention.
[Figure 6] Figure 6 shows an example of output data in
list format in an embodiment of the present invention.
[Figure 7] Figure 7 is a flow diagram illustrating
operations of the subject candidate extraction system in
an embodiment of the present invention.
Description of Embodiments
[0021]
A subject candidate extraction method according to
an embodiment of the present invention is described below
with drawings. This embodiment illustrates a case of a
subject candidate extraction method which is used with a
subject candidate extraction system.
[0022]
A configuration of the subject candidate extraction
system according to an embodiment of the present
invention is described with reference to a drawing.
Figure 1 is a block diagram showing the subject candidate
extraction system in this embodiment. As shown in Figure
1, a subject candidate extraction system 1 is connected
with a database 3 of a medical information system 2. In
the database 3, electronic health record information for
a multitude of patients has been registered. The
database 3 also has the functions of creating and
outputting input data in extraction format (e.g., CSV
format) based on electronic health record information.
[0023]
The subject candidate extraction system 1 includes
an input data acquisition unit 4, a criteria information
input unit 5, an extraction processing unit 6, and an
output unit 7. The input data acquisition unit 4 has a
function of retrieving input data in extraction format
created based on electronic health record information
from the database 3 of the medical information system 2.
[0024]
The criteria information input unit 5 is a user
interface to which criteria information defined by a
clinical trial protocol of a pharmaceutical company is
input. The criteria information defined by the clinical
trial protocol is input by a user (such as a person in
charge at a medical institution). The criteria information includes selection criteria and exclusion criteria.
[0025]
The extraction processing unit 6 extracts subject
candidates matching the clinical trial protocol from
multiple patients by performing an extraction process
with the criteria information on input data.
Specifically, the extraction processing unit 6 selects
subject candidates who match the selection criteria and
excludes subject candidates who match the exclusion
criteria among multiple patients.
[0026]
Figures 2 to 5 show examples of the extraction
process. Figure 2 shows an example of a clinical trial
that targets diabetes patients. In the example of Figure
2, Condition 1: "taking diabetes drug DPP4", Condition 2:
"being diagnosed with diabetes", Condition 3: "HbAlc
being 8-10", and Condition 4: "being 40 to 80 years old"
are the selection criteria, and Condition 5: "not being a
cancer patient" is the exclusion criteria.
[0027]
Figure 3 shows an example of a clinical trial that
targets mild Alzheimer's dementia patients. In the
example of Figure 3, Condition 1: "having mild
Alzheimer's dementia" and Condition 2: "being 50 to 85
years old" are the selection criteria, and Condition 3:
"not being a patient using Memary" and Condition 4: "not
being a cancer patient" are the exclusion criteria.
[0028]
Figure 4 shows an example of a clinical trial that
targets multiple sclerosis patients. In the example of
Figure 4, Condition 1: "having multiple sclerosis" and
Condition 2: "being 16 to 75 years old" are the selection
criteria, and Condition 3: "not being a cancer patient"
is the exclusion criteria.
[0029]
Figure 5 shows an example of a clinical trial that
targets atrial fibrillation patients who have renal
dysfunction and are being treated with Apixaban. In the
example of Figure 5, Condition 1: "being an atrial
fibrillation patient", Condition 2: "being 75 years old
or above", Condition 3 "being a patient prescribed with
Apixaban", and Condition 4: "Cre being 1.0 or higher or
eGFR being 50 or lower" are the selection criteria, and
Condition 5: "not being a cancer patient" is the
exclusion criteria.
[0030]
The output unit 7 outputs a result of the extraction
process as output data in list format. Figure 6 shows an
example of output data for the extraction result in the
case of the clinical trial that targets diabetes patients
(the example of Figure 2). As shown in Figure 6, the
output data for the extraction result includes items such as "patient code", "type 2 diabetes patient", "alive",
"taking diabetes drug DPP4", "HbAlc of 8-10", "40 to 80
years old", and "not being a cancer patient". Of course,
other items than those described above may be included in
the output data for an extraction result.
[0031]
The "patient code" is an identification code for
identifying a patient. With the patient code, the
patient can be specified and also the personal
information of the patient can be protected. A "Type 2
diabetes patient" is data indicating whether the patient
is a type 2 diabetes patient or not at the time of
extraction. In the example of Figure 6, "0" is indicated
if the patient is a type 2 diabetes patient at the time
of extraction. "Alive" is data indicating whether the
patient is alive or not at the time of extraction. In
the example of Figure 6, "0" is indicated if the patient
has a clinic appointment at the time of extraction.
[0032]
"Taking diabetes drug DPP4" is data indicating
whether the patient is taking diabetes drug DPP4 or not
in a predetermined period (in the example of Figure 6,
from February 1 to May 1, 2018). In the example of
Figure 6, "0" is indicated if the patient is taking
diabetes drug DPP4 in that period. "HbAlc of 8-10" is
data indicating whether the HbAlc of the patient is 8-10
in a predetermined period (in the example of Figure 6, from December 1, 2017 to May 1, 2018). In the example of
Figure 6, the HbAlc value in the period is indicated.
[0033]
"40 to 80 years old" is data indicating whether the
patient is 40 to 80 years old or not at the time of
extraction. In the example of Figure 6, the patient's
age at the time of extraction is indicated. "Not being a
cancer patient" is data indicating whether the patient is
a cancer patient or not at the time of extraction. In
the example of Figure 6, "0" is indicated if the patient
is not a cancer patient at the time of extraction.
[0034]
The subject candidate extraction system 1 thus
configured is described for its operation with reference
to the flow diagram of Figure 7.
[0035]
To extract subject candidates matching a clinical
trial protocol from multiple patients for whom electronic
health record information has been registered using the
subject candidate extraction system 1 according to this
embodiment, first, input data in extraction format
created based on electronic health record information is
acquired from the database 3 of the medical information
system 2 (Si). Then, upon input of criteria information
(the selection criteria and the exclusion criteria)
defined by the clinical trial protocol (S2), an extraction process with the criteria information is performed on the input data (S3).
[0036]
As a result, subject candidates matching the
clinical trial protocol are extracted from the multiple
patients. For example, with an extraction process using
the conditions (the selection criteria and the exclusion
criteria) of Figure 2, subject candidates matching the
clinical trial protocol targeting diabetes patients (e.g.,
73 subject candidates out of all the diabetes patients)
are extracted.
[0037]
With an extraction process using the conditions (the
selection criteria and the exclusion criteria) of Figure
3, for example, subject candidates matching the clinical
trial protocol targeting mild Alzheimer's dementia
patients (e.g., 63 subject candidates out of all the
Alzheimer's disease patients) are extracted.
[0038]
With an extraction process using the conditions (the
selection criteria and the exclusion criteria) of Figure
4, for example, subject candidates matching the clinical
trial protocol targeting multiple sclerosis patients
(e.g., 23 subject candidates out of all the multiple
sclerosis patients) are extracted.
[0039]
With an extraction process using the conditions (the
selection criteria and the exclusion criteria) of Figure
, for example, subject candidates matching the clinical
trial protocol targeting atrial fibrillation patients who
have renal dysfunction and are being treated with
Apixaban (e.g., 32 subject candidates out of all the
atrial fibrillation patients) are extracted.
[0040]
Then, the result of the extraction process is output
as output data in list format (see Figure 6) (S4). In
this manner, subject candidates matching the clinical
trial protocol can be extracted from multiple patients
for whom electronic health record information has been
registered.
[0041]
The subject candidate extraction system 1 according
to this embodiment enables easy extraction of subject
candidates matching a clinical trial protocol from
multiple patients. Here, subject candidates can be
extracted in a short time and with high accuracy even
with an extremely large number of patients as a
population of subject candidates.
[0042]
This embodiment can appropriately select patients
who should be selected (patients satisfying the selection
criteria) as subject candidates from multiple patients in conformance with the selection criteria defined by the clinical trial protocol.
[0043]
This embodiment can also appropriately exclude
patients who should be excluded (patients satisfying the
exclusion criteria) among multiple patients from subject
candidates in conformance with the exclusion criteria
defined by the clinical trial protocol.
[0044]
As described above, while embodiments of the present
invention have been described by way of illustration, the
scope of the present invention is not limited thereto;
alterations or modifications may be made within the scope
set forth in the claims according to an object.
Industrial Applicability
[0045]
As described above, the subject candidate extraction
method according to the present invention has the effect
of being able to extract subject candidates matching a
clinical trial protocol in a short time and with high
accuracy, and is advantageously used with a subject
candidate extraction system.
Reference Signs List
[0046]
1 subject candidate extraction system
2 medical information system
3 database
4 input data acquisition unit
criteria information input unit
6 extraction processing unit
7 output unit

Claims (6)

  1. Claims
    [Claim 1]
    A subject candidate extraction method to be
    performed in a subject candidate extraction system for
    extracting subject candidates matching a clinical trial
    protocol from a plurality of patients for whom electronic
    health record information has been registered, the
    subject candidate extraction method comprising the steps
    of:
    acquiring input data in extraction format created
    based on the electronic health record information from a
    database in which the electronic health record
    information is registered;
    receiving an input of criteria information defined
    in the clinical trial protocol;
    extracting subject candidates matching the clinical
    trial protocol from the plurality of patients by
    performing an extraction process with the criteria
    information on the input data; and
    outputting a result of the extraction process as
    output data in list format.
  2. [Claim 2]
    The subject candidate extraction method according to
    Claim 1, wherein the criteria information includes selection criteria, and in the extraction process, subject candidates who match the selection criteria are selected from the plurality of patients.
  3. [Claim 3]
    The subject candidate extraction method according to
    Claim 1 or Claim 2, wherein
    the criteria information includes exclusion criteria,
    and
    in the extraction process, subject candidates who
    match the exclusion criteria are excluded from the
    plurality of patients.
  4. [Claim 4]
    A subject candidate extraction system for extracting
    subject candidates matching a clinical trial protocol
    from a plurality of patients for whom electronic health
    record information has been registered, the subject
    candidate extraction system comprising:
    an input data acquisition unit that acquires input
    data in extraction format created based on the electronic
    health record information from a database in which the
    electronic health record information is registered; a criteria information input unit to which criteria information defined in the clinical trial protocol is input; an extraction processing unit that extracts subject candidates matching the clinical trial protocol from the plurality of patients by performing an extraction process with the criteria information on the input data; and an output unit that outputs a result of the extraction process as output data in list format.
  5. [Claim 5]
    The subject candidate extraction system according to
    Claim 4, wherein
    the criteria information includes selection criteria,
    and
    in the extraction process, subject candidates who
    match the selection criteria are selected from the
    plurality of patients.
  6. [Claim 6]
    The subject candidate extraction system according to
    Claim 4 or Claim 5, wherein
    the criteria information includes exclusion criteria,
    and
    in the extraction process, subject candidates who
    match the exclusion criteria are excluded from the
    plurality of patients.
AU2019273572A 2018-05-23 2019-05-23 Subject candidate extracting method, and subject candidate extracting system Pending AU2019273572A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
JP2018098405A JP6974256B2 (en) 2018-05-23 2018-05-23 Subject candidate extraction method and subject candidate extraction system
JP2018-098405 2018-05-23
PCT/JP2019/020390 WO2019225678A1 (en) 2018-05-23 2019-05-23 Subject candidate extracting method, and subject candidate extracting system

Publications (1)

Publication Number Publication Date
AU2019273572A1 true AU2019273572A1 (en) 2020-12-03

Family

ID=68616986

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2019273572A Pending AU2019273572A1 (en) 2018-05-23 2019-05-23 Subject candidate extracting method, and subject candidate extracting system

Country Status (5)

Country Link
JP (3) JP6974256B2 (en)
KR (1) KR20210015767A (en)
CN (2) CN112154511B (en)
AU (1) AU2019273572A1 (en)
WO (1) WO2019225678A1 (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6974256B2 (en) * 2018-05-23 2021-12-01 シミックヘルスケア・インスティテュート株式会社 Subject candidate extraction method and subject candidate extraction system
KR102251778B1 (en) * 2020-07-07 2021-05-14 울산대학교 산학협력단 Apparatus, method, computer-readable storage medium and computer program for sorting clinical trial subject
JP6887194B1 (en) * 2020-09-14 2021-06-16 株式会社Ａｒｂｌｅｔ Information processing systems, servers, information processing methods and programs
JP6869584B1 (en) * 2020-09-14 2021-05-12 株式会社Ａｒｂｌｅｔ Information processing systems, servers, information processing methods and programs
KR102397234B1 (en) * 2020-09-17 2022-05-12 가천대학교 산학협력산 Method and system for assessing medication adherence
KR102536431B1 (en) * 2022-10-12 2023-05-26 주식회사 사이클룩스 Method And Systems for Managing Clinical Trial Based on Gait Analysis

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006323864A (en) * 2000-04-28 2006-11-30 Mebix Kk Clinical test performance management system
JP2003337864A (en) 2002-05-17 2003-11-28 Ogawa Masanori Business model for registration and collation of candidate subject of clinical trial
JP3840481B2 (en) * 2003-05-15 2006-11-01 嘉久 倉智 Clinical trial management system and method using case database
JP2004348271A (en) * 2003-05-20 2004-12-09 Sanyo Electric Co Ltd Clinical trial data outputting device, clinical trial data outputting method, and clinical trial data outputting program
JP2006107055A (en) * 2004-10-04 2006-04-20 Gunma Univ Clinical test protocol execution system, clinical test protocol execution method and clinical test protocol execution program
JP2006215820A (en) * 2005-02-03 2006-08-17 Gunma Univ Clinical trial management system and clinical trial management method
EP2044431B1 (en) * 2006-07-17 2019-04-24 H. Lee Moffitt Cancer Center & Research Institute, Inc. Computer systems and methods for selecting subjects for clinical trials
JP2008047157A (en) 2007-10-29 2008-02-28 Masanori Fukushima Medical information management support device
JP2014019459A (en) * 2012-07-17 2014-02-03 Toppan Printing Co Ltd Paper container for liquid
JP6135241B2 (en) * 2013-03-28 2017-05-31 富士通株式会社 Program, clinical trial candidate extraction method, and clinical trial candidate extraction apparatus
JP6338957B2 (en) * 2014-07-22 2018-06-06 株式会社メディカルフロント Clinical trial compatible patient selection device, system and method
CN106980767A (en) * 2017-03-31 2017-07-25 上海森亿医疗科技有限公司 A kind of data search method and system based on structured medical database
CN107480456A (en) * 2017-08-22 2017-12-15 浙江大学医学院附属第医院 clinical trial management method and system
CN107767960A (en) * 2017-09-13 2018-03-06 温州悦康信息技术有限公司 Data processing method, device and the electronic equipment of clinical detection project
JP6974256B2 (en) 2018-05-23 2021-12-01 シミックヘルスケア・インスティテュート株式会社 Subject candidate extraction method and subject candidate extraction system

Also Published As

Publication number Publication date
WO2019225678A1 (en) 2019-11-28
CN112154511A (en) 2020-12-29
CN112154511B (en) 2024-03-08
JP2019204247A (en) 2019-11-28
JP7432099B2 (en) 2024-02-16
CN117976167A (en) 2024-05-03
JP6974256B2 (en) 2021-12-01
JP2022010023A (en) 2022-01-14
JP2024028423A (en) 2024-03-04
KR20210015767A (en) 2021-02-10

Similar Documents

Publication Publication Date Title
AU2019273572A1 (en) Subject candidate extracting method, and subject candidate extracting system
US11468975B2 (en) Medication reconciliation system and method
JP7010946B2 (en) Systems and methods that facilitate computational analysis of health status
Williams et al. Process mining in primary care: a literature review
CN106295182B (en) A kind of personal identification method based on patient biological information
KR101885111B1 (en) Method and apparatus for predicting probability of the outbreak of a disease
CN106663136B (en) System and method for scheduling healthcare follow-up appointments based on written recommendations
US8417548B2 (en) Medical service support apparatus
CN105095332B (en) Information processing unit and information processing method
CN104978478A (en) Information processing apparatus, information processing method
EP3105687A1 (en) Biomedical research database development and uses
WO2020004556A1 (en) Patient assessment support device, patient assessment support method, and recording medium
Fararouei et al. Completeness of cancer registry data in a small Iranian province: a capture–recapture approach
KR101969907B1 (en) Medical support system for foreigners and computer application saved in recording medium for medical supporting of foreigners
TW201835938A (en) Data integration method generating integrated medical history information according to the at least one first record and/or the at least one second record
Soto-Rey et al. Protocol feasibility workflow using an automated multi-country patient cohort system
Tache et al. Text mining of medical records
JP6537121B1 (en) Device and method for estimating medical expenses by injury and diseases and program
KR20160085021A (en) Patient customized automatic response apparatus and method
JP7052504B2 (en) Information processing device, waiting time calculation program and waiting time calculation method
EP4276847A1 (en) Defining a timestamp for a target medical event
US20230351793A1 (en) Information processing apparatus, information processing method, and computer-program-readable recording medium
JP2007047979A (en) Health information management device and control method for health information management device, and program
AU2016357545A1 (en) A method for matching with known variants in a database
US20210383917A1 (en) Nursing assistance device, nursing assistance method, and recording medium