WO2008093977A1 - Clinical decision support system using home health care data and medical information in hospital - Google Patents
Clinical decision support system using home health care data and medical information in hospital Download PDFInfo
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- WO2008093977A1 WO2008093977A1 PCT/KR2008/000520 KR2008000520W WO2008093977A1 WO 2008093977 A1 WO2008093977 A1 WO 2008093977A1 KR 2008000520 W KR2008000520 W KR 2008000520W WO 2008093977 A1 WO2008093977 A1 WO 2008093977A1
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- 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
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
-
- 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
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Definitions
- the present invention relates to a clinical decision support system researched and developed by linking a measurement data, sent by sensors on a home health care network, with a validated medical data already established in a medical information system in a medical institute.
- the present invention provides an automated clinical decision support system which enables quick medical care and emergency treatment by linking data sent through a home health network with medical data managed by a pre-existing medical institute, for an effective disease management.
- the present invention also provides a clinical knowledge engineering module and management system which can be linked to a new ubiquitous medical environment based on the long experience and knowledge of medical institutes and practitioners.
- an automated clinical decision support system which links data sent through a home health network and medical information within the electronic medical record (EMR) system of medical institutes, wherein: various symptom data and measurement data are sent to a clinical decision support system (CDSS) server of the medical institutes through a home health server; the data is linked with necessary information such as medical records or test results among the medical information within an electronic medical record system according to a clinical knowledge engineering module program; information within the EMR system can be linked with medical record contents filled out directly by the practitioner and quantified or codified test results entirely; the automated CDSS compiles the home health server data and the medical records or test result data within the EMR system to derive a result by an algorithm; the processed result by the CDSS is sent to a patient or a home health server, and also sent to an assigned practitioner when necessary; and a method of sending the result to the patient, the home health server or the authorized practitioner may include a text messaging system, or be sent in a form of an image, video, or audio.
- CDSS clinical decision support system
- a clinical knowledge engineering module and management system for diabetes, cardiovascular diseases such as hypertension, asthma, and obesity that can be applied to the CDSS including: a clinical knowledge engineering module for managing diabetes, cardiovascular diseases such as hypertension, asthma, and obesity, in which data can be sent by a home health network; and a management system that can easily be expanded and managed with the development of additional clinical knowledge engineering modules.
- the present invention enables quick medical care and emergency treatment by linking data sent through a home health network with medical data managed by a pre-existing medical institute, for an effective disease management, and also provides a clinical knowledge engineering module which can be linked to a new ubiquitous medical environment based on long experience and knowledge of medical institutes and practitioners.
- FIG. 1 is a schematic diagram of a related system in which a clinical decision support system (CDSS) according to an embodiment of the present invention is included;
- CDSS clinical decision support system
- FIG. 2 is a work flow chart of the process taking place in the CDSS of FIG. 1 ;
- FIG. 3 is a functional block diagram of a CDSS server of FIG. 1 ;
- FIGS. 4 and 5 are specific examples that describe the operation of a clinical knowledge engineering module and management system, according to an embodiment of the present invention;
- FIG. 6 is a user interface (Ul) screen illustrating an example of a CDSS web service established in the CDSS server of the present invention and paged from a data collecting server;
- FIG. 7 is an exemplary diagram of source code of a validation program of the CDSS server
- FIG. 8 is an exemplary diagram of a process being performed in a CDSS server engine;
- FIG. 9 illustrates an inquiry screen of registered rules;
- FIG. 10 illustrates a Ul screen for new addition of registered rules.
- FIG. 11 illustrates a Ul screen for managing the current status of the rules and history;
- FIG. 12 illustrates an example of a text message sent to a patient from a result manager.
- FIG. 1 is a schematic diagram of a related system in which a clinical decision support system (CDSS) according to an embodiment of the present invention is included.
- Data measured such as blood pressure or blood glucose level
- the data collecting server 20 is a server collecting data generated from the measuring sensors 10 through the home health network and communicates with the CDSS server 30.
- the data, collected by the data collecting server 20, is sent to the CDSS server 30 by being linked with electronic medical records (EMR, medical records of patients) of a backbone system 40 of a hospital to run a process.
- EMR electronic medical records of patients
- a firewall may be installed in the CDSS server 30.
- FIG. 2 illustrates a work flow chart of the process taking place in the CDSS of FIG.
- the measured values measured with the measuring sensor 10 is sent to the data collecting server 20.
- the data are screened in the data collecting server 20 by a predetermined algorithm, and the screened data are sent to the CDSS server 30.
- This screening algorithm is similar to an algorithm used in screening and filtering data within a conventional data sending system, and can be carried out easily by one skilled in the art.
- the screened data are then received by the CDSS server 30 to run a validation process that is used to validate data in a predetermined manner in order to link with the backbone system 40 of a hospital (such as EMR). (4) Then, the backbone system 40 of the hospital is requested for data. (5) When the results are returned, they are analyzed and a decision is processed. (6) Then, the results are sent to the measuring sensor 10, that is, to the patient by text messaging, and (6') the sent results are returned to the data collecting server 20 in a predetermined format.
- FIG. 3 is a functional block diagram of the CDSS server 30 of FIG. 1.
- the CDSS server 30 includes an input data manager 31 , decision rule manager (engine) 32, an EMR interface manager 33, and a result manager 34.
- the input data manager 31 acts as a data interface with the measuring sensor 10 through the data collecting server 20, receiving the measured data and saving data log as previously described.
- the input data manager 31 is linked with the decision rule manager 32 to process data validation.
- the decision rule manager 32 registers predetermined decision support rules (decision rules), and manages the current status and history of the rules, thereby supporting a decision process based on the rules.
- the decision process is executed in association with the EMR interface manager 33, which exchanges data with the EMR system 40. That is, the EMR interface manager 33 requests and receives data from the EMR system 40.
- the EMR interface manager 33 maintains decision rules and acts as an interface with the EMR system 40 by requesting and receiving EMR data from the EMR system 40.
- the result manager 34 maintains the types of results, and sends the result messages and the result values of various forms to an external system 50.
- FIGS. 4 and 5 are specific examples that describe the operation of a clinical knowledge engineering module and management system, according to an embodiment of the present invention, showing the flow and the result of a decision making process of a hypertension knowledge engineering module.
- an A1 message 105 is a message for a case where the result of a first measurement 101 is that a systolic blood pressure (SBP) > 180 or a diastolic blood pressure (DBP) > 110, and may be for example, "Warning: high blood pressure” or "Rest for 10 minutes before retaking the measurement".
- SBP systolic blood pressure
- DBP diastolic blood pressure
- An A2 message 109 is a message for a case when SBP ⁇ 100, and may be a message such as "Warning: low blood pressure" or "Rest for 10 minutes before retaking the measurement”.
- An A3 message 110 is a message for a case when the blood pressure is none of the two cases above, and may be a message such as "Blood pressure is high due to stress etc.” or "Rest is needed.”
- An A4 message 115 is a message for a case when the blood pressure was measured two or more times 111 , and it results that SBP>180 or DBP>110, such that the message may be "Medical attention is required” or "Call XXX-XXXX for a medical care"
- the EMR data is used to determine if the patient has been prescribed with hypertension drugs (119). If it is determined that the patient has been prescribed with hypertension drugs, an A5 message 121 is produced indicating that the drug has been prescribed. Otherwise, if it is determined that the patient has not been prescribed with hypertension drugs, an A6 message 123 is produced indicating that the drug has not been prescribed.
- the A5 message may be "Symptomatic: Medical care needed” and the A6 message may be "Low blood pressure: Rest needed.”
- FIG. 5 is an extended process flow chart for when it does not result that SBP ⁇ 100 (117) of FIG. 4, the process includes checking for diabetes and proteinuria, in addition to the blood pressure. Messages of produced results in each process can be as follows.
- FIG. 6 illustrates a Ul screen of an example of a CDSS web service established in the CDSS server 30 of the present invention and paged from the data collecting server 20.
- FIG. 7 illustrates an example of source code of a validation program of the CDSS server 30
- FIG. 8 illustrates a process being performed in a CDSS server engine
- FIGS. 9 to 11 illustrate Ul screens exemplifying the decision registration and a managing function, where FIG. 9 illustrates an inquiry screen of registered rules
- FIG. 10 illustrates a Ul screen for new addition of registered rules.
- FIG. 11 illustrates a Ul screen for managing the current status of the rules and history
- FIG. 12 illustrates an example of a text message sent to a patient by the result manager 34.
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Abstract
The present invention relates to a clinical decision support system researched and developed by linking a measurement data, sent by various sensors on a home health care network, with a validated medical data already established in a medical information system in a medical institute. According to an aspect of the present invention, there is provided an automated clinical decision support system which links data sent through a home health network and medical information within the EMR system of medical institutes. According to another aspect of the present invention, there is provided a clinical knowledge engineering module and management system which can be linked to a new ubiquitous medical environment based on long experience and knowledge of medical institutes and practitioners.
Description
CLINICAL DECISION SUPPORT SYSTEM USING HOME HEALTH CARE DATA AND
MEDICAL INFORMATION IN HOSPITAL
TECHNICAL FIELD
The present invention relates to a clinical decision support system researched and developed by linking a measurement data, sent by sensors on a home health care network, with a validated medical data already established in a medical information system in a medical institute.
BACKGROUND ART
As home health networks such as household devices and wired/wireless communication systems become ubiquitous, there is a demand for medical services applying various health information generated by the home health networks. In particular, such a demand for development is ever increasing in association with a clinical decision support system established in medical institutes.
However, operating the decision support system solely based on data produced at home can be extremely dangerous in the field of medicine. Therefore, a complex system and knowledge engineering module to which clinical information compiled in a pre-existing medical institute and verification of a physician can be added is required.
DETAILED DESCRIPTION OF THE INVENTION TECHNICAL PROBLEM
The present invention provides an automated clinical decision support system which enables quick medical care and emergency treatment by linking data sent through a home health network with medical data managed by a pre-existing medical institute, for an effective disease management. The present invention also provides a clinical knowledge engineering module and management system which can be linked to a new ubiquitous medical environment based on the long experience and knowledge of medical institutes and practitioners.
TECHNICAL SOLUTION
According to an aspect of the present invention, there is provided an automated clinical decision support system which links data sent through a home health network and medical information within the electronic medical record (EMR) system of medical institutes, wherein: various symptom data and measurement data are sent to a clinical decision support system (CDSS) server of the medical institutes through a home health server; the data is linked with necessary information such as medical records or test results among the medical information within an electronic medical record system according to a clinical knowledge engineering module program; information within the EMR system can be linked with medical record contents filled out directly by the practitioner and quantified or codified test results entirely; the automated CDSS compiles the home health server data and the medical records or test result data within the EMR system to derive a result by an algorithm; the processed result by the CDSS is sent to a patient or a home health server, and also sent to an assigned practitioner when necessary; and a method of sending the result to the patient, the home health server or the authorized practitioner may include a text messaging system, or be sent in a form of an image, video, or audio.
According to another aspect of the present invention, there is provided a clinical knowledge engineering module and management system for diabetes, cardiovascular diseases such as hypertension, asthma, and obesity that can be applied to the CDSS including: a clinical knowledge engineering module for managing diabetes, cardiovascular diseases such as hypertension, asthma, and obesity, in which data can be sent by a home health network; and a management system that can easily be expanded and managed with the development of additional clinical knowledge engineering modules.
ADVANTAGEOUS EFFECTS
The present invention enables quick medical care and emergency treatment by linking data sent through a home health network with medical data managed by a pre-existing medical institute, for an effective disease management, and also provides a clinical knowledge engineering module which can be linked to a new ubiquitous medical environment based on long experience and knowledge of medical institutes and practitioners.
DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic diagram of a related system in which a clinical decision support system (CDSS) according to an embodiment of the present invention is included;
FIG. 2 is a work flow chart of the process taking place in the CDSS of FIG. 1 ; FIG. 3 is a functional block diagram of a CDSS server of FIG. 1 ; FIGS. 4 and 5 are specific examples that describe the operation of a clinical knowledge engineering module and management system, according to an embodiment of the present invention;
FIG. 6 is a user interface (Ul) screen illustrating an example of a CDSS web service established in the CDSS server of the present invention and paged from a data collecting server;
FIG. 7 is an exemplary diagram of source code of a validation program of the CDSS server;
FIG. 8 is an exemplary diagram of a process being performed in a CDSS server engine; FIG. 9 illustrates an inquiry screen of registered rules;
FIG. 10 illustrates a Ul screen for new addition of registered rules. FIG. 11 illustrates a Ul screen for managing the current status of the rules and history; and
FIG. 12 illustrates an example of a text message sent to a patient from a result manager.
BEST MODE
FIG. 1 is a schematic diagram of a related system in which a clinical decision support system (CDSS) according to an embodiment of the present invention is included. Data measured (such as blood pressure or blood glucose level) with at least one measuring sensor 10 at home is collected in a data collecting server 20 through a home health network. The data collecting server 20 is a server collecting data generated from the measuring sensors 10 through the home health network and communicates with the CDSS server 30. The data, collected by the data collecting server 20, is sent to the CDSS server 30 by being linked with electronic medical records (EMR, medical records of patients) of a backbone system 40 of a hospital to run a process. A firewall may be installed in the CDSS server 30.
FIG. 2 illustrates a work flow chart of the process taking place in the CDSS of FIG.
1. (1 ) The measured values measured with the measuring sensor 10 is sent to the data collecting server 20. (2) The data are screened in the data collecting server 20 by a predetermined algorithm, and the screened data are sent to the CDSS server 30. This screening algorithm is similar to an algorithm used in screening and filtering data within a conventional data sending system, and can be carried out easily by one skilled in the art.
(3) The screened data are then received by the CDSS server 30 to run a validation process that is used to validate data in a predetermined manner in order to link with the backbone system 40 of a hospital (such as EMR). (4) Then, the backbone system 40 of the hospital is requested for data. (5) When the results are returned, they are analyzed and a decision is processed. (6) Then, the results are sent to the measuring sensor 10, that is, to the patient by text messaging, and (6') the sent results are returned to the data collecting server 20 in a predetermined format.
FIG. 3 is a functional block diagram of the CDSS server 30 of FIG. 1. The CDSS server 30 includes an input data manager 31 , decision rule manager (engine) 32, an EMR interface manager 33, and a result manager 34.
The input data manager 31 acts as a data interface with the measuring sensor 10 through the data collecting server 20, receiving the measured data and saving data log as previously described. The input data manager 31 is linked with the decision rule manager 32 to process data validation.
The decision rule manager 32 registers predetermined decision support rules
(decision rules), and manages the current status and history of the rules, thereby supporting a decision process based on the rules. The decision process is executed in association with the EMR interface manager 33, which exchanges data with the EMR system 40. That is, the EMR interface manager 33 requests and receives data from the EMR system 40.
Therefore, the EMR interface manager 33 maintains decision rules and acts as an interface with the EMR system 40 by requesting and receiving EMR data from the EMR system 40.
The result manager 34 maintains the types of results, and sends the result messages and the result values of various forms to an external system 50.
FIGS. 4 and 5 are specific examples that describe the operation of a clinical knowledge engineering module and management system, according to an embodiment of the present invention, showing the flow and the result of a decision making process of a hypertension knowledge engineering module. Referring to FIG. 4, it shows that an A1 message 105 is a message for a case where the result of a first measurement 101 is that a systolic blood pressure (SBP) > 180 or a diastolic blood pressure (DBP) > 110, and may be for example, "Warning: high blood pressure" or "Rest for 10 minutes before retaking the measurement".
An A2 message 109 is a message for a case when SBP < 100, and may be a message such as "Warning: low blood pressure" or "Rest for 10 minutes before retaking the measurement".
An A3 message 110 is a message for a case when the blood pressure is none of the two cases above, and may be a message such as "Blood pressure is high due to stress etc." or "Rest is needed." An A4 message 115 is a message for a case when the blood pressure was measured two or more times 111 , and it results that SBP>180 or DBP>110, such that the message may be "Medical attention is required" or "Call XXX-XXXX for a medical care"
When the blood pressure is measured for two or more times 111 and it results that SBP<100 (117), the EMR data is used to determine if the patient has been prescribed with hypertension drugs (119). If it is determined that the patient has been prescribed with hypertension drugs, an A5 message 121 is produced indicating that the drug has been prescribed. Otherwise, if it is determined that the patient has not been prescribed with hypertension drugs, an A6 message 123 is produced indicating that the drug has
not been prescribed. The A5 message may be "Symptomatic: Medical care needed" and the A6 message may be "Low blood pressure: Rest needed."
FIG. 5 is an extended process flow chart for when it does not result that SBP<100 (117) of FIG. 4, the process includes checking for diabetes and proteinuria, in addition to the blood pressure. Messages of produced results in each process can be as follows.
B1. Blood pressure is normal.
B2. Check the antihypertension drug.
B3. Blood pressure is high. Low salt diet and regular exercise is needed.
B4. Blood pressure is high. Low salt diet and regular exercise is needed. B5. Blood pressure is normal.
B6. Check the antihypertension drug.
B7. Blood pressure is high. Low salt diet and regular exercise is needed.
B8. Blood pressure is high. Low salt diet and regular exercise is needed.
FIG. 6 illustrates a Ul screen of an example of a CDSS web service established in the CDSS server 30 of the present invention and paged from the data collecting server 20.
FIG. 7 illustrates an example of source code of a validation program of the CDSS server 30;
FIG. 8 illustrates a process being performed in a CDSS server engine; FIGS. 9 to 11 illustrate Ul screens exemplifying the decision registration and a managing function, where FIG. 9 illustrates an inquiry screen of registered rules;
FIG. 10 illustrates a Ul screen for new addition of registered rules.
FIG. 11 illustrates a Ul screen for managing the current status of the rules and history; and FIG. 12 illustrates an example of a text message sent to a patient by the result manager 34.
Claims
1. A clinical decision support system using home healthcare data and health care information of medical institutes, the system comprising: an input data manager acting as a data interface with at least one measuring sensor through a data collecting server, and processing data validation; a decision rule manager registering predetermined decision support rules (decision rules), managing the current status and history of the rules, thereby supporting a decision process based on the rules; an electronic medical record (EMR) interface manager maintaining the decision rules, acting as an interface with the EMR system, and requesting and receiving EMR data; and a result manager maintaining the types of results so as to send the result messages and the result values of various forms to an external system.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020070009015A KR20090000196A (en) | 2007-01-29 | 2007-01-29 | Clinical Decision Support System Using Home Healthcare Data and Medical Institution Information |
| KR10-2007-0009015 | 2007-01-29 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2008093977A1 true WO2008093977A1 (en) | 2008-08-07 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/KR2008/000520 Ceased WO2008093977A1 (en) | 2007-01-29 | 2008-01-29 | Clinical decision support system using home health care data and medical information in hospital |
Country Status (2)
| Country | Link |
|---|---|
| KR (1) | KR20090000196A (en) |
| WO (1) | WO2008093977A1 (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012073166A1 (en) * | 2010-12-03 | 2012-06-07 | Koninklijke Philips Electronics N.V. | Medical information system ruleset creation and/or evaluation graphical user interface |
| US8936555B2 (en) | 2009-10-08 | 2015-01-20 | The Regents Of The University Of Michigan | Real time clinical decision support system having linked references |
| US9211096B2 (en) | 2009-10-08 | 2015-12-15 | The Regents Of The University Of Michigan | Real time clinical decision support system having medical systems as display elements |
| CN107169259A (en) * | 2016-12-12 | 2017-09-15 | 为朔生物医学有限公司 | Personalized medicine based on collaborative filtering and suggestion determines support system |
| CN107731313A (en) * | 2017-09-20 | 2018-02-23 | 上海林康医疗信息技术有限公司 | The system and method for online tracking slow disease patient curative effect |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101066246B1 (en) * | 2009-02-26 | 2011-09-20 | 서울대학교산학협력단 | Clinical Decision Support System and Method |
| KR101141103B1 (en) * | 2009-12-15 | 2012-05-02 | 계명대학교 산학협력단 | Method of generating decision rule for clinical diagnosis |
| KR102160831B1 (en) | 2013-12-13 | 2020-09-28 | 인바이츠헬스케어 주식회사 | Method and server apparatus for clinical decision support |
| KR101719401B1 (en) * | 2014-12-12 | 2017-03-23 | 경희대학교 산학협력단 | Clinical knowledge validation system and method based on case base reasoning |
| EP3255573A1 (en) | 2016-06-10 | 2017-12-13 | Electronics and Telecommunications Research Institute | Clinical decision supporting ensemble system and clinical decison supporting method using the same |
| KR101948091B1 (en) * | 2016-12-20 | 2019-02-14 | 서울여자대학교 산학협력단 | System for anonymizing user information of Healthcare Smart Home |
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| KR20020009302A (en) * | 2000-07-25 | 2002-02-01 | 석무술 | System and method for an unmanned telemedicine |
| KR20040031469A (en) * | 2002-10-07 | 2004-04-13 | (주)메드 밴 | Medical expert system for urology and managing metohd of the same |
| US20040210548A1 (en) * | 2003-02-07 | 2004-10-21 | Theradoc, Inc. | System, method, and computer program for interfacing an expert system to a clinical information system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8936555B2 (en) | 2009-10-08 | 2015-01-20 | The Regents Of The University Of Michigan | Real time clinical decision support system having linked references |
| US9211096B2 (en) | 2009-10-08 | 2015-12-15 | The Regents Of The University Of Michigan | Real time clinical decision support system having medical systems as display elements |
| WO2012073166A1 (en) * | 2010-12-03 | 2012-06-07 | Koninklijke Philips Electronics N.V. | Medical information system ruleset creation and/or evaluation graphical user interface |
| CN107169259A (en) * | 2016-12-12 | 2017-09-15 | 为朔生物医学有限公司 | Personalized medicine based on collaborative filtering and suggestion determines support system |
| CN107731313A (en) * | 2017-09-20 | 2018-02-23 | 上海林康医疗信息技术有限公司 | The system and method for online tracking slow disease patient curative effect |
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| KR20090000196A (en) | 2009-01-07 |
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