KR20180020601A - Clinical decision support system using new rule by created a medical professional - Google Patents

Clinical decision support system using new rule by created a medical professional Download PDF

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Publication number
KR20180020601A
KR20180020601A KR1020160105206A KR20160105206A KR20180020601A KR 20180020601 A KR20180020601 A KR 20180020601A KR 1020160105206 A KR1020160105206 A KR 1020160105206A KR 20160105206 A KR20160105206 A KR 20160105206A KR 20180020601 A KR20180020601 A KR 20180020601A
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KR
South Korea
Prior art keywords
rule
input
unit
storage
data
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KR1020160105206A
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Korean (ko)
Inventor
최익준
조인수
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헤인앤드윗(주)
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Priority to KR1020160105206A priority Critical patent/KR20180020601A/en
Publication of KR20180020601A publication Critical patent/KR20180020601A/en

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    • 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
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work
    • 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
    • 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

Abstract

The clinical decision support system of the present invention includes an input unit for receiving input data directly input by a medical care provider, and input data received through the input unit, into a storage rule and an input rule using a storage rule stored in a rule database An algorithm operation unit for receiving a storage rule and an input rule output by the parsing unit and determining whether to store the input rule in a new storage rule; A rule judging unit for performing an additional analysis on the input rule using the article data and the clinical result data when it is judged that the judgment as to whether or not a new storing rule is incomplete is made, Basis for collecting internal or external papers And a clinical result referencing unit connected to the rule judging unit and collecting internal or external clinical outcome data.

Description

[0001] The present invention relates to a clinical decision support system,

The present invention relates to a clinical decision support system, in which a rule is generated by a medical staff so that a result of diagnosis by a medical doctor or a medical doctor such as a doctor or the like can be databaseized, To be reflected in the system.

A recording system has been developed and used in which a patient's medical record is stored using an electronic health record instead of a method in which a medical institution records patient information on a paper or film.

Electronic health records can provide better medical services by exchanging and exchanging medical information with various fields that require information as well as between medical institutions.

In addition, in combination with the dissemination of equipment that can measure the patient's health condition and the development of technology including IT, NT, and BT, the life-like healthcare services such as ubiquitous health care have been developed, You can easily check your health condition.

These medical services can be combined with the Clinical Decision Support System to provide a wider range of services quickly. The clinical decision support system is a computer-based support system designed to make more accurate decision-making at the point of time when decision-making is needed by utilizing the data measured or inputted from the patient and the knowledge information of the rule database. With the realization of healthcare information such as electronic health records and ubiquitous healthcare, there has been a growing interest in improving medical services and reducing time and costs. At the same time, interest in clinical decision support devices, which are very effective tools to support, is increasing.

These electronic health records are typically stored as text files and are configured to be regularly updated by users or system experts. The input data entered into the clinical decision support device contains the measured values of the patients or the knowledge of the disease, and these contents are judged as one rule. These rules are usually in the form of natural language. Natural language is a common language used by people to distinguish them from artificial language designed for effective communication in specific fields such as machine language. Since natural language is different from machine language used in computers and computers can not understand natural language itself, in order to input data into a computer, a programming process such as compiling to machine language is required. However, this process is time consuming and inefficient because it requires the help and intervention of experts in the field.

In addition, there is a disadvantage in that a strict format is required in application of an inference engine or storing of a storage rule in an information storage process in common, and two inference engines having different input methods can not be provided in one storage rule .

As a result, updating the stored data stored in the rule database in the case of a clinical decision support device, in connection with the stored data of the above-mentioned systems that deal with professional contents, requires doctors or programmers who are experts in the field concerned with device production . This has an inefficient structure in which continuous updating is difficult or when an update is performed, a lot of time and manpower is wasted.

The present invention proposes a device that can update the rule database freely to reduce the time and manpower consumed in updating the rule database, apply the self-evolution rule-based algorithm, and use the information sources of various papers and clinical results We propose a device that can generate rules.

The clinical decision support system of the present invention includes an input unit for receiving input data directly input by a medical care provider, and input data received through the input unit, into a storage rule and an input rule using a storage rule stored in a rule database An algorithm operation unit for receiving a storage rule and an input rule output by the parsing unit and determining whether to store the input rule in a new storage rule; A rule judging unit for performing an additional analysis on the input rule using the article data and the clinical result data when it is judged that the judgment as to whether or not a new storing rule is incomplete is made, Basis for collecting internal or external papers And a clinical result referencing unit connected to the rule judging unit and collecting internal or external clinical outcome data.

The clinical decision support apparatus of the present invention can store the new storage rules for the input data directly input by the medical staff and provide the back data for more accurate clinical decision support to the medical staff.

1 to 3 are diagrams showing a configuration and a relation of a clinical decision support apparatus of the present invention.
4 is a flowchart illustrating an analysis of a clinical decision support apparatus according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals are used to designate identical or similar elements, and redundant description thereof will be omitted. The suffix "module" and " part "for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role. In the following description of the embodiments of the present invention, a detailed description of related arts will be omitted when it is determined that the gist of the embodiments disclosed herein may be blurred. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. , ≪ / RTI > equivalents, and alternatives.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The singular expressions include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used to specify that a feature, a number, a step, an operation, an element, a component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

1 to 3 are diagrams showing a configuration and a relation of a clinical decision support apparatus of the present invention.

First, according to the present invention, the clinical decision support means 100 receives data inputted by a medical staff, such as a doctor, who cares for a patient, and the clinical decision support means 100, .

That is, the medical staff can input the language for directly updating and updating the data. The clinical decision support means 100 assigns rules to the inputted data, Refer to the database.

FIG. 2 shows a configuration of a rule determination unit 110 and a rule database 120 constituting the clinical decision support means 100. As shown in FIG.

The natural language type input data input by the medical staff such as a doctor is received by the input unit 101 and the input data received through the input unit 101 is stored in the natural language of the input data by the parsing unit 130 Input rules are analyzed and separated.

The input unit 101 is information input by the medical staff, and includes a state of the patient, a measurement value, medical knowledge, and diagnosis. The input data has a natural language form, have.

The parsing unit 130 extracts words included in the input data using the ontology technique for the input data input by the medical staff and stores the words used for word extraction and analysis among the storage rules stored in the rule database 120 And the input rule included in the input data in addition to the storage rule.

The parsing unit 130 uses the storage rules stored in the rule database 120 in the case of storage rules for the input data received through the input unit 101, Generate input rules for things.

The rule database 120 stores stored data in a natural language format, and a plurality of storage rules including items and details are stored as stored data or storage rules. As will be described later, the stored data and the storage rule stored in the rule database 120 are updated by the rule determination unit 110 and the algorithm operation unit 140.

The storage rules stored in the rule database 120 include data and facts, and the data may include mainly input values, medical fields such as numerical values indicating the measured values or states measured from the patient, Lt; / RTI > And fact refers to opinions and knowledge of experts on situations and problems. In other words, the medical field indicates symptoms of a disease or a method of treatment, for example, in the clinical decision support apparatus of the embodiment, the output result is calculated based on a storage rule.

After the input data is classified into the storage rule and the input rule by the parser 130, the storage rule and the input rule are transmitted to the algorithm operation unit 140.

The algorithm operation unit 140 compares the details of the input rule and the storage rule, and updates the rule database 120 according to the comparison result. According to an exemplary embodiment of the present invention, a rule determination unit 110 that can compare an input rule with a storage rule and refer to an external source of an article and a clinical result for storage rules to update the rule database 120, The update can be made.

That is, the algorithm operation unit 140 compares the input rule with the item of the storage rule, and when it is determined that the input rule needs to be stored as a new storage rule, the algorithm operation unit 140 stores the input rule in the rule database 120 The storage rule and the corresponding input rule can be updated as a storage rule. However, if it is difficult to determine whether the input rule is updated as a result of comparing the input rule and the storage rule, the rule determination unit 110 may determine whether the input rule is updated.

If the compared items are the same as the comparison result of the algorithm operation unit 140, the details of the input rule and the storage rule may be compared to update details of the storage rule when the details are different have. However, according to the embodiment, when it is determined that the storage rule and the input rule are the same as the result of the comparison by the algorithm operation unit 140, the rule determination unit 110 may determine whether the rule database is updated .

The rule determination unit 110 checks the storage rule used for parsing the input data by the parser 130 from among the storage rules stored in the rule database 120, And compares the input rules. The comparison between the input rule and the storage rule may be performed by comparing the internal or external papers collected by the papers reference unit 150 and the internal or external clinical results collected by the clinical result reference unit 160 Resources are available.

At this time, the rule determination unit 110 performs a task of dividing the data collected through the reference article reference unit 150 and the clinical result reference unit 160 into a storage rule and an input rule, It is determined whether or not the input rule included in the storage rule corresponds to the item that can be stored as a new storage rule.

As a result of the determination by the rule determination unit 110, the storage rule classified by the parsing unit 130 and the input rule among the input rules may be related to the published papers or clinical results, When it is determined as a rule, the rule database 120 is updated.

The algorithm analysis unit of the present invention and the process of determining and analyzing the input rules included in the input data by the rule determination unit will be described in detail.

4 is a flowchart illustrating an analysis of a clinical decision support apparatus according to the present invention.

The algorithm operation unit and the rule determination unit call one or more input rules identified in the input data, and call the storage rule from the stored data corresponding to the input rule (S101).

The algorithm operation unit and the rule determination unit compare and analyze the stored input rules with the storage rules determined in the rule database 120 (S102).

Comparing the one or more items included in the input rule with the items included in the storage rule and if the item included in the input rule does not match the item included in the storage rule, Judges a new rule, and adds / updates a new input rule to the rule database 120. [ If at least one item included in the input rule is the same item as the item included in the storage rule as a result of the comparison, the detailed information included in the storage rule having the same item as the pressure rule And then compare them.

If the details of the input rule and the details of the storage rule are the same as the comparison result, the rule determination unit performs an analysis process using the article and the clinical result data (S103).

If there is an item in which the details of the storage rule are consistent with the items included in the article or the clinical result as a result of further comparison based on the collected article data and the clinical result data, , And updates the rule database 120 (S104).

By repeating these processes, new data stored in the input data directly input by the medical staff can be stored, and the back data for more accurate clinical decision support can be provided to the medical staff.

Claims (1)

An input unit for receiving input data directly inputted by a medical staff,
A parser for separating input data received through the input unit into a storage rule and an input rule using a storage rule pre-stored in a rule database;
An algorithm operation unit for receiving a storage rule and an input rule output by the parsing unit and determining whether to store the input rule in a new storage rule,
A rule determination unit for performing an additional analysis on the input rule using the article data and the clinical result data when the algorithm operation unit determines that the determination as to whether the input rule is a new storage rule is incomplete,
A reference papers reference unit connected to the rule determination unit and for collecting internal or external papers,
A clinical decision support system connected with the rule determination unit and using rule generation of a medical staff member including a clinical result reference unit for collecting internal or external clinical result data.
KR1020160105206A 2016-08-19 2016-08-19 Clinical decision support system using new rule by created a medical professional KR20180020601A (en)

Priority Applications (1)

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KR1020160105206A KR20180020601A (en) 2016-08-19 2016-08-19 Clinical decision support system using new rule by created a medical professional

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
KR1020160105206A KR20180020601A (en) 2016-08-19 2016-08-19 Clinical decision support system using new rule by created a medical professional

Publications (1)

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KR20180020601A true KR20180020601A (en) 2018-02-28

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