• Journal of Korean Academy of Nursing
• /
• v.44 no.3
• /
• pp.294-304
• /
• 2014

Purpose: The influence of dietary composition on blood pressure is an important subject in healthcare. Interactions between antihypertensive drugs and diet (IBADD) is the most important factor in the management of hypertension. It is therefore essential to support healthcare providers' decision making role in active and continuous interaction control in hypertension management. The aim of this study was to implement an ontology-based clinical decision support system (CDSS) for IBADD management (IBADDM). We considered the concepts of antihypertensive drugs and foods, and focused on the interchangeability between the database and the CDSS when providing tailored information. Methods: An ontology-based CDSS for IBADDM was implemented in eight phases: (1) determining the domain and scope of ontology, (2) reviewing existing ontology, (3) extracting and defining the concepts, (4) assigning relationships between concepts, (5) creating a conceptual map with CmapTools, (6) selecting upper ontology, (7) formally representing the ontology with Protege (ver.4.3), (8) implementing an ontology-based CDSS as a JAVA prototype application. Results: We extracted 5,926 concepts, 15 properties, and formally represented them using Protege. An ontology-based CDSS for IBADDM was implemented and the evaluation score was 4.60 out of 5. Conclusion: We endeavored to map functions of a CDSS and implement an ontology-based CDSS for IBADDM.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2005.11a
• /
• pp.425-428
• /
• 2005

Healthcare is a research field suitable for applying the recent ubiquitous techniques. As a test system, we developed a kind of CDSS (Clinical Decision Support System) running in ubiquitous environment. called as 'uCDSS'. The uCDSS is a core system of the ubiquitous healthcare and is composed of some 'uMLMs(Ubiquitous Medical Logic Modules)'. The uMLMs based on the class in C# programming language could be reused in development of CDSS, or another EHR system running in .NET environment. As a test system, we developed the DM(Diabetes Mellitus knowledge system using ASP.NET. This system shows the potential of C# class-based uMLMs and the extensibility to any .NET development project.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.357-358
• /
• 2022

이 논문은 Deep Learning 을 이용해 의사의 진단의 도움을 줄 수 있는 Clinic Decision Support System(CDSS) Framework 를 제안한다. 당뇨병, 고혈압, 고지혈증 같은 대사질환은 증상이 있는 경우도 있지만 없는 경우가 대부분이다.[1] 그렇기 때문에 원격으로 진료할 경우 대사질환에 대한 부분을 놓칠 수 있다. 이러한 부분을 챗봇이 의사에게 Deep Neural Network(DNN)으로 예측된 정보를 제공해 도움을 준다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.1321-1322
• /
• 2012

With the advance of Information Technology (IT) and dynamic requirements, diverse application services have been provided for end users. With huge volume of these services and information, users are required to acquire customized services that provide personalized information and decision at particular extent of time. The case is more appealing in healthcare, where patients wish to have access to their medical record where they have control and provided with recommendation on the medical information. PHR (Personal Health Record) is most prevailing initiative that gives secure access on patient record at anytime and anywhere. PHR should also incorporate decision support to help patients in self-management of their diseases. Available PHR system incorporates basic recommendations based on patient routine data. We have proposed decision support service called "Smart CDSS" that provides recommendations on PHR data for diabetic patients. Smart CDSS follows HL7 vMR (Virtual Medical Record) to help in integration with diverse application including PHR. PHR shares patient data with Smart CDSS through standard interfaces that pass through Adaptability Engine (AE). AE transforms the PHR CCR/CCD (Continuity of Care Record/Document) into standard HL7 vMR format. Smart CDSS produces recommendation on PHR datasets based on diabetic knowledge base represented in shareable HL7 Arden Syntax format. The Smart CDSS service is deployed on public cloud over MS Azure environment and PHR is maintaining on private cloud. The system has been evaluated for recommendation for 100 diabetic patients from Saint's Mary Hospital. The recommendations were compared with physicians' guidelines which complement the self-management of the patient.

• Journal of Pharmacopuncture
• /
• v.22 no.4
• /
• pp.260-268
• /
• 2019

Objectives: The Clinical Decision Support System (CDSS), which analyzes and uses electronic health records (EHR) for medical care, pursues patient-centered medical care. It is necessary to establish the CDSS in Korean medical services for objectification and standardization. For this purpose, analyses were performed on the points to be followed for CDSS implementation with a focus on herbal medicine prescription. Methods: To establish the CDSS in the prescription of Traditional Korean Medicine, the current prescription practices of Traditional Korean Medicine doctors were analyzed. We also analyzed whether the prescription support function of the electronic chart was implemented. A questionnaire survey was conducted querying Traditional Korean Medicine doctors working at Traditional Korean Medicine clinics and hospitals, to investigate their desired CDSS functions, and their perceived effects on herbal medicine prescription. The implementation of the CDSS among the audit software developers used by the Korean medical doctors was examined. Results: On average, 41.2% of Traditional Korean Medicine doctors working in Traditional Korean Medicine clinics manipulated 1 to 4 herbs, and 31.2% adjusted 4 to 7 herbs. On average, 52.5% of Traditional Korean Medicine doctors working in Traditional Korean Medicine hospitals adjusted 1 to 4 herbs, and 35.5% adjusted 4 to 7 herbs. Questioning the desired prescription support function in the electronic medical record system, the Traditional Korean Medicine doctors working at Korean medicine clinics desired information on 'medicine name, meridian entry, flavor of medicinals, nature of medicinals, efficacy,' 'herb combination information' and 'search engine by efficacy of prescription.' The doctors also desired compounding contraindications (eighteen antagonisms, nineteen incompatibilities) and other contraindicatory prescriptions, 'medicine information' and 'prescription analysis information through basic constitution analyses.' The implementation of prescription support function varied by clinics and hospitals. Conclusion: In order to implement and utilize the CDSS in a medical service, clinical information must be generated and managed in a standardized form. For this purpose, standardization of terminology, coding of prescriptions using a combination of herbal medicines, and unification such as the preparation method and the weights and measures should be integrated.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06b
• /
• pp.114-115
• /
• 2011

Chronic disease may leads to other life threatening health complications like heart disease, stroke, diabetes and peripheral vascular disease that diminished quality of life. This paper points out the importance of social interaction and smart space integration in existing CDSS for chronic diseases. Social interaction allows the patients to interact with system, through this continuous learning and digesting patient experience, our CDSS becomes intelligent and dynamically enhanced. Smart spaces automatically provide new knowledge and construct the behavioral profile by monitoring the daily life activities. Through these features, patients can get continuous relevant recommendations from the system, so they can get a chance to improve their health condition which in terms keeping on their quality of life. It also helps the health practitioners in better decision making about medication and living patterns.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.478-485
• /
• 2001

In this study, we have developed a prototype of clinical decision support systems (CDSS) for diagnosing neurogenic bladder and compared its predicted diagnoses with the actual diagnoses using 92 patient\`s Urodynamic study cases. The CDSS was developed using a Visual Basic based on the evidence-based rules extracted from guidelines and other references regarding a diagnosis of neurogenic bladder. To compare with the 92 final diagnoses made by doctors at the Yonsei Rehabilitation Center, we classified all diagnoses into 5 groups. The predictive rates of the CDSS were: 48.0% for areflexic neurogenic bladder; 60.0% for hyperreflexic neurogenic bladder in a spinal shock recovery stage; 72.9% for hyperreflexic neurogenic bladder, and 80.0% for areflexic neurogenic bladder in a spinal shock stage, which was the highest predicted rate. There were only 2 cases for hyperreflexic neurogenic bladder in a well controlled detrusor activity, and its predictive rate was 0%. The study results showed that CDSS for diagnosing neurogenic bladder could provide a helpful advice on decision-making for doctors. The findings also suggest that physicians should be involved in all development stages to ensure that systems are developed in a fashion that maximizes their beneficial effect on patient care, and that systems are acceptable to both professionals and patients. The future studies will concentrate on including more validating the system.

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.312-320
• /
• 2011

The goal of this paper is to examine the effects of a CDSS(Clinical Decision Support System) for drug prescription on organizational performance in medical institutions using POC(Point Of Care) systems. For achieving this goal, evaluation factors for influencing performance of information system were identified by using the performance evaluation model for CDSS. In the results, there was significant causality between each evaluation domain except system quality domain. In addition, the system quality of CDSS for optimal drug prescription has no influence on user satisfaction. But information quality has positive influence on user satisfaction which has also a positive influence on organizational performance.

• The KIPS Transactions:PartB
• /
• v.17B no.4
• /
• pp.317-326
• /
• 2010

To improve the diagnosis and prescription for military personnel, it is required to adopt Clinical Decision Support System (CDSS) in armed forces hospitals. The objective of this paper is to suggest a CDSS for armed forces hospitals using semantic web technologies. To this end, we designed military medical ontologies and military medical rules which consist of the various concepts and rules for supporting medical activities. We developed a semantic web-based CDSS to demonstrate the use of the ontologies and rules for treating military patients. We also showed the process of semantic search for the medical records which are created from the semantic web-based CDSS.

• Journal of Korean Society for Quality Management
• /
• v.42 no.1
• /
• pp.81-89
• /
• 2014

Purpose: The purpose of this study is to propose Clinical Practice Guideline(CPG) model and Clinical Index(CI) for implementing CDSS in digital hospitals. Methods: This study uses EMR data at department of family practice in A hospital; 636 patients, 570 diseases (based on ICD 10-CM criteria), and 37,000 data related with labs and treatments. This study focuses on disease J342 which is the most high rate of incidence. Results: Using the suggested model, this study calculates frequency matrix and probability matrix to find out the correlation of diseases and labs. This study indicates the lab sets of Disease (J342) as CI for CPG. Conclusion: This study suggests CPG model including Lab-based, Disease-Based and Case-based modules. Through 6 level cased-based CPG model, especially, this study develops Clinical Index(CI) such as the Incidence Rate, Lab Rate, Disease Lab Rate, Disease confirmed by Lab.