• 한국콘텐츠학회논문지
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• 제11권4호
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• pp.312-320
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• 2011

이 논문에서는 일개 POC(Point Of Care) 시스템을 사용하는 의료기관을 중심으로 의약품 처방조제지원 시스템(Clinical Decision Support System, CDSS)과 조직성과와의 관계를 규명하는 것에 목적을 두고 있다. 이를 위하여 정보시스템 평가요소에 대해 정의를 내리고, CDSS의 성과 평가 모형을 제시하여 설문조사 분석을 통해 의약품 처방조제지원시스템의 도입 효과를 밝히고자 하였다. 분석결과 시스템 품질을 제외하고는 각 평가 영역들 사이에 인과성이 존재하는 것으로 분석되었으며, 통계적으로 유의하게 지지되는 것으로 분석되었다. 평가모형 검증결과 의약품처방최적화를 위한 CDSS의 시스템 품질이 사용자 만족도에 영향을 미친다는 근거를 발견할 수 없었다. 그러나 정보품질이 사용자의 만족도에 긍정적인 영향을 미치며 사용자 만족은 조직성과에 긍정적인 영향을 미치는 것으로 나타났다.

• 한국임상약학회지
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• 제23권1호
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• pp.26-32
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• 2013

Objective: This study was to define the clinical effect on the clinical decision support system (CDSS) for prescribing antibiotics integrated with the order communication system in a National Hospital. Method: We extracted data collected before integrating the CDSS of 4,406 adult patients in 2007 and data collected after integrating the CDSS of 4,278 adult patients in 2009. These patients were 50.4% and 45.2% of all patients admitted in 2007 and 2009, respectively. The clinical effect was defined as the proportion of prescribed antibiotics, the length of antibiotics use, and the DDDs (defined daily doses) of antibiotics per 1,000 patient-days using these retrospective data. Results: There were a significant change in the proportion of patient prescribed penicillins with extended spectrum (OR=0.55, p=001), penicillins included beta-lactamase inhibitors (OR=0.75, p<.001), 3rd cephalosporin (OR=1.47, p<.001). The mean of the length of antibiotics use was decreased statistically from $6.09{\pm}5.48$ to $5.85{\pm}5.51$ days (p=.003). The DDD of glycopeptides was decreased from 24.43 DDD to 19.55 DDD per 1000 patient-days. The DDD of 3rd cephalosporins was also decreased from 15.88 to 11.65. Conclusion: Therefore, the clinical decision support system for prescribing antibiotics was effective for the clinical outcomes.

• 대한간호학회지
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• 제44권3호
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• pp.294-304
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• 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.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.478-485
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• 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.

• 정보처리학회논문지B
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• 제17B권4호
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• pp.317-326
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• 2010

군 병원에서는 장병들에 대한 진단과 처방 과정을 보다 효율적으로 지원하기 위해 진료 의사결정지원 시스템의 도입이 요구되고 있다. 본 논문에서는 시맨틱 웹 기술을 기반으로 구현된 군 병원을 위한 진료 의사결정지원 시스템을 제안하고자 한다. 이를 위해, 의료 지원에 사용되는 다양한 개념들과 지식들로 구성된 국방 의료 온톨로지와 국방 의료 규칙을 구축하였고, 구축된 온톨로지와 규칙이 환자 진료에 활용되는 것을 보여주기 위해 진료 의사결정지원 시스템을 구현하였다. 또한 진료 의사결정지원 시스템을 통해 작성된 진료 기록들을 활용하여 의미 기반 검색이 수행되는 과정을 설명하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권15호
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• pp.6605-6608
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• 2015

Background: Colorectal cancer is a major cause of morbidity and mortality throughout the world. Colorectal cancer screening is an optimal way for reducing of morbidity and mortality and a clinical decision support system (CDSS) plays an important role in predicting success of screening processes. DSS is a computer-based information system that improves the delivery of preventive care services. The aim of this article was to detail engineering of information requirements and work flow design of CDSS for a colorectal cancer screening program. Materials and Methods: In the first stage a screening minimum data set was determined. Developed and developing countries were analyzed for identifying this data set. Then information deficiencies and gaps were determined by check list. The second stage was a qualitative survey with a semi-structured interview as the study tool. A total of 15 users and stakeholders' perspectives about workflow of CDSS were studied. Finally workflow of DSS of control program was designed by standard clinical practice guidelines and perspectives. Results: Screening minimum data set of national colorectal cancer screening program was defined in five sections, including colonoscopy data set, surgery, pathology, genetics and pedigree data set. Deficiencies and information gaps were analyzed. Then we designed a work process standard of screening. Finally workflow of DSS and entry stage were determined. Conclusions: A CDSS facilitates complex decision making for screening and has key roles in designing optimal interactions between colonoscopy, pathology and laboratory departments. Also workflow analysis is useful to identify data reconciliation strategies to address documentation gaps. Following recommendations of CDSS should improve quality of colorectal cancer screening.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.425-428
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• 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.

• 대한약침학회지
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• 제22권4호
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• pp.260-268
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• 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.

• 산업공학
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• 제20권4호
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• pp.488-497
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• 2007

In order to provide appropriate decision supports in medical domain, it is required that clinical knowledge should be implemented in a computable form and integrated with hospital information systems. Healthcare organizations are increasingly adopting tools that provide decision support functions to improve patient outcomes and reduce medical errors. This paper proposes a process centric clinical decision support system based on medical knowledge. The proposed system consists of three major parts - CPG (Clinical Practice Guideline) repository, service pool, and decision support module. The decision support module interprets knowledge base generated by the CPG and service part and then generates a personalized and patient centered clinical process satisfying specific requirements of an individual patient during the entire treatment in hospitals. The proposed system helps health professionals to select appropriate clinical procedures according to the circumstances of each patient resulting in improving the quality of care and reducing medical errors.

• 전기학회논문지
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• 제57권6호
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• pp.1058-1062
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• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.