• 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.

• Korean Journal of Clinical Pharmacy
• /
• v.23 no.1
• /
• pp.26-32
• /
• 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.

• 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
• /
• 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 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.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.15
• /
• pp.6605-6608
• /
• 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.

• 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.

• 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.

• IE interfaces
• /
• v.20 no.4
• /
• pp.488-497
• /
• 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.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.6
• /
• pp.1058-1062
• /
• 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.