No abstract available.
Informatics

OBJECTIVES: This report describes the development process of a drug dosing database for ethical drugs approved by the Korea Food & Drug Administration (KFDA). The goal of this study was to develop a computerized system that supports physicians' prescribing decisions, particularly in regards to medication dosing. METHODS: The advisory committee, comprised of doctors, pharmacists, and nurses from the Seoul National University Bundang Hospital, pharmacists familiar with drug databases, KFDA officials, and software developers from the BIT Computer Co. Ltd. analyzed approved KFDA drug dosing information, defined the fields and properties of the information structure, and designed a management program used to enter dosing information. The management program was developed using a web based system that allows multiple researchers to input drug dosing information in an organized manner. The whole process was improved by adding additional input fields and eliminating the unnecessary existing fields used when the dosing information was entered, resulting in an improved field structure. RESULTS: A total of 16,994 drugs sold in the Korean market in July 2009, excluding the exclusion criteria (e.g., radioactivity drugs, X-ray contrast medium), usage and dosing information were made into a database. CONCLUSIONS: The drug dosing database was successfully developed and the dosing information for new drugs can be continually maintained through the management mode. This database will be used to develop the drug utilization review standards and to provide appropriate dosing information.
Advisory Committees ; Databases, Pharmaceutical ; Drug Utilization Review ; Humans ; Isothiocyanates ; Korea ; Pharmacists ; Radioactivity

OBJECTIVES: We were to analyze the effect of managing metabolic syndrome using a u-health service in a health center. METHODS: We collected biometric data from 316 subjects living in a county (gun) in South Korea before and after the introduction of uhealth services in 2010. Analysis was done by contingency table using SPSS and latent growth model using AMOS. RESULTS: We found that regional u-health services affected instance of metabolic syndrome. Further, biometrics and health behavior improved. After six months of u-health services, the number of subjects with three or more factors for metabolic syndrome decreased by 62.5%; 63.3% of regular drinkers stopped drinking; 83.3% of subjects who rarely exercised began to exercise twice a week or more; and 60.9% of smokers stopped smoking. CONCLUSIONS: U-health services can change health behavior and biometrics to manage metabolic syndrome in rural areas. The usefulness of u-health services is discussed.
Disease Management ; Health Behavior ; Republic of Korea

OBJECTIVES: In this study, we measured the extent of ten levels of classified symptoms by 300 (male and female) patients visiting the hair loss clinics of "S" hospitals in Gangbuk and Gangnam between January 2009 and June 2011 by analyzing the patients' chief complaints. METHODS: The method of measurement was based on a symptom questionnaire possessing 51 categories. Through the statistical analysis of data mining techniques, decision trees, and logistic regression, we derived a logistic regression model and decision tree model that improved both the response rate and significant hair loss-related characteristics of the questionnaire. RESULTS: The results of this study indicate that dry hair, seborrheic scalps and skin, tobacco and/or coffee addiction, anxiety, nausea, indigestion, and facial flushing correlate to hair loss. CONCLUSIONS: We anticipate that the subjective symptoms of hair loss can provide a foundation for preventing secondary diseases and provide clinical data information during the period of treatment. This can contribute to the improvement of patient satisfaction after customized treatment.
Alopecia ; Anxiety ; Coffee ; Data Mining ; Decision Trees ; Dyspepsia ; Flushing ; Hair ; Humans ; Logistic Models ; Nausea ; Patient Satisfaction ; Scalp ; Skin ; Tobacco ; Surveys and Questionnaires

OBJECTIVES: The aim of this study was to develop and validate Detailed Clinical Models (DCMs) for nursing assessments and interventions. METHODS: First, we identified the nursing assessment and nursing intervention entities. Second, we identified the attributes and the attribute values in order to describe the entities in more detail. The data type and optionality of the attributes were then defined. Third, the entities, attributes and value sets in the DCMs were mapped to the International Classification for Nursing Practice Version 2 concepts. Finally, the DCMs were validated by domain experts and applied to case reports. RESULTS: In total 481 DCMs, 429 DCMs for nursing assessments and 52 DCMs for nursing interventions, were developed and validated. The DCMs developed in this study were found to be sufficiently comprehensive in representing the clinical concepts of nursing assessments and interventions. CONCLUSIONS: The DCMs developed in this study can be used in electronic nursing records. These DCMs can be used to ensure the semantic interoperability of the nursing information documented in electronic nursing records.
Concept Formation ; Dietary Sucrose ; Electronics ; Electrons ; Nursing Assessment ; Nursing Process ; Nursing Records ; Semantics

OBJECTIVES: The intensive care environment generates a wealth of critical care data suited to developing a well-calibrated prediction tool. This study was done to develop an intensive care unit (ICU) mortality prediction model built on University of Kentucky Hospital (UKH)'s data and to assess whether the performance of various data mining techniques, such as the artificial neural network (ANN), support vector machine (SVM) and decision trees (DT), outperform the conventional logistic regression (LR) statistical model. METHODS: The models were built on ICU data collected regarding 38,474 admissions to the UKH between January 1998 and September 2007. The first 24 hours of the ICU admission data were used, including patient demographics, admission information, physiology data, chronic health items, and outcome information. RESULTS: Only 15 study variables were identified as significant for inclusion in the model development. The DT algorithm slightly outperformed (AUC, 0.892) the other data mining techniques, followed by the ANN (AUC, 0.874), and SVM (AUC, 0.876), compared to that of the APACHE III performance (AUC, 0.871). CONCLUSIONS: With fewer variables needed, the machine learning algorithms that we developed were proven to be as good as the conventional APACHE III prediction.
APACHE ; Critical Care ; Data Mining ; Decision Trees ; Demography ; Humans ; Intensive Care Units ; Kentucky ; Logistic Models ; Machine Learning ; Support Vector Machine

OBJECTIVES: An efficient clinical process guideline (CPG) modeling service was designed that uses an enhanced intelligent search protocol. The need for a search system arises from the requirement for CPG models to be able to adapt to dynamic patient contexts, allowing them to be updated based on new evidence that arises from medical guidelines and papers. METHODS: A sentence category classifier combined with the AdaBoost.M1 algorithm was used to evaluate the contribution of the CPG to the quality of the search mechanism. Three annotators each tagged 340 sentences hand-chosen from the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) clinical guideline. The three annotators then carried out cross-validations of the tagged corpus. A transformation function is also used that extracts a predefined set of structural feature vectors determined by analyzing the sentential instance in terms of the underlying syntactic structures and phrase-level co-occurrences that lie beneath the surface of the lexical generation event. RESULTS: The additional sub-filtering using a combination of multi-classifiers was found to be more effective than a single conventional Term Frequency-Inverse Document Frequency (TF-IDF)-based search system in pinpointing the page containing or adjacent to the guideline information. CONCLUSIONS: We found that transformation has the advantage of exploiting the structural and underlying features which go unseen by the bag-of-words (BOW) model. We also realized that integrating a sentential classifier with a TF-IDF-based search engine enhances the search process by maximizing the probability of the automatically presented relevant information required in the context generated by the guideline authoring environment.
Data Mining ; Humans ; Hypertension ; Imidazoles ; Joints ; Knowledge Bases ; Natural Language Processing ; Nitro Compounds ; Search Engine

OBJECTIVES: The Health Level Seven Interface Engine (HL7 IE), developed by Kyungpook National University, has been employed in health information systems, however users without a background in programming have reported difficulties in using it. Therefore, we developed a graphical user interface (GUI) engine to make the use of the HL7 IE more convenient. METHODS: The GUI engine was directly connected with the HL7 IE to handle the HL7 version 2.x messages. Furthermore, the information exchange rules (called the mapping data), represented by a conceptual graph in the GUI engine, were transformed into program objects that were made available to the HL7 IE; the mapping data were stored as binary files for reuse. The usefulness of the GUI engine was examined through information exchange tests between an HL7 version 2.x message and a health information database system. RESULTS: Users could easily create HL7 version 2.x messages by creating a conceptual graph through the GUI engine without requiring assistance from programmers. In addition, time could be saved when creating new information exchange rules by reusing the stored mapping data. CONCLUSIONS: The GUI engine was not able to incorporate information types (e.g., extensible markup language, XML) other than the HL7 version 2.x messages and the database, because it was designed exclusively for the HL7 IE protocol. However, in future work, by including additional parsers to manage XML-based information such as Continuity of Care Documents (CCD) and Continuity of Care Records (CCR), we plan to ensure that the GUI engine will be more widely accessible for the health field.
Antineoplastic Combined Chemotherapy Protocols ; Computer Graphics ; Continuity of Patient Care ; Dietary Sucrose ; Etoposide ; Health Information Systems ; Health Level Seven ; Ifosfamide ; Medical Informatics ; Software Design

OBJECTIVES: This study is aimed at developing a set of data groups (DGs) to be employed as reusable building blocks for the construction of the eight most common clinical documents used in China's general hospitals in order to achieve their structural and semantic standardization. METHODS: The Diagnostics knowledge framework, the related approaches taken from the Health Level Seven (HL7), the Integrating the Healthcare Enterprise (IHE), and the Healthcare Information Technology Standards Panel (HITSP) and 1,487 original clinical records were considered together to form the DG architecture and data sets. The internal structure, content, and semantics of each DG were then defined by mapping each DG data set to a corresponding Clinical Document Architecture data element and matching each DG data set to the metadata in the Chinese National Health Data Dictionary. By using the DGs as reusable building blocks, standardized structures and semantics regarding the clinical documents for semantic interoperability were able to be constructed. RESULTS: Altogether, 5 header DGs, 48 section DGs, and 17 entry DGs were developed. Several issues regarding the DGs, including their internal structure, identifiers, data set names, definitions, length and format, data types, and value sets, were further defined. Standardized structures and semantics regarding the eight clinical documents were structured by the DGs. CONCLUSIONS: This approach of constructing clinical document standards using DGs is a feasible standard-driven solution useful in preparing documents possessing semantic interoperability among the disparate information systems in China. These standards need to be validated and refined through further study.
Asian Continental Ancestry Group ; China ; Delivery of Health Care ; Electronic Health Records ; Health Level Seven ; Hospitals, General ; Humans ; Information Systems ; Semantics

OBJECTIVES: The purpose of this study was to examine the applicability of the International Organization for Standardization (ISO) reference terminology model for nursing to describe the terminological value domain content regarding the entities and attributes of the detailed clinical models (DCMs) used for nursing assessments. METHODS: The first author mapped 52 DCM entities and 45 DCM attributes used for perinatal care nursing assessments to semantic domains and their qualifiers to the ISO model. The mapping results of the entity and attribute concepts were classified into four categories: mapped to a semantic domain qualifier, mapped to a semantic domain, mapped to a broader semantic domain concept, and not mapped. The DCM mapping results were classified into three categories: fully mapped, partially mapped, and not mapped. The second author verified the mapping. RESULTS: All of the entities and 53.3% of the attribute concepts of the DCMs were mapped to semantic domains or semantic domain qualifiers of the ISO model, 37.8% of the attributes were mapped to the broader semantic domain concept, and 8.9% of the attributes were not mapped. At the model level, 48.1% of the DCMs were fully mapped to semantic domains or semantic domain qualifiers of the ISO model, and 51.9% of the DCMs were partially mapped. CONCLUSIONS: The findings of this study demonstrate that the ISO reference terminology model for nursing is applicable in representing the DCM structure for perinatal care nursing assessment. However, more qualifiers of the Judgment semantic domain are required in order to clearly and fully represent all of the entities and attributes of the DCMs used for nursing assessment.
Concept Formation ; Judgment ; Medical Records Systems, Computerized ; Nursing Assessment ; Perinatal Care ; Semantics