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Objective In South Korea, the Gyeonggi Fire Services introduced a multi-tiered dispatch system for out-of-hospital cardiac arrest (OHCA) cases in July 2015. In this study, we investigated whether the multi-tiered dispatch system improved the pre-hospital return of the spontaneous circulation (ROSC) rate. Methods All non-traumatic adult OHCAs treated and transported by the 119 emergency medical system from July 2015 to December 2015 were included in the study. Demographic and pre-hospital Utstein element-data were collected from the emergency medical system OHCA database. The primary outcome was pre-hospital ROSC as measured at the scene. Results Of the included OHCAs, 1,436 (89.0%) were categorized to the single-tiered dispatch group and 162 (10.1%) to the multi-tiered dispatch group. The rate of administration of advanced airway ventilation (61.1% vs. 48.0%, P=0.002) and intravenous access (18.5% vs. 12.5%, P=0.037) was higher in the multi-tiered group compared to that in the single-tiered group. The use of epinephrine was higher in the multi-tiered group (4.9% vs. 1.5%, P=0.002). The pre-hospital ROSC rates in the multi-tiered group were higher when compared with the single-tiered group, but the difference was not significant (10.5% vs. 7.5%, P=0.218). The adjusted odds ratio for pre-hospital ROSC rates in the multi-tiered group was 1.29 (95% confidence interval, 0.69 to 2.40). Conclusion The multi-tiered dispatch system was not associated with a significant increase in the pre-hospital ROSC rate during the early phase of its implementation, even though advanced maneuvers were performed more frequently.

This study developed a nursing process database based on the object-oriented database model for the development of the nursing process computerization program. Received (September 15, 2015), Review Result(Octorber 02, 2015) Accepted(October 22, 2015), Published(December 31, 2015) 41156 Dept. of Medical Informatics, Kyungpook National Univ., 680, Gukchaebosang-ro, Jung-gu, Daegu, Korea email: phs510@naver.com 41156 Dept. of Medical Informatics, Kyungpook National Univ., 680, Gukchaebosang-ro, Jung-gu, Daegu, Korea email: medinfo@knu.ac.kr 27136 Dept. of Nursing, Semyung Univ., 65, Semyeong-ro, Jecheon-si, Chungcheongbuk-do, Korea email: ag392@naver.com (Corresponding Author) 38610 Faculty of Medical Industry Convergence, Daegu Haany Univ., 1, Hanuidae-ro, Gyeongsan-si, Gyeongsangbuk-do, Korea email: pulala@dhu.ac.kr Development and application of the nursing process database based on the object-oriented database model Copyright c 2015 HSST 168 The database coded the data of the North American Nursing Diagnosis Association (NANDA) 2015-2017, Nursing Outcomes Classification (NOC) 5th edition and Nursing Interventions Classification (NIC) 6th edition, and it produced the appropriate entities based on the class diagram to design data structure in an object-oriented perspective. The nursing process database is composed of classification systems, patient information and nursing process, user information entities, and it has the separate structure that all of the information is dependent on user and patient information entity. That is, the database developed can integrate and develop the computerized program without a separate process by resetting only the relationship between the core entities. In order to take advantage of these object-oriented database model, this study developed a part of the nursing process education program by using the Java programming language, Java Swing, JDBC Connector. The further studies are scheduled to develop the complete program which includes standard protocol transfer function for the standardization of nursing practice, the interoperability between other information systems, and the nursing process macro function.

With the shift from an industry-based society to a knowledge-based one, there has been a gradual increase in the importance of intangible assets such as technologies and information. Patents are a representative intellectual outcome of intangible assets and can be used as an objective measure of the level of technology or innovation of individuals, firms, and countries. In addition, patents can be regarded as a rich source of data for the provision of technological and commercial information. Patent data facilitate research on technological advances and innovation; hence, an analysis of this data can provide important insights into innovation activity and technology management strategies. This paper presents a method for extracting core technologies from core fuel cell vehicle (FCV) patents registered with the United States Patent and Trademark Office by using a data mining technique. Core patents are determined by analyzing patent citations, and the data mining technique identifies those firms with core FCV technologies and reveals the overall research focus of the firms by deriving patent portfolios and and technology recommendations considering the extracted core technologies.

The existing Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) toolkit includes only a clinical term search, and its output functions are not linked to a particular database, making it difficult for users to map biological data, and the use of biobanks requires much time and effort. This study developed a SNOMED-CT toolkit using an optimized search, allowing users to map clinical items for efficient utilization and standardization of biobank resources. The toolkit was developed using the Java programming language and Java Database Connectivity to connect to a previously developed research database. The user interface was implemented using Swing. The functions and interfaces of the toolkit were developed after a requirement analysis by SNOMED-CT experts. Using the toolkit, the user can search SNOMED-CT concepts. Using pre-and post-coordinated mapping of clinical items with the toolkit, it is possible to maximize the semantic interoperability of the previously developed database.

The purpose of this study was to build Ontology based database for efficient operation and interoperability of the human resource bank. The team 7,197,252 of human resources information was collected through previous studies and classifies the 1,796 clinical item through high quality work. For a clear expression of clinical terminology mapping and item of international standard terminology Received (April 15, 2015), Review Request(April 16, 2015), Review Result(May 01, 2015) Accepted(May 21, 2015), Published(June 30, 2015) 700-842 Dept. of Medical Informatics, Kyungpook National Univ., Gukchaebosang-ro, Jung-gu, Deagu, Korea email: yth2320@naver.com 712-715 Dept. of Faculty of Medical Industry Convergence, Daegu Haany Univ., Yugok-dong, Gyeongsan-si, Gyeongsangbuk-do, Korea email: daspula@daum.net (Corresponding Author) 700-842 Dept. of Medical Informatics, Kyungpook National Univ., Gukchaebosang-ro, Jung-gu, Deagu, Korea email: medinfo@knu.ac.kr Study on OWL-based database built for the efficient operation of human resources bank Copyright c 2015 HSST 56 SNOMED-CT it was found to have 826 different synonyms of the term and value types, the data type for the international standard code. In this study, we selected a preferred term of 76 to minimize the redundancy due to the synonyms. Also define the relationship between synonyms and preferred terms using the OWL for interoperability between human resources banks and were stored in XML and databases. OWL-based database built in this study has a common terminology, it can be interchangeably without complex mapping process between the human resource banks.

The Resource Description Framework (RDF) is widely used for sharing biomedical data, such as gene ontology or the online protein database UniProt. SPARQL is a native query language for RDF, featuring regular expressions in queries for which exact values are either irrelevant or unknown. The use of regular expression indexes in SPARQL query processing improves the performance of queries containing regular expressions by up to two orders of magnitude. In this study, we address the update operation for regular expression indexes in RDF databases. We identify major performance problems of straightforward index update algorithms and propose a new algorithm that utilises unique properties of regular expression indexes to increase performance. Our contributions can be summarised as follows: (1) we propose an efficient update algorithm for regular expression indexes in RDF databases, (2) we build a prototype system for the proposed algorithm in C++ and (3) we conduct extensive experiments demonstrating the improvement of our algorithm over the straightforward approaches by an order of magnitude.

The purpose of this study was to develop and evaluate a mobile health application (Self-Management mobile Personal Health Record: "SmPHR") to ensure the interoperability of various personal health devices (PHDs) and electronic medical record systems (EMRs) for continuous self-management of chronic disease patients. The SmPHR was developed for Android 4.0.3, and implemented according to the optimized standard protocol for each interface of healthcare services adopted by the Continua Health Alliance (CHA). That is, the Personal Area Network (PAN) interface between the application and PHD implements ISO/IEEE 11073-20,601, 10,404, 10,407, 10,415, 10,417, and Bluetooth Health Device Profile (HDP), and EMRs with a wide area network (WAN) interface implement HL7 V2.6; the Health Record Network (HRN) interface implements Continuity of Care Document (CCD) and Continuity of Care Record (CCR). Also, for SmPHR, we evaluated the transmission error rate between the interface using four PHDs and personal health record systems (PHRs) from previous research, with 611 users and elderly people after receiving institutional review board (IRB) approval. In the evaluation, the PAN interface showed 15 (2.4 %) errors, and the WAN and HRN interface showed 13 (2.1 %) errors in a total of 611 transmission attempts. Also, we received opinions regarding SmPHR from 15 healthcare professionals who took part in the clinical trial. Thus, SmPHR can be provided as an interconnected PHR mobile health service to patients, allowing `plug and play' of PHDs and EMRs through various standard protocols.

Objectives This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. Methods We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. Results As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. Conclusions The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.