Development of a Multi-Agent m-Health Application Based on Various Protocols for Chronic Disease Self-Management.

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.

Processing SPARQL queries with regular expressions in RDF databases.

BACKGROUND: As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. RESULTS: In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. CONCLUSIONS: Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Health level 7 development framework for medication administration.

We propose the creation of a standard data model for medication administration activities through the development of a clinical document architecture using the Health Level 7 Development Framework process based on an object-oriented analysis and the development method of Health Level 7 Version 3. Medication administration is the most common activity performed by clinical professionals in healthcare settings. A standardized information model and structured hospital information system are necessary to achieve evidence-based clinical activities. A virtual scenario is used to demonstrate the proposed method of administering medication. We used the Health Level 7 Development Framework and other tools to create the clinical document architecture, which allowed us to illustrate each step of the Health Level 7 Development Framework in the administration of medication. We generated an information model of the medication administration process as one clinical activity. It should become a fundamental conceptual model for understanding international-standard methodology by healthcare professionals and nursing practitioners with the objective of modeling healthcare information systems.

Development of an Integrated Biospecimen Database among the Regional Biobanks in Korea.

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.

Development of an HL7 interface engine, based on tree structure and streaming algorithm, for large-size messages which include image data.

A basic assumption of Health Level Seven (HL7) protocol is 'No limitation of message length'. However, most existing commercial HL7 interface engines do limit message length because they use the string array method, which is run in the main memory for the HL7 message parsing process. Specifically, messages with image and multi-media data create a long string array and thus cause the computer system to raise critical and fatal problem. Consequently, HL7 messages cannot handle the image and multi-media data necessary in modern medical records. This study aims to solve this problem with the 'streaming algorithm' method. This new method for HL7 message parsing applies the character-stream object which process character by character between the main memory and hard disk device with the consequence that the processing load on main memory could be alleviated. The main functions of this new engine are generating, parsing, validating, browsing, sending, and receiving HL7 messages. Also, the engine can parse and generate XML-formatted HL7 messages. This new HL7 engine successfully exchanged HL7 messages with 10 megabyte size images and discharge summary information between two university hospitals.

Correction: Value of Analog in Medicine: Digital Compromise to Teach Old-Timer New Trick.

[This corrects the article on p. 141 in vol. 21, PMID: 26279949.].

Development of Cell Phone Application for Blood Glucose Self-Monitoring Based on ISO/IEEE 11073 and HL7 CCD.

OBJECTIVES: The objectives of this research were to develop and evaluate a cell phone application based on the standard protocol for personal health devices and the standard information model for personal health records to support effective blood glucose management and standardized service for patients with diabetes. METHODS: An application was developed for Android 4.0.3. In addition, an IEEE 11073 Manager, Medical Device Encoding Rule, and Bluetooth Health Device Profile Connector were developed for standardized health communication with a glucometer, and a Continuity of Care Document (CCD) Composer and CCD Parser were developed for CCD document exchange. The developed application was evaluated by five healthcare professionals and 87 users through a questionnaire comprising the following variables: usage intention, effort expectancy, social influence, facilitating condition, perceived risk, and voluntariness. RESULTS: As a result of the evaluation of usability, it was confirmed that the developed application is useful for blood glucose self-monitoring by diabetic patients. In particular, the healthcare professionals stated their own views that the application is useful to observe the trends in blood glucose change through the automatic function which records a blood glucose level measured using Bluetooth function, and the function which checks accumulated records of blood glucose levels. Also, a result of the evaluation of usage intention was 3.52 ± 0.42 out of 5 points. CONCLUSIONS: The application developed by our research team was confirmed by the verification of healthcare professionals that accurate feedback can be provided to healthcare professionals during the management of diabetic patients or education for glucose management.

An efficient algorithm for updating regular expression indexes in RDF databases.

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.

Construction of the Nursing Diagnosis Ontology in Obstetric and Gynecologic Nursing Unit using Nursing Process and SNOMED CT.

PURPOSE: This study was performed to propose an ontology methodology based on standardized nursing process as framework in obstetric and gynecologic nursing practice. METHODS: The instrument used in this study was based on the nursing diagnosis classification established by North American Nursing Diagnosis Association (NANDA) (2009-2011), fifth edition of the Nursing Interventions Classification (NIC) (2008), forth edition of the Nursing Outcomes Classification (NOC) (2008) developed by Iowa State University and systematized nomenclature of medicine clinical terms (SNOMED CT). The nursing records data were collected from electronic medical records of one hospital from August to October 2010. RESULTS: One hundred and forty-one nursing diagnosis statements used in obstetric and gynecologic nursing unit were linked standardized nursing classifications and constructed nursing diagnosis ontology including interoperability. CONCLUSION: Not only will this result be helpful to complete nurse's lack of knowledge and experience, it will also help to determine nursing diagnosis logically by using standardized nursing process. It will be utilized as the method to construct ontology including interoperability in other nursing units. It will be presented nursing interventions according to nursing diagnosis and thus will be easier to establish nursing planning. This can provide immediate feedback of the nursing process application.

Design of activation functions for inference of fuzzy cognitive maps: application to clinical decision making in diagnosis of pulmonary infection.

OBJECTIVES: Fuzzy cognitive maps (FCMs) representing causal knowledge of relationships between medical concepts have been used as prediction tools for clinical decision making. Activation functions used for inferences of FCMs are very important factors in helping physicians make correct decision. Therefore, in order to increase the visibility of inference results, we propose a method for designing certain types of activation functions by considering the characteristics of FCMs. METHODS: The activation functions, such as the sinusoidal-type function and linear function, are designed by calculating the domain range of the functions to be reached during the inference process of FCMs. Moreover, the designed activation functions were applied to the decision making process with the inference of an FCM model representing the causal knowledge of pulmonary infections. RESULTS: Even though sinusoidal-type functions oscillate and linear functions monotonously increase within the entire range of the domain, the designed activation functions make the inference stable because the proposed method notices where the function is used in the inference. And, the designed functions provide more visible numeric results than do other functions. CONCLUSIONS: Comparing inference results derived using activation functions designed with the proposed method and results derived using activation functions designed with the existing method, we confirmed that the proposed method could be more appropriately used for designing activation functions for the inference process of an FCM for clinical decision making.

Development of an electronic claim system based on an integrated electronic health record platform to guarantee interoperability.

OBJECTIVES: We design and develop an electronic claim system based on an integrated electronic health record (EHR) platform. This system is designed to be used for ambulatory care by office-based physicians in the United States. This is achieved by integrating various medical standard technologies for interoperability between heterogeneous information systems. METHODS: The developed system serves as a simple clinical data repository, it automatically fills out the Centers for Medicare and Medicaid Services (CMS)-1500 form based on information regarding the patients and physicians' clinical activities. It supports electronic insurance claims by creating reimbursement charges. It also contains an HL7 interface engine to exchange clinical messages between heterogeneous devices. RESULTS: The system partially prevents physician malpractice by suggesting proper treatments according to patient diagnoses and supports physicians by easily preparing documents for reimbursement and submitting claim documents to insurance organizations electronically, without additional effort by the user. To show the usability of the developed system, we performed an experiment that compares the time spent filling out the CMS-1500 form directly and time required create electronic claim data using the developed system. From the experimental results, we conclude that the system could save considerable time for physicians in making claim documents. CONCLUSIONS: The developed system might be particularly useful for those who need a reimbursement-specialized EHR system, even though the proposed system does not completely satisfy all criteria requested by the CMS and Office of the National Coordinator for Health Information Technology (ONC). This is because the criteria are not sufficient but necessary condition for the implementation of EHR systems. The system will be upgraded continuously to implement the criteria and to offer more stable and transparent transmission of electronic claim data.

The Development of a Graphical User Interface Engine for the Convenient Use of the HL7 Version 2.x Interface 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.

An improved auto-generation system to obtain reference intervals for laboratory medicine.

OBJECTIVES: Reference values are highly required parameters for all tests in the clinical laboratory, and the supplementary provision of reliable reference intervals is an important task for both clinical laboratories and diagnostic test manufacturers. Despite the progress that has been made in the conceptual aspects of reference intervals, in practice their use is still not completely satisfactory. Most of the laboratories have used various methods to calculate statistic-based reference intervals, and they have mainly focused on extracted data, yet its use is considerably limited. We had to deal with the inconvenience of using a number of programs (SPSS or SAS, MS Excel) in order to calculate the results of reference intervals. METHODS: In order to obtain standardized reference intervals, we developed an integrated program that can calculate, by a nonparametric method, reference intervals with using the Clinical and Laboratory Standards Institute (CLSI) processes as its guideline. We also developed a grouping interface that enables users to customize classification of each group (age, gender, blood group, race, etc) when calculating reference intervals. RESULTS: To verify the developed program, we compared the reference intervals of the current data on 281 persons for 8 total areas, and the reference intervals were was already calculated beforehand with by using this new program. As a result, both results perfectly matched. CONCLUSIONS: This integrated program will be convenience for calculating reasonable values through continual datainspection at an inspection lab for calculating reference intervals. The newly developed program will improve the consistency and reliability of the statistics on reference intervals.

Proposed Algorithm with Standard Terminologies (SNOMED and CPT) for Automated Generation of Medical Bills for Laboratory Tests.

OBJECTIVES: In this study, we proposed an algorithm for mapping standard terminologies for the automated generation of medical bills. As the Korean and American structures of health insurance claim codes for laboratory tests are similar, we used Current Procedural Terminology (CPT) instead of the Korean health insurance code set due to the advantages of mapping in the English language. METHODS: 1,149 CPT codes for laboratory tests were chosen for study. Each CPT code was divided into two parts, a Logical Observation Identifi ers Names and Codes (LOINC) matched part (matching part) and an unmatched part (unmatched part). The matching parts were assigned to LOINC axes. An ontology set was designed to express the unmatched parts, and a mapping strategy with Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) was also proposed. Through the proceeding analysis, an algorithm for mapping CPT with SNOMED CT arranged by LOINC was developed. RESULTS: 75% of the 1,149 CPT codes could be assigned to LOINC codes. Two hundred and twenty-five CPT codes had only one component part of LOINC, whereas others had more than two parts of LOINC. The system of LOINC axes was found in 309 CPT codes, scale 555, property 9, method 42, and time aspect 4. From the unmatched parts, three classes, 'types', 'objects', and 'subjects', were determined. By determining the relationship between the classes with several properties, all unmatched parts could be described. Since the 'subject to' class was strongly connected to the six axes of LOINC, links between the matching parts and unmatched parts were made. CONCLUSIONS: The proposed method may be useful for translating CPT into concept-oriented terminology, facilitating the automated generation of medical bills, and could be adapted for the Korean health insurance claim code set.