• Convergence Security Journal
• /
• v.11 no.3
• /
• pp.39-46
• /
• 2011

Smart environment of health information technology, u-Healthcare architecture, ad-hoc networking and wireless communications environment are major factors that increase vulnerability of u-healthcare information systems. Traffic domain is the concept of network route that identifies the u-Healthcare information systems area as the traffic passing and security technologies application. The criterion of division is an area requiring the application of security technology. u-Healthcare information system domains are derived from the intranet section. the public switched network infrastructure, and networking sectors. Domains of health information systems are separated by domain vulnerability reason. In this study, domain-specific security vulnerability assessment system based on the USN in u-Healthcare system is derived. The model used in this study suggests how to establish more effective measurement USN-based health information network security vulnerability which has been vague until now.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2007.05a
• /
• pp.84-102
• /
• 2007

Security is crucial for the successful deployment of large distributed systems. Many of these systems provide services to people across different administrative domains. The traditional identity-based access control mechanisms are un scalable and difficult to manage. Unlike the closed systems, open systems provide services to people from different security domains. Healthcare systems need to be highly available in order for the patients to get a timely treatment. The health care information should be available to authorized users both inside the administrative domain and outside the domain, such as pharmacies and insurance companies. In this paper, we first analyzed the necessities and advantages of importing attribute-based trust-management models into open distributed systems. Then we reviewed traditional access-control models and presented the basic elements of the new trust-management model.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.9
• /
• pp.3933-3938
• /
• 2014

Background: Assessment of supportive needs is the requirement to plan any supportive care program for cancer patients. There is no evidence about supportive care needs of Iranian breast cancer patients. So, the aims of present study were to investigate this question and s predictive factors. Materials and Methods: A descriptive-correlational study was conducted, followed by logistic regression analyses. The Supportive Care Needs Survey was completed by 136 breast cancer patients residing in Iran following their initial treatment. This assessed needs in five domains: psychological, health system and information, physical and daily living, patient care and support, and sexuality. Results: Patient perceived needs were highest in the health systems and information (71%), and physical and daily living (68%) domains. Logistic regression modeling revealed that younger participants have more un-met needs in all domains and those with more children reported fewer un-met needs in patient care and support domains. In addition, married women had more un-met supportive care needs related to sexuality. Conclusions: The high rate of un-met supportive care needs in all domains suggests that supportive care services are desperately required for breast cancer patients in Iran. Moreover, services that address informational needs and physical and daily living needs ought to be the priority, with particular attention paid to younger women. Further research is clearly needed to fully understand supportive care needs in this cultural context.

• The Journal of the Korean dental association
• /
• v.57 no.9
• /
• pp.504-513
• /
• 2019

Dental education is gradually transitioning to competency-based education system, which aims to help dentists achieve certain core competencies by means of various systems, such as curriculum accreditation. This study examined satisfaction with dental school education and the differences in the perceived importance and self-assessment of competencies among general dentists, in an attempt to propose a desirable direction for dental education. A questionnaire was administered to new general dentists who graduated from a dental school within the past 10 years. The results of the survey were analyzed using the Importance-Performance Analysis to understand differences in dentists' perceptions. Overall satisfaction with education was low in terms of the curriculum's relevance to actual practice and its capacity for cultivating required competencies. Furthermore, many of the respondents strongly perceived the need to improve dental education. Additional investigations into the satisfaction with education showed no difference. Among the seven key competency domains, dentists perceived Health Promotion to be important and also assessed themselves as having high competence. However, regarding the perceived importance of the remaining domains, self-assessment of competence was low for Professionalism, Communication & Interpersonal Skills, Knowledge Base, Information Handling & Critical Thinking, Clinical Information Gathering, Diagnosis & Treatment Planning, and Establishment & Maintenance of Oral Health. The results of this study suggest that a competency-based education model should be developed and incorporated into dental education to set performance standards and to promote systematic self-assessment in order to foster the development of competence in dental students.

• Genomics & Informatics
• /
• v.11 no.4
• /
• pp.186-190
• /
• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• Communications of the Korean Institute of Information Scientists and Engineers
• /
• v.35 no.7
• /
• pp.9-25
• /
• 2017

In this paper, we surveyed state-of-the-art health and wellness platforms. The motivation of this paper is to review the state-of-the-art health and wellness platforms and their maturity with respect to adoption of latest enabling technologies. The is review is classified into four categories: healthcare systems, AI-assisted healthcare, wellness platforms, and open source health and wellness initiatives. From this comprehensive review, it can be stated that the contemporary healthcare systems are well-adopting wellness due to the concentration shift towards prevention. Thus, the gap between health and wellness is slowly yet carefully entering gray area. Where both the domains can freely invoke each other's services, and supporting enabling technologies. Furthermore, the biomedical researchers and physicians are no longer carrying the myopic views of trusting their knowledge for diagnosis. AI-assisted technologies based on machine learning and big data are influencing today's prognosis with trust and confidence.

• Asia pacific journal of information systems
• /
• v.24 no.3
• /
• pp.345-370
• /
• 2014

The notion of technological adoption such as Radio Frequency Identification (RFID) has been examined in various domains such as supply chain management, inventory management and health care. However, there are several unanswered questions surrounding how this technology is adopted in disaster management. This study attempts to explore the potential of RFID in disaster management. The notion of Task-Technology Fit (TTF) is deemed suitable for this purpose and thus used as the theoretical framework that is further validated by employing multiple case studies. The empirical findings indicate that there are six key factors influencing the decision to adopt RFID in disaster management. Some relate to aspects of RFID when it is put into practice, namely cost, compatibility, standardisation, implementation and locatability; while the other key factor relates to privacy and security aspect of information. It is hoped that the findings of this research will inform disaster management organizations to better plan the adoption of RFID for their operations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.10
• /
• pp.1830-1840
• /
• 2011

CDISC (Clinical Data Interchanging Standards Consortium) standards are to support the acquisition, exchange, submission and archival of clinical trial and research data. SDTM (Study Data Tabulation Model) for Case Report Forms (CRFs) was recommended for U.S. Food and Drug Administration (FDA) regulatory submissions since 2004. Although the SDTM Implementation Guide gives a standardized and predefined collection of submission metadata 'domains' containing extensive variable collections, transforming CRFs to SDTM files for FDA submission is still a very hard and time-consuming task. For addressing this issue, we developed metadata based SDTM mapping rules. Using these mapping rules, we also developed a semi-automatic tool, named CDISC Transformer, for transforming clinical trial data to CDISC standard compliant data. The performance of CDISC Transformer with or without MDR support was evaluated using CDISC blank CRF as the 'gold standard'. Both MDR and user inquiry-supported transformation substantially improved the accuracy of our transformation rules. CDISC Transformer will greatly reduce the workloads and enhance standardized data entry and integration for clinical trial and research in various healthcare domains.

• Journal of the Korea Convergence Society
• /
• v.6 no.6
• /
• pp.81-86
• /
• 2015

The threats to privacy and security have received increasing attention as ubiquitous healthcare applications over the Internet become more prevalent, mobile and universal. In particular, we address the communication security issues of access sharing of health information resources in the ubiquitous healthcare environment. The proposed scheme resolves the sender and data authentication problem in information systems and group communications. We propose a novel key management scheme for generating and distributing cryptographic keys to constituent users to provide form of data encryption method for certain types of data concerning resource constraints for secure communications in the ubiquitous healthcare domains.

• Research in Community and Public Health Nursing
• /
• v.28 no.4
• /
• pp.513-523
• /
• 2017

Purpose: We evaluated the psychometric properties of a questionnaire on the acceptance of the quality improvement information system (QIIS) among long-term care workers (mostly nurses). Methods: The questionnaire composes of 21 preliminary questions with 5 domains based on the Technology Acceptance Model and related literature reviews. We developed a prototype web-based comprehensive resident assessment system, and collected data from 126 subjects at 75 long-term care facilities and hospitals, who used the system and responded to the questionnaire. A priori factor structure was developed using an exploratory factor analysis and validated by a confirmatory factor analysis; its reliability was also evaluated. Results: A total of 16 items were yielded, and 5 factors were extracted from the explanatory factor analysis: Usage Intention, Perceived Usefulness, Perceived Ease of Use, Social Influence, and Innovative Characteristics. The five-factor structure model had a good fit (Tucker-Lewis index [TLI]=.976; comparative fit index [CFI]=.969; standardized root mean squared residual [SRMR]=.052; root mean square error of approximation [RMSEA]=.048), and the items were internally consistent(Cronbach's ${\alpha}=.91$). Conclusion: The questionnaire was valid and reliable to measure the technology acceptance of QIIS among long-term care workers, using the prototype.