An Integrated Medical Information System Using XML

Ahn, Cheolbum; Nah, Yunmook; Park, Seunghun; Kim, Jung-Sun

doi:10.1007/3-540-47749-7_25

Cited by 7 publications

(3 citation statements)

References 1 publication

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“…These information systems are classified according to place they are used and the type of data stored. Generally they are classified as Hospital Information Systems (HIS), Radiology Information Systems (RIS), Laboratory Information Systems (LIS), Picture Archiving and Communication System (PACS) and so on [18]. All these systems are centralized stand-alone systems, so they work independently from each other.…”

Section: Integration Of Medical Databasesmentioning

confidence: 99%

Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

Atilgan

Dogan

2009

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. As computerization in healthcare services increase, the amount of available digital data is growing at an unprecedented rate and as a result healthcare organizations are much more able to store data than to extract knowledge from it. Today the major challenge is to transform these data into useful information and knowledge. It is important for healthcare organizations to use stored data to improve quality while reducing cost. This paper first investigates the data mining applications on centralized medical databases, and how they are used for diagnostic and population health, then introduces distributed databases. The integration needs and issues of distributed medical databases are described. Finally the paper focuses on data mining studies on distributed medical databases.

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Section: Integration Of Medical Databasesmentioning

confidence: 99%

Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

Atilgan

Dogan

2009

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…As health care systems are expanding, digital data is also increasing. These systems are grouped based on their location, and the sort of data stored in them; such as Hospital Information Systems (HIS), Radiology Information Systems (RIS), Laboratory Information Systems (LIS) and Picture Archiving & Communication System (PACS) [21]. Even with the advantages of EHRs in disease diagnosis and prediction, they are still not widely adopted by physicians [22].…”

Section: Related Researchmentioning

confidence: 99%

An Efficient Association Rule Mining From Distributed Medical Databases for Predicting Heart Diseases

et al. 2021

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Electronic Health Records (EHRs) are aggregated, combined and analyzed for suitable treatment planning and safe therapeutic procedures of patients. Integrated EHRs facilitate the examination, diagnosis and treatment of diseases. However, the existing EHRs models are centralized. There are several obstacles that limit the proliferation of centralized EHRs, such as data size, privacy and data ownership consideration. In this paper, we propose a novel methodology and algorithm to handle the mining of distributed medical data sources at different sites (hospitals and clinics) using Association Rules. These medical data resources cannot be moved to other network sites. Therefore, the desired global computation must be decomposed into local computations to match the distribution of data across the network. The capability to decompose computations must be general enough to handle different distributions of data and different participating nodes in each instance of the global computation. In the proposed methodology, each distributed data source is represented by an agent. The global association rule computation is then performed by the agent either exchanging some minimal summaries with other agents or travelling to all the sites and performing local tasks that can be done at each local site. The objective is to perform global tasks with a minimum of communication or travel by participating agents across the network, this will preserve the privacy and the security of the local data. The proposed association rule mining methodology will be used for heart disease prediction using real heart disease data. These real data exist at different clinics and cannot be moved to a central site. The proposed model protects the patient data privacy and achieves the same results as if the data are moved and joined at a central site. We also validate the extracted association rules from all the data providers using an independent test datasets.INDEX TERMS Association rules, medical distributed databases, electronic health care records, agents, data privacy.

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“…Besides that, there are many studies related to the HISs as medical informatization spreads rapidly. Particularly, research in Korea has tended to focus on the technological aspects of HIS design and realization [21,22,23,24,25,26,27], privacy protection and system security [26,28,29,30,31], system standardization [32,33,34] and, more recently, the integration of HISs [22,35,36,37,38,39]. Though there are many forms of relevant research, few studies related to the users’ attitudes towards or perceptions of the HISs have been conducted.…”

Section: Introductionmentioning

confidence: 99%

Current Status of the Adoption, Utilization and Helpfulness of Health Information Systems in Korea

Seo¹,

Kim²,

Kim

2019

IJERPH

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As interest in medical informatization has been increasing steadily worldwide, the adoption of health information systems (HISs) in medical institutions is essential. In this study, we intended to identify users’ adoption, utilization and helpfulness derived from HISs to determine the status of medical informatization by using 2016 Korean Physician Survey data. A total of 8564 members responded to the 2016 survey, we extracted the data of 6949 HISs related part for this study. As a result, about 68% of the self-employed physicians adopted the Order Communication System and Electronic Medical Records, while only one-third adopted the Picture Archiving and Communication System. Overall, the proportions of utilization and helpfulness of HISs were higher for females; for employed physicians or professors; for physicians working in hospitals; and for those specializing in surgical medicine. As applying information technology to the medical environment becomes more important, HIS will become a necessary requirement and the demand for information systems considering user and patient oriented information environments will be increasing. Therefore, it is necessary to discuss the HISs use environment considering not only technical aspects but also users’ or patients’ viewpoints. In that respect, this study will give a meaningful evidence of HIS related policies.

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An Integrated Medical Information System Using XML

Cited by 7 publications

References 1 publication

Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

An Efficient Association Rule Mining From Distributed Medical Databases for Predicting Heart Diseases

Current Status of the Adoption, Utilization and Helpfulness of Health Information Systems in Korea

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