A Data-Mining Framework for Transnational Healthcare System

Shen, Chia-Ping; Jigjidsuren, Chinburen; Dorjgochoo, Sarangerel; Chen, Chi-Huang; Chen, Wei‐Hsin; Hsu, Chih-Kuo; Wu, Jin-Ming; Hsueh, Chih-Wen; Lai, Mei‐Shu; Tan, Cui; Altangerel, Erdenebaatar; Lai, Feipei

doi:10.1007/s10916-011-9729-7

Cited by 17 publications

(13 citation statements)

References 20 publications

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“…They mention that data mining models and results might be shared between different hospitals over a cloud-based server. Nevertheless the authors equal cloud computing with the Internet in general [ 68 ].…”

Section: Resultsmentioning

confidence: 99%

“…a physical network of many computers [ 5 , 26 , 77 , 84 ]. In five papers the cloud is even equated with the Internet in general [ 8 , 9 , 68 , 71 , 102 ].…”

Section: Resultsmentioning

confidence: 99%

“…Patients are mainly focused in projects on personal healthcare management [ 16 , 19 , 22 , 29 , 36 - 43 , 49 , 96 ]. Medical researchers should be enabled to access large pools of data for medical research purposes [ 18 , 30 , 35 , 57 , 65 , 66 , 68 , 69 ], whereas programmers and hospital IT staff should be enabled to work on the creation of cloud-based solutions [ 8 , 34 , 53 , 62 , 93 , 95 ].…”

Section: Resultsmentioning

confidence: 99%

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A scoping review of cloud computing in healthcare

Griebel

Prokosch

Köpcke

et al. 2015

BMC Med Inform Decis Mak

191

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BackgroundCloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an “OMICS-context”, e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain.MethodsMEDLINE was searched in July 2013 and in December 2014 for publications containing the terms “cloud computing” and “cloud-based”. Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings.Results102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated.ConclusionsEven though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term “cloud” synonymously for “using virtual machines” or “web-based” with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-015-0145-7) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

“…a physical network of many computers [ 5 , 26 , 77 , 84 ]. In five papers the cloud is even equated with the Internet in general [ 8 , 9 , 68 , 71 , 102 ].…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A scoping review of cloud computing in healthcare

Griebel

Prokosch

Köpcke

et al. 2015

BMC Med Inform Decis Mak

191

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“…A sizable amount ($37.6 billion) of healthcare costs is attributable to medical errors, 45% of which stems from preventable errors [ 95 ]. To aid in physician decision-making and reduce medical errors, researchers [ 95 ] proposed a data mining-based framework-Sequential Clustering Algorithm.…”

Section: Application Of Analytics In Healthcarementioning

confidence: 99%

A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining

et al. 2018

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The growing healthcare industry is generating a large volume of useful data on patient demographics, treatment plans, payment, and insurance coverage—attracting the attention of clinicians and scientists alike. In recent years, a number of peer-reviewed articles have addressed different dimensions of data mining application in healthcare. However, the lack of a comprehensive and systematic narrative motivated us to construct a literature review on this topic. In this paper, we present a review of the literature on healthcare analytics using data mining and big data. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a database search between 2005 and 2016. Critical elements of the selected studies—healthcare sub-areas, data mining techniques, types of analytics, data, and data sources—were extracted to provide a systematic view of development in this field and possible future directions. We found that the existing literature mostly examines analytics in clinical and administrative decision-making. Use of human-generated data is predominant considering the wide adoption of Electronic Medical Record in clinical care. However, analytics based on website and social media data has been increasing in recent years. Lack of prescriptive analytics in practice and integration of domain expert knowledge in the decision-making process emphasizes the necessity of future research.

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“…It is important to note that only 12 papers [3,22,52,60,73,93,96,119,120,124,143,170] state that their research/product was implemented/informed policythis is only 6.9% of the papers surveyed. Previous reviews have found similar results in regards to implementation (e.g.…”

Section: Obtaining the Pathwaymentioning

confidence: 99%

Clinical pathway modelling: a literature review

2019

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Hospital information systems are increasingly used as part of decision support tools for planning at strategic, tactical and operational decision levels. Clinical pathways are an effective and efficient approach in standardising the progression of treatment, to support patient care and facilitate clinical decision making. This literature review proposes a taxonomy of problems related to clinical pathways and explores the intersection between Information Systems (IS), Operational Research (OR) and industrial engineering. A structured search identified 175 papers included in the taxonomy and analysed in this review. The findings suggest that future work should consider industrial engineering integrated with OR techniques, with an aim to improving the handling of multiple scopes within one model, while encouraging interaction between the disjoint care levels and with a more direct focus on patient outcomes. Achieving this would continue to bridge the gap between OR, IS and industrial engineering, for clinical pathways to aid decision support.

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A Data-Mining Framework for Transnational Healthcare System

Cited by 17 publications

References 20 publications

A scoping review of cloud computing in healthcare

A scoping review of cloud computing in healthcare

A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining

Clinical pathway modelling: a literature review

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