From data to decisions: introducing Knowledge Management to effect superior operations in a radiology department

Goodfellow, T.; Bali, Rajeev K.; Wickramasinghe, Nilmini; Naguib, R.N.G.

doi:10.1504/ijbet.2008.016960

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…Another goal of this system is to have available functionalities to improve patient care and administration, clinical decision-making, and to get an optimal use of the healthcare resources. Today, the discipline of 'Health Informatics' takes care of the design and implementation of this kind of systems including supporting tools, from the collection of clinical and administrative data, to their organisation, processing, integration, storage, distribution and management (Goodfellow et al, 2008). Here, the presented project is a complex information system, mainly devoted to cardiology and pneumology, which enhances the important role of contemporary Information and Communication Technologies (ICTs) for the management of information and how this can act as a foundation for a KM-based system, as also recently focused on other environments (Bali et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Models of information systems devoted to medical-imaging labs: an experience in the CNR Clinical Physiology Institute

Ferdeghini

Macerata

Benassi

2010

IJBET

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At the end of the 1990s, the SPERIGEST project, supported by the Italian Health Ministry, and fully developed at the Institute of Clinical Physiology, established an operative integrated clinical and healthcare information system. Continuously evolving and dynamically optimising procedures and protocols solve problems of: harmonisation of instrumentation of different brands; management of multimedia data provided by different medical imaging labs; satisfaction of both clinical and research needs; legal and economical requirements; user-friendship of the system. A ten years experience shows positive approach by medical and healthcare operators, coordinated activity, higher efficiency, simplified procedures, major concentration on medical decision-making.

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Section: Introductionmentioning

confidence: 99%

Models of information systems devoted to medical-imaging labs: an experience in the CNR Clinical Physiology Institute

Ferdeghini

Macerata

Benassi

2010

IJBET

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A knowledge-based primary care approach to increase breast screening attendance

Baskaran

Bali

Arochena

et al. 2009

IJBET

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Grid Technology

Monrad

Grid Technologies for E-Health

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The present chapter is about telemedicine, but not about software and hardware. It is about humanware. Telemedicine’s greatest problem is not to make the technology work. It is organizations and humans in organizations who will decide the future of telemedicine. Telemedicine is not just a simple success story and the diffusion of telemedicine has been slower than many expected. For the future of telemedicine, a shift in the way we think may be necessary. Few authors have focused on learning in telemedicine (with what is here considered as associated aspects: team organization; learning organizations; network organization). The learning potential connected to telemedicine is significant. Learning may constitute an important argument for telemedicine. In the present chapter, focus is on the role learning and collaboration may have for the future of telemedicine. To take the full advantage of the learning potential a higher volume of telemedicine is necessary, but this requires more organizational collaboration. Improved collaboration is obtainable by implementing collaboration measures. The chapter shows that focus on learning and collaboration may well be important for the future of telemedicine. It is recommended that managers lead change processes in their organizations, where the different aspects of importance for realization of learning benefits of telemedicine are treated. For telemedicine, it is important that future research includes: investigations on how to obtain learning benefits and which collaboration measures are relevant for the different telemedicine applications. Objectives of the present chapter are to propose: 1) more international research on learning in telemedicine (with mentioned associated aspects) and telemedicine collaboration problems and 2) to show the background for this proposal.

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From data to decisions: introducing Knowledge Management to effect superior operations in a radiology department

Cited by 3 publications

References 18 publications

Models of information systems devoted to medical-imaging labs: an experience in the CNR Clinical Physiology Institute

Models of information systems devoted to medical-imaging labs: an experience in the CNR Clinical Physiology Institute

A knowledge-based primary care approach to increase breast screening attendance

Grid Technology

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