A new proposal of quality indicators for clinical engineering

Rodríguez, Elena Urbaneja; Miguel, Angelimarie; Sanchez, Malhena; Tolkmitt, F.; Pozo, E.

doi:10.1109/iembs.2003.1280931

Cited by 8 publications

(5 citation statements)

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“…Methodology development must confront the critical phase by providing support for efficient corrective maintenance [3,4] by providing fast technical functionality recovery without affecting non critical phase activities.…”

Section: A Special Assistance Levels Definitionmentioning

confidence: 99%

A methodology aimed to guarantee technology continuity in health structures

Miniati

Dori

Iadanza

et al. 2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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In healthcare the importance of clinical continuity is essential for both patients life and health organization activity. Since technology continuity is having more and more importance for the service continuity, a correct management of medical devices must be guided by criteria that ensure its safe, appropriate and economical use through a well planned purchase, appropriate preventive and corrective maintenance Indeed, the aim of health technology managers is to optimize the integration of external interventions assistance and internal technical service to guarantee an efficient and cost-effective maintenance system. This paper proposes an innovative carefully thought methodology which is aimed to provide technological and procedural actions which offer support to decision makers in technology management regarding the implementation of continuity in medical services and response to technology failures and emergency events.

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Section: A Special Assistance Levels Definitionmentioning

confidence: 99%

A methodology aimed to guarantee technology continuity in health structures

Miniati

Dori

Iadanza

et al. 2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…Ordinary maintenance is suggested for devices where special continuity is not contextually requested [6] and shows a PI=0 and CI>0.99. Purchase is suggested when 0.95<CI<0.99 and PI>X p , where X p is defined as the corresponding "PI threshold" which defines a HIGH severity clinical risk deriving by the device failure.…”

Section: A Queueing Theory Based Model For Business Continuity In Hosmentioning

confidence: 99%

A queueing theory based model for business continuity in hospitals

Miniati

Cecconi

Dori

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Clinical activities can be seen as results of precise and defined events' succession where every single phase is characterized by a waiting time which includes working duration and possible delay. Technology makes part of this process. For a proper business continuity management, planning the minimum number of devices according to the working load only is not enough. A risk analysis on the whole process should be carried out in order to define which interventions and extra purchase have to be made. Markov models and reliability engineering approaches can be used for evaluating the possible interventions and to protect the whole system from technology failures. The following paper reports a case study on the application of the proposed integrated model, including risk analysis approach and queuing theory model, for defining the proper number of device which are essential to guarantee medical activity and comply the business continuity management requirements in hospitals.

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“…Regardless of the adopted data management architecture, data can be aggregated in different ways to answer to a wide range of queries. Numeric indexes have been proposed by the scientific community to monitor the performance of buildings so that quantitative analysis can be made for different healthcare facilities [14,15]. These Key Performance Indicators (KPIs) can be automatically calculated starting from these data.…”

Section: Introductionmentioning

confidence: 99%

An integrated custom decision-support computer aided facility management informative system for healthcare facilities and analysis

Iadanza

Luschi

2019

Health Technol.

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This article presents a Computer Aided Facility Management informative system which can output Key Performance Indicators and quantitative parameters about the analysed healthcare facility. The designed system is a self-sufficient application able to manage and analyse digital plans of hospital buildings with no need of third-party plugins or licenses. The system maps hospital’s inner organisation, destinations of use and environmental comforts giving quantitative, qualitative and graphical reports. The core database is linked to other existing hospital databases, so that the system can act as a central control cockpit. Outputs can be used by top-management and decisional staff as a decision-support tool in order to improve hospital’s structure and organisation and to reduce the major workflow risks. Furthermore, many plug-ins and modules have been developed through the years which can be easily linked to the main application thanks to its REST architecture, and which contribute to a complete analysis and management of the healthcare facilities.

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A new proposal of quality indicators for clinical engineering

Cited by 8 publications

References 0 publications

A methodology aimed to guarantee technology continuity in health structures

A methodology aimed to guarantee technology continuity in health structures

A queueing theory based model for business continuity in hospitals

An integrated custom decision-support computer aided facility management informative system for healthcare facilities and analysis

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