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Record W1514692584 · doi:10.1108/tqm-01-2015-0017

Application of the IEC80001 standard towards integration of a real time alarm communication and management system

2015· article· en· W1514692584 on OpenAlexaffabout
Kyle Eckhardt, Andrew Hayes, Michael Hamilton, Tidimogo Gaamangwe

Bibliographic record

VenueThe TQM Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsResearch ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsWorkflowComputer scienceWorkgroupUsabilityStaffingRisk analysis (engineering)Scope (computer science)Risk managementProcess managementEngineering managementEngineeringBusinessMedicine

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to report on use of the IEC80001 standard, Application of Risk Management for Information Technolody (IT) Networks Incorporating Medical Devices, to deploy a wireless alarm management solution in a long-term care home facility. Design/methodology/approach – The standard suggests the use of a unique responsibility matrix and a continuous quality improvement approach for analysis, evaluation and control of risks. A unique leadership committee and workgroup were formed to develop processes and procedures for integrating medical devices with IT systems; as well as execution of the project itself. The leadership committee oversaw the phased approach of assessing the technology, the clinical environment, proponent technology-based solutions and a specified risk management file. The project expanded its scope beyond the standard to include a risk focussed analysis of clinical workflow to evaluate the usability of the solution. Findings – The standard focussed approach identified numerous risks associated with the technical and network solution and the future state workflow. Medical devices proved to be the most limiting technology needing to be incorporated into the solution. Although faced with a daunting list of network related risks, it was concluded that all residual risks would have been acceptable. The analysis of the future state workflow identified various risks related to usability (human factors), battery management and the absence of additional operating dollars for supplementary staffing duties and new operational expenses. Originality/value – To the best of the authors knowledge, this paper is the first one to detail the process of following the IEC80001 standard in Canada. It offers insight into building an organizational framework around the standard and identifies gaps that should be considered by executive and project sponsors before proceeding with a project.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.328
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes2
Has abstractyes

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