MétaCan
Menu
Back to cohort
Record W2903259819

Development of a Standard of Practice for Medical Device Preventive Maintenance in BC Hospitals

2005· article· en· W2903259819 on OpenAlexaff
Martin Poulin, Anthony Y. Chan

Bibliographic record

VenueCMBES Proceedings · 2005
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsBritish Columbia Institute of TechnologyIsland Health
Fundersnot available
KeywordsClinical engineeringPreventive maintenanceRanking (information retrieval)Medical deviceReliability engineeringMedicineOperations managementComputer scienceMedical emergencyRisk analysis (engineering)EngineeringHealth careBiomedical engineeringInformation retrieval
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the process to establish a recommended minimum standard of practice for medical device preventive maintenance (PM) and performance assurance (PA) inspections in B.C. hospitals. This is a project embarked by the Clinical Engineering Committee of B.C. (CECBC) in 2003/04 to assist biomedical engineering departments to assess their medical device PM/PA requirements. A simple ranking system based on risk and utilization of each type of medical device was developed as a first level criterion to determine PM/PA requirements. Based on this ranking system, each hospital region then reviewed their list of medical devices and assigned their own ranking scores and PM/PA intervals. The scores and intervals were reviewed by the CECBC to arrive at a consensus of the minimum mandatory and recommended PM/PA interval for each of the common device types. The result for this exercise is included in this paper. In addition, a list of essential PM/PA procedures for each device type is being developed as part of this 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)0.137
metaresearch head score (Gemma)0.194
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.726

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1370.194
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.005
Science and technology studies0.0050.003
Scholarly communication0.0110.004
Open science0.0070.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.003

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 head0.057
GPT teacher head0.466
Teacher spread0.408 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCMBES ProceedingsSame topicQuality and Safety in HealthcareFrench-language works237,207