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Record W2059346558 · doi:10.1504/ijeb.2004.006129

E-health: applying business process reengineering principles to healthcare in Canada

2004· article· en· W2059346558 on OpenAlexafffundabout
Michael Bliemel, Khaled Hassanein

Bibliographic record

VenueInternational Journal of Electronic Business · 2004
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of Waterloo
KeywordsBusiness process reengineeringHealth careProcess (computing)Business processProcess managementBusinessKey (lock)Healthcare deliverySet (abstract data type)Computer scienceRisk analysis (engineering)Knowledge managementComputer securityWork in processMarketingPolitical science

Abstract

fetched live from OpenAlex

Healthcare in Canada is facing many problems. The most publicised symptoms are excessive waiting times for patients, lack of access, high cost of delivery and medical errors. e-Health has been introduced as a potential solution for such problems. This research will explore the area of e-health and the technologies as well as the concepts that are included under its large umbrella. Bearing in mind that e-health is more than a set of technological applications, a business process reengineering (BPR) framework will be used to examine the application of particular BPR principles to address specific problems that are plaguing the Canadian healthcare system. The framework identifies the e-health technologies and processes that could best support the effective application of these BPR principles within a healthcare environment, as well as the key barriers impeding their implementation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.387
Teacher spread0.350 · 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 teacher head, not a consensus.

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

Citations35
Published2004
Admission routes3
Has abstractyes

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