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Record W2463719334 · doi:10.3233/978-1-58603-979-0-93

Technical and Architectural Issues in Deploying Electronic Health Records (EHRs) over the WWW

2009· article· en· W2463719334 on OpenAlexaff
Brian Armstrong, André Kushniruk, Elizabeth M. Borycki

Bibliographic record

VenueStudies in health technology and informatics · 2009
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHealth recordsElectronic health recordComputer scienceData scienceWorld Wide WebInternet privacyHealth carePolitical science

Abstract

fetched live from OpenAlex

In this paper technical and architectural issues are described in deploying electronic health records (EHRs) over the WWW. The project described involved deployment of EHRs that have been designed to serve in the education of health professionals and health/biomedical informaticians. In order to allow for ubiquitous access to a range of EHRs remotely an architecture was designed with three layers: (a) the "Internet" or remote user access layer (2) the "Perimeter Network", or middle firewall security and authentication layer (3) the "HINF EHR Network", consisting of the internal servers hosting EHR applications and databases. The approaches allow for a large number of remote users running a range of operating systems to access the educational EHRs from any location remotely. Virtual machine (VM) technology is employed to allow multiple versions and platforms of operating systems to be installed side-by-side on a single server. Security, technical and budgetary considerations are described as well as past and current applications of the architecture for a number of projects for the education of health professionals in the area of electronic health records.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.359
Teacher spread0.331 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations12
Published2009
Admission routes1
Has abstractyes

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