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Record W3143840993 · doi:10.1109/sehc.2012.6227001

A case study in interoperable support for collaborative community healthcare

2012· article· en· W3143840993 on OpenAlexafffund
Liam Peyton, Craig Kuziemsky, Dishant Langayan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInteroperabilityWorkflowSoftware deploymentOntologyHealth careComputer scienceWork (physics)Knowledge managementArchitectureInformation systemProcess managementEngineering managementSoftware engineeringEngineeringWorld Wide WebDatabase

Abstract

fetched live from OpenAlex

This paper describes a two year case study in the engineering and deployment of a Clinical Information System (CIS) called Palliative Care Information System (PAL-IS) for managing and monitoring team-based community care of palliative patients. The case study followed the methodology, architecture and ontology proposed in previous work to address workflow, behavioral and technology issues for CIS that support collaborative, mobile, and accessible healthcare. Both PAL-IS and the methodology used in its development are evaluated. The results give fresh insight into interoperability issues which complicate CIS design. They also highlight the importance of reporting requirements as a major driver for investment in CIS and a critical factor in CIS design.

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)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.285
GPT teacher head0.540
Teacher spread0.255 · 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 designQualitative
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

Citations4
Published2012
Admission routes2
Has abstractyes

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