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Home Care and Technology: A Case Study

2012· article· en· W139661178 on OpenAlexaff
Eleni Stroulia, Sharla King, Lysanne Lessard

Bibliographic record

VenueStudies in health technology and informatics · 2012
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWorkflowInformation and Communications TechnologySoftware deploymentSuiteHealth careProductivityKnowledge managementBusinessProcess managementComputer scienceWorld Wide WebSoftware engineering

Abstract

fetched live from OpenAlex

Health care aides (HCAs) are the backbone of the home care system and provide a range of services to people who, for various reasons related to chronic conditions and aging, are not able to take care of themselves independently. The demand for HCA services will increase and the current HCA supply will likely not keep up with this increasing demand without fundamental changes in the current environment. Information and communication technology (ICT) can address some of the workflow challenges HCAs face. In this project, we conducted an ethnographic study to document and analyse HCAs' workflows and team interactions. Based on our findings, we designed an ICT tool suite, integrating easily available existing and newly developed (by our team) technologies to address these issues. Finally, we simulated the deployment of our technologies, to assess the potential impact of these technological solutions on the workflow and productivity of HCAs, their healthcare teams and client care.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0080.003
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.088
GPT teacher head0.485
Teacher spread0.398 · 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 designCase report
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

Citations10
Published2012
Admission routes1
Has abstractyes

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