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Record W1983761597 · doi:10.2196/medinform.3699

Information Persistence Services Designed to Support Home Care

2015· article· en· W1983761597 on OpenAlexvenueno aff
Nelson Pacheco Rocha, Alexandra Queirós, Filipe Augusto, Yosvany Llerena Rodríguez, Carlos Cardoso, José Miguel Grade, João Quintas

Bibliographic record

VenueJMIR Medical Informatics · 2015
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careDocumentationContext (archaeology)eHealthNursingInstitutionalisationKnowledge managementBusinessMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Due to the challenges faced by health and social care systems, in particular those related to actual demographic trends, home care emerges as a potentially cost-effective solution to answer the needs of citizens, and to allow the reallocation of resources to alternatives to hospitalization or institutionalization. OBJECTIVE: Home care services require cooperation between different actors, including health and social caregivers, care receivers, and their informal caregivers (eg, relatives or friends), across time, space, and organizational boundaries. Therefore, it is foreseeable that eHealth services can contribute to their improvement. The aim of this study is to evaluate information persistence services based on the Reference Information Model (RIM) of the Health Level Seven (HL7) version 3 to support formal caregivers, both health and social care providers, and informal caregivers in the context of home care services. METHODS: A pilot study was set up involving two Portuguese institutions that provide home care services for the elderly. Defining of information requirements was performed according to a comprehensive process. This included a review of the literature, observations of work activities, interviews with caregivers, care receivers and their relatives, analysis of paper documentation related to care receivers' histories, health conditions and care plans, and brainstorming groups involving specialized professionals. Following this, information objects were implemented and validated. RESULTS: The methodological approach, as well as the information persistence services, proved to be robust and adequate to specify, implement, and validate different types of information objects related to home care services for the elderly. This study also reinforces the application of the RIM of the HL7 version 3 beyond the strict scope of health care, allowing the persistence of not only health care information, but also information related to social assistance activities. CONCLUSIONS: This study contributes to the ongoing efforts related to the development of eHealth applications to improve the cooperation among formal health care and social caregivers, as well as care receivers and their informal caregivers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.023
GPT teacher head0.318
Teacher spread0.295 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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