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Classification of Emergency Departments According to Their Services for Community‐dwelling Seniors

2012· article· en· W1541504392 on OpenAlexafffundabout
Roxane Borgès Da Silva, Jane McCusker, Danièle Roberge, Antonio Ciampi, Jean‐Frédéric Lévesque, Éric Belzile

Bibliographic record

VenueAcademic Emergency Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsMcGill UniversityHôpital Charles-Le MoyneInstitut National de Santé Publique du QuébecMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineSample (material)Community organizationCommunity serviceGerontologyPublic relations

Abstract

fetched live from OpenAlex

OBJECTIVES: The goal was to develop a classification of emergency departments (EDs) based on their organization of services for seniors discharged to the community. METHODS: This was a secondary analysis of data collected in a survey of key informants (chief physicians and head nurses) in EDs in Quebec on the organization of services for community-dwelling seniors discharged to the community. Organizational characteristics were classified a priori in the following three categories: 1) availability of human resources, 2) care processes, and 3) links to community services. A multifactorial analysis (MFA) was used to analyze the variables by category and globally, thus investigating not only the relationships between variables within each category, but also the relationships between different categories. The authors then proceeded to classify EDs using Ward's method (hierarchical ascendant classification) applied to reduced data dimensions. RESULTS: The sample consisted of 103 EDs. Analyses were carried out on data from the 68 (66%) of these EDs that supplied complete data. These 68 EDs did not differ in terms of their size or geographical location from the 35 other departments that supplied incomplete or no data. We identified three groups of EDs: most specialized (with regard to internal staff and care processes) and less community-oriented (n = 12), moderately specialized and less community-oriented (n = 28), and least specialized and more community-oriented (n = 28). CONCLUSIONS: This classification of EDs with respect to their organization of services for community-dwelling seniors may be helpful to those planning services, to decision-makers, and to researchers. The three groups of EDs identified in this study represent three types of organizations with differing assets and limitations. The generalizability of these groups to other settings and the implications for patient outcomes should be investigated.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.107
GPT teacher head0.398
Teacher spread0.291 · 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 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

Citations9
Published2012
Admission routes3
Has abstractyes

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