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Record W2316623747 · doi:10.12927/hcpol.2016.24536

Impact of Type of Medical Specialist Involvement in Chronic Illness Care on Emergency Department Use

2016· article· en· W2316623747 on OpenAlexafffundvenue
Jean-Louis Larochelle, Debbie Ehrmann Feldman, Jean‐Frédéric Lévesque

Bibliographic record

VenueHealthcare policy · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsMedicineEmergency departmentPrimary careEmergency medicinePulmonary diseaseType 2 diabetesLogistic regressionDiabetes mellitusFamily medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: Medical specialist physicians may act as either consultants or co-managers for patients managed in primary care settings. We assessed whether the type of specialist involvement affected emergency department (ED) use for patients with chronic diseases. METHODS: In total, 709 primary care patients with arthritis, chronic obstructive pulmonary disease, diabetes or congestive heart failure were followed for one year using survey and administrative data. Multivariate logistic regressions were used to compare all-cause ED use according to specialist involvement (none, co-manager or consultant). RESULTS: In total, 240 (34%) patients visited the ED. ED use did not differ between those with specialist involvement and those without it, either as co-managers (adjusted OR = 1.06, 95% CI = [0.61, 1.85]) or consultants (adjusted OR = 0.97, 95% CI = [0.63, 1.50]). DISCUSSION: The type of specialist involvement is not associated with all-cause ED use in primary care patients with chronic diseases. Indications for co-management should be further 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.384
Teacher spread0.320 · 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 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

Citations2
Published2016
Admission routes3
Has abstractyes

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