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Record W2095741694

Collaboration in caring for psychiatric inpatients: Family physicians team up with psychiatrists and psychiatric nurses.

2008· article· en· W2095741694 on OpenAlexaff
Dara Behroozi, Garey Mazowita, M. Duff Davis

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicinePsychological interventionPsychiatryProtocol (science)NursingFamily medicineHealth careAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED: The standard organization of psychiatric inpatient care at our hospital involved consultations with various specialist physicians visiting the psychiatry wards to assess patients' medical needs and to provide appropriate interventions. We thought that this type of clinical care pathway might not be leading to the best integration and timeliness of patient care, the most efficient use of specialist resources, or the least cost to the health care system. OBJECTIVE OF PROGRAM: To initiate a protocol that would involve an FP visiting all the psychiatry wards daily (on weekdays) to conduct medical consultations. We hoped this program would improve the timeliness and integration of patient care, reduce patients' length of stay in hospital, and alter the pattern of specialist consultations. PROGRAM DESCRIPTION: The FP consulted on patients referred by psychiatrists and registered psychiatric nurses; carried out assessments; initiated treatment of commonmedical problems; referred to other specialists when necessary; and made arrangements for follow-up care as appropriate. CONCLUSION: The FP consultations improved patient care in several ways, was highly valued by staff, and modified the pattern of specialist consultations on participatingpsychiatry wards.

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 score0.149
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.233
Teacher spread0.218 · 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

Citations8
Published2008
Admission routes1
Has abstractyes

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