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Brief Report: Does Your Patient Know Your Name? An Approach to Enhancing Patients' Awareness of Their Caretaker's Name

2005· article· en· W2002790083 on OpenAlexaboutno aff
Amgad N. Makaryus, Eli A. Friedman

Bibliographic record

VenueJournal for Healthcare Quality · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsRecallMedicineQuarter (Canadian coin)Family medicinePediatricsPsychologyHistory

Abstract

fetched live from OpenAlex

This brief report determines whether patients admitted to a large teaching hospital knew the name of their caretaker (physician or nurse) and whether emphasis on patients' awareness of this name improved their recall. A survey of 100 patients on the internal medicine and neurology services at a large teaching hospital in BrookLyn, NY, was conducted. A derivative survey was also conducted on 30 different patients to see whether caretaker name recall was enhanced after the patients were advised of the importance of remembering this name. Of patients initially tested, 14.7% correctly stated their physician's name, and 21.3% correctly stated their nurse's name (p < 0.3). After being given the name of their physician in writing and being asked to remember it, 76.2% of a different group of patients correctly stated their physician's name. Less than a quarter of the patients initiaLLy surveyed were able to state either their physician's or nurse's name. However, after a specific effort to have a smaller group of patients remember their physician's name, more than 75% did so. Therefore, it was concluded that simple interventions such as providing the patients with their physician's name in writing and emphasizing the importance of knowing it result in a significantly greater percentage of physician-name recall.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.262
GPT teacher head0.486
Teacher spread0.224 · 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

Citations37
Published2005
Admission routes1
Has abstractyes

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