MétaCan
Menu
Back to cohort
Record W2363782193

Implementing three-level visit system in critical patients' management

2012· article· en· W2363782193 on OpenAlexaboutno aff
Jin Zhang

Bibliographic record

VenueChinese Nursing Management · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNursingQuality managementIntensive care unitCritical care nursingQuarter (Canadian coin)Medical emergencyEmergency medicineFamily medicineManagement systemHealth careOperations managementIntensive care medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective: To explore the effect of three-level visit system in critical patients' management. Methods: We implemented three-level visit, so called unit, division and department level visit, to critical patients from all departments of our hospital since October, 2010. In department level, we organized a group of professional experts from different divisions to supervise critical patients if needed. We call them Critical Care Supervision Team (CCST). Nursing care quality, suggestions raised by professional visitors, and patients' demographic data were collected and analyzed. Results: Since three-level visit system implemented, 1189 critical patients were visited from October, 2010 to December, 2011 by the CCST. From October, 2010 to December, 2010,The nursing quality score for critical patients increased from 97.64 to 99.05, and then maintain at this level. Moreover, more suggestions were given to the staff nurses to provide better specialized care for critical patients, from 0 to 26 per quarter of a year. Conclusion:Three-level visit for critical patients was an effective method to enhance patients management and care quality.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.076
GPT teacher head0.485
Teacher spread0.409 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueChinese Nursing ManagementSame topicHealth and Wellbeing ResearchFrench-language works237,207