MétaCan
Menu
Back to cohort
Record W1966871096 · doi:10.1377/hlthaff.2012.0504

An Increase In The Number Of Nurses With Baccalaureate Degrees Is Linked To Lower Rates Of Postsurgery Mortality

2013· article· en· W1966871096 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Affairs · 2013
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsInstitute of Health Economics
FundersNational Institute of Nursing ResearchAgency for Healthcare Research and Quality
KeywordsMedicineFamily medicineBaccalaureate DegreeHealth careEmergency medicineNursingHigher education

Abstract

fetched live from OpenAlex

An Institute of Medicine report has called for registered nurses to achieve higher levels of education, but health care policy makers and others have limited evidence to support a substantial increase in the number of nurses with baccalaureate degrees. Using Pennsylvania nurse survey and patient discharge data from 1999 and 2006, we found that a ten-point increase in the percentage of nurses holding a baccalaureate degree in nursing within a hospital was associated with an average reduction of 2.12 deaths for every 1,000 patients--and for a subset of patients with complications, an average reduction of 7.47 deaths per 1,000 patients. We estimate that if all 134 hospitals in our study had increased the percentage of their nurses with baccalaureates by ten points during our study's time period, some 500 deaths among general, orthopedic, and vascular surgery patients might have been prevented. The findings provide support for efforts to increase the production and employment of baccalaureate nurses.

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.

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 score0.008
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.363
Teacher spread0.337 · 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