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Record W2021285598 · doi:10.1097/naq.0b013e3182032208

Optimizing Quality, Service, and Cost Through Innovation

2011· article· en· W2021285598 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNursing Administration Quarterly · 2011
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueQuarter (Canadian coin)BusinessOutreachIncentiveQuality (philosophy)Emergency departmentHealth careRepurposingOperations managementService (business)Medical emergencyNursingMedicineFinanceMarketingEconomicsEconomic growthEngineering

Abstract

fetched live from OpenAlex

With dramatic increases in health care costs and growing concerns about the quality of health care services, nurse executives are seeking ways to transform their organizations to improve operational and financial performance while enhancing quality care and patient safety. Nurse leaders are challenged to meet new cost, quality and service imperatives, and change cannot be achieved by traditional approaches, it must occur through innovation. Imagine an organization that can mitigate a $56 million loss in revenue and claim the following successes: Increase admissions by a 8 day and a $5.5 million annualized increase by repurposing existing space. Decrease emergency department holding hours by an average of 174 hours a day, with a labor savings of $502,000 annually. Reduce overall inpatient length of stay by 0.5 day with total compensation running $4.2 million less than the budget for first quarter of 2010. Grow emergency department volume 272 visits greater than budgeted for first quarter of 2010. Complete admission assessments and diagnostics in 90 minutes. This article will address how these outcomes were achieved by transforming care delivery, creating a patient transition center, enhancing outreach referrals, and revising admission processes through collaboration and innovation.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.235
GPT teacher head0.491
Teacher spread0.256 · 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