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Record W2810123833 · doi:10.1177/0840470418773108

Delivering improved patient and system outcomes for hospitalized older adults through an Acute Care for Elders Strategy

2018· article· en· W2810123833 on OpenAlex
Samir K. Sinha, Jocelyn Bennett, Rebecca Ramsden, Joanne Bon, Tyler Chalk

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealthcare Management Forum · 2018
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSinai Health SystemSouthlake Regional Health CenterUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAcute careMedicineOlder peopleAcute hospitalIntervention (counseling)Continuum of careEmergency medicineHealth careGerontologyMedical emergencyNursing

Abstract

fetched live from OpenAlex

Acute care hospitals are widely recognized as potentially high-risk environments for older adults. In 2010, Mount Sinai Hospital conceived its Acute Care for Elders (ACE) Strategy as a multi-component intervention to improve the care of hospitalized older adults. In order to determine its effectiveness, we conducted a quasi-experimental time series analysis of 12,008 older patients admitted non-electively for acute medical issues over a 6-year period. Despite a 53% increase in annual admissions of older patients between 2009/2010 and 2014/2015, Mount Sinai decreased total lengths of stay and readmissions and reduced the direct cost of care per patient, leading to net savings of CDN$4.2 million in 2014/2015. This article presents Mount Sinai's ACE Strategy and discusses the benefits of implementing integrated evidence-based models across the continuum of care and how it is supporting the implementation of ACE Strategy models of care and care practices across Canada and beyond.

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 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 score0.685
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.367
Teacher spread0.344 · 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