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Record W2032063546 · doi:10.1377/hlthaff.2012.0366

Low-Cost Transitional Care With Nurse Managers Making Mostly Phone Contact With Patients Cut Rehospitalization At A VA Hospital

2012· article· en· W2032063546 on OpenAlexaff
Amy Kind, Laury Jensen, Steve Barczi, Alan J. Bridges, Rebecca Kordahl, Maureen A. Smith, Sanjay Asthana

Bibliographic record

VenueHealth Affairs · 2012
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSmiths Detection (Canada)
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute on Aging
KeywordsPhoneTransitional careMedicineNursingHealth careAcute careMedical emergencyWork (physics)Family medicineBusiness

Abstract

fetched live from OpenAlex

The Coordinated-Transitional Care (C-TraC) Program was designed to improve care coordination and outcomes among veterans with high-risk conditions discharged to community settings from the William S. Middleton Memorial Veterans Hospital, in Madison, Wisconsin. Under the program, patients work with nurse case managers on care and health issues, including medication reconciliation, before and after hospital discharge, with all contacts made by phone once the patient is at home. Patients who received the C-TraC protocol experienced one-third fewer rehospitalizations than those in a baseline comparison group, producing an estimated savings of $1,225 per patient net of programmatic costs. This model requires a relatively small amount of resources to operate and may represent a viable alternative for hospitals seeking to offer improved transitional care as encouraged by the Affordable Care Act. In particular, the model may be attractive for providers in rural areas or other care settings challenged by wide geographic dispersion of patients or by constrained resources.

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)0.000
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 score0.053
Threshold uncertainty score0.831

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)0.0000.000

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 head0.007
GPT teacher head0.255
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations110
Published2012
Admission routes1
Has abstractyes

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