MétaCan
Menu
Back to cohort
Record W1901710508 · doi:10.1002/hed.24196

Understanding the impact of a clinical care pathway for major head and neck cancer resection on postdischarge healthcare utilization

2015· article· en· W1901710508 on OpenAlexafffund
Jonathan F. Dautremont, Lucas R. Rudmik, Steven C. Nakoneshny, Shamir Chandarana, T. Wayne Matthews, Christiaan Schrag, Gordon H. Fick, Joseph C. Dort

Bibliographic record

VenueHead & Neck · 2015
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of Calgary
FundersAlberta Health Services
KeywordsMedicineCare pathwayPoisson regressionHead and neck cancerHealth careClinical pathwayHead and neckCritical pathwaysCancerEmergency medicineIntensive care medicineInternal medicineSurgeryEnvironmental healthNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The purposes of this study were to explore the association of a postoperative clinical care pathway for patients undergoing major head and neck surgery with microvascular reconstruction on postdischarge health care utilization and cost and to compares a nonpathway group (n = 60) to a prospective, pathway-managed group (n = 54). Our primary purpose was to understand whether pathway-managed patients used postdischarge health care resources differently than patients managed without a care pathway. METHODS: Health care utilization data (counts and costs) were collected for the 3 months after discharge. Differences in utilization were compared using Poisson regression. The null hypothesis was that there were no differences in utilization between the pathway and nonpathway groups. RESULTS: Pathway patients had fewer postdischarge encounters in 2 of 4 sectors. Readmission costs were significantly less in the pathway group only. CONCLUSION: A postoperative inpatient clinical care pathway in patients with head and neck cancer is associated with decreased health care utilization and inpatient costs in the 3 months after discharge. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1216-E1220, 2016.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.344

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 studies0.0000.000
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 head0.346
GPT teacher head0.475
Teacher spread0.129 · 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

Citations23
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueHead & NeckSame topicReconstructive Surgery and Microvascular TechniquesFrench-language works237,207