MétaCan
Menu
Back to cohort
Record W2579564243 · doi:10.1186/s13643-016-0401-7

Risk assessment tools to predict location of discharge and need for supportive services for medical patients after discharge from hospital: a systematic review protocol

2017· review· en· W2579564243 on OpenAlexaff
Daniel Kobewka, Daniel I. McIsaac, Michaël Chassé, Kednapa Thavorn, Sunita Mulpuru, Luke T. Lavallée, Shane English, Justin Presseau, Alan J. Forster

Bibliographic record

VenueSystematic Reviews · 2017
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsInstitute for Clinical Evaluative SciencesOttawa HospitalUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsMedicineCINAHLMEDLINEIntensive care medicineProtocol (science)Hospital dischargeSystematic reviewResidenceAcute careHealth careMedical emergencyEmergency medicinePsychological interventionNursingAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Patients who are discharged from hospital after an acute medical illness often have impaired function that prevents them from returning to their previous place of residence. Assessing each patient's post-discharge needs takes time and resources but is important in order to reduce unplanned readmissions and adverse events post-discharge. METHODS/DESIGN: We will conduct a systematic review to synthesize the evidence on prognostic models and their reported accuracy in predicting the location of discharge after a medical admission to an acute care hospital. We will perform searches in MEDLINE, EMBASE, CINAHL, and COCHRANE databases. Pre-defined study, population, and model characteristics will be reported. We will write a narrative summary of included studies. Methodological quality of the studies will be assessed using the QUIPS tool, and the quality of evidence will be evaluated using the GRADE tool. DISCUSSION: Early and accurate assessment of patient needs for supportive services after discharge has the potential to improve patient outcomes and health system efficiency. This systematic review will identify factors that can accurately predict location of discharge using existing tools and identify priority knowledge gaps to inform future research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016037144.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.055
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.055
Threshold uncertainty score0.292

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.070
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0170.020
Bibliometrics0.0150.012
Science and technology studies0.0040.003
Scholarly communication0.0060.007
Open science0.0050.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0390.004

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 head0.048
GPT teacher head0.408
Teacher spread0.360 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueSystematic ReviewsSame topicHeart Failure Treatment and ManagementFrench-language works237,207