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Record W2783278359 · doi:10.1093/ageing/afx128

Outcomes of Mobilisation of Vulnerable Elders in Ontario (MOVE ON): a multisite interrupted time series evaluation of an implementation intervention to increase patient mobilisation

2017· article· en· W2783278359 on OpenAlexafffundabout
Barbara Liu, Julia E. Moore, Ummukulthum Almaawiy, Wai-Hin Chan, Sobia Khan, Joycelyne Ewusie, Jemila S. Hamid, Sharon E. Straus

Bibliographic record

VenueAge and Ageing · 2017
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsSt. Michael's HospitalSunnybrook Health Science CentreHealth Sciences CentreMcMaster UniversityUniversity of Toronto
FundersNorth York General HospitalOntario Ministry of Health and Long-Term CareUniversity of TorontoHamilton Health SciencesUniversity Health NetworkLondon Health Sciences CentreOttawa HospitalKingston General HospitalThunder Bay Regional Health Sciences Centre
KeywordsMedicineInterrupted time seriesIntervention (counseling)Interrupted Time Series AnalysisGerontologySeries (stratigraphy)Physical therapyPsychological interventionNursing

Abstract

fetched live from OpenAlex

Background: older patients admitted to hospitals are at risk for hospital-acquired morbidity related to immobility. The aim of this study was to implement and evaluate an evidence-based intervention targeting staff to promote early mobilisation in older patients admitted to general medical inpatient units. Methods: the early mobilisation implementation intervention for staff was multi-component and tailored to local context at 14 academic hospitals in Ontario, Canada. The primary outcome was patient mobilisation. Secondary outcomes included length of stay (LOS), discharge destination, falls and functional status. The targeted patients were aged ≥ 65 years and admitted between January 2012 and December 2013. The intervention was evaluated over three time periods-pre-intervention, during and post-intervention using an interrupted time series design. Results: in total, 12,490 patients (mean age 80.0 years [standard deviation 8.36]) were included in the overall analysis. An increase in mobilisation was observed post-intervention, where significantly more patients were out of bed daily (intercept difference = 10.56%, 95% CI: [4.94, 16.18]; P < 0.001) post-intervention compared to pre-intervention. Hospital median LOS was significantly shorter during the intervention period (intercept difference = -3.45 days, 95% CI: [-6.67,-0.23], P = 0.0356) compared to pre-intervention. It continued to decrease post-intervention with significantly fewer days in hospital (intercept difference= -6.1, 95% CI: [-11,-1.2]; P = 0.015) in the post-intervention period compared to pre-intervention. Conclusions: this is a large-scale study evaluating an implementation strategy for early mobilisation in older, general medical inpatients. The positive outcome of this simple intervention on an important functional goal of getting more patients out of bed is a striking success for improving care for hospitalised older patients.

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 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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.643
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.348
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), 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

Citations129
Published2017
Admission routes3
Has abstractyes

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