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Record W3015523277 · doi:10.1186/s12913-020-05168-8

Current state of fall prevention and management policies and procedures in Canadian spinal cord injury rehabilitation

2020· article· en· W3015523277 on OpenAlexafffundabout
Hardeep Singh, Heather Flett, Michelle Pannor Silver, B. Catharine Craven, Susan Jaglal, Kristin E. Musselman

Bibliographic record

VenueBMC Health Services Research · 2020
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersToronto Rehabilitation InstituteCraig H. Neilsen Foundation
KeywordsMedicineRehabilitationHealth administrationNursing researchSpinal cord injuryPain medicineHealth informaticsPublic healthNursing managementPhysical medicine and rehabilitationSpinal cordPhysical therapyNursingAnesthesiologyAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Preventing patient falls is a priority in tertiary spinal cord injury (SCI) rehabilitation. Falls can result in patient or staff injury, delayed rehabilitation, and hospital liability. A comprehensive overview of fall prevention/management policies and procedures in Canadian SCI rehabilitation is currently lacking. We describe and compare the fall prevention/management policies and procedures implemented in Canadian tertiary hospitals that provide SCI rehabilitation. METHODS: Fall prevention/management documents implemented in SCI rehabilitation at six Canadian tertiary rehabilitation hospitals across five provinces were analyzed using a document analysis. Analysis involved multiple readings of the documents followed by a content and thematic document analysis. RESULTS: Fall prevention/management policies and procedures in SCI rehabilitation were organized into three main categories: 1) pre-fall policies and procedures; 2) post-fall policies and procedures; and, 3) communication between and amongst staff, patients, and families. Pre-fall policies and procedures encompassed: a) the definition of a fall; b) fall risk assessments in SCI rehabilitation; and, c) fall prevention strategies. The post-fall policies and procedures included: a) recovery from a fall; b) incident reporting process; and, c) fall classification. Components of fall prevention/management policies and practices that differed between hospitals included the fall risk assessments, post-fall huddles, and fall classifications. CONCLUSIONS: Fall prevention/management is a required organizational practice for all hospitals. Although Canadian tertiary hospitals that provide SCI rehabilitation have similar components of fall prevention/management policies and procedures, the specific requirements differ at each site. There is a need for evidence-informed, consensus-driven implementation of SCI-specific fall prevention and management procedures across Canadian SCI rehabilitation settings.

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)0.015
metaresearch head score (Gemma)0.047
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.019
Science and technology studies0.0110.005
Scholarly communication0.0060.002
Open science0.0060.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.085
GPT teacher head0.503
Teacher spread0.418 · 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

Citations9
Published2020
Admission routes3
Has abstractyes

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