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Record W3165601301 · doi:10.1002/pmrj.12650

The incidence and nature of adverse events in rehabilitation inpatients with acquired brain injuries

2021· article· en· W3165601301 on OpenAlexaffabout
Meiqi Guo, Rouaa Mandurah, Alan Tam, Mark Bayley, Alice Kam

Bibliographic record

VenuePM&R · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAdverse effectRehabilitationIncidence (geometry)Patient safetyEmergency medicineRehabilitation hospitalRetrospective cohort studyPhysical therapyHealth careInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Patient safety is important in all healthcare settings. Few studies have examined the state of patient safety in rehabilitation and none have examined patient safety in the setting of acquired brain injury (ABI) rehabilitation. OBJECTIVES: To determine the incidence, most common types, and severities of adverse events among inpatients undergoing ABI rehabilitation. DESIGN: Retrospective case series descriptive study. SETTING: The inpatient ABI rehabilitation program at an academic, tertiary rehabilitation hospital in Canada. PARTICIPANTS: One hundred eight consecutive inpatients with acquired brain injuries. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Patient charts and incident reports from the hospital's voluntary reporting system were reviewed by three board-certified physiatrists to determine the incidence, type, severity and preventability of adverse events. Adverse events were identified and classified for severity and type using the World Health Organization (WHO) International Classification for Patient Safety. Preventability was rated on a six-point Likert scale. RESULTS: During the study period, the incidence of adverse events was 17.42 ± 3.86 per 1000 patient days. Adverse events affected 52.8% of patients. Most adverse events identified were mild in severity (81.6%) and the rest were of moderate severity. The two most common types of adverse events were (1) patient incidents (50%) such as falls, pressure ulcers and skin tears and (2) patient behaviors such as missing patient, assault, or sexual behaviors (14.5%). Of the 76 adverse events identified in the study, 44.8% were preventable. The hospital's voluntary reporting system did not capture 57.9% of the adverse events identified. CONCLUSIONS: Future efforts to improve patient safety in ABI rehabilitation should focus on reducing falls, skin injuries and behaviors, and removing barriers to voluntary incident reporting. Detection of adverse events through chart reviews provides a more complete understanding of patient safety risks in ABI rehab than relying on incident reporting alone.

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)0.003
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 score0.006
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.015
GPT teacher head0.325
Teacher spread0.311 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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