Exploring and evaluating five paediatric falls assessment instruments and injury risk indicators: an ambispective study in a tertiary care setting.

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Nursing, Quality Improvement

Journal Title

Journal of nursing management

MeSH Headings

Accidental Falls, Adolescent, Case-Control Studies, Child, Child Welfare, Child, Preschool, Confidence Intervals, Female, Health Status Indicators, Humans, Infant, Infant, Newborn, Length of Stay, Logistic Models, Male, Nursing, Supervisory, Odds Ratio, Pediatric Nursing, Reproducibility of Results, Retrospective Studies, Risk Assessment, Sensitivity and Specificity, Wounds and Injuries


AIM: To evaluate currently available paediatric falls assessments instruments and to build a predictive fall model while also evaluating injury risk as a predictor of fall likelihood within the paediatric inpatient population.

BACKGROUND: There is lack of paediatric-specific fall assessment instruments and little information on the exploration of injury risk as related to falls in hospitalized children.

METHOD: An ambispective, matched case-control design conducted in a sample of 100 inpatient paediatric patients. Results Two out of five instruments performed well to classify children at risk of falls. Longer length of stay, bleeding cautions/blood disorders and temperament/behaviour issues were significant predictors of fall likelihood. Cognitive impairment or neurological disease was not related to an increased likelihood of fall or injury risk for this sample.

CONCLUSIONS: More research is required to institute and standardize paediatric fall and injury risk assessments for everyday use. The explicit approach of using predictive modelling is critical in creating a universal, baseline reference for the most reliable and valid measure of assessment in children.

IMPLICATIONS FOR NURSING MANAGEMENT: Findings of the present study increase awareness of nursing managers and leaders as to the necessity for fall and injury risk assessment as a safety and quality measure for inpatient paediatric populations.



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