Fall prediction according to nurses' clinical judgment: differences between medical, surgical, and geriatric wards

Autor: Steven Boonen, Ellen Vlaeyen, Kurt Surmont, Koen Milisen, René Schwendimann, Joke Coussement, Eddy Dejaeger, Flamaing J
Rok vydání: 2012
Předmět:
Zdroj: Journal of the American Geriatrics Society. 60(6)
ISSN: 1532-5415
Popis: Objectives: To assess the value of nurses' clinical judgment (NCJ) in predicting hospital inpatient falls. Design: Prospective multicenter study. Setting: Six Belgian hospitals. Participants: Two thousand four hundred seventy participants (mean age 67.6 ± 18.3; female, 55.7%) on four surgical (n = 812, 32.9%), eight geriatric (n = 666, 27.0%), and four general medical wards (n = 992, 40.1%) were included upon admission. All participants were hospitalized for at least 48 hours. Measurements: Within 24 hours after admission, nurses gave their judgment on the question �Do you think your patient is at high risk for falling?� Nurses were not trained in assessing fall risk. Falls were documented on a standardized incident report form. Results: During hospitalization, 143 (5.8%) participants experienced one or more falls, accounting for 202 falls and corresponding to an overall rate of 7.9 falls per 1,000 patient days. NCJ of participant's risk of falling had high sensitivity (78�92%) with high negative predictive value (94�100%) but low positive predictive value (4�17%). Although false-negative rates were low (8�22%) for all departments and age groups, false-positive rates were high (55�74%), except on surgical and general medical wards and in participants younger than 75. Conclusion: This analysis, based on multicenter data and a large sample size, suggests that NCJ can be recommended on surgical and general medical wards and in individuals younger than 75, but on geriatric wards and in participants aged 75 and older, NCJ overestimates risk of falling and is thus not recommended because expensive comprehensive fall-prevention measures would be implemented in a large number of individuals who do not need it.
Databáze: OpenAIRE