Moderate and severe falls: predictive model based on six years of reports in southern Brazil.
Sandiely de Araujo Mees, Greici Capellari Fabrizzio, Michelle Mariah Malkiewiez and 4 others
PMID 42684127WHAT IT FOUND
In 300 hospital fall reports, longer stay over 14 days, male sex, morning shift, disorientation, chronic disease, and circulatory disease were linked to moderate or severe harm.
Previous hospitalization was linked to lower risk of moderate or severe harm.
Key findings
01In the final model, moderate or severe falls were associated with hospital stay longer than 14 days (PR 7.21), male sex (PR 2.89), morning shift (PR 2.54), disorientation (PR 1.86), chronic diseases (PR 1.36), and circulatory system disease (PR 1.58), while previous hospitalization was associated with lower risk (PR 0.37).
02The final model had moderate discrimination for moderate or severe falls, with an area under the ROC curve of 0.768, sensitivity of 74.6%, and specificity of 62.3%.
03Most patients had been classified as high fall risk before the event (61.7%), and falls occurred mainly among hospitalized patients (89.2%), in patient rooms (42.9%) or bathrooms (34.5%), with standing-height falls most common (54.9%).
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
It was a single-hospital study in a SUS setting, so the model may not apply to other hospitals. The study analysed fall reports only, not all hospitalized patients, so it cannot estimate fall rates. Severity, causes, and circumstances were classified subjectively by the Risk Management Team or reporting professionals. Important variables had high missing data, including BMI (42.0%), obesity (28.0%), smoking (26.0%), and alcohol consumption (25.3%). Some variables were excluded from the final model because of instability, collinearity, or too few cases. The design cannot show that these factors caused more severe falls, and the model was not externally validated.
Declared interests
Financial support was from Conselho Nacional de Desenvolvimento Científico e Tecnológico, Ministério da Saúde, and Programa Nacional de Genômica e Saúde de Precisão Genomas Brasil. No other conflicts are stated.
The easy way to misread this
Do not conclude that changing shift staffing or reducing length of stay will prevent severe falls. These are associations from 300 hospital fall reports at one hospital, not evidence from a tested prevention strategy.