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The Johns Hopkins Fall Risk Assessment Tool: A Study of Reliability and Validity
Stephanie S Poe1, Patricia B Dawson, Maria Cvach
1The Johns Hopkins Hospital, Baltimore, Maryland (Dr Poe and Mss Dawson, Burnett, Kumble, and Lewis); Johns Hopkins Health System, Baltimore, Maryland (Drs Poe and Cvach); The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (Ms Thompson); School of Nursing, The Johns Hopkins University, Baltimore, Maryland (Dr Hill); and College of Nursing, The Pennsylvania State University, University Park (Dr Hill).
The Johns Hopkins Fall Risk Assessment Tool (JHFRAT) reliably identifies patients at risk for falls. While sensitive, its specificity in predicting falls needs improvement for acute care settings.
Area of Science:
- Healthcare quality and safety
- Clinical assessment tools
- Nursing research
Background:
- Patient falls and associated injuries are significant safety issues in healthcare.
- The Johns Hopkins Fall Risk Assessment Tool (JHFRAT) was designed for early detection of fall risk in adult inpatients.
- The psychometric properties of JHFRAT in acute care settings require further validation.
Purpose of the Study:
- To evaluate the psychometric properties of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in acute care settings.
- To establish the reliability, sensitivity, specificity, and predictive validity of JHFRAT for fall risk assessment.
Main Methods:
- Utilized psychometric analysis to assess the Johns Hopkins Fall Risk Assessment Tool (JHFRAT).
- Evaluated reliability, sensitivity, negative predictive validity, specificity, and positive predictive validity.
- Focused on adult inpatients in acute care environments.
Main Results:
- The Johns Hopkins Fall Risk Assessment Tool (JHFRAT) demonstrated high reliability.
- High sensitivity and negative predictive validity were observed.
- Specificity and positive predictive validity were lower than anticipated.
Conclusions:
- The Johns Hopkins Fall Risk Assessment Tool (JHFRAT) is a reliable instrument for fall risk assessment.
- JHFRAT shows strong potential for ruling out fall risk (high sensitivity/NPV).
- Further refinement may be needed to improve the tool's ability to specifically identify patients who will fall.
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