Heterogeneity between studies indicates that the Morse Falls Scale and STRATIFY may still be useful in particular setting s , but that widespread adoption of either is unlikely to generate benefits significantly greater than that of nursing staff clinical judgment
INTRODUCTION Fall risk screening tools are frequently used as a part of falls prevention programs in hospitals .
Design -related bias in evaluations of tool predictive accuracy could lead to overoptimistic results , which would then contribute to program failure in practice .
Fall risk assessment: a prospective investigation of nurses' clinical judgement and risk assessment tools in predicting patient falls.
A prospect i ve cohort study was used to determine the reliability and validity of two fall risk assessment tools and  nurses ' clinical judgement in predicting patient falls .  The study wards comprised two aged care and rehabilitation wards within a 570 bed acute care tertiary teaching hospital in Western Australia . Instrument testing included test-retest reliability and calculations of sensitivity , specificity , positive predictive value , negative predictive value and accuracy . The test retest reliability of all methods was good . In this setting , the three methods of assessing fall risk showed good sensitivity but poor specificity . Also , all methods had limited accuracy , and overall , exhibited an inability to adequately discriminate between patient population s at risk of falling and those not at risk of falling . Consequently , neither nurses ' clinical judgement nor the fall risk assessment tools could be recommended for assessing fall risk in this clinical setting
Heterogeneity between studies indicates that the Morse Falls Scale and STRATIFY may still be useful in particular setting s , but that widespread adoption of either is unlikely to generate benefits significantly greater than that of nursing staff clinical judgment
INTRODUCTION Fall risk screening tools are frequently used as a part of falls prevention programs in hospitals .
Design -related bias in evaluations of tool predictive accuracy could lead to overoptimistic results , which would then contribute to program failure in practice .