Comparing Sensitivity, Specificity, and Accuracy of Fall Risk Assessments in Community-Dwelling Older Adults

Abstract

Purpose

The US Centers for Disease Control and Prevention (CDC) has implemented the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) initiative. This initiative provides an algorithm for fall risk screening. However, the algorithm has the potential to overcategorize individuals as high risk for falling upon initial screening, which may burden clinicians with the task of recategorizing individuals after follow-up testing. Therefore, this study aimed to compare the accuracy, sensitivity, and specificity of fall risk appraisal between the STEADI, Short Fall-Efficacy Scale International (FES-I), and portable balance system (BTrackS) assessments in community-dwelling older adults.

Patients and Methods

This cross-sectional analysis included 122 community-dwelling older adults, comprising 94 women and 28 men. Center-of-pressure postural sway was assessed using the BTrackS, fear of falling was assessed using the Short FES-I questionnaire, and all participants completed the STEADI checklist. Each assessment categorized participants as either high or low fall risk and fall risk appraisal was compared between groups using McNemar tests.

Results

The STEADI checklist (high risk: n = 62; low risk: n = 60) significantly differed in fall risk appraisal compared to the BTrackS (high risk: n = 44; low risk: n = 78; p = 0.014) and the Short FES-I (high risk: n = 42; low risk: n = 80; p = 0.002). Compared to the BTrackS, the STEADI checklist had a specificity of 62.8%, sensitivity of 70.5%, and accuracy of 65.6%. Compared to the Short FES-I, the STEADI checklist had a specificity of 67.5%, sensitivity of 81.0%, and accuracy of 72.1%.

Conclusion

The STEADI checklist appears to overcategorize individuals as high fall risk more frequently than direct assessments of postural sway and fear of falling. Further research is needed to examine potential improvements in accuracy when combining the STEADI checklist with direct assessments of postural sway and/or fear of falling.

Plain Language Summary

Fall risk assessments are crucial for preventative care in older adults. However, the demands of clinical practice require an accurate and time-efficient method. The U.S Centers for Disease Control and Prevention (CDC) has implemented a fall risk checklist through the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) initiative. However, the STEADI checklist might cost clinicians more time than expected, as some patients initially classified as high risk for falling may not actually be at high risk. This leads to unnecessary follow-up assessments. In this study, we compared the STEADI checklist to direct measures of postural sway (balance) using the BTrackS system and fear of falling using the Short FES-I survey to determine how they differed in classifying community-dwelling older adults as high versus low fall risk. Our results show that the STEADI checklist classifies older adults as high risk more frequently than the BTrackS and Short FES-I. Considering that the follow-up assessments for a high-risk classification by the STEADI checklist include a balance test, we suggest that combining a balance test such as the BTrackS with a questionnaire or checklist may yield better screening outcomes and accurately identify high-risk individuals in a timely manner. Further research is needed to determine the effectiveness of this combination and to establish a true gold standard method for fall risk appraisal.

Keywords:

• balance
• postural sway
• fall efficacy
• clinical practice

Data Sharing Statement

The deidentified data that support the findings of this study are available from the corresponding author, LT, upon reasonable request.

Disclosure

KL, AB, and JRS received financial support from the National Institutes of Health under supplemental Grant number 3R01MD018025-02S1. JRS, ET, NL, JP, RX and LT received financial support from the National Institute on Aging (R03AG06799), the National Institute on Minority Health and Health Disparities (R01MD018025) and the Office of the Director, Chief Officer for Scientific Workforce Diversity (COSWD) Office (3R01MD018025-02S1) of the National Institutes of Health. LT also received support from the National Science Foundation (NSF2222662). DHF has no conflicts of interest to report. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Additional information

Funding

This work was supported by the National Institute on Aging under Grant R03AG06799; the National Institute on Minority Health and Health Disparities under Grant R01MD018025; and the Office of the Director, Chief Officer for Scientific Workforce Diversity, Office the National Institutes of Health under supplemental Grant number 3R01MD018025-02S1.