Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls

Ihn Sook Park; InSook Cho; Eun Man Kim; Min Kyung Kim

doi:10.11111/jkana.2011.17.4.484

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Park, Cho, Kim, and Kim: Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls

Original Article

Journal of Korean Academy of Nursing Administration

Journal of Korean Academy of Nursing Administration 2011; 17(4): 484-492.

Published online: 31 December 2011

DOI: https://doi.org/10.11111/jkana.2011.17.4.484

Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls

Ihn Sook Park¹, InSook Cho², Eun Man Kim³, Min Kyung Kim⁴

¹Department of Nursing, Seoul National University, Korea.

²Associated professor, Department of Nursing, Inha University, Korea.

³Associate Professor, College of Nursing, SunMoon University, Korea.

⁴Graduate student, Department of Nursing, Inha University, Korea.

Correspondence: Cho, InSook. Department of Nursing, Inha University, 253, Yonghyeon-dong, Nam-gu, Incheon 402-751. Tel: 82-32-860-8201, Fax: 82-32-874-5880, insook.cho@inha.ac.kr

Received 11 September 2011 Revised 24 October 2011 Accepted 18 November 2011

Abstract

Purpose

The aims of study were; (1) to evaluate the validity and sensitivity of a fall-risk assessment tool, and (2) to establish continuous quality improvement (CQI) methods to monitor the effective use of the risk assessment tool.

Methods

A retrospective case-control cohort design was used. Analysis was conducted for 90 admissions as cases and 3,716 as controls during the 2006 and 2007 calendar years was conducted. Fallers were identified from the hospital's Accident Reporting System, and non-fallers were selected by randomized selection. Accuracy estimates, sensitivity analysis and logistic regression were used.

Results

At the lower cutoff score of one, sensitivity, specificity, and positive and negative predictive values were 82.2%, 19.3%, 0.03%, and 96.9%, respectively. The area under the ROC was 0.60 implying poor prediction. Logistic regression analysis showed that five out of nine constitutional items; age, history of falls, gait problems, and confusion were significantly associated with falls. Based on these results, we suggested a tailored falls CQI process with specific indexes.

Conclusion

The fall-risk assessment tool was found to need considerable reviews for its validity and usage problems in practice. It is also necessary to develop protocols for use and identify strategies that reflect changes in patient conditions during hospital stay.

Keywords: Risk assessment, Predictive value of tests, Validation studies, Accidental falls, Hospitalization

Figures and Tables

Figure 1

ROC curve plotting sensitivity versus 1 specificity for each possible score of the fall risk assessment tool (AROC = 0.6017)

Figure 2

Fall CQI(c ontinuous quality improvement) process

Table 1

Comparison of Patient Characteristics between the Faller and Non-Faller Groups

^†The Other category includes rehabilitation, gynecology, urology and internal medicine. ^***p<.001

Table 2

Comparison of Items of the Fall Risk Assessment Tool between the Faller and Non Faller Groups

Table 3

Confusion Matrix of the Fall Risk Assessment Tool

Table 4

Results of the Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), Odds Ratio and 95% Confidence Interval(CI) of the Fall Risk Assessment Tool

Table 5

Results of the Logistic Regression Analysis of the Fall Risk Assessment Tool

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