• KANAD
  • Contact us
  • E-Submission
ABOUT
BROWSE ARTICLES
EDITORIAL POLICY
FOR CONTRIBUTORS

Articles

Original Article

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

Journal of Korean Academy of Nursing Administration 2011;17(4):484-492.
Published online: December 31, 2011

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: September 11, 2011   • Revised: October 24, 2011   • Accepted: November 18, 2011

Copyright © 2011 Korean Academy of Nursing Administration

  • 23 Views
  • 0 Download
  • 10 Crossref
prev next
  • 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.
  • 1. American Medical Directors Association. Falls and fall risk. 2002;Columbia, MD, American Medical Directors Association.
  • 2. Atman DG. Practical statistics for medical research. 1990;London, Champman & Hall.
  • 3. Berwick DM. Continuous improvement as an ideal in health care. N Engl J Med. 1989;320(1):53-56.
  • 4. Brenner H, Gefeller O. Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence. Stat Med. 1997;16:981-991.
  • 5. Capezuti E, Zwicker D, Mezey M, Fulmer TT, Gray-Miceli D, Kluger M. Evidence-based geriatric nursing protocols for best practice. 2008;3rd ed. New York, Springer Publishing Company.
  • 6. Chang JT, Morton SC, Rubenstein LZ, Mojica WA, Maglione M, Suttorp MJ, et al. Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomized controlled trials. BMJ. 2004;328(7441):680.
  • 7. Gevirtz F, Nash DB. Ransom S, Pinsky W, Tropman J. Enhancing physician performance through practice profiling. In: Enhancing physician performance: advanced principles of medical management. 2000;Tampa, FL, American College of Physician Executives. 91-116.
  • 8. Gray-Miceli D. Capezuti E, Zwicker D, Mezey M, Fulmer TT, Gray-Miceli D, Kluger M. Preventing falls in acute care. In: Evidence-based geriatric nursing protocols for best practice. 2008;3rd ed. New York, Springer Publishing Company. 161-193.
  • 9. Kim CG, Seo MJ. An analysis of fall incidence rate and its related factors of fall in hospital. J Korean Soc Qual Assur Health Care. 2002;9(2):210-228.
  • 10. Kim EK, Lee JC, Eom MR. Falls risk factors of inpatients. J Korean Acad Nurs. 2008;38(5):676-684.
  • 11. Kim KS, Kim JA, Kim MS, Kim YJ, Kim ES, Park KO, et al. Development of performance measures based on the nursing process for prevention and management of pressure ulcers, falls and pain. J Korean Clin Nurs Res. 2009;15(1):133-147.
  • 12. Laffel G, Blumenthal D. The case for using industrial quality management science in health care organizations. JAMA. 1989;262(20):2869-2873.
  • 13. Milisen K, Staelens N, Schwendimann R, De Paepe L, Verhaeghe J, Braes T, et al. Fall prediction in inpatients by bedside nurses using the St. Thomas's risk assessment tool in falling elderly inpatients (STRATIFY) instrument: a multicenter Study. J Am Geriatr Soc. 2007;55(5):725-733.
  • 14. Morse JM, Morse RM. Calculating all rates: methodological concerns. QRB Qual Rev Bull. 1988;14(12):369-371.
  • 15. Nakai A, Akeda M, Kawabata I. Incidence and risk factors for inpatient falls in an academic acute-care hospital. J Nippon Med Sch. 2006;73(5):265-270.
  • 16. Oliver D, Daly F, Martin FC, McMurdo MET. Risk factors and risk assessment tools for falls in hospital in-patients: a systematic review. Age Ageing. 2004;33(2):122-130.
  • 17. O'Connell B, Myers H. Research in brief: the sensitivity and specificity of the morse fall scale in acute care setting. J Clin Nurs. 2002;11(1):134-135.
  • 18. Park I, Cho I, Kim EM. Comparison of fall rates from different resources: a self report system and an electronic medical record system. Paper presented at the 10th International Congress on Nursing Informatics. 2009;Helsinki, Finland.
  • 19. Perell KL, Nelson A, Goldman R, Luther SL, Prieto-Lewis N, Rubenstein LZ. Fall-risk assessment measures: an analytic review. J Gerontol A Biol Sci Med Sci. 2001;56(12):761-766.
  • 20. Poses R, Cebul R, Collins M, Fager S. The importance of disease prevalence in transporting clinical prediction rules: the case of streptococcal pharyngitis. Ann Intern Med. 1986;105(4):586-591.
  • 21. Shortell SM, Bennett CL, Byck GR. Assessing the impact of continuous quality improvement on clinical practice: what is will take to accelerate progress. Milbank Q. 1998;76(4):593-624.
  • 22. Steinberg D. Sample size for positive and negative predictive value in diagnostic research using case-control designs. Biostatistics. 2009;10(1):94-105.
  • 23. Wyatt JC, Altman DG. Commentary: prognostic models: clinically useful or quickly forgotten? BMJ. 1995;311(7019):1539-1541.
Figure 1
ROC curve plotting sensitivity versus 1 specificity for each possible score of the fall risk assessment tool (AROC = 0.6017)
jkana-17-484-g001.jpg
Figure 2
Fall CQI(c ontinuous quality improvement) process
jkana-17-484-g002.jpg
Table 1
Comparison of Patient Characteristics between the Faller and Non-Faller Groups
jkana-17-484-i001.jpg

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
jkana-17-484-i002.jpg
Table 3
Confusion Matrix of the Fall Risk Assessment Tool
jkana-17-484-i003.jpg
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
jkana-17-484-i004.jpg
Table 5
Results of the Logistic Regression Analysis of the Fall Risk Assessment Tool
jkana-17-484-i005.jpg

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Influence of the Patient Safety Culture and Nursing Work Environment on Fall Prevention Activities of Hospital Nurses
      Se-Young Jung, Eun-Young Kim
      Journal of Korean Academy of Nursing Administration.2022; 28(2): 78.     CrossRef
    • Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis
      Yeji Seo, Kyunghee Kim, Ji-Su Kim
      International Journal of Environmental Research and Public Health.2021; 18(8): 3963.     CrossRef
    • A risk-factor analysis of medical litigation judgments related to fall injuries in Korea
      Insook Kim, Seonae Won, Mijin Lee, Won Lee
      Medicine, Science and the Law.2018; 58(1): 16.     CrossRef
    • Automatic population of eMeasurements from EHR systems for inpatient falls
      Insook Cho, Eun-Hee Boo, Soo-Youn Lee, Patricia C Dykes
      Journal of the American Medical Informatics Association.2018; 25(6): 730.     CrossRef
    • Comparison of Content Coverage of Domestic and International Inpatient Falls Prevention Guidelines Using Standard Nursing Terminologies
      Insook Cho, Jihye Kim, Jisun Chae, Miran Jung, Yeon Hee Kim
      Korean Journal of Adult Nursing.2018; 30(6): 622.     CrossRef
    • Characteristics and Risk Factors for Falls in Tertiary Hospital Inpatients
      Eun-Ju Choi, Young-Shin Lee, Eun-Jung Yang, Ji-Hui Kim, Yeon-Hee Kim, Hyeoun-Ae Park
      Journal of Korean Academy of Nursing.2017; 47(3): 420.     CrossRef
    • The Affect Factors of Geriatric Hospital Nurse’s Falls Prevention Activities
      Ji-Young Jung, Gye Hyun Jung
      Journal of Health Informatics and Statistics.2016; 41(2): 203.     CrossRef
    • Validation of Fall Risk Assessment Scales among Hospitalized Patients in South Korea using Retrospective Data Analysis
      Young Ok Kang, Rhayun Song
      Korean Journal of Adult Nursing.2015; 27(1): 29.     CrossRef
    • Fall Risk Factors and Fall Risk Assessment of Inpatients
      Yoon Sook Kim, Smi Choi-Kwon
      Korean Journal of Adult Nursing.2013; 25(1): 74.     CrossRef
    • Predictive Effects of Previous Fall History on Accuracy of Fall Risk Assessment Tool in Acute Care Settings
      Ihn Sook Park
      Journal of Korean Academy of Fundamentals of Nursing.2012; 19(4): 444.     CrossRef

    Download Citation

    Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

    Format:

    Include:

    Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls
    J Korean Acad Nurs Adm. 2011;17(4):484-492.   Published online December 31, 2011
    Download Citation
    Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

    Format:
    • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
    • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
    Include:
    • Citation for the content below
    Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls
    J Korean Acad Nurs Adm. 2011;17(4):484-492.   Published online December 31, 2011
    Close

    Figure

    • 0
    • 1
    Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls
    Image Image
    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
    Evaluation of a Fall Risk Assessment Tool to Establish Continuous Quality Improvement Process for Inpatients' Falls

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

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

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

    Confusion Matrix of the Fall Risk Assessment Tool

    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

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

    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

    TOP