DOI QR코드

DOI QR Code

Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders

급성기 신경계 환자에서 낙상 위험 사정 도구의 신뢰도 및 타당도 비교

  • Received : 2012.10.09
  • Accepted : 2013.02.17
  • Published : 2013.02.28

Abstract

Purpose: The aim of the study was to identify the most appropriate fall-risk assessment tool for neurological patients in an acute care setting. Methods: This descriptive study compared the reliability and validity of three fall-risk assessment tools (Morse Fall Scale, MFS; St Thomas's Risk Assessment Tool in Falling Elderly Inpatients, STRATIFY; Hendrich II Fall Risk Model, HFRM II). We assessed patients who were admitted to the Department of Neurology, Neurosurgery, and Rehabilitation at Asan Medical Center between July 1 and October 31, 2011, using a constructive questionnaire including general and clinical characteristics, and each item from the three tools. We analyzed inter-rater reliability with the kappa value, and the sensitivity, specificity, predictive value, and the area under the curve (AUC) of the three tools. Results: The analysis included 1,026 patients, and 32 falls occurred during this study. Inter-rater reliability was above 80% in all three tools. and the sensitivity was 50.0% (MFS), 84.4%(STRATIFY), and 59.4%(HFRM II). The AUC of the STRATIFY was 82.8. However, when the cutoff point was regulated as not 50 but 40 points, the AUC of the MFS was higher at 83.7. Conclusion: These results suggest that the STRATIFY may be the best tool for predicting falls for acute neurological patients.

Keywords

References

  1. Advanced Analytics. (2010), Inter-rater reliability discussion corner by Kilem L. Gwet-sample size determination. Retrieved May 1, 2011, Web site: http://agreestat.com/blog_irr/ sample_size_determination.html.
  2. Australian Council for Safety and Quality in Health Care. (2005). Preventing falls and harm from falls in older people: Best practice guidelines for Australian hospitals and residential aged care facilities. Safety and Quality Council, Canberra, Australia: Author.
  3. Barker, A., Kamar, J., Graco, M., Lawlor, V., & Hill, K. (2011), Adding value to the STRATIFY falls risk assessment in acute hospitals. Journal of Advanced Nursing, 67, 450-457. http:// dx.doi.org/10.1111/j.1365-2648.2010.05503.x
  4. Chapman, J., Bachand, D., & Hyrkas, T. (2011). Testing of the sensitivity, specificity and feasibility of four falls risk assessment tools in a clinical setting. Journal of Nursing Management, 19, 133-142. http://dx.doi.org/10.1111/j.1365-2834.2010.01218.x
  5. Eagle, D. J., Salama, S., Whitman, D., Evans, L. A., Ho, E., & Olde, J. (1999). Comparison of three instruments in predicting accidental falls in selected inpatients in a general teaching hospital. Journal of Gerontological Nursing, 25 (7), 40-45. PMID:10476130
  6. Evans, D., Hodgkinson, B., Lambert, L., Wood, J., & Kowanko, I. (1998). Falls in acute hospitals: A systematic review. The Joanna Briggs Institute for evidence based nursing and midwifery, in conjunction with the royal adelaide hospital, adelaide, South Australia. National Library of Australia Cataloguing-in-publication data ISBN Number: 0-95861312-5.
  7. Friedman, S. M., Munoz, B., West, S. K., Rubin, G. S., & Fried, L. P. (2002). Falls and fear of falling: Which comes first? A longitudinal prediction model suggests strategies for primary and secondary prevention. Journal of American Geriatric Society, 50, 1329-1335. http://dx.doi.org/10.1046/j.1532-5415.
  8. Gu, M. O., Jeon, M. Y., & Eun, Y. (2006), The development and effect of an tailored falls prevention exercise for older adults. Journal of Korean Academy of Nursing, 36, 341-352. https://doi.org/10.4040/jkan.2006.36.2.341
  9. Harlein, J., Halfens, R. J. G., Dassen, T., & Lahmann, N. A. (2011). Falls in older hospital inpatients and the effect of cognitive impairment: A secondary analysis of prevalence studies. Journal of Clinical Nursing, 20, 175-183. http://dx.doi.org/ 10.1111/j.1365-2702.2010.03460.x
  10. Heinze, C., Halfens, R. J., Roll, S., & Dassen, T. (2006). Psychometric evaluation of the Hendrich Fall Risk Model. Journal of Advanced Nursing, 53, 327-332. http://dx.doi.org/10.1111/j.1365-2648. 2006.03728.x
  11. Hendrich, A. L., Bender, P. S., & Nyhuis, A. (2003). Validation of the Hendrich II Fall Risk Model: A large concurrent case/ control study of hospitalized patients. Applied Nursing Research, 16, 9-21. http://dx.doi.org/10.1053/apnr.2003.YAPNR2
  12. Hur, J. Y., & Kim, H. J. (2009). Relationship of risk factors, knowledge and attitude to falls in elderly in patients. Journal of Korean Gerontological Nursing, 11, 38-50.
  13. Jang, I. S., & Kim, D. J. (2002). Home safety assessment for fall prevention in elderly people in a rural community. Journal of Korean Gerontological Nursing, 4, 176-186.
  14. Kim, E. A., Mordiffi, S. Z., Bee, W. H., Devi, K., & Evans, D. (2007). Evaluation of three fall-risk assessment tools in an acute care setting. Journal of Advanced Nursing, 60, 427-435. http://dx.doi.org/10.1111/j.1365-2648.2007.04419.x
  15. Lovallo, C., Rolandi, S., Rossetti, A. M., & Lusignani, M. (2010). Accidental falls in hospital inpatients: Evaluation of sensitivity and specificity of two risk assessment tools. Journal of Advanced Nursing, 66, 690-696. http://dx.doi.org/10.1111/ j.1365-2648.2009.05231.x
  16. Milisen, K., Staelens, N., Schwendimann, R., Paepe, L. D., Verhaeghe, J., Braes, T., et al. (2007). Fall prediction in inpatients by bedside nurses using the St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) instrument: A multicenter study. Journal of the American Geriatrics Society, 55. 725-733, http://dx.doi.org/10.1111/ j.1532- 5415.2007.01151.x
  17. Morse, J. M., Morse, R. M., & Tylko, S. J. (1989). Development of a scale to identify the fall-prone patient. Canadian Journal on Aging, 8, 366-371. http://dx.doi.org/10.1017/S0714980
  18. Myers, H. (2003). Hospital fall risk assessment tools: A critique of the literature. International Journal of Nursing Practice, 9, 223-235. http://dx.doi.org/10.1046/j.1440-172X.2003.00430.x
  19. Myers, H., & Nikoletti, S. (2003). Fall risk assessment: A prospective investigation of nurses' clinical judgement and risk assessment tools in predicting patient falls. International Journal of Nursing Practice, 9, 158-165. http://dx.doi.org/10.1046/j.1440-172X.2003.00409.x
  20. O'Connell, B., & Myers, H. (2002). The sensitivity and specificity of the Morse Fall Scale in an acute care setting. Journal of Clinical Nursing, 11, 134-136. http://dx.doi.org/10.1046/j.1365-2702.2002.00578.x
  21. Oliver, D., Britton, M., Seed, P., Martin, F. C., & Hopper, A. H. (1997). Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies. British Medical Journal, 315, 1049-1053. http://dx.doi.org/10.1136/bmj.315.7115.1049
  22. Oliver, D., Papaioannou, A., Giangregorio, L., Thabane, L., Reizgys, K., & Foster, G. (2008). A systematic review and meta-analysis of studies using the STRATIFY tool for prediction of falls in hospital patients: How well does it work? Age and Ageing, 37, 621-627. http://dx.doi.org/10.1093/ageing/afn203
  23. Papaioannou, A., Parkinson, W., Cook, R., Ferko, N., Coker, E., & Adachi, J. D. (2004). Prediction of falls using a risk assessment tool in the acute care setting. BMC Medicine, 2, 1. http://dx.doi.org/10.1186/1741-7015-2-1
  24. Perell, K. L., Nelson, A., Goldman, R. L., Luther, S. L., Prieto-Lewis, N., & Rubenstein, L. Z. (2001). Fall risk assessment measures: An analytic review. Journal of Gerontology Series A: Biological Sciences and Medical Sciences, 56, M761-M766. PMID: 11723150 https://doi.org/10.1093/gerona/56.12.M761
  25. Petitpierre, N. J., Trombetti, A., Carroll, I., Michel, J. P., & Herrmann, F. R. (2010). The FIM instrument to identify patients at risk of falling in geriatric wards: A 10-year retrospective study. Age and Ageing, 39, 326-331. http://dx.doi.org/10.1093/ageing/afq010
  26. Ryu, Y. M., Roche, J. P., & Brunton, M. (2009). Patient and family education for fall prevention involving patients and families in a fall prevention program on a neuroscience unit. Journal of Nursing Care Quality, 24, 243-249. http://dx.doi. org/10.1097/NCQ.0b013e318194fd7c.
  27. Shin, K. R., Shin, S. J., Kim, J, S., & Kim, J. Y. (2005). The effects of fall prevention program on knowledge, self-efficacy, and preventive activity related to fall, and depression of low-income elderly women. Journal of Korean Academy of Nursing, 35, 104-112. https://doi.org/10.4040/jkan.2005.35.1.104

Cited by

  1. Characteristics and Risk Factors for Falls in Tertiary Hospital Inpatients vol.47, pp.3, 2017, https://doi.org/10.4040/jkan.2017.47.3.420
  2. Validation of Fall Risk Assessment Scales among Hospitalized Patients in South Korea using Retrospective Data Analysis vol.27, pp.1, 2015, https://doi.org/10.7475/kjan.2015.27.1.29
  3. Effects of Fall Prevention Education Program on Attitudes, Prevention Behaviors, and Satisfaction among Elderly Inpatients vol.30, pp.1, 2018, https://doi.org/10.7475/kjan.2018.30.1.49
  4. Evaluation of Clinical Usefulness of Delirium Assessment Tools for Elderly Patients after Neurosurgery vol.17, pp.1, 2013, https://doi.org/10.17079/jkgn.2015.17.1.38
  5. Risk factors of falling in patients with neurological diseases vol.20, pp.3, 2018, https://doi.org/10.1016/j.kontakt.2018.07.002
  6. 재가노인 방문요양보호사의 낙상관련 대처 경험에 관한 연구 vol.9, pp.3, 2013, https://doi.org/10.15268/ksim.2021.9.3.99
  7. Factors included in adult fall risk assessment tools (FRATs): a systematic review vol.41, pp.11, 2013, https://doi.org/10.1017/s0144686x2000046x