DOI QR코드

DOI QR Code

Validation of the Short Form Bobath Memorial Hospital Fall Risk Assessment Scale at a Specialized Geriatric Hospital in Korea

단축형 노인 낙상위험 사정도구의 타당도

  • Received : 2014.11.18
  • Accepted : 2014.12.21
  • Published : 2014.12.31

Abstract

Purpose: This study was conducted in order to evaluate the reliability, validity, sensitivity, and specificity of the Short Form of Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS-SF). Methods: A validation study was conducted on 207 elderly patients aged over 65 who were admitted to Bobath Memorial Hospital. Fall risk scores of BMFRAS, composed of eight subscales (age, fall history, physical activity, consciousness level, communication, fall risk factors, underlying disease, and medications) were assessed from the electronic medical record. BMFRAS-SF was derived from eight subscales of the BMFRAS representing the significance between fallers and non-fallers (fall history, physical activity, fall risk factors, underlying disease, and medications). Internal consistency reliability and interrater reliability were assessed by Cronbach's alpha and kappa coefficient. Validity was assessed by Spearman correlation analysis, factor analysis. Sensitivity, specificity, positive predictive and negative predictive values, and a receiver-operating characteristic curve (ROC) were generated. Results: Fallers had significantly higher risk scores than non-fallers in fall history, physical activity, fall risk factors, underlying disease, and medication scales. The BMFRAS-SF demonstrated acceptable Cronbach's alpha (.706) and kappa coefficients of .95. The BMFRAS-SF subscales showed good convergent validity and construct validity. The BMFRAS-SF presented good sensitivity(86.7%), specificity(67.9%), positive predictive value(42.9%) and good negative predictive value(94.8%) at a cut-off score of 5. Areas under the ROC curves were .860 for the BMFRAS and .861 for the BMFRAS-SF. Conclusion: The BMFRAS-SF was proved to be reliable and valid. It could be used for time-saving assessment and evaluation of the high risks for falls in clinical practice settings.

Keywords

References

  1. Cumming, R. G., Sherrington, C., Lord, S. R., Simpson, J. M., Vogler, C., Cameron, I. D., & Naganathan, V. (2008). Cluster randomised trial of a targeted multifactorial intervention to prevent falls among older people in hospital. British medical journal, 5, 336 (7647):758-760. http://dx.doi:10.1136/bmj.39499.546030.BE
  2. Halfon, P., Egglib, Y., Melle, G. V., & Vagnair, A. (2001). Risk of falls for hospitalized patients: A predictive model based on routinely available data. Journal of Clinical Epidemiology, 54, 1258-1266. http://dx.doi:10.1016/S0895-4356(01)00406-1
  3. Healey, F., Scobie, S., Oliver, D., Pryce, A., Thomson, R., & Glampsonet, B. (2008). Falls in english and welsh hospitals: a national observational study based on retrospective analysis of 12 months of patient safety incident reports. Quality and Safety in Health Care, 17, 424-430. http://dx.doi:10.1136/qshc.2007.024695
  4. Heinze, C., Dassen, T., Halfens, R., & Lohrmann, C. (2009). Screening the risk of falls: a general or a specific instrument? Journal of Clinical Nursing, 18(3), 350-356. http://dx.doi:10.1111/j.1365-2702.2008.02 453.x
  5. Hendrich, A., Nyhuuis, A., Kppenbrock, T., & Soja, M. E. (1995). Hospital falls: Development of predictive model for clinical practice. Applied Nursing Research, 8, 129-139. http://dx.doi:10.1016/S0897-1897(95)80592-3
  6. 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(1), 9-21. http://dx.doi:10.1053/apnr.2003.016009
  7. Hitcho, E. B., Krauss, M. J., Birge, S., Claiborne Dunagan, W., Fischer, I., Johnson, S., Nast, P. A., Costantinou, E., & Fraser, V.,J. (2004). Characteristics and circumstances of falls in a hospital setting: a prospective analysis. Journal of General Internal Medicine, 19, 732-739. http://dx.doi:10.1111/j.1525-1497. 2004.30387.x
  8. Ivziku, D., Matarese, M., & Pedone, C. (2011). Predictive validity of the Hendrich fall risk model II in an acute geriatric unit. International Journal of Nursing Studies, 48, 468-474. http://dx.doi:10.1016/j.ijnurstu.2010.09.002
  9. Jang, I. S., & Park, E. O. (2013). The prevalence and factors of falls among the community-dwelling elderly. Journal of Korean Academy of Public Health Nursing, 27(1), 89-101. http://dx.doi.org/10.5932/JKPHN.2013.27.1.89
  10. Kim, C. G., (2003). An analysis of fall incidence rate and the related factors of fall in hospitalized patients. Unpublished master's thesis, Seoul National University, Seoul.
  11. Kim, E. A. N., 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:10.1111/j.1365-2648.2007.04419.x
  12. Kim, E. K., Lee, J. C., & Eum, M. R. (2008). Fall risk factors of inpatients. Journal of Korean Academy of Nursing, 38(5), 676-684. http://dx.doi.org/10.4040/jkan.2008.38.5.676
  13. Kim, K. S., Kim, J. A., Choi, Y. K., Kim, Y. J., Park, M. H., Kim, H. Y., & Song, M. S. (2011). A Comparative Study on the Validity of Fall Risk Assessment Scales in Korean Hospitals. Asian Nursing Research, 5(1), 28-37. http://dx.doi.org/10.1016/S1976-1317(11)60011-X
  14. Kim, O. H., Lee, E. K., & Kim, E. M. (2011). Effects of fall prevention program on fall efficacy scale and activities-specific of balance confidence scale in rural residents. Journal of Korean Public Health Nursing, 25(2), 187-196.
  15. Miller, C. A. (2002). The connection between drugs and falls in elders. Geriatric Nursing, 23(2), 109-110. http://dx.doi.org/10.1067/mgn.2002.123794
  16. Milisen, K., Staelens, N., Schwendimann, R., De Paepe, L., Verhaeghe, J., Braes, T., Boonen, S., Pelemans, W., Kressig, R. W., & Dejaeger, E. (2007). Fall prediction inpatients by bedside nurses 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: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 patients. Canadian Journal on Aging, 8, 366-377. http://dx.doi.org/10.1017/S0714980800008576
  18. Mun, Y. H. (2005). The prevalence and associated factors of the in-home falls of the elderly. Journal of Korean Academy of Public Health Nursing, 19(2), 324-333.
  19. Oliver, D., Britton, M., Seed, P., Martin, F. C., & Hopper, A. H. (1997). Development and evaluation of evidence based assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies. British Medical Journal, 315, 1049-1053. http://dx.doi:10.1136/bmj.315.7115.1049
  20. Oliver., D., Daly, F., Martin, F. C. & McMurdo, M. E. T. (2004). Risk factors and risk assessment tools for falls in hospital in-patient: a systematic review. Age and Ageing, 33, 122-130. http://dx.doi:10.1093/ageing/afh017
  21. Oliver, D., & Healey, F. (2009) Falls risk prediction tools for hospital inpatients: do they work?, Nursing Times, 105(7), 18-21. Retrieved August 10, 2011, from http://www. nursingtimes.net/nursing-practice-clinical-research/falls-risk-prediction-tools-for-hospital-inpatients-do-they-work/1999146.article
  22. Park, M. H., & Sohng, K. Y. (2005). Risk Factors of Stroke Patients Falling in Geriatric Hospital. Journal of Korean Gerontological Nursing, 7(1), 104-113.
  23. Rosenberg, L., Joseph, L., & Barkum, A. (2000). Surgical arithmetic: epidemiological statistical and outcome based approach to surgical practice. Georgetown, Tx: Landes Bioscience.
  24. Korea Hospital Nurses Association (2005). Safety management guidelines for nursing (6th ed.). Seoul: Korea Hospital Nurses Association.
  25. Saverino, A., Benevolo, E., Ottonello, M., Zsirai, E., & Sessarego, P. (2006). Falls in a rehabilitation setting: functional independence and fall risk. Europa Medicophysica, 42, 179-184. Retrieved August 10, 2011, from http://www.minervamedica.it/en/getfreepdf/
  26. Schwendimann, R., Buhler1, H., De Geest, S., & Milisen, K. (2006). Falls and consequent injuries in hospitalized patients: effects of an interdisciplinary falls prevention program. BMC Health Services Research, 6, 69. Retrieved August 10, 2011, from http://www.biomedcentral.com/1472-6963/6/69 https://doi.org/10.1186/1472-6963-6-69
  27. Smith, J., Forster, A., & Young, J. (2006). Use of the 'STRATIFY' falls risk assessment in patients recovering from acute stroke. Age and Ageing, 35, 138-143. http://dx.doi:10.1093/ageing/afj027
  28. Sohng, K. Y., Moon, J. S., Song, H. H., Lee, K. S., & Kim, Y. S. (2004) Risk factors for falls among the community-dwelling elderly in korea. Journal of Korean Academy of Nursing, 34(8), 1483-1490. https://doi.org/10.4040/jkan.2004.34.8.1483
  29. Vassallo, M., Stockdale, R., Sharma, J. C., Briggs, R., & Allen, S. (2005). A comparative study of the use of four fall risk assessment tools on acute medical wards. Journal of the American Geriatrics Society, 53(6), 1034-1038. http://dx.doi.org/10.1111/j.1532-5415.2005.53316.x
  30. Vieira, E. R., Freund-Heritage, R., & da Costa, B. R. (2011). Risk factors for geriatric patient falls in rehabilitation hospital settings: a systematic review. Clinical Rehabilitation, 25, 788-799. http://dx.doi:10.1177/0269215511400639