낙상위험 사정도구의 타당도 비교: 일개 종합병원의 입원 환자를 중심으로
Validation on Adult Fall Assessment Tools: Focusing on Hospitalized Patients in a General Hospital
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초록
Purpose: This study was conducted to verify fall predictive power and reasonable fall risk assessment tool by acomparative analysis of the sensitivity, specificity, positive forecast and negative forecast of each tool by applying MorseFall Scale (MFS), Johns Hopkins Fall Risk Assessment Tool (JHFRAT), and Fall Assessment Scale-Korean version(FAS-K) through electronic medical records to adult patients hospitalized in a general hospital in Korea. Methods: Weperformed a retrospective evaluation study from January to December 2018, 123 fall groups experiencing falls duringhospitalization and 123 non-falls groups were selected. Data presented a reasonable assessment tool that predicts anddistinguishes fall high-risk patients through area comparison based on the ROC curve for each tool. Results: In the ROCcurve analysis by fall risk assessment group, the AUC of MFS is shown to be .706 (good), JHFRAT is shown to be .649(sufficient) and FAS-K is shown to be .804 (very good). FAS-K at a cut-off score of 4, sensitivity, specificity, and positiveand negative prediction values were 83.7%, 60.2%, 67.8%, and 78.7%, respectively. Conclusion: Based on the abovefindings, it is believed that the FAS-K was presented as a suitable and reasonable tool for predicting falls for adult patientsin general hospitals.
Abstract
Purpose: This study was conducted to verify fall predictive power and reasonable fall risk assessment tool by acomparative analysis of the sensitivity, specificity, positive forecast and negative forecast of each tool by applying MorseFall Scale (MFS), Johns Hopkins Fall Risk Assessment Tool (JHFRAT), and Fall Assessment Scale-Korean version(FAS-K) through electronic medical records to adult patients hospitalized in a general hospital in Korea. Methods: Weperformed a retrospective evaluation study from January to December 2018, 123 fall groups experiencing falls duringhospitalization and 123 non-falls groups were selected. Data presented a reasonable assessment tool that predicts anddistinguishes fall high-risk patients through area comparison based on the ROC curve for each tool. Results: In the ROCcurve analysis by fall risk assessment group, the AUC of MFS is shown to be .706 (good), JHFRAT is shown to be .649(sufficient) and FAS-K is shown to be .804 (very good). FAS-K at a cut-off score of 4, sensitivity, specificity, and positiveand negative prediction values were 83.7%, 60.2%, 67.8%, and 78.7%, respectively. Conclusion: Based on the abovefindings, it is believed that the FAS-K was presented as a suitable and reasonable tool for predicting falls for adult patientsin general hospitals.
참고문헌 (29)
- Ang, N. K. E., "Evaluation of three fall-risk assessment tools in an acute care setting", Journal of Advanced Nursing, 60(4), pp.427~435 (2007)[DOI]
- Beack, Y. G., "Fall risk of patients admitted to emergency room", Global Health and Nursing, 2(1), pp.34~42 (2012)
- Bergland, A., "Risk factors for serious fall related injury in elderly women living at home", Injury Prevention, 10(5), pp.308~313 (2004)[DOI]
- Bouldin, E. D., "Falls among adult patients hospitalized in the United States : prevalence and trends", Journal of Patient Safety, 9(1), pp.13~17 (2013)[DOI]
- Cho, I., "Automatic population of eMeasurements from EHR systems for inpatient falls", Journal of the American Medical Informatics Association, 25(6), pp.730~738 (2018)[DOI]
- Cho, M. S., "Factors associated with injuries after inpatient falls in a tertiary hospital", Journal of Korean Clinical Nursing Research, 23(2), pp.202~210 (2017)[DOI]
- Choi, E. H., "Characteristics of fall events and fall risk factors among inpatients in general hospitals in Korea", Journal of Korean Clinical Nursing Research, 23(3), pp.350~360 (2017)[DOI]
- Choi, E. H., "Development of fall assessment scale in adult inpatients", Journal of Korean Clinical Nursing Research, 25(2), pp.179~188 (2019)[DOI]
- Choi, E. H., "Validation of Adult Fall Assessment Scale Korean Version for adult patients in general hospitals in Korea", Journal of Korean Clinical Nursing Research, 26(2), pp.265~273 (2020)[DOI]
- Choi, E. J., "Characteristics and risk factors for falls in tertiary hospital inpatients", Journal of Korean Academy Nursing, 47(3), pp.420~430 (2017)[DOI]
- Coussement, J., "Interventions for preventing falls in acute-and chronic-care hospitals : A systematic review and meta-analysis", Journal of the American Geriatric Society, 56(1), pp.29~36 (2008)[DOI]
- DiBardino, D., "Meta-analysis : Multidisciplinary fall pre vention strategies in the acute care inpatient population", Journal of Hospital Medicine, 7(6), pp.497~503 (2012)[DOI]
- Haines, T. P., "Design-related bias in hospital fall risk screening tool predictive accuracy evaluations : Systematic review and meta-analysis", The Journals of Gerontology : Series A, 62(6), pp.664~672 (2007)[DOI]
- Healey, F., "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(6), pp.424~430 (2008)[DOI]
- Jung, M. K., "Triggers and outcomes of falls in hematology patients : Analysis of electronic health records", Journal of Korean Academy of Fundamentals of Nursing, 26(1), pp.1~11 (2019)[DOI]
- Kang, Y. O., "Identifying characteristics of fall episodes and fall-related risks of hospitalized patients", Journal of Muscle and Joint Health, 22(3), pp.149~159 (2015)[DOI]
- Kim, J. H., "A case study on the use of ROC curve and AUC in the evaluation of discriminant model", Journal of The Korean Data Analysis Society, 20(2), pp.609~619 (2018)[DOI]
- Kim, K. S., "A comparative study on the validity of fall risk assessment scales in Korean hospitals", Asian Nursing Research, 5(1), pp.28~37 (2011)[DOI]
- Morse, J. M., "Development of a scale to identify the fall-prone patient", Canadian Journal on Aging, 8(4), pp.366~377 (1989)[DOI]
- Nam, A., "Development of Korean Intensive Care Delirium Screening Tool(KICDST)", Journal of Korean Academy of Nursing, 46(1), pp.149~158 (2016)[DOI]
- Oliver, D., "Preventing falls and fall-related injuries in hospitals", Clinics in Geriatric Medicine, 26(4), pp.645~692 (2010)[DOI]
- Park, S. H., "Systematic review and meta-analysis for usefulness of fall risk assessment tools in adult inpatients", Korean Journal of Health Promotion, 16(3), pp.180~191 (2016)[DOI]
- Perell, K, L., "Fall risk assessment measures : An analytic review", Journal of Gerontology, 56(12), pp.761~766 (2001)[DOI]
- Poe, S, S., "The Johns Hopkins Fall Risk Assessment Tool : Postimplementation evaluation", Journal of Nursing Care Quality, 22(4), pp.293~298 (2007)[DOI]
- Poe, S. S., "An evidence based approach to fall risk assessment, prevention, and management : lessons learned", Journal of Nursing Care Quality, 20(2), pp.107~116 (2005)[DOI]
- Schwendimann, R., "Evaluation of the Morse Fall Scale in hospitalised patients", Age and Ageing, 35(3), pp.311~313 (2006)[DOI]
- Simundic, A. M., "Measures of diagnostic accuracy : Basic definitions", The Journal of the International Federation of Clinical Chemistry and Laboratory Medicine, 19(4), pp.203~211 (2009)
- Wong, C. A., "The cost of serious fall-related injuries at three mid western hospitals", The Joint Commission Journal on Quality and Patient Safety, 37(2), pp.81~87 (2011)[DOI]
- Yoon, S. J., "Incidence of falls and risk factors of falls in inpatients", Quality Improvement in Health Care, 24(2), pp.2~14 (2018)[DOI]