The World Health Organization Disability Assessment Schedule 2.0 can predict the institutionalization of patients with stroke

Hsiang Yueh Hu, Wen Chou Chi, Kwang Hwa Chang, Chia Feng Yen, Reuben Escorpizo, Hua Fang Liao, Shih Wei Huang, Tsan Hon Liou

研究成果: 雜誌貢獻文章

4 引文 (Scopus)

摘要

BACKGROUND: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known questionnaire used to evaluate disability. We can not only evaluate disability but also obtain additional information by using the standardized WHODAS 2.0 scores. AIM: To predict the institutionalization of the patients with stroke by using the standardized WHODAS 2.0 scores. DESIGN: Observational study. SETTING: The data of 10,255 patients with stroke were acquired from the Data Bank of Persons with Disabilities (TDPD) in Taiwan. POPULATION : Patients with either ischemic or hemorrhagic stroke during chronic stage. METHODS: For the patients with stroke, we used a χ2 analysis for the categorical variables, and an independent Student's t test to compare the standardized WHODAS 2.0 scores in the six domains between different groups. We also generated a receiver operating characteristic curve using the standardized WHODAS 2.0 scores, and applied Youden Index to calculating the optimal cut-off point on the ROC curve. Then, we used a binary logistic regression analysis to determine risk factors for the institutionalization. RESULTS : All WHODAS 2.0 domains had higher scores in the institution group than in the community group. The ROC curve used to predict the institutionalization of patients with stroke revealed that all WHODAS 2.0 domains were statistically significant. The cognition, and mobility domains and the sum of WHODAS 2.0 scores were more accurate for predicting the risk of institutionalization in a long-term care facility. In a logistic regression analysis, standardized WHODAS 2.0 scores >69, residence in an urban area, and severity of impairment were factors for predicting the institutionalization of the patients with stroke. CONCLUSIONS: WHODAS 2.0 scores, urbanization level, and severity of impairment were positive factors for the institutionalization of patients with stroke in long-term care facilities, whereas the female sex and an age of >85 years were negative factors. The cognition and mobility domains and standardized WHODAS 2.0 scores were more accurate for predicting the institutionalization of patients with stroke. CLINICAL REHABILITATION IMPACT : Proper analysis of the functioning status and risk factors, as well as prediction of discharge destination for the patients with stroke can help the healthcare system reduce unnecessary expenditures and make the allocation of social resources more efficient.
原文英語
頁(從 - 到)856-862
頁數7
期刊European Journal of Physical and Rehabilitation Medicine
53
發行號6
DOIs
出版狀態已發佈 - 一月 1 2017

指紋

Institutionalization
Appointments and Schedules
Stroke
ROC Curve
Long-Term Care
Cognition
Logistic Models
Regression Analysis
Urbanization
Resource Allocation
Patient Discharge
Disabled Persons
Health Expenditures
Taiwan
Observational Studies
Rehabilitation
Databases

ASJC Scopus subject areas

  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation

引用此文

The World Health Organization Disability Assessment Schedule 2.0 can predict the institutionalization of patients with stroke. / Hu, Hsiang Yueh; Chi, Wen Chou; Chang, Kwang Hwa; Yen, Chia Feng; Escorpizo, Reuben; Liao, Hua Fang; Huang, Shih Wei; Liou, Tsan Hon.

於: European Journal of Physical and Rehabilitation Medicine, 卷 53, 編號 6, 01.01.2017, p. 856-862.

研究成果: 雜誌貢獻文章

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AU - Yen, Chia Feng

AU - Escorpizo, Reuben

AU - Liao, Hua Fang

AU - Huang, Shih Wei

AU - Liou, Tsan Hon

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N2 - BACKGROUND: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known questionnaire used to evaluate disability. We can not only evaluate disability but also obtain additional information by using the standardized WHODAS 2.0 scores. AIM: To predict the institutionalization of the patients with stroke by using the standardized WHODAS 2.0 scores. DESIGN: Observational study. SETTING: The data of 10,255 patients with stroke were acquired from the Data Bank of Persons with Disabilities (TDPD) in Taiwan. POPULATION : Patients with either ischemic or hemorrhagic stroke during chronic stage. METHODS: For the patients with stroke, we used a χ2 analysis for the categorical variables, and an independent Student's t test to compare the standardized WHODAS 2.0 scores in the six domains between different groups. We also generated a receiver operating characteristic curve using the standardized WHODAS 2.0 scores, and applied Youden Index to calculating the optimal cut-off point on the ROC curve. Then, we used a binary logistic regression analysis to determine risk factors for the institutionalization. RESULTS : All WHODAS 2.0 domains had higher scores in the institution group than in the community group. The ROC curve used to predict the institutionalization of patients with stroke revealed that all WHODAS 2.0 domains were statistically significant. The cognition, and mobility domains and the sum of WHODAS 2.0 scores were more accurate for predicting the risk of institutionalization in a long-term care facility. In a logistic regression analysis, standardized WHODAS 2.0 scores >69, residence in an urban area, and severity of impairment were factors for predicting the institutionalization of the patients with stroke. CONCLUSIONS: WHODAS 2.0 scores, urbanization level, and severity of impairment were positive factors for the institutionalization of patients with stroke in long-term care facilities, whereas the female sex and an age of >85 years were negative factors. The cognition and mobility domains and standardized WHODAS 2.0 scores were more accurate for predicting the institutionalization of patients with stroke. CLINICAL REHABILITATION IMPACT : Proper analysis of the functioning status and risk factors, as well as prediction of discharge destination for the patients with stroke can help the healthcare system reduce unnecessary expenditures and make the allocation of social resources more efficient.

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