| contributor author | Cimellaro G. P.;Malavisi M.;Mahin S. | |
| date accessioned | 2019-02-26T07:54:17Z | |
| date available | 2019-02-26T07:54:17Z | |
| date issued | 2018 | |
| identifier other | AJRUA6.0000952.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4250180 | |
| description abstract | Health care facilities should be able to quickly adapt to catastrophic events such as natural and human-made disasters. One way to reduce the impacts of extreme events is to enhance a hospital’s resilience. Resilience is defined as the ability to absorb and recover from hazardous events, containing the effects of disasters when they occur. The goal of this paper is to propose a fast methodology for quantifying disaster resilience of health care facilities. An evaluation of disaster resilience was conducted on empirical data from tertiary hospitals in the San Francisco Bay area. A survey was conducted during a 4-month period using an ad hoc questionnaire, and the collected data were analyzed using factor analysis. A combination of variables was used to describe the characteristics of the hidden factors. Three factors were identified as most representative of hospital disaster resilience: (1) cooperation and training management; (2) resources and equipment capability; and (3) structural and organizational operating procedures. Together they cover 83% of the total variance. The overall level of hospital disaster resilience (R) was calculated by linearly combining the three extracted factors. This methodology provides a relatively simple way to evaluate a hospital’s ability to manage extreme events. | |
| publisher | American Society of Civil Engineers | |
| title | Factor Analysis to Evaluate Hospital Resilience | |
| type | Journal Paper | |
| journal volume | 4 | |
| journal issue | 1 | |
| journal title | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering | |
| identifier doi | 10.1061/AJRUA6.0000952 | |
| page | 4018002 | |
| tree | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2018:;Volume ( 004 ):;issue: 001 | |
| contenttype | Fulltext | |