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1.
Waste Manag ; 34(7): 1324-9, 2014 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-24726188

RESUMEN

Using the failure mode and effects analysis, this study examined biomedical waste companies through risk assessment. Moreover, it evaluated the supervisors of biomedical waste units in hospitals, and factors relating to the outsourcing risk assessment of biomedical waste in hospitals by referring to waste disposal acts. An expert questionnaire survey was conducted on the personnel involved in waste disposal units in hospitals, in order to identify important factors relating to the outsourcing risk of biomedical waste in hospitals. This study calculated the risk priority number (RPN) and selected items with an RPN value higher than 80 for improvement. These items included "availability of freezing devices", "availability of containers for sharp items", "disposal frequency", "disposal volume", "disposal method", "vehicles meeting the regulations", and "declaration of three lists". This study also aimed to identify important selection factors of biomedical waste disposal companies by hospitals in terms of risk. These findings can serve as references for hospitals in the selection of outsourcing companies for biomedical waste disposal.


Asunto(s)
Eliminación de Residuos Sanitarios/métodos , Residuos Sanitarios/análisis , Servicios Externos/métodos , Gestión de Riesgos , Administradores de Hospital , Eliminación de Residuos Sanitarios/economía , Eliminación de Residuos Sanitarios/normas , Servicios Externos/economía , Servicios Externos/normas , Encuestas y Cuestionarios , Taiwán
2.
Waste Manag ; 31(12): 2631-7, 2011 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-21807493

RESUMEN

In recent times, the quality of medical care has been continuously improving in medical institutions wherein patient-centred care has been emphasized. Failure mode and effects analysis (FMEA) has also been promoted as a method of basic risk management and as part of total quality management (TQM) for improving the quality of medical care and preventing mistakes. Therefore, a study was conducted using FMEA to evaluate the potential risk causes in the process of infectious medical waste disposal, devise standard procedures concerning the waste, and propose feasible plans for facilitating the detection of exceptional cases of infectious waste. The analysis revealed the following results regarding medical institutions: (a) FMEA can be used to identify the risk factors of infectious waste disposal. (b) During the infectious waste disposal process, six items were scored over 100 in the assessment of uncontrolled risks: erroneous discarding of infectious waste by patients and their families, erroneous discarding by nursing staff, erroneous discarding by medical staff, cleaning drivers pierced by sharp articles, cleaning staff pierced by sharp articles, and unmarked output units. Therefore, the study concluded that it was necessary to (1) provide education and training about waste classification to the medical staff, patients and their families, nursing staff, and cleaning staff; (2) clarify the signs of caution; and (3) evaluate the failure mode and strengthen the effects.


Asunto(s)
Hospitales , Eliminación de Residuos Sanitarios/métodos , Personal de Hospital/educación , Garantía de la Calidad de Atención de Salud/métodos , Gestión de Riesgos/métodos , Taiwán
3.
Waste Manag ; 31(12): 2414-21, 2011 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-21839628

RESUMEN

In recent years, the issue of environmental protection has received considerable attention. This paper adds to the literature by investigating a scheduling problem in the manufacturing of a glass recycling factory in Taiwan. The objective is to minimize the sum of the total holding cost and loss cost. We first represent the problem as an integer programming (IP) model, and then develop two heuristics based on the IP model to find near-optimal solutions for the problem. To validate the proposed heuristics, comparisons between optimal solutions from the IP model and solutions from the current method are conducted. The comparisons involve two problem sizes, small and large, where the small problems range from 15 to 45 jobs, and the large problems from 50 to 100 jobs. Finally, a genetic algorithm is applied to evaluate the proposed heuristics. Computational experiments show that the proposed heuristics can find good solutions in a reasonable time for the considered problem.


Asunto(s)
Algoritmos , Vidrio , Modelos Teóricos , Reciclaje/economía , Reciclaje/métodos , Taiwán
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