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TopIntroduction
Sustainable development may be defined as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (World Commission on Environment and Development, 1987).
Decision-making in an environmental framework incorporates different technical, socio-economic, environmental and political questions, which conflict with one another; it is also necessary to add the existence of different stakeholder views (Huang, Keisler, & Linkov, 2011). These conditions are ideal for the application of Multi-Criteria Decision Analysis (MCDA) techniques, since they provide acceptable compromise solutions (Munda, Nijkamp, & Rietveld, 1994); in fact, the literature indicates that the application of MCDA techniques produces a significant improvement in the decision-making process which could guarantee public acceptance of a specific solution (Huang, Keisler, & Linkov, 2011). This has allowed the literature which applies MCDA in the environmental field to grow considerably over the last two decades.
There are many contributions which apply MCDA in order to analyse different environmental questions in a variety of industries, for example, the textile industry (Aragones-Beltran et al., 2009), renewable energy (Higgs et al., 2008), the electronic industry (Hsu & Hu, 2008), waste treatment (Lahdelma, Salminen, & Hokkanen, 2002), the extraction industry (Lamelas et al., 2008), power generation (Liang et al., 2006), manufacturing (Tseng, Lin, & Chiu, 2009), chemical industry (Pilavachi, Chatzipanagi, & Spyropoulou, 2009), public transport (Tzeng & Lin, 2005). Herva and Roca (2013) review the application of MCDA techniques to corporate environmental evaluation However, contributions regarding the hospital environment are almost non-existent, despite the fact that hospital facilities also generate waste and environmentally harmful pollutants.
Healthcare organizations should promote environmental awareness, keeping a balance with economic and clinical needs, such as to guarantee sustainable development. This implies minimizing the environmental impact, as well as improving the health of hospital workers and users and those who live nearby (Comunidad de Madrid, 2005).
A body committed to looking after the health of the public must be aware of the need to include within its strategy objectives which lead to sustainable development. A large number of health organizations are therefore working towards certificates in environmental standard ISO 14001 or the EMAS regulation. As a part of this process, health centres produce annual sustainability records, which have necessitated the definition of environmental indicators to facilitate data comparison and the long term development of the environmental behaviour of the hospital. However, not all the environmental areas or the indicators recorded have the same impact on the environment; some may have serious repercussions while other only involve slight costs. It is also possible that several indicators are related and so the same environmental area is assessed more than once.
Key Terms in this Chapter
Environmental Audit: A management tool which includes the systematic, documented, periodic and objective assessment of the efficiency of an organization, the management system and procedures intended to protect the environment with the aim of facilitating control of practices which affect the environment and evaluating the suitability of environmental policies to the company.
Eco-Management and Audit Scheme (EMAS): Regulation (EC) nº 761/2001 of the European Union originally passed in 1993 (Regulation (EEC) nº 1836/1993), which allows organizations to commit voluntarily to a community system of environmental management and auditing. The aim of EMAS is, as well as complying with legislation on the environment, encourages continuous improvements in the environmental behaviour of the organizations through the design and application of environmental management systems, systematic, objective and periodic assessment of the working of these systems, the spread of information about environmental behaviour, open dialogue with the public and other interested parties, the active involvement of the staff of the organization, and suitable training.
ISO Standard 14001:2004: This gives standards practice to be followed in order to introduce an environmental management system which allows companies to identify, analyse and improve their environmental behaviour, reduce environmental costs, and achieve compliance with environmental regulation. This international standard has the aim of providing different organizations with the elements of an effective environmental management system, independently of their side, location and social and cultural characteristics.
Environmental Indicator: Measurable parameter which provides information about some economic, social, political, biological, etc. matter which affects the environment. Its use serves to give synthetic information which allows the size and development of the problems to be known and assessed, objectives to be set, and the degree of compliance with the objectives measured.
Sustainable Development: This consists of meeting the current needs without risking the growth capacities of future generations. Sustainable development has social, economic and environmental dimensions.
Utility Function: Is a function which allows a number, an index of the preferences of the decision maker, to be associated with the different possible results of the decision alternatives. The higher the number, the higher the preference of the associated consequence. A utility function can be represented in three forms depending on the attitude of the decision maker to risk; a concave function in the case of risk-averse decision makers; a linear function with risk-indifferent decision makers, who behave according to the expected value; a convex function with risk-attracted decision makers.
Fuzzy Logic: Introduced by Lotfy A. Zadeh in 1965, it is a technique of computational intelligence which facilitates working with imprecise data, or data which are not well defined. The elements which human thought is based on are not numbers but linguistic tokens. Thus, knowledge, which is mainly qualitative and linguistic, can be represented in mathematical language by diffuse sets and characteristic functions associated with them.