سلسله مراتب حساسیت فازی با استفاده از روش دلفی برای ارزیابی عملکرد سازمان بیمارستان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|994||2010||9 صفحه PDF||سفارش دهید||1 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 37, Issue 8, August 2010, Pages 5533–5541
The conventional accreditation policy of Taiwanese hospitals involves helping promote and executing national healthcare quality policies, certifying healthcare quality, supervising the management of health care organizations, pursuing a harmonious relationship between care providers and patients, and enhancing national healthcare quality. However, the quality indicators in use by Department of Health, Executive Yuan, Taiwan (DOH) cannot indicate overall organization performance of each hospital and assess hospital operating crisis. In many cases the preference model of the human decision maker is uncertain, and it is relatively difficult for the decision maker to provide exact numerical values for the comparison ratios. This study proposal fuzzy analytic hierarchy process (FAHP) and fuzzy sensitive analysis-based approach to resolve the uncertainty and imprecision of service evaluations during pre-negotiation stages, where the comparison judgments of a decision maker are represented as fuzzy triangular numbers. A novel fuzzy prioritization method, which derives crisp priorities (criteria weights and scores of alternatives) from consistent and inconsistent fuzzy comparison matrices, is also proposed. Importantly, the proposed model can provide Taiwan’s hospital accreditation policy a reference material, making it highly applicable for academic and government purposes.
To enforce health insurance and enhance medical technology, the Taiwanese government implemented the NHI plan in March 1995. The NHI scheme has resulted in financial unbalance. Therefore, the Bureau of National Health Insurance (BNHI) has sought to prevent further increases in health care expenditures and implemented a Global Budget System (GBS) in July 2002. Under the policy change environment, the hospitals’ managers need to change their management strategy, by discarding their past conservative attitudes. Other than fundamental improvement of diagnosis treatment technology and replacement of medical equipment, appropriate assistance and caring for patients should be as well taken into consideration. The conventional accreditation policy of Taiwanese hospitals involves helping promote and executing national healthcare quality policies, certifying healthcare quality, supervising the management of health care organizations, pursuing a harmonious relationship between care providers and patients, and enhancing national healthcare quality. However, the quality indicators in use by DOH cannot indicate overall organization performance of each hospital and assess hospital operating crisis. Furthermore, when facing the same operating objects payment standard and medical environment with finite medical resource, competitiveness is naturally to soar. This situation is exacerbated by large reductions of the medical budget by government, which has caused an operating crisis in hospitals. According to report from DOH, the number of hospitals in Taiwan declined by 231 or 29.35%, from 787 in 1989 to 556 in 2004. Additionally, the number of public hospitals declined by 5 or 5.38%, from 93 in 1989 to 88 in 2004; correspondingly, the number of private hospitals declined by 126 or 32.56%, from 694 in 1989 to 468 in 2004 (DOH, 2005). Therefore, administrators or decision makers of the hospitals requires effectively monitoring the organizational performance of the hospitals. Organizational performance is a perhaps the key issue for top administrator (Finkelstein & Hambrick, 1996). Although the position held by administrator is multifaceted, their most important role is to ensure the long-term success and viability of their organizations (Andrews, 1987). To fulfill this role, administrator must be able to monitor and interpret organizational performance. Such tasks are facilitated through comparisons of performance indicators against referent points. Nevertheless, the organization performance problem is a multi-criteria problem, and evaluating an ideal model requires suitable criteria and strict screening. Evans (2004) proposal an effective performance measurement system, which includes the selection of appropriate measures and approaches for analyzing results, is central to aligning an organization’s operations with its strategic direction. Kast and Rosenzweig (1974) suggested incorporating efficiency and effectiveness analysis to assess organizational performance. In the existing efficiency and effectiveness analysis studies have utilized data envelopment analysis (DEA) to evaluate performance (e.g., Abagail et al., 2005, Butler and Li, 2005 and Laine and Linna, 2005). Venkatraman and Ramanujam (1986) contended that organizational performance should include financial performance, business performance and organizational effectiveness. However, the organization performance is a multi-criteria decision-making (MCDM) problem. Among those well-known methods, MCDM is relatively new to be employed to evaluation of performance. MCDM aims at using a set of criteria for a decision problem. Since these criteria may vary in the degree of importance, the analytic hierarchy process (AHP) methodology is employed to prioritize the selection criteria (i.e., assign weights to the criteria). In the existing measurement of performance or studies have utilized AHP to set up a hierarchical skeleton within which multi-attribute decision problems can be structured (Kima et al., 2005, Nieminen and Takala, 2006, Uzoka and Michael, 2005, Wu et al., 2007, Wu et al., 2009, Chang et al., 2008, Chang et al., 2009 and Yurdakul, 2005). AHP has thus been successfully applied to a diverse array of problems. Despite its popularity, this method cannot adequately resolve the inherent uncertainty and imprecision associated with the mapping of a decision maker’s perception to exact numbers. In the traditional formulation of AHP, human judgment is represented as exact numbers. However, in many cases the preference model of the human decision maker is uncertain, and it is relatively difficult for the decision maker to provide exact numerical values for the comparison ratios. The decision makers could be uncertain about their own level of preference, due to incomplete information or knowledge, complexity and uncertainty within the decision environment, or a lack of an appropriate measurement units and scale. Therefore, this study proposes an evaluation framework through modified Delphi method. Next, the study presents FAHP and fuzzy sensitive analysis-based approach to resolve the uncertainty and imprecision of service evaluations during pre-negotiation stages, where the comparison judgments of a decision maker are represented as fuzzy triangular numbers, followed a case which identifies proposed model capable of choosing an effective monitor to adequately implement an organizational performance model in hospital management practices. Subsequently, the result can provide hospital accreditation policies or hospital administrators in Taiwan with the most effective strategic policy for promoting operating efforts. The fuzzy hierarchy sensitive analysis-based decision-making method for constructing an evaluation method can provide hospital decision makers or administrators with a valuable reference for evaluating the organizational performance. Importantly, the proposed model can provide Taiwan’s hospital accreditation policy a reference material, making it highly applicable for academic and government purposes.
نتیجه گیری انگلیسی
In order to ascertain the value of FAHP, results of the normalized relative weights of the OP of hospitals obtained from AHP and FAHP are compared. Table 7 presents the local relative weights of the four hospitals based on the results from FAHP, as well as the local relative weights from AHP. In the demonstrated example, Hospital A should be perfect because it has the largest relative weights (Hospital A = 0.412, from FAHP in Table 7). However, if the decision model does not specify the human judgment (i.e., only AHP model), Hospital B should have been perfect since it had the largest relative weights (Hospital B = 0.320, from AHP in Table 7). It is because the FAHP decision model has taken into account adequately resolve the inherent uncertainty and imprecision associated with the mapping of a decision maker’s perception to exact numbers on the model. AHP has its limitation because it cannot resolve the inherent uncertainty and imprecision, while FAHP provides powerful capability in solving nowadays construction management issues that involve more complicated decision problems. It is not to say that results from AHP would be different from those of FAHP. It depends on the subjective and/or objective ratings given to the judgment numbers. However, FAHP model is applied in evaluation of performance, and fuzzy theory enhances the increasingly popular MCDM approach to criteria prioritization. This example suggests that FAHP are able to affect the decision a real organization performance. The main benefit of the development of the performance measurement system is to provide a structure for performance measurement in hospitals and to reduce dependence on human judgments. The performance measurement model developed here structured the performance measurement problem in a hierarchical form, critical areas and performance measures. In addition, the model combined two different approaches developed in the literature. The performance measurement model developed here contributed to the previous performance measurement models available in the literature by including and quantifying interdependencies that exist between system components. Besides, fuzzy theory can adequately resolve the inherent uncertainty and imprecision associated with the mapping of a decision maker’s perception to exact numbers. Combining AHP and fuzzy theory resulted in increases importance of areas of success that contribute to other areas in their performance. It can be concluded that enabling areas of success contributes to the performance level of other areas of success, and consequently their importance should also include their contributions to the other areas. The application of the FAHP approach provides the DOH with a more accurate and realistic performance score. In a possible application of the proposed performance measurement model, a hospital can see its overall performance, detect its weak areas, in which its performance scores are lower than the other hospital average, and develop necessary programs to close the performance gaps in weak areas. The model provides not only the performance scores, but also weights of the areas of success. Lower weighted areas are considered more important for the hospital and are selected for improvement. Finally, we recommend that administrators or decision makers can use this model to evaluate the organizational performance of hospitals.