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As clinics strive to select information technology contractors that meet their particular outsourcing needs, the medical sector urgently needs evaluation criteria for outsourcing to information technology contractors to alleviate unnecessary risks and achieve an excellent performance. Therefore, this work presents an entropy combined technique for order preference by similarity to ideal solution (TOPSIS)-based decision-making method for clinics to objectively assess the quality of an information technology supplier when outsourcing their medical information needs, as an alternative to previous decision-making approaches based on subjective evaluations. Each sub-criterion for outsourcing vendors is evaluated using the Delphi method. Moreover, results of interviews with experts are integrated with the entropy method to calculate each criterion of an objective evaluation weight for medical information system (MIS) vendors. Furthermore, a TOPSIS-based survey is designed using comparison to effectively respond to MIS outsourcing demand scores for each item. Furthermore, the proposed entropy and TOPSIS-based decision-making method can provide administrators in hospital clinics with a decision-making and evaluation criteria that actively encourage the medical sector to outsource its information technology needs to contractors. [ABSTRACT FROM AUTHOR]

This work presents a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) model that adopts several important criteria. A questionnaire based on selection criteria identified from pertinent literature and interviews with experts is designed using the modified Delphi Technique and then sent to experts and decision makers. Major selection criteria are then analyzed and ranked using Fuzzy AHP. The proposed selection model not only enables a franchiser to select franchisees more objectively, but also be apply to other brand bedding company chain stores, thus enhancing commercial operations. [ABSTRACT FROM AUTHOR]