Optimizing the Information Outsourcing Practices of Primary Care Medical Organizations Using Entropy and TOPSIS

Optimizing the Information Outsourcing Practices of Primary Care Medical Organizations Using... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Optimizing the Information Outsourcing Practices of Primary Care Medical Organizations Using Entropy and TOPSIS

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Springer Netherlands
Copyright © 2006 by Springer Science + Business Media B.V.
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
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