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Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems

Overview of attention for article published in SpringerPlus, July 2016
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60 Mendeley
Title
Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems
Published in
SpringerPlus, July 2016
DOI 10.1186/s40064-016-2686-3
Pubmed ID
Authors

Wen-Hwa Liao, Wan-Li Qiu

Abstract

Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 20%
Student > Master 10 17%
Student > Bachelor 4 7%
Student > Doctoral Student 4 7%
Researcher 4 7%
Other 7 12%
Unknown 19 32%
Readers by discipline Count As %
Computer Science 18 30%
Engineering 6 10%
Business, Management and Accounting 5 8%
Nursing and Health Professions 3 5%
Economics, Econometrics and Finance 2 3%
Other 8 13%
Unknown 18 30%