A novel conceptual framework of Health Information Systems (HIS) sustainability

Sustainable technology means technology is capable of being maintained over a long span of time; independent of shifts in both hardware and software. Effective implementation and use of Health Information Systems (HIS) for years to come are crucial as sustainable HIS. Numbers of studies have discussed various factors contributes towards barriers for successful implementation of HIS. However, very few studies discussed factors on HIS sustainability. Through critical analysis of existing literature on success, failure, and challenges of HIS adoption, this paper identifies four crucial factors that shape the sustainable HIS. The importance of strong leadership support, proper contingency planning, and practice, continuous vendor support, and protection of security and privacy issues are identified by classifying all the factors within these four constructs, and with it, we argue these factors crucial for sustainable HIS. This paper proposes a novel conceptual framework which incorporated all these constructs as HIS sustainability factors. This paper also described the theoretical basics behind the development of the model and methodology to be employed to validate the proposed model

Regression Analysis of Cloud Computing Adoption for U.S. Hospitals

Industrial experts agree that cloud computing can significantly improve business and public access to low cost computing power and storage. Despite the benefits of cloud computing, recent research surveys indicated that its adoption in U.S. hospitals is slower than expected. The purpose of this study was to understand what factors influence cloud adoption in U.S. hospitals. The theoretical foundation of the research was the diffusion of innovations and technology-organization-environment framework. The research question was to examine the predictability of cloud computing adoption for U.S. hospitals as a function of 6 influential factors: relative advantage, compatibility, complexity, organizational size, structure, and culture. The research methodology included a cross-sectional survey with an existing validated questionnaire. A stratified random sample of 118 information technology managers from qualified U.S. hospitals completed the questionnaire. The categorical regression analysis rendered F statistics and R2 values to test the predictive models. The research results revealed that all 6 influential factors had significant correlations with the public cloud adoption intent (adjusted R2 = .583) while only the 3 technological factors had significant correlations with the private cloud adoption intent (adjusted R2 = .785). The recommendation is to include environmental factors and increase sample size in the similar future research. The developed predictive models provided a clearer understanding among hospital IT executives and cloud service providers of cloud adoption drivers. The potential implications for positive social change can be the increase of efficiency and effectiveness in U.S. hospital operation once their speed of cloud adoption has increased