Recent developments in the field of integration technologies like Enterprise Application Integration (EAI) have emerged to support organizations towards improving the quality of services and reducing integration costs. Despite the importance of EAI, there is limited empirical research reported on its adoption in the healthcare sector. Khoumbati et al. [2006] developed a model for the evaluation of EAI in healthcare organizations. In doing so, the causal interrelationship of EAI adoption factors was identified by using fuzzy cognitive mapping. This paper is a progression of previous work in the area and seeks to contribute by validating the model through a different case environment. Thus, this paper contributes by deriving and proposing the MAESTRO model for EAI adoption. MAESTRO identifies a set of factors that influence EAI adoption and it is evaluated through a real-life case study. It provides an understanding of the EAI adoption process through its grounding on empirical data. In doing so, the MAESTRO model supports the management of healthcare organizations during the decision-making process for EAI adoption

Irani, Z

Khoumbati, K

Mantzana, V

Themistocleous, M

Communications of the Association for Information Systems

English

Brunel University Research Archive

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Information systems and healthcare XXIV: Factors affecting the EAI adoption in the healthcare sector

Khoumbati, Khalil

Themistocleous, Marinos

Irani, Zahir

Mantzana, Vasiliki

AIS Electronic Library (AISeL)

Information Systems and Healthcare XXIV: Factors Affecting the EAI Adoption in the Healthcare Sector

This paper focuses on Enterprise Application Integration (EAI) adoption in healthcare organisations. EAI has emerged to support organisations overcoming their integration problems, and it has been adopted by many sectors. Despite its importance, the healthcare sector develops EAI solutions at a slower pace and can be characterised as a laggard compared to other sectors. The small number of EAI applications in healthcare has resulted in limited research in this area, with many issues requiring further investigation. The normative literature analyses the factors that influence EAI adoption in healthcare but it has not yet explored the role of actors during the adoption process. This paper makes a step forward and contributes to the body of knowledge as it: (a) highlights the role of healthcare actors and attitudes towards EAI adoption; (b) introduces an actor-oriented approach; (c) identifies those actors involved in this process; and (d) combines the actor-oriented approach with the factors influencing EAI adoption. The authors believe that such an approach is significant and novel as it: (a) enhances existing EAI adoption models by incorporating an actor-oriented analysis; and (b) facilitates healthcare organisations in making robust decisions for EAI adoption. The authors discuss the application of their approach through a hospital case study. While a single case study alone cannot be proof, the engagement of the actors was encouraging

Information Systems and Healthcare XXV: Factors and Actors Affecting the EAI Adoption in the Healthcare Sector

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=3333&amp;context=cais

Information systems and healthcare XXIV: Factors affecting the EAI adoption in the healthcare sector

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