Razzaque, A., Mohamed, M., & Birasnav, M. (2013). A New Model for Improving Healthcare Quality Using Web 3.0 Decision Making. In A. Green, & L. Vandergriff (Eds.), Sustaining Knowledge Management (KM): Making It Real – adapting for success in the knowledge-based economy. TBD. 1 A New Model for Improving Healthcare Quality Using Web 3.0 Decision Making ANJUM RAZZAQUE New York Institute of Technology, Vancouver, BC VTY1KB, Canada arazza01@nyit.edu MIRGHANI MOHAMED Vice-President and Chief Technology Officer Applied Knowledge Sciences, Inc. Leesburg, VA 20176, USA mirghani@gmail.com BIRASNAV M New York Institute of Technology, Adliya, Manama, Kingdom of Bahrain birasnav@gmail.com ABSTRACT The recent ubiquity of social networking tools and the appearance of semantic web will have direct effects on improving the quality of the medical decision-making. This betterment in the decision-making process comes as a result of sharing heterogeneous mental models of the contributors and the pooling of opinions within the decision sharing platforms. These social networks facilitate the improvement of healthcare (HC) service quality, but only if used as knowledge management's (KM) collaborative systems that promote synergy, transfer and sharing of relevant knowledge. The amalgamation of social networking and social media sharing, through an intelligent personal agent, deems vital for the future sustenance of social networking in Web 3.0 within cloud computing setting. This merger through Software-as-a-service (SaaS) in the cloud infrastructure will form a new layer called Knowledge Management-as-a-service (KMaaS is a pre-requisite for the future sustenance of e-health that will materialize in the next decade. This study proposes a conceptual framework, for future empirical testing, so KM constellations such as communities of practice (CoP) can facilitate the enhancement of the quality of medical decision-making within cross- functional environs. Keywords - Knowledge Management, Social computing, Cloud computing, Web 3.0, Medical decision- making Quality 1. INTRODUCTION HC still staggers in its service quality causing a rise in patient mortality rate, HC costs and medical errors (DeMarco, 2010; Bodenheimer & Fernandez, 2005; Hrg, 2008; Chernichovsky & Leibowitz, 2010; Kozer, Macpherson, & Shi, 2002). Most frequently ignored medical errors are diagnostic errors. Statistics shows that one out of every ten diagnoses in the US, are concluded incorrectly (Campbell, 2010), costing $ 55.6 billion annually (Chicago Injury Attorney Blog, 2010). Forty out of every hundred Americans visit the emergency room (ER) where evidence-based quick decision-making (DM) is very critical (Kopun, 2010). Most clinical DM either lacks the support of or is without a HC Knowledge Management System (KMS). Abundant HC literature, related to decision support, fails to show the importance of HC KM in facilitating medical DM. Clinicians are asked to: (1) gather and interpret information, and (2) implicitly or explicitly bridge the daily inferential gap even when lacking evidence needed to reason a decision (Jalal-Karim & Balachandran 2008). This is possible through sharing experiential knowledge among HC physicians to