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Scaling Innovations in Healthcare
Govindasamy, Saravana P
Govindasamy, Saravana P
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Date
2019
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Business Administration/Management Information Systems
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http://dx.doi.org/10.34944/dspace/2924
Abstract
This research paper examines the innovation adoption of technology, specifically Artificial Intelligence (AI) implementations in hospitals by exploring the capabilities that enables AI innovations using the dynamic capabilities (sensing, seizing and reconfiguring) framework and clinicians’ intentions to use AI innovations for patient care by applying the technology adoption/acceptance framework Unified Theory of Acceptance and Use of Technology (UTAUT) utilizing qualitative case study analysis and quantitative survey methodology respectively. This multi-disciplinary research has considerable relevance to both healthcare business leaders and clinical practitioners by identifying the key factors that drives the decisions to adopt innovations to improve healthcare organizations' competitiveness to enhance patient care as well as to reduce overall healthcare costs. The main findings are: (1) On an organizational level, healthcare organizations with strong and versatile dynamic capabilities, who build on their existing knowledge and capabilities are better able to integrate the innovations into their internal operations and existing services. The identified barriers provide a clear sense of organizational barriers and resistance points for innovation adoption (2) On an individual level, the impact of quality of care and organization leadership support are the key factors that facilitates the adoption of innovation among the clinicians. (3) Current trends and key impact areas of AI technology in the healthcare industry are identified Key words: Innovation, Innovation Adoption, Dynamic Capabilities, Healthcare, Artificial Intelligence, AI, Technology, Strategic Management
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