Scott Warren, University of North Texas
Stephanie L. Robinson, University of North Texas
Brent Tincher, Lockheed Martin
Annette Fog, Globe Life
Janetta Boone, NASA
Predicts technology adoption based on two key beliefs: perceived usefulness and perceived ease of use, which influence behavioral intention to use.
Davis (1989); Venkatesh & Davis (2000)Integrates eight theories to predict user intention and technology use behavior through four key constructs.
Venkatesh, Morris, Davis, & Davis (2003)Both adopt a narrow perspective that primarily focuses on individual users' beliefs, perceptions, and usage intentions, narrowing the complexity of the socio-technical system to just individual users' perceptions or expectations.
Holden & Karsh (2010); Cresswell et al. (2013)Healthcare processes occur within complex socio-technical systems comprising people, processes, and technology, where workflow issues are defined by exceptions.
Berg et al. (2003); Sittig & Singh (2010); Greenhalgh et al. (2017)Multidimensional approaches needed to capture this complexity
Views the world as networks where objects like software have an active role in shaping social relations, not as passive equipment but as agents that actively transform established practices.
Latour (2005); Callon (1986); Law (1992)Identifies, characterizes, and explains the mechanisms that promote and inhibit implementation, embedding, and integration by focusing on the "work" people do to implement new practices into their routines.
May & Finch (2009); Murray et al. (2010)Considers the influence of external forces such as the organizational environment, regulations, professionalism, and network externalities on individual behavior and decision-making.
DiMaggio & Powell (1983); Scott (2008); Meyer & Rowan (1977)Organizational Environment
Regulations
Professionalism
Network Externalities
Zucker (1987); Tolbert & Zucker (1996)
Recognizes that interventions are configured and co-constructed over time and can be adapted, with implementation as a dynamic process rather than a discrete event.
DeSanctis & Poole (1994); Orlikowski (2000)Promoting Action on Research Implementation in Health Services
Encompasses broader contextual factors impacting across wider settings or services
Sources: Kitson et al. (1998); Rycroft-Malone (2004)Consolidated Framework for Implementation Research
Comprehensive framework addressing implementation factors across multiple contexts
Sources: Damschroder et al. (2009)Socio-technical complexity: Recognize healthcare as dynamic systems of people, processes, and technology
Berg et al. (2003); Sittig & Singh (2010)
Networks and relationships: Focus on pivotal role of actors (human and non-human), relationships, and networks in mobilizing knowledge
Latour (2005); Cresswell et al. (2010)
Embedding and integration: Understanding the work required to implement and integrate new practices into routines
May & Finch (2009); Greenhalgh et al. (2004)
Structural context: Consider external forces, regulations, organizational environment, and professionalism
Scott (2008); DiMaggio & Powell (1983)
Dynamic processes: Implementation evolves over time, not a discrete event; acknowledging fluidity and multiple realities
Rogers (2003); Greenhalgh et al. (2017)
By drawing on these multidimensional and systemic theories, researchers and practitioners can gain a more sophisticated and comprehensive understanding of why implementation succeeds or fails in complex healthcare settings.
Greenhalgh et al. (2017); May et al. (2016); Cresswell & Sheikh (2013)Move beyond simply measuring individual acceptance
Questions and Discussion Welcome
Theoretical Framework Citations:
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Berg, M. (1999). Patient care information systems and health care work. Social Science & Medicine, 48(11), 1505-1518.
Berg, M., Aarts, J., & van der Lei, J. (2003). ICT in health care: sociotechnical approaches. Methods of Information in Medicine, 42(4), 297-301.
Callon, M. (1986). Some elements of a sociology of translation. In J. Law (Ed.), Power, action and belief (pp. 196-223). Routledge.
Cresswell, K. M., Worth, A., & Sheikh, A. (2010). Actor-Network Theory and its role in understanding implementation. BMC Health Services Research, 10(1), 67.
Cresswell, K., & Sheikh, A. (2013). Organizational issues in the implementation and adoption of health information technology. International Journal of Medical Informatics, 82(5), e73-e86.
Damschroder, L. J., et al. (2009). Fostering implementation of health services research findings into practice: a consolidated framework. Implementation Science, 4(1), 50.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
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Kitson, A., Harvey, G., & McCormack, B. (1998). Enabling the implementation of evidence based practice. Quality in Health Care, 7(3), 149-158.
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May, C., & Finch, T. (2009). Implementing, embedding, and integrating practices: An outline of normalization process theory. Sociology, 43(3), 535-554.
May, C. R., et al. (2009). Development of a theory of implementation and integration. Implementation Science, 4, 29.
May, C. R., et al. (2016). Using Normalization Process Theory in feasibility studies. Implementation Science, 11(1), 80.
McEvoy, R., et al. (2014). A qualitative systematic review of studies using the normalization process theory. Implementation Science, 9(1), 2.
Meyer, J. W., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2), 340-363.
Murray, E., et al. (2010). Normalisation process theory: A framework for developing, evaluating and implementing complex interventions. BMC Medicine, 8, 63.
Orlikowski, W. J. (2000). Using technology and constituting structures. Organization Science, 11(4), 404-428.
Psek, W. A., & Greenhalgh, T. (2001). Viewing organizations as complex adaptive systems. Quality and Safety in Health Care, 10(4), 248-251.
Rapley, T., et al. (2018). Improving the normalization of complex interventions. BMJ Quality & Safety, 27(4), 289-298.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Rycroft-Malone, J. (2004). The PARIHS framework. Journal of Nursing Scholarship, 36(2), 152-156.
Scott, W. R. (2008). Institutions and organizations: Ideas and interests (3rd ed.). Sage Publications.
Sittig, D. F., & Singh, H. (2010). A new sociotechnical model for studying health information technology. International Journal of Medical Informatics, 79(4), e81-e90.
Tolbert, P. S., & Zucker, L. G. (1996). The institutionalization of institutional theory. In S. Clegg, C. Hardy, & W. Nord (Eds.), Handbook of organization studies (pp. 175-190). Sage.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model. Management Science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology. MIS Quarterly, 27(3), 425-478.
Zucker, L. G. (1987). Institutional theories of organization. Annual Review of Sociology, 13, 443-464.
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