A Risk Assessment of Two Interorganizational Clinical Information Systems

Abstract

A risk analysis framework was used to examine the implementation barriers that may hamper the successful implementation of interorganizational clinical information systems (ICIS). In terms of study design, an extensive literature review was first performed in order to elaborate a comprehensive model of project risk factors. To test the applicability of the model, we next conducted a longitudinal multiple-case study of two large-scale ICIS demonstration projects carried out in Quebec, Canada. Variations in the levels of several risk dimensions measured throughout the duration of the projects were analyzed to determine their impact on successful implementation. The analysis shows that the proposed framework, composed of five risk dimensions, was very robust, and suitable for conducting a thorough risk analysis. The results also show that there are links between the quality of the risk management and the level of project outcomes. To be successful, it is important that the implementation efforts be distributed proportionally according to the importance of each of the risk factors. Furthermore, because the risks evolve dynamically, there is a need for high responsiveness to emerging implementation problems. Thus, implementation success lies in the ability of the project management team to be aware of and to manage several risk threats simultaneously and coherently since they evolve dynamically through time and interact with one another.

Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens

“…As a result, internationally health systems have undergone major changes in the past few decades to address the call for enhanced patient care and improved outcomes (Anderson 2007, Bush et al 2009, Pare et al 2008, Patil et al 2014, Sicotte et al 2006. IT and deployment of information systems (IS) is identified as central to this transformation of healthcare systems (Bush et al 2009).…”

Starting with small health data opportunities for Mhealth in Africa

“…[10,11]) in an attempt to improve the livelihood of civilians in resource-poor settings whether at a local, regional and/or national level [12,13]. Given the geographic dispersion of healthcare services in developing countries, the interaction of many healthcare providers and the need to balance the complex sequence of events required to care for each patient requires substantial application of mobile technologies [14].…”

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“…Storing patient information on these systems further exacerbates the level of this risk factor (Sicotte et al 2006). Failure of software in these systems/devices can have potentially catastrophic effects, leading to injury of patients or even death (Burton et al 2006).…”

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