USING A CO-EVOLUTIONARY IS-ALIGNMENT APPROACH TO UNDERSTAND EMR IMPLEMENTATIONS

Electronic Medical Records (EMRs) are repositories of electronic medical histories of patients, main-tained over time. Hospital operations and EMRs typically become interdependent, due to the inclusion of medical workflow- and administrative process support as core functionalities. Hence, it is profoundly challenging to effectively enable complex, multi-stakeholder clinical processes, enhance patient care, and align EMRs with hospital strategies, goals, and needs. In this study, we build upon co-evolutionary IS-alignment (COISA) theories and argue that current approaches to business-IT alignment in hospitals should be reconceptualised, particularly regarding modern EMR implementations. In this effort, we respond to the call for more empirical research on business-IT co-evolution. We unfold how COISA manifests during EMR implementations using a multiple case study method. This method allows us to get a rich understanding of the complex social phenomena that emerge during EMR implementations. Outcomes show that COISA manifests in all three cases, involving different stakeholder groups, but in different localities and intensities. These findings suggest that COISA is a suitable framework to de-scribe and understand EMR implementations and that different configurations of interaction patterns can lead to comparable results. This understanding enables EMR practitioners to more effectively iden-tify improvement areas in dealing with internal and external complexity

Leveraging IS in the complexity of healthcare: a combined NCA- and PLS-SEM analysis on the effects of co-evolutionary IS-alignment

Several studies have advocated for the value of co-evolutionary approaches to business-IT alignment in healthcare settings because they would be better suited to deal with complexity. However, empirical evidence supporting this premise is scarce and mainly based on qualitative works. We address this research gap by performing a survey among 85 Dutch healthcare organizations, looking into the effects of co-evolutionary information systems alignment (COISA) on organizational performance and the role of dynamic capabilities in this value path. We combine Necessary Condition Analysis and Partial Least Squares Modeling to see which aspects are indispensable and help further develop dynamic capabilities and performance. Our results confirm that COISA indeed positively influences healthcare organizations’ organizational performance through dynamic capabilities. Furthermore, we demonstrate that alignment motivation and interconnections between heterogeneous IS stakeholders are indispensable, and show the seemingly higher importance of the operational and orchestrational alignment competencies and the sensing dimension of dynamic capabilities

Business Process Redesign in the Perioperative Process: A Case Perspective for Digital Transformation

This case study investigates business process redesign within the perioperative process as a method to achieve digital transformation. Specific perioperative sub-processes are targeted for re-design and digitalization, which yield improvement. Based on a 184-month longitudinal study of a large 1,157 registered-bed academic medical center, the observed effects are viewed through a lens of information technology (IT) impact on core capabilities and core strategy to yield a digital transformation framework that supports patient-centric improvement across perioperative sub-processes. This research identifies existing limitations, potential capabilities, and subsequent contextual understanding to minimize perioperative process complexity, target opportunity for improvement, and ultimately yield improved capabilities. Dynamic technological activities of analysis, evaluation, and synthesis applied to specific perioperative patient-centric data collected within integrated hospital information systems yield the organizational resource for process management and control. Conclusions include theoretical and practical implications as well as study limitations