Policy Driven Digital Infrastructure Development In The Us Healthcare Industry PDF Download

The increasing capabilities of information technologies (IT) stand to change various types of work. Realizing the transformative potential of IT applications such as artificial intelligence and Big Data analytics relies upon the construction of digital infrastructures capable of capturing, storing, and communicating large amounts of data. In many industries, digital infrastructure development occurs organically as organizations decide to adopt IT that enable access to the infrastructure, with the goal of innovating work processes, collaborating with other organizations, or providing new strategies for evaluating and managing work. Recently, though, government agencies have begun expediting the digital infrastructure creation and growth processes in hopes that infrastructures will enable data-driven innovation, collaboration, and evaluation in public sectors, including education and healthcare. The literature on IT implementations in organizations tells us that the deployment of new IT rarely goes smoothly, particularly when IT use requires substantial changes to everyday practices, existing roles, or established power hierarchies. When workers perceive the effort or threat of IT use to outweigh the benefits of use, they resist the IT in various ways (e.g., by misusing the IT or voicing concerns to managers). Given that digital infrastructure development requires commitment from workers in contributing high-quality data, resistance to new IT should be of particular concern to scholars of digital infrastructures and practitioners who participate in infrastructure development. However, few studies of digital infrastructure development identify and explain why and how resistance to digital infrastructure IT emerges, perhaps because most research on digital infrastructure development has occurred in industries such as scientific and academic research, where the implementation process is assumed to be gradual, participation is assumed to be voluntary, and control over IT use is left for organizations to decide. In such cases, organizations can deal with resistance to the IT in traditional ways—by incorporating workers into the IT design and selection process, by customizing or replacing the IT, or by easing requirements for use—and gradually develop practices that are sensitive to local needs and suitable for contributing to the digital infrastructure. The shift toward rapid, mandatory, and centralized IT implementation under federal policies renders these options unavailable to organizations and workers. Particularly, the forms of resistance and responses to resistance traditionally documented by scholars of IT implementations—such as workers misusing the IT and managers reactively customizing IT—might be insufficient in explaining how and why workers and organizations reach IT implementation outcomes because strict government policies govern what workers and organizations can and cannot do to alleviate the burdens introduced by the new IT. How, then, might workers resist policy-driven IT implementations in the absence of traditional avenues for resistance, and how might organizations deal with resistance when government policies direct IT decisions? This dissertation examines this question and related questions through a qualitative study of mandatory electronic medical records (EMR) implementation in the U.S. healthcare industry. The federal government recently invested over $30 billion to subsidize EMR adoption costs, develop certification programs to promote EMR interoperability, and implement strict guidelines for how caregivers must use the new IT. I traced worker responses to the implementation by first conducting a case study of one healthcare organization’s implementation of federally-certified EMR. Based on analysis of semi-structured interviews, ethnographic observations, and documents collected during the study, I found that workers became frustrated with the time EMR use added to their days, the practices they had to develop to comply with policies for EMR use, and the administrative compliance-gaining strategies that managers developed using EMR. Unlike workers studied in previous accounts of new IT implementation, caregivers had no outlet for shaping outcomes at the point of IT use. Likewise, organizations could not customize or replace the IT; instead, they used data automatically recorded in the EMR to develop EMR compliance strategies. Workers, faced with no local opportunities for resistance, turned to powerful professional organizations to resist the EMR program on their behalf. In the second part of the study, I documented this resistance movement and demonstrated how the presence of political opportunity structures enabled doctors and other caregivers to stall the progress of the digital infrastructure development program. Based on my analysis, I build a model of resistance to mandated digital infrastructure IT implementations that accounts for workers’ inability to resist these IT at the point of IT use, for organizations’ and managers’ inability to make locally-sensitive IT decisions, and for the influence of actors outside of the boundaries of the organization. The model illustrates how managers in policy-driven IT implementations do not have traditional means available for gaining worker acceptance of the IT; instead, they develop strategies to gain worker compliance with both federal and local policies. Workers, stuck with a particular IT and new policies, route their resistance to the national level. I conclude the study by considering how this model might be applied and adapted to other policy-driven digital infrastructure programs.