Telemedicine, the use of information technology to deliver health care from one location to another, has the potential to increase the quality and access to health care and to lower costs. This growth of telemedicine installations is occurring even as the utilization rates for installed telemedicine projects are falling well below expectations. Drawing on data collected from three operational telemedicine projects involving different clinical telemedicine applications, we examine how the technological barriers to telemedicine are impacting telemedicine utilization rates. Addressing technological barriers is a necessary but not sufficient condition if telemedicine is to fulfill its promise, and it is predominantly only after such barriers are addressed that the other barriers-professional, legal, and financial-come to the fore. Our findings support end-user and technical training as major barriers but do not support the quality of the video, system reliability, or the perceived inconvenience for physicians to use the equipment as barriers to telemedicine. The mismatch between the sophistication of the technology and end-user requirements for clinical activities and patient confidentiality and privacy issues were supported as barriers, but how they impacted telemedicine utilization was different than expected. Finally, unsatisfactory sound quality of the telemedicine equipment was identified as a frequent and unexpected barrier to telemedicine utilization rates. Index Terms-Medical informatics, technology management, telemedicine. (T)he emphasis placed on high technology systems without sufficient consideration of the specific clinical and health care requirements and infrastructure capabilities in each setting has created a poor fit between telemedicine system design and end-user needs [1, p. 70]. T ELEMEDICINE, the use of information technology to deliver health care from one location to another, has the potential to increase the quality and access to health care and to lower costs [2]-[8]. It has been earmarked as a strategic component of the National Information Infrastructure [2], [3] and is at the center of Department of Defense plans to provide better health care to its remotely located active forces [9] and revamp its network of veterans hospitals [10]. In the United States, at least 35 federal organizations were involved in telemedicine projects, and between 1994 and 1996, the federal government provided over $600 million to fund Manuscript

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Organizational cybersecurity requires more than just the latest technology. To secure an organization, all members of the organization must act to reduce risk. Leaders have a special responsibility to understand, shape and align the beliefs, values, and attitudes of the entire organization with overall security goals. Managers need practical solutions for dealing with the human side of cybersecurity. The model presented in this paper describes organizational cybersecurity culture, the factors that contribute to its creation, and how it can be measured. A case study of a "culture of data protection" created by leaders at financial services firm Liberty Mutual illustrates these factors to help managers understand and apply recommendations to create a more mature cyber security culture in their organization.

A framework for andacomputational model of organizational behavior based on an artificial adaptive system (AAS) is presented. An AAS, a modeling approach based on genetic algorithms, enables the modeling of organizational learning and adaptability.This learning can be represented as decisions to allocate resources to the higher performing organizational agents (i.e., individuals, groups, departments, or processes, depending on the level of analysis) critical to the organization's survival in different environments. Adaptability results from the learning function enabling the organizations to change as the environment changes. An AAS models organizational behavior from a micro-unit perspective, where organizational behavior is a function of the aggregate actions and interactions of each of the individual agents of which the organization is composed. An AAS enables organizational decision making in a dynamic environment to be modeled as a satisficing process and not as a maximization process. To demonstrate the feasibility and usefulness of such an approach, a financial trading adaptive system (FTAS) organization is computationally modeled based on the AAS framework. An FfAS is an example of how the learning mechanism in an AAS can be used to allocate resources to critical individuals, processes, functions, or departments within an organization.

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