The primary focus of this teaching case is the patient journey, as facilitated and influenced by an e-system or electronic health record (EHR) system. The goal of this case is to provide the learner with the knowledge and skills needed to effectively incorporate patient-centered e-health (PCEH) principles into existing and planned e-health systems such as EHRs. This case can be used to help students understand a hospital experience from the perspective of a patient and her family. It is loosely based on an experience one of the authors had with an actual patient. This case is intended for use with upper level undergraduate and graduate health informatics, information systems, and nursing students. Students assigned to this case should have a working knowledge of clinical terms and the general workings of a hospital. This teaching case is best suited to an advanced course in a health informatics curriculum. Possible applications of the case include, but are not limited to, describing the patient journey, modeling the process flow, diagramming the data flow, and applying the principles of patient-centered ehealth.
This study proposes that structured labs using groups can help foster individual student acceptance of software engineering methodologies. The technology acceptance model (TAM) is employed in an empirical test using students in freshman and sophomore‐level programming courses. Our findings suggest that a structured group lab experience does influence a student's belief system regarding the usefulness of a software engineering methodology, leading to an individual decision to accept and use the methodology on a voluntary basis. On average, the software engineering methodology was accepted by the students sampled. We recommend that structured group labs be designed to use peer groups, reinforce successful results, and use an iterative process design with phase‐by‐phase deliverables.
Effective IT curricula balances tradition with innovation. One way to enhance that balance is to examine the common threads in the various knowledge areas.The movement toward a more applied and professional computing degree has resulted in the creation of new programs in IT schools [5]. Arguably, the development of IT curricula is one of the most important educational innovations in recent years. Such IT innovativeness comes from an attempt to move beyond the confines of traditional academic and disciplinary boundaries to meet the breadth of knowledge needed by the IT This evolution tends to follow d cycli-developing competing variations oi IT. cal pattern [1]. First there is the introduc-From these alternative designs and the tion of the new idea or innovation, work of computing associations, such as followed hy a period of variation where the IT Dean's Council, a standard will innovators experiment with alternative eventually emerge allowing IT to reach designs hased on the new idea. During the level of maturity comparable to this period, alternative designs draw inspi-traditional computing disciplines, ration from prior and current knowledge Because the IT movement is in a and practice. For the innovation to he period of variation, we thought it worthwidely adopted, one of the competing white to look for inspiration for alternavariations must emerge as the standard or tive designs in current knowledge areas of norm. Once this happens, the innovation computing and IT degree programs. We is refined and improved until the next looked at knowledge areas across a broad major innovation comes along to threaten set of computing programs to discover a its position as the established norm.focus that transcends disciplinary special-The evolution of IT programs is fol-ization with an ultimate eye toward the lowing a similar cyclical pattern. As the emergence of an established norm. What growth of IT programs continues to gain we found was a set of common knowlmomentum, innovative schools with tra-edge areas that focus on what we dcscrihe ditional computing degree programs are as the systems development process.
Manufacturing industries in the IT sector, which are characterized by very low inertia, rapid technological change, and swift technological obsolescence, are a vivid example of how the rapid and effective commercialization of technical advances is critical to the success of high‐technology industries. Radical or breakthrough technologies have both short‐ and long‐term impacts. This paper argues that classical technology diffusion modeling approaches fail to give a fully dynamic picture of technology adoption in an industry, and do not adequately capture dynamic transients caused by short‐term trends and the effect of individual technical changes. It then demonstrates the usefulness of the system dynamics approach in modeling the long‐term system behavior of the commercialization process arising from the dynamic transients caused by short‐term trends and rare events in IT producing industries. Capturing such dynamic transients is critically important because the commercialization process is ultimately shaped by individual decision‐makers making the strategic investment decisions within an industry operating in a particular short‐term context. Copyright © 1999 John Wiley & Sons, Ltd.
Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.
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