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validity and reliability of the confusion assessment method for the intensive care

t is essential to remember the nuances in these data. What is clear from the literature in this area is that HIT adoption alone is not likely to result in meaningful improvements in safety or quality. For example, while HIT offers significant advantages in terms of accessibility and legibility over paper records, this does not result directly in improved patient-centered outcomes. Even in situations where HIT would appear to offer clear advantages over paper-based alternatives, such as the availability of electronic prescribing with in-built alerts, HIT adoption has a very real potential to disrupt established practices and result in worse outcomes for patients, decreased efficiency, and increased cost [9,10]. In one particular study, Han and colleagues [10] reported that the adoption of a commercially available physician order entry system was associated with a two-fold increase in severity-adjusted mortality in a pediatric ICU. In order to best leverage the potential advantages of HIT adoption, a more refined understanding of how technology disrupts or supports health care providers’ ability to deliver high quality care is needed. The field of systems engineering offers some promising tools that may be adapted to the study of health care delivery, providing a buffer against some of the unintended consequences of HIT adoption and highlighting new mechanisms for improving care delivery [11]. The primary task of this approach is to identify the most relevant characteristics of a system and to represent it in a mathematical model. These models can be analyzed to reveal patterns in the behavior of the system and to devise and test improvements. This process is radically different from the classical hypothesis-driven epidemiological approach to biomedical research