Comments on return on investment (ROI) as it applies to clinical systems.
Author(s): Frisse, Mark E
DOI: 10.1197/jamia.M2072
Author(s): Frisse, Mark E
DOI: 10.1197/jamia.M2072
Many computerized physician order entry (CPOE) systems have integrated drug safety alerts. The authors reviewed the literature on physician response to drug safety alerts and interpreted the results using Reason's framework of accident causation. In total, 17 papers met the inclusion criteria. Drug safety alerts are overridden by clinicians in 49% to 96% of cases. Alert overriding may often be justified and adverse drug events due to overridden alerts are [...]
Author(s): van der Sijs, Heleen, Aarts, Jos, Vulto, Arnold, Berg, Marc
DOI: 10.1197/jamia.M1809
The idea of testing a hypothesis is central to the practice of biomedical research. However, the results of testing a hypothesis are published mainly in the form of prose articles. Encoding the results as scientific assertions that are both human and machine readable would greatly enhance the synergistic growth and dissemination of knowledge.
Author(s): Dinakarpandian, Deendayal, Lee, Yugyung, Vishwanath, Kartik, Lingambhotla, Rohini
DOI: 10.1197/jamia.M1910
Motivated by the need to push further our understanding of physicians' acceptance of clinical information systems, we propose a relatively new construct, namely, psychological ownership. We situated the construct within a nomological net using a prevailing and dominant information technology adoption behavior model as a logical starting point.
Author(s): Paré, Guy, Sicotte, Claude, Jacques, Hélène
DOI: 10.1197/jamia.M1930
Author(s): Lindberg, Donald A B
DOI: 10.1197/jamia.M2022
Recently there has been a remarkable upsurge in activity surrounding the adoption of personal health record (PHR) systems for patients and consumers. The biomedical literature does not yet adequately describe the potential capabilities and utility of PHR systems. In addition, the lack of a proven business case for widespread deployment hinders PHR adoption. In a 2005 working symposium, the American Medical Informatics Association's College of Medical Informatics discussed the issues [...]
Author(s): Tang, Paul C, Ash, Joan S, Bates, David W, Overhage, J Marc, Sands, Daniel Z
DOI: 10.1197/jamia.M2025
The Public Health Information Network (PHIN) Preparedness initiative strives to implement, on an accelerated pace, a consistent national network of information systems that will support public health in being prepared for public health emergencies. Using the principles and practices of the broader PHIN initiative, PHIN Preparedness concentrates in the short term on ensuring that all public health jurisdictions have, or have access to, systems to accomplish known preparedness functions. The [...]
Author(s): Loonsk, John W, McGarvey, Sunanda R, Conn, Laura A, Johnson, Jennifer
DOI: 10.1197/jamia.M1815
Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. Our objective was to improve clinician acceptance of drug alerts by designing a selective set of drug alerts for the ambulatory care setting and minimizing workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow. The alerts were presented to clinicians using computerized prescribing within an [...]
Author(s): Shah, Nidhi R, Seger, Andrew C, Seger, Diane L, Fiskio, Julie M, Kuperman, Gilad J, Blumenfeld, Barry, Recklet, Elaine G, Bates, David W, Gandhi, Tejal K
DOI: 10.1197/jamia.M1868
Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes.
Author(s): Demner-Fushman, Dina, Few, Barbara, Hauser, Susan E, Thoma, George
DOI: 10.1197/jamia.M1911
The authors performed this study to determine the accuracy of several text classification methods to categorize wrist x-ray reports. We randomly sampled 751 textual wrist x-ray reports. Two expert reviewers rated the presence (n = 301) or absence (n = 450) of an acute fracture of wrist. We developed two information retrieval (IR) text classification methods and a machine learning method using a support vector machine (TC-1). In cross-validation on [...]
Author(s): de Bruijn, Berry, Cranney, Ann, O'Donnell, Siobhan, Martin, Joel D, Forster, Alan J
DOI: 10.1197/jamia.M1995