Journal of biomedical informatics
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Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. ⋯ We show that side effect knowledge from JCO articles is largely complementary to that from the US Food and Drug Administration (FDA) drug labels. Through integrative correlation analysis, we show that targeted drug-associated side effects positively correlate with their gene targets and disease indications. In conclusion, this unique database that we built from a large number of high-profile oncological articles could facilitate the development of computational models to understand toxic effects associated with targeted anticancer drugs.
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Bioengineering is a field in expansion. New technologies are appearing to provide a more efficient treatment of diseases or human deficiencies. Implantable Medical Devices (IMDs) constitute one example, these being devices with more computing, decision making and communication capabilities. ⋯ This article surveys the main security goals for the next generation of IMDs and analyzes the most relevant protection mechanisms proposed so far. On the one hand, the security proposals must have into consideration the inherent constraints of these small and implanted devices: energy, storage and computing power. On the other hand, proposed solutions must achieve an adequate balance between the safety of the patient and the security level offered, with the battery lifetime being another critical parameter in the design phase.
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Comparative Study
The value of Retrospective and Concurrent Think Aloud in formative usability testing of a physician data query tool.
To compare the performance of the Concurrent (CTA) and Retrospective (RTA) Think Aloud method and to assess their value in a formative usability evaluation of an Intensive Care Registry-physician data query tool designed to support ICU quality improvement processes. ⋯ In this study, the CTA is more effective in usability-problem detection and provided clarification of intensive care physician query design strategies to inform redesign of the query tool. However, CTA does not outperform RTA. The RTA additionally elucidated unique usability problems and new user requirements. Based on the results of this study, we recommend the use of CTA in formative usability evaluation studies of health information technology. However, we recommend further research on the application of RTA in usability studies with regard to user expertise and experience when focusing on user profile customized (re)design.
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Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems. ⋯ Phenotypic topics learned from EHR data can be more stable and transferable than billing codes for characterizing the general status of a patient population. This suggests that EHR-based research may be able to leverage such phenotypic topics as variables when pooling patient populations in predictive models.
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To facilitate personalized drug dosing (PDD), this pilot study explored the communication effectiveness and clinical impact of using a prototype clinical decision support (CDS) system embedded in an electronic health record (EHR) to deliver pharmacogenomic (PGx) information to physicians. We employed a conceptual framework and measurement model to access the impact of physician characteristics (previous experience, awareness, relative advantage, perceived usefulness), technology characteristics (methods of implementation-semi-active/active, actionability-low/high) and a task characteristic (drug prescribed) on communication effectiveness (usefulness, confidence in prescribing decision), and clinical impact (uptake, prescribing intent, change in drug dosing). Physicians performed prescribing tasks using five simulated clinical case scenarios, presented in random order within the prototype PGx-CDS system. ⋯ Specifically, sixty-five percent of physicians reduced their dosing, significantly for capecitabine (p=0.002) and mercaptopurine/thioguanine (p=0.03). These findings suggest a need to improve our prototype such that PGx CDS content is more useful and delivered in a way that improves physician's confidence in their prescribing decisions. The greatest increases in communication effectiveness and clinical impact of PGx-CDS are likely to be realized through continued focus on content, content delivery, and tailoring to physician characteristics.