Search AMIA.org

Drug-drug interactions (DDIs) are an important consideration in both drug development and clinical application, especially for co-administered medications. While it is necessary to identify all possible DDIs during clinical trials, DDIs are frequently reported after the drugs are approved for clinical use, and they are a common cause of adverse drug reactions (ADR) and increasing healthcare costs. Computational prediction may assist in identifying potential DDIs during clinical trials.

Critical care environments are information-intensive environments where effective decisions are predicated on successfully finding and using the 'right information at the right time'. We characterize the differences in processes and strategies of information seeking between residents, nurse practitioners (NPs), and physician assistants (PAs).

In a previous study, we developed the Health Information Technology Usability Evaluation Scale (Health-ITUES), which is designed to support customization at the item level. Such customization matches the specific tasks/expectations of a health IT system while retaining comparability at the construct level, and provides evidence of its factorial validity and internal consistency reliability through exploratory factor analysis.

We conducted a prospective evaluation of different forms of electronic health record (EHR) systems to better understand the costs incurred during implementation and the factors that can influence these costs.

The Secretary of Health and Human Services (HHS) acting through the Food and Drug Administration (FDA), and in collaboration with the Federal Communications Commission (FCC) and Office of the National Coordinator for Health IT (ONC) was tasked with delivering a report on an appropriate, risk-based regulatory framework for health information technology (IT). An expert stakeholder group was established under the auspices of the Health IT Policy Committee to help provide [...]

To evaluate attitudes regarding privacy of genomic data in a sample of patients with breast cancer.

To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors.

Health information technology (HIT) can increase preventive care. There are hopes and fears about the impact of HIT on racial disparities in cancer screening.

To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread.

To determine the sensitivity and specificity of a dosing alert system for dosing errors and to compare the sensitivity of a proprietary system with and without institutional customization at a pediatric hospital.