Search AMIA.org

To systematically synthesize the literature on information visualizations of symptoms included as National Institute of Nursing Research common data elements and designed for use by patients and/or healthcare providers.

Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology Gamuts Ontology (RGO)-an ontology of 16 918 diseases, interventions, and imaging observations-provides a resource for differential diagnosis and automated textual report understanding in radiology. An automated process with subsequent manual review was used to identify exact and partial matches of RGO entities to the Disease Ontology (DO) and the Human Phenotype Ontology (HPO). Exact mappings identified equivalent concepts [...]

To better understand the real-world effects of pharmacogenomic (PGx) alerts, this study aimed to characterize alert design within the eMERGE Network, and to establish a method for sharing PGx alert response data for aggregate analysis. Seven eMERGE sites submitted design details and established an alert logging data dictionary. Six sites participated in a pilot study, sharing alert response data from their electronic health record systems. PGx alert design varied, with [...]

The creation of people-driven data collaboratives, with governance structures that enable participants to have a meaningful voice in issues surrounding the use of their own data, is a novel strategy to harness our growing capacity to develop and maintain immense data assets from the real health experiences of individuals.

To determine the effects of an inpatient portal intervention on patient activation, patient satisfaction, patient engagement with health information, and 30-day hospital readmissions.

To quantify how stress related to use of health information technology (HIT) predicts burnout among physicians.

Most electronic health records display historical medication information only in a data table or clinician notes. We designed a medication timeline visualization intended to improve ease of use, speed, and accuracy in the ambulatory care of chronic disease.

Information reconciliation is a common yet complex and often time-consuming task performed by healthcare providers. While electronic health record systems can receive "outside information" about a patient in electronic documents, rarely does the computer automate reconciling information about a patient across all documents.

The clinical diagnosis of genetic disorders is undergoing transformation, driven by whole exome sequencing and whole genome sequencing (WES/WGS). However, such nucleotide-level resolution technologies create an interpretive challenge. Prior literature suggests that clinicians may employ characteristic cognitive processes during WES/WGS investigations to identify disruptions in genes causal for the observed disease. Based on cognitive ergonomics, we designed and evaluated a gene prioritization workflow that supported these cognitive processes.