Search AMIA.org

This project examined and produced a general practice (GP) based decision support tool (DST), namely POLAR Diversion, to predict a patient's risk of emergency department (ED) presentation. The tool was built using both GP/family practice and ED data, but is designed to operate on GP data alone.

Despite evidence suggesting higher quality and safer care in hospitals with comprehensive electronic health record (EHR) systems, factors related to advanced system usability remain largely unknown, particularly among nurses. Little empirical research has examined sociotechnical factors, such as the work environment, that may shape the relationship between advanced EHR adoption and quality of care.

Investigators conducting prospective clinical trials must report patient flow using the Consolidated Standards of Reporting Trials (CONSORT) statement. Depending on how data are collected, this can be a laborious, time-intensive process. However, because many trials enter data electronically, CONSORT diagrams may be generated in an automated fashion.

Disadvantaged populations, including minorities and the elderly, use patient portals less often than relatively more advantaged populations. Limited access to and experience with technology contribute to these disparities. Free access to devices, the Internet, and technical assistance may eliminate disparities in portal use.

To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions.

Blockchain-based platforms are emerging to provide solutions for technical and governance challenges associated with genomic data sharing. Providing capabilities for distributed data stewardship and participatory access control along with effective ways for enforcement of the data access agreements and data ownership are among the major promises of these platforms.

Accurate and efficient identification of complex chronic conditions in the electronic health record (EHR) is an important but challenging task that has historically relied on tedious clinician review and oversimplification of the disease. Here we adapt methods that allow for automated "noisy labeling" of positive and negative controls to create a "silver standard" for machine learning to automate identification of systemic lupus erythematosus (SLE). Our final model, which includes both [...]

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) people experience significant health disparities across the life course and require health care that addresses their unique needs. Collecting information on the sexual orientation and gender identity (SO/GI) of patients and entering SO/GI data in electronic health records has been recommended by the Institute of Medicine, the Joint Commission, and the Health Resources and Services Administration as fundamental to improving access to and [...]

Clinical interface terminologies (CITs) consist of terms designed for clinical documentation and, through mappings to standardized vocabularies, to support secondary uses of patient data, including clinical decision support, quality measurement, and billing for health care services. The latter purpose requires maps to administrative coding systems, such as the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), for diagnoses in the United States.