Search AMIA.org

We aim to investigate the application and accuracy of artificial intelligence (AI) methods for automated medical literature screening for systematic reviews.

Assess the effectiveness of providing Logical Observation Identifiers Names and Codes (LOINC®)-to-In Vitro Diagnostic (LIVD) coding specification, required by the United States Department of Health and Human Services for SARS-CoV-2 reporting, in medical center laboratories and utilize findings to inform future United States Food and Drug Administration policy on the use of real-world evidence in regulatory decisions.

Certified electronic health record (EHR) technology has been adopted by most hospitals and health care providers. In 2015, the Office of the National Coordinator for Health Information Technology (ONC) published new EHR certification requirements, known as the 2015 Edition. To date, no research has examined the impact of hospitals' adoption of the 2015 Edition on health care delivery.

Sepsis has a high rate of 30-day unplanned readmissions. Predictive modeling has been suggested as a tool to identify high-risk patients. However, existing sepsis readmission models have low predictive value and most predictive factors in such models are not actionable.

This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether using text data in addition to more commonly used structured data improves the prediction performance.

Participant willingness to share electronic health record (EHR) information is central to success of the National Institutes of Health All of Us Research Program (AoURP). We describe the demographic characteristics of participants who decline access to their EHR data.

To assess whether previously observed differences in interoperable exchange by physician practice size persisted in 2019 and identify the role of 3 factors shaping interoperable exchange among physicians in practices of varying sizes: Federal incentive programs designed to encourage health IT use, value-based care, and selection of electronic health record (EHR) developer.

The goals of this study were to harmonize data from electronic health records (EHRs) into common units, and impute units that were missing.

We conducted a horizon scan to (1) identify challenges in patient-centered clinical decision support (PC CDS) and (2) identify future directions for PC CDS.