Search AMIA.org

The Internet and social media are revolutionizing how social support is exchanged and perceived, making online health communities (OHCs) one of the most exciting research areas in health informatics. This paper aims to provide a framework for organizing research of OHCs and help identify questions to explore for future informatics research. Based on the framework, we conceptualize OHCs from a social support standpoint and identify variables of interest in characterizing [...]

We explored whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would improve model performance in predicting initial diagnosis of heart failure (HF) compared to conventional methods that ignore temporality.

Electronic trigger detection tools hold promise to reduce Adverse drug event (ADEs) through efficiencies of scale and real-time reporting. We hypothesized that such a tool could automatically detect medication dosing errors as well as manage and evaluate dosing rule modifications.

Quantifying alert override has been the focus of much research in health informatics, with override rate traditionally viewed as a surrogate inverse indicator for alert effectiveness. However, relying on alert override to assess computerized alerts assumes that alerts are being read and determined to be irrelevant by users. Our research suggests that this is unlikely to be the case when users are experiencing alert overload. We propose that over time [...]

We have developed an interface to serve patient data from Informatics for Integrating Biology and the Bedside (i2b2) repositories in the Fast Healthcare Interoperability Resources (FHIR) format, referred to as a SMART-on-FHIR cell. The cell serves FHIR resources on a per-patient basis, and supports the "substitutable" modular third-party applications (SMART) OAuth2 specification for authorization of client applications. It is implemented as an i2b2 server plug-in, consisting of 6 modules: authentication [...]

Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, and is time- and labor-intensive. We developed and evaluated 4 types of phenotyping algorithms and categories of EHR information to identify hypertensive individuals and controls and provide a portable module for implementation at other sites.

This paper outlines the implementation of a comprehensive clinical pharmacogenomics (PGx) service within a pediatric teaching hospital and the integration of clinical decision support in the electronic health record (EHR).

Patients with limited health literacy (LHL) and limited English proficiency (LEP) experience suboptimal communication and health outcomes. Electronic health record implementation in safety net clinics may affect communication with LHL and LEP patients.We investigated the associations between safety net clinician computer use and patient-provider communication for patients with LEP and LHL.