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Our objective is to develop algorithms for encoding clinical text into representations that can be used for a variety of phenotyping tasks.

The study sought to present the findings of a systematic review of studies involving secondary analyses of data coded with standardized nursing terminologies (SNTs) retrieved from electronic health records (EHRs).

Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP).

The study sought to characterize institution-wide participation in secure messaging (SM) at a large academic health network, describe our experience with electronic medical record (EMR)-based cohort selection, and discuss the potential roles of SM for research recruitment.

Clinical decision support (CDS) systems are prevalent in electronic health records and drive many safety advantages. However, CDS systems can also cause unintended consequences. Monitoring programs focused on alert firing rates are important to detect anomalies and ensure systems are working as intended. Monitoring efforts do not generally include system load and time to generate decision support, which is becoming increasingly important as more CDS systems rely on external, web-based [...]

Despite the widespread and increasing use of electronic health records (EHRs), the quality of EHRs is problematic. Efforts have been made to address reasons for poor EHR documentation quality. Previous systematic reviews have assessed intervention effectiveness within the outpatient setting or paper documentation. The purpose of this systematic review was to assess the effectiveness of interventions seeking to improve EHR documentation within an inpatient setting.

Prospective enrollment of research subjects in the fast-paced emergency department (ED) is challenging. We sought to develop a software application to increase real-time clinical trial enrollment during an ED visit. The Prospective Intelligence System for Clinical Emergency Services (PISCES) scans the electronic health record during ED encounters for preselected clinical characteristics of potentially eligible study participants and notifies the treating physician via mobile phone text alerts. PISCES alerts began 3 [...]