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Healthcare information technologies are now a routine component of patient-clinician interactions. Originally designed for operational functions including billing and regulatory compliance, these systems have had unintended consequences including increased exam room documentation, divided attention during the visit, and use of scribes to alleviate documentation burdens. In an age in which technology is ubiquitous in everyday life, we must re-envision healthcare technology to support both clinical operations and, above all, the [...]

Electronic health records (EHRs) were expected to yield numerous benefits. However, early studies found mixed evidence of this. We sought to determine whether widespread adoption of modern EHRs in the US has improved clinical care.

We aimed to investigate bias in applying machine learning to predict real-world individual treatment effects.

Alert fatigue limits the effectiveness of medication safety alerts, a type of computerized clinical decision support (CDS). Researchers have suggested alternative interactive designs, as well as tailoring alerts to clinical roles. As examples, alerts may be tiered to convey risk, and certain alerts may be sent to pharmacists. We aimed to evaluate which variants elicit less alert fatigue.

The study sought to develop and evaluate an electronic health record-based child abuse clinical decision support system in 2 general emergency departments.

This study aimed to develop a novel, regulatory-compliant approach for openly exposing integrated clinical and environmental exposures data: the Integrated Clinical and Environmental Exposures Service (ICEES).

We assess working relationships and collaborations within and between diabetes health care provider teams using social network analysis and a multi-scale community detection.

Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article, we assessed the ability of natural language processing (NLP) systems to unlock DDC information from clinical narratives automatically.