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Early clinical informatics (CI) education provides an introduction to CI methodologies for resident physicians to apply within their boarded specialties. A specialty notably absent from the effort to train residents in CI is psychiatry. We present a novel means of integrating CI exposure into a structured educational track within a psychiatry residency training program. The clinical informatics track at the University of North Carolina Department of Psychiatry is a 3-year [...]

This study evaluates and characterizes the use of a confidential clinic note type as part of the implementation of open notes at a free-standing children's hospital. We describe how this electronic health record feature which disables patient and family access to selected notes in the patient portal is used across our institution, which clinicians are using this feature, and the type of data our clinicians consider confidential.

To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.

The objective was to understand how people respond to coronavirus disease 2019 (COVID-19) screening chatbots.

Developing algorithms to extract phenotypes from electronic health records (EHRs) can be challenging and time-consuming. We developed PheMap, a high-throughput phenotyping approach that leverages multiple independent, online resources to streamline the phenotyping process within EHRs.

People with long-term conditions require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in long-term conditions.

Health and healthcare disparities continue despite clinical, research, and policy efforts. Large clinical datasets may not contain data relevant to healthcare disparities and leveraging these for research may be crucial to improve health equity. The Health Disparities Collaborative Research Group was commissioned by the Patient-Centered Outcomes Research Institute to examine the data science needs for quality and complete data and provide recommendations for improving data science around health disparities. The [...]

The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners.