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Clinical decision support (CDS) tools in electronic health records (EHRs) often face low uptake due to limited usability, workflow integration, and other implementation issues. We recently designed and implemented the STRATIFY-CDS tool, which calculates a validated risk-prediction model and recommends disposition for emergency department (ED) patients with acute heart failure. Despite applying human-centered design and implementation science strategies, initial utilization in the first 3 months of the STRATIFY-CDS tool was [...]

Hospitals are looking to AI and other innovative applications to help alleviate provider burden and dissatisfaction associated with clinical documentation in oncology. Ambient artificial intelligence (AI) scribes are a promising technology to address these issues. However, they generally have not been optimized for oncology. This study aimed to evaluate an ambient AI scribe application with oncology providers to determine opportunities and potential challenges.This prospective pilot study of a scribe application [...]

The goal of national interoperability is to improve care quality and decrease administrative burden and costs. Patients, providers, and other stakeholders are increasingly concerned that indiscriminate sharing of data may have deleterious, permanent consequences, as well as fail to provide granular control over the sharing of individual health data. Data segmentation and consent standards to date have been limited in scope and implementation, which has hindered efforts to scale data [...]

As healthcare delivery becomes increasingly digital, nursing informatics knowledge has become essential for nurses to participate effectively in digitally enabled healthcare environments. The Canadian Association of Schools of Nursing (CASN) released updated nursing informatics entry-to-practice competencies in 2025 to inform nursing education in Canada. However, the integration of informatics knowledge and content into nursing curricula and professional practice education remains inconsistent. Mapping the teaching strategies used by nursing educators to [...]

Studies on symptom concordance between patients and their caregivers often use cross-sectional designs, which may fail to capture the longitudinal, dynamic symptom experience. The Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) is a remote health monitoring system that utilizes smartwatches and ecological momentary assessments (EMAs) to empower patients and caregivers to monitor and manage cancer pain at home. BESI-C collects real-time symptom data in naturalistic settings, enabling longitudinal [...]

Major depression in adolescents is recognized as a serious psychiatric illness and a risk factor for suicide. It is important for providers to screen for depression and suicidality and have clinical decision support (CDS) for evaluation, risk assessment, and initial management. Our efforts focused on leveraging the electronic health record (EHR) to ensure that high-risk adolescents received appropriate interventions before leaving the office.This study aims to improve notification of positive [...]

This study aimed to develop a human factors assessment for medication-related clinical decision support (CDS) based on a previously validated tool that assessed the integration of human factors principles in CDS, the instrument for evaluating human factors principles in medication-related decision support alerts (I-MeDeSA), and pilot it with 10 outpatient clinics across the United States.The human factors assessment was developed based on past validations of I-MeDeSA. Examples included changing the [...]

Our objective is to compare different pre-training strategies for electronic health record (EHR) foundation models.

Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment recommendations, and resource allocation. However, its implementation also raises ethical concerns, particularly regarding biases in AI algorithms trained on inequitable data, which may reinforce health disparities. This article introduces the AI COmmunity-based Ethical Dialogue and DEcision-making (CODE) framework to embed ethical deliberation into AI development, focusing on Electronic Health Records (EHRs).

Emergency department (ED) handoff to inpatient teams is a potential source of error. Generative artificial intelligence (AI) has shown promise in succinctly summarizing large quantities of clinical data and may help improve ED handoff.Our objectives were to: (1) evaluate the accuracy, clinical utility, and safety of AI-generated ED-to-inpatient handoff summaries; (2) identify patient and visit characteristics influencing summary effectiveness; and (3) characterize potential error patterns to inform implementation strategies.This exploratory [...]