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To examine the implications for clinical informatics of an inflection in open foundation models designed for on-device and edge deployment, exemplified by the Qwen 3.5 small series (2 March 2026) and Gemma 4 (2 April 2026).

Developing technology may assist paramedics in the competing tasks of providing life-saving care and accurately documenting that care. The objective of this study was to identify and classify paramedic user requirements for speech recognition (SR)-aided documentation.

Objectives To design and evaluate the usability of an electronic health record (EHR)-integrated clinical decision support (CDS) prototype supporting pediatric surgical site infection (SSI) risk estimation and preoperative optimization using a multi-phase human-centered design approach. Methods We conducted a three-phase study at a quaternary pediatric academic health system involving clinicians from anesthesia and seven surgical specialties. Phase 1 used contextual inquiry to examine preoperative information gathering, infection risk assessment, and [...]

Patient portal messaging connects patients with their healthcare teams but is underused by Spanish-speaking patients.

Diagnostic errors are common in medical care and can significantly affect patient outcomes. Symptom checker apps promise to help patients understand their symptoms, possible diagnoses and actions to take, but lack evidence on accuracy, safety and usability.

Sepsis is a life-threatening condition in which delayed recognition and treatment are associated with increased mortality. While predictive models such as Epic's Early Detection of Sepsis Model (ESM) were developed to support early intervention, their real-world effects after integration into clinical workflows remain difficult to evaluate.

Background Though interruptive alerts, or pop-ups, are one of the most common forms of clinical decision support (CDS) tools within the electronic health record (EHR), they are often ignored. Interruptive alerts have the potential to enhance patient care and reduce clinician burden, but end-users frequently experience alert fatigue and override alerts, defeating their purpose. Few studies have elicited the perspectives of all stakeholder groups involved in the development, experience, and [...]

BACKGROUND: The use of large language model (LLM)-based artificial intelligence (AI) to assess the quality of outpatient mental health documentation represents an understudied application. Critical questions remain about the effects of exposing human auditors to AI-generated recommendations on auditor efficiency, agreement, and patterns of decision-making.

OBJECTIVE: Assess inter-rater agreement on clinician- and clinical decision support (CDS)-driven diuretic titrations and risk classifications to benchmark a semi-autonomous CDS (OTTO-FM).

OBJECTIVES: The objective of this study is to evaluate the effect of a continuous remote patient monitoring (CRPM) program on reducing 30-day readmissions in a case-versus-retrospective-propensity-matched-control study of heart failure (HF) patients.