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To evaluate ChatGPT's ability to perform thematic analysis of medical Best Practice Advisory (BPA) free-text comments and identify prompt engineering strategies that optimize performance.

Sleep quality critically influences recovery in neurological patients, yet its longitudinal monitoring during hospitalization remains limited. Nursing narrative notes offer an underutilized resource to track sleep trajectories objectively across time.To propose and apply a formal pipeline that integrates structured clinical data and unstructured nursing annotations to monitor sleep trajectories during post-acute inpatient neurorehabilitation, relying exclusively on free-to-use software tools and without increasing nursing workload.A total of 17,039 nighttime nursing annotations [...]

Patient experience mechanisms (e.g., safety netting, patient partnership) are routinely used by health care professionals (HCPs) to support high-quality care. However, there is limited synthesis of these mechanisms across studies, and little is known about how they translate to virtual care.This study aimed to conduct a scoping review to (1) identify mechanisms used by HCPs to enhance patient experience during consultations and (2) to consider how these may be adapted [...]

Anticoagulation decisions in atrial fibrillation (AF) depend on balancing stroke and bleeding risk, often guided by CHA2DS2-VASc (a validated clinical score used to estimate stroke risk in patients with atrial fibrillation) and HAS-BLED (a validated clinical score used to estimate bleeding risk in patients treated with anticoagulation) scores. Manual calculation of these scores can be time-consuming and inconsistently performed.This study evaluated whether implementing real-time, electronic health record (EHR)-integrated alerts in [...]

Clinical documentation improvement is critical for pediatric care, yet leveraging electronic health record (EHR) tools for this population is not well established. We aimed to adapt and implement a real-time, automated documentation assistance tool (AutoDx) to decrease clinical documentation integrity (CDI) coding queries and improve perceived ease of practice for pediatric inpatient providers.In this quality improvement study at an urban academic pediatric hospital, we adapted and implemented AutoDx for pediatric [...]

Pain medicine triage plays a crucial role in ensuring patients receive timely and appropriate care by scheduling them to the most suitable treatment path. However, the absence of standardized triage protocols in pain medicine often leads to inefficiencies, including delay of care and wastage of healthcare resources.This study aims to develop a rule-based automated referral triage system leveraging information from patients' medical notes for scheduling patients to specific procedures in [...]

Effective communication in the intensive care unit (ICU) is essential, particularly for patients with non-English language preference, yet timely access to professional interpreters remains limited. While artificial intelligence (AI)-based translation tools have been explored in outpatient and nonacute care settings, studies evaluating their use in acute care, environments such as the ICU remain limited. To address this gap, we developed AI-TransLATE (AI-enhanced Transition to Language-Agnostic Transcultural Engagement), a speech-based translation [...]

Many academic medical centers (AMCs) rely on systems like the Vizient Quality and Accountability Scorecard to track quality metrics such as the observed-to-expected (O/E) mortality ratio. The O/E mortality ratio calculation relies on clinical documentation. Missed documentation of diagnoses and risk factors for mortality leads to an underestimated expected mortality, which negatively affects the O/E metric.We aimed to reduce our O/E mortality ratio from a median of 1.08 (± 0.10) to [...]

The German Federal Ministry of Health introduced the Pflegepersonalregelung 2.0 (PPR 2.0) to address the nursing staffing crisis. It establishes a framework to determine personnel requirements, ensuring adequate staffing. However, the required daily classification of patient care levels imposes a significant administrative burden on nursing staff. Digitizing this process may reduce documentation time and enhance efficiency, but effectiveness depends on usability and acceptance.This study evaluates the acceptance and usability of [...]

Claude Opus 4 is a large language model (LLM) that features improved reasoning capabilities and broader contextual understanding compared to earlier versions. Despite the growing use of LLM systems for seeking medical information, structured and simulation-based evaluations of Claude Opus 4's capabilities in diabetes management remain limited, particularly across domains such as patient education, clinical reasoning, and emotional support.This study aimed to conduct a baseline evaluation of Claude Opus 4's [...]