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 This study aimed to assist residents in selecting the correct Current Procedural Terminology (CPT) code for evaluation and management (E/M) services through the addition of disappearing help text into a standardized note template.

 The NIH Pragmatic Trials Collaboratory supports the design and conduct of 31 embedded pragmatic clinical trials, and many of these trials use patient-reported outcome measures (PROMs) to provide valuable information about the patients' health and wellness. Often these trials enroll medically underserved patients, including people with incomes below the federal poverty threshold, racial or ethnic minority groups, or rural or frontier communities.

 Healthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care. Ambient artificial intelligence (AI) offers a novel approach to mitigating burnout by reducing the documentation burden through advanced speech recognition and natural language processing technologies that summarize the patient encounter into a clinical note to be [...]

 Effective data management is critical in medical informatics research, ensuring the success and integrity of clinical studies. However, students often lack comprehensive training in this area, highlighting the need for tailored educational programs.

To assess the efficacy of a biomedical informatics boot camp with regards to improving the skill sets of its participants.

Despite the proven usefulness of appropriate clinical decision support (CDS) alerts, many CDS systems fire excessive, clinically irrelevant alerts that are often ignored by clinicians. We have developed a method to suppress false-positive alerts based on prior drug tolerance but encountered substantial barriers to integrate the method into widely adopted commercial electronic health record (EHR) systems.

Direct electronic access to multiple electronic health record (EHR) systems through patient portals offers a novel avenue for decentralized research. Given the critical value of patient characterization, we sought to compare computable evaluation of health conditions from patient-portal EHR against the traditional self-report.

We developed and validated a large language model (LLM)-assisted system for conducting systematic literature reviews in health technology assessment (HTA) submissions.

At a large quaternary health system, tissue specimens were frequently sent to the microbiology laboratory with an incorrect wound culture order meant for swab specimens due to poor electronic health record menu design. Wound cultures were also requested in chronic wound cases with a low index of suspicion for acute infection.

The objective of this study is to provide an overview of the current landscape of individualized treatment effects (ITE) estimation, specifically focusing on methodologies proposed for time-series electronic health records (EHRs). We aim to identify gaps in the literature, discuss challenges, and propose future research directions to advance the field of personalized medicine.