Session Type
Meeting
Search Results for IgE
Abstract Number: 62
SHM Converge 2024
Background: Interprofessional collaboration (IPC) is vital for high-quality patient care, and effective IPC among medical professionals, especially trainees, is crucial to supporting positive individual and team outcomes. Measuring IPC and understanding its impact on patient care remains underexplored. Understanding which IPC patterns are associated with better patient and individual outcomes will inform how to best [...]
Abstract Number: 65
SHM Converge 2024
Background: By law, patients have prompt access to electronic discharge notes in their charts. Technical language and abbreviations make notes difficult to read and understand for a typical patient. Large language models such as GPT-4 may have the potential to transform these notes into patient-friendly language and format. Our objective was to determine whether GPT-4 [...]
Abstract Number: 82
Hospital Medicine 2016, March 6-9, San Diego, Calif.
Background: Oligella urethralis is an organism which is normally isolated as a commensal from the genitourinary tract. Clinical infection due to this organism is rarely reported in the literature. We hereby report a case series of six patients with oligella urethralis infection. We studied the clinical features, antibiotic susceptibility and clinical outcome in these patients. [...]
Abstract Number: L2
SHM Converge 2022
Case Presentation: A 79-year-old male with vasculopathy, hypertension, diastolic heart failure, and dialysis-dependent end stage renal disease presented after having hypotensive syncopal episodes during initiation of his last 3 outpatient dialysis sessions. Upon dialysis cessation, he quickly awakened fully oriented with a normal hemodynamics. On arrival, physical exam findings were unrevealing, as were a subsequent [...]
Abstract Number: 102
SHM Converge 2021
Background: The World Health Organization defines anemia in females as a hemoglobin (Hb)
Abstract Number: 244
SHM Converge 2024
Background: Artificial intelligence (AI) is increasingly being integrated into healthcare, but there is limited data on clinicians’ perceptions and preparedness regarding AI in medical practice. This survey aimed to understand clinicians’ knowledge, attitudes, and experiences of healthcare providers with AI tools in healthcare. This is crucial as the adoption of AI in healthcare can enhance [...]
Abstract Number: 246
SHM Converge 2021
Background: Advance care planning (ACP) helps patients plan end of life care in accordance with their goals and values, but is often performed too late and infrequently. Hospitalists play an important role in delivering ACP for patients admitted for serious illnesses, but often cite competing inpatient priorities, lack of time and training, and uncertainty about [...]
Abstract Number: 253
SHM Converge 2024
Background: Large Language Model (LLM) chatbots, like ChatGPT (from Open-AI), have received widespread attention in the last year for their ability to process large amounts of text data and produce human-like script responses on a wide array of topics. In particular, LLM chatbots have performed well in areas of patient communication, whether it’s answering cardiovascular [...]
Abstract Number: 258
SHM Converge 2024
Background: Clinicians, researchers, educators, and administrators have grappled with the implications of generative artificial intelligence (AI) in healthcare since the release of the first publicly available large language model (LLM) in late 2022. Efforts have been directed towards evaluating LLMs’ performance in common clinical and scholarly tasks and debating important considerations including patient safety, information [...]
Abstract Number: 266
SHM Converge 2024
Background: Diagnostic uncertainty, defined as the subjective perception of an inability to provide an accurate explanation of the patient’s health problem, has been implicated in diagnostic error.1 Clinician notes, such as the admission notes, often include hedging terms, uncertainty phrases, and diagnostic differentials that can be used to assess uncertainty in unstructured documentation.1,2 Quantifying diagnostic [...]