Background: Frailty is linked to poor outcomes in older patients, especially those with multiple conditions. The electronic frailty index (eFI) is a validated tool based on the cumulative deficit model used to screen hospitalized patients at risk for poor outcomes1. The eFI relies on 35 ICD-10 codes associated with encounters across four domains (morbidity, sensory, [...]

Background: Frailty is linked to poor outcomes in older patients, especially those with multiple conditions. The electronic frailty index (eFI) is a validated tool based on the cumulative deficit model used to screen hospitalized patients at risk for poor outcomes1. The eFI relies on 35 ICD-10 codes associated with encounters across four domains (morbidity, sensory, [...]

Background: We created a generative artificial intelligence chatbot (“VLRChat”) that draws from a comprehensive curricular resource (the 480-page Vanderbilt Housestaff Handbook) to answer point-of-care clinical questions by hospitalists and inpatient clinical teams. Time constraints and cognitive overload frequently prevent hospitalist faculty and learners from determining the optimal, most current answers to clinical questions: as many [...]

Background: Hospitalists vary in their ordering practices related to labs, imaging, and discharge order times. Variations in these practices has been associated with over-utilization of services and inefficient clustering of discharges later in the day. Prior studies suggest that peer comparison can be effective to change provider behavior and reduce unnecessary variation in ordering practices, [...]

Background: Delirium, an acute neuropsychiatric syndrome marked by fluctuating disturbances in attention, cognition, and consciousness, is prevalent among older hospitalized cancer patients. The Mayo Delirium Prediction (MDP) tool, designed to predict delirium risk in older adults using electronic health record (EHR) data, may help identify individuals at increased risk, thus offering valuable insights for targeted [...]

Background: Real-Time Prescription Benefit (RTPB) tools remain underutilized by hospitalists, partly due to concerns surrounding the tools’ availability and accuracy of the co-payment estimates provided. The RTPB tool’s functionality is contingent on the patient’s pharmacy benefit manager (PBM) identification and selection in the electronic health record (EHR). This study aims to investigate the availability of [...]

Background: According to the Global Burden of Disease (GBD) study, 523 million (95% UI: 497 to 550 million) people worldwide had cardiovascular diseases (CVDs) in 2019, resulting in a significant increase in DALYs and years of life lost, mostly due to ischemic heart disease. There are various accurate and economical gold standard tests to identify [...]

Background: The application of machine learning (ML) to predict hospital length of stay (LoS) displays promise for advancements in healthcare management and patient care. LoS is frequently seen as a metric that can help determine the severity of sickness, cost of care, and resource use. Furthermore, individualized discharge planning has been linked to quantifiable outcomes [...]

Background: Evidence suggests female physicians experience higher rates of burnout compared to male counterparts1,2. The Electronic Health Record (EHR) is a recognized source of physician burnout (4,5,6). Therefore, efforts to understand gender disparities in EHR use may offer insights into burnout disparities at large. Studies in outpatient settings have found female physicians spend more time [...]

Background: Left atrial enlargement (LAE) is a common disorder that is associated with cardiovascular morbidity and mortality. Cardiac point-of-care ultrasound (POCUS) is frequently used to assess for LAE. However, prior studies reported only modest test characteristics with sensitivity, specificity, and 60-75% accuracy using outdated gold standard reference ranges. This study was designed to determine the [...]