Background: Clinically stable inpatients may receive potentially unnecessary care, such as overnight vital sign assessment. Nighttime vital signs can disrupt sleep and adversely affect patient satisfaction and contribute to delirium. However, it may be difficult for individual clinicians to determine which patients could safely forego overnight vital signs. Purpose: We developed a predictive algorithm designed [...]

Background: The HCAHPS survey is used nationally by health systems as a standard to measure the patient experience and identify opportunities for improvement. Historically, process improvement initiatives based on the survey are implemented retroactively, attempting to prevent negative experiences for future patients. However, given the increasing complexity of patient care, proactively addressing the identified concerns [...]

Background: Clinically stable inpatients may receive potentially unnecessary care, such as overnight vital sign assessment. Nighttime vital signs can disrupt sleep and adversely affect patient satisfaction and contribute to delirium. However, it may be difficult for individual clinicians to determine which patients could safely forego overnight vital signs. Purpose: We developed a predictive algorithm designed [...]

Background: Hospital at home (HaH) programs have shown efficacy as substitutes for high-cost, traditional hospitalization in patients who are primarily low-acuity and with a range of medical conditions, including community-acquired pneumonia (CAP) and urinary tract infection (UTI). However, wide-spread adoption is minimal as providers and patients are challenged to consider HaH at the time of [...]

Background: Chronic Obstructive Pulmonary Disease (COPD) is a lung disease characterized by chronic, irreversible airway obstruction that can precipitate into acute exacerbations (AECOPD) of cough, dyspnea and sputum production, often requiring hospitalization. Hospital systems aiming to improve outcomes for patients with AECOPD are testing innovative approaches to care in the acute care setting. To enroll [...]

Background: Sepsis is one of the top causes of inpatient mortality and rapid detection presents numerous challenges. In March, 2016, an interdisciplinary team consisting of top clinicians, data scientists and machine learning experts at a large academic medical center (AMC) embarked on an innovation pilot to develop a novel machine learning model to detect sepsis. [...]

Background: The United States government has made decreasing 30-day unplanned readmissions a national priority, as early hospital readmissions are a common and costly occurrence. Establishment of the Hospital Readmission Reduction Program (HRRP) in 2012 led to financial penalties to hospitals with high 30-day readmission rates. As such, decreasing 30-day unplanned readmissions has become a key [...]

Background: The HCAHPS survey is used nationally by health systems as a standard to measure the patient experience and identify opportunities for improvement. Historically, process improvement initiatives based on the survey are implemented retroactively, attempting to prevent negative experiences for future patients. However, given the increasing complexity of patient care, proactively addressing the identified concerns [...]

Background: Individuals with diabetes have a 2–3 fold higher hospitalization rate compared to those without diabetes. During hospitalization, individuals with diabetes frequently experience elevated blood glucose levels (or, hyperglycemia) (1), which can increase monitoring by nurses and hospitalists, length of stay, and healthcare cost. Therefore, we sought to develop a machine learning model to predict [...]

Background: Hypoglycemia occurs frequently in hospitalized adults with diabetes, and is associated with adverse clinical events, increased use of rapid response teams, prolonged hospital length of stay, and higher healthcare costs (1). Identifying risk of hypoglycemia in hospitalized adults is vital to preventing adverse events and maximizing patient safety. However, there are no tools/models to [...]